Volume 10, Number 11, November 2011 (Serial Number 101)dl.ueb.edu.vn/bitstream/1247/9920/1/31. Ngo Dang... · Effectiveness of the Global Banking System in 2010: A Data Envelopment

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Chinese Business Review

Volume 10, Number 11, November 2011 (Serial Number 101)

Contents Financial Forum

Effectiveness of the Global Banking System in 2010: A Data Envelopment Analysis Approach 961

Ngo Dang-Thanh Application of Pareto Distribution in Wage Models 974

Diana Bílková

The Chaotic Monopoly Price Growth Model 985

Vesna D. Jablanovic

Marketing

Analysis of the Relationship Between Perceived Security and Customer Trust and Loyalty in Online Shopping 990

Nihan Özgüven

Industrial Economics

Growth Potential and Profitability Analysis of Insurance Companies in the Republic of Serbia 998

Dragana Ikonić, Nina Arsić, Snežana Milošević

Regional Economics

Sustainable Consumption and Production in the Baltic Sea Region 1009

Janis Brizga, Dzintra Atstaja, Dzineta Dimante

Enterprise Management Motifs and Impediments for the Harmonization of Accounting Regulations

for Small and Medium-Sized Companies in the EU 1021

Tamara Cirkveni

Change of Management Values in Estonian Business Life in 2007-2009 1028

Anu Virovere, Mari Meel, Eneken Titov

Public Economics The Impact of Tax Policies on Taxpayers Budget in Terms of Risk, Sensitivity and Volatility 1043

Boloş Marcel Ioan, Otgon Cristian Ioan, Pop Răzvan Valentin

Interactions Between Knowledge Sharing and Organizational Citizenship Behavior 1061

Yavuz Demirel, Zeliha Seçkin, Mehmet Faruk Özçınar

Social Economics Enhancing Organization’s Performance Through Effective Vision and Mission 1071

Ben E. Akpoyomare Oghojafor, Olufemi O. Olayemi, Patrick S. Okonji, James. U. Okolie

Determinants of Female Employment Rate in the European Union 1076

Irena Spasenoska, Merale Fetahu-Vehapi

Chinese Business Review, ISSN 1537-1506 November 2011, Vol. 10, No. 11, 961-973

Effectiveness of the Global Banking System in 2010:

A Data Envelopment Analysis Approach∗

Ngo Dang-Thanh University of Economics and Business (Vietnam National University), Hanoi, Vietnam

Massey University, Palmerston North, New Zealand

The current crisis has revealed the weaknesses of the global financial in general and its banking system in particular,

and puts forward a requirement for assessing the effectiveness and stability of the banking sectors across countries.

Based on available data from 64 countries over the world, the author tried to evaluate the effectiveness of the

banking sectors in those countries through the view point of the data envelopment analysis approach to define how

the global banking systems is under the effect of the current crisis. Findings from the research showed that banking

systems in advanced economies are still more effective than in developing countries. Moreover, it explained the

effect of the current financial crisis, the role of public finance (and the government), and the development of the

(privately) commercial banks to the effectiveness of the banking sectors. The research also explained some

determinants that can affect the effectiveness of the banking system, including inflation, bank concentration, and

level of economic development.

Keywords: data envelopment analysis, effectiveness, efficiency, banking, cross countries

Introduction

Because of the important role of the banking and financial system in the rapid development of new industrial economies (NIEs) in the 1960s-1970s, there were renewed interests in the relationship between financial and economic growth. Schumpeter (1911) argued that the role of financial intermediaries in savings mobilization, projects evaluation and selection, risk management, entrepreneurs monitor, and facilitating transactions is important to technological innovation and economic growth. Following this argument, many other leading economists continuing emphasized the positively essential role of the financial sector in economic development, including Goldsmith (1969), Shaw (1973), McKinnon (1973), King and Levine (1993a, 1993b).

Banks are the core of the financial system. They accept deposits from savers and lend them to borrowers.

∗ Acknowledgement: The author would like to offer special thanks to Professor David Tripe at Centre for Banking studies, Massey University, New Zealand for his supports, encouragement and useful comments. The author also thanks participants at the 18th Annual Global Finance Conference in Bangkok, Thailand, April 2011 for their constructive comments and feedback to improve the quality of the paper. The usual disclaimer applies. Ngo Dang-Thanh, Ph.D. candidate, Lecturer, Faculty of Political Economy, University of Economics and Business (Vietnam

National University), Centre for Banking Studies, Massey University. Correspondence concerning this article should be addressed to Ngo Dang-Thanh, Faculty of Political Economy, University of

Economics and Business (Vietnam National University). E-mail: [email protected].

EFFECTIVENESS OF THE GLOBAL BANKING SYSTEM IN 2010 962

They hold liquid reserves which allowing predictable withdrawal demand. They issue liabilities which are more liquid than the deposits. They also reduce (or some times eliminate) the need of self-finance (Bencivenga & Smith, 1991, p. 195). Banks hold an important role within the financial system, and to some certain level, researching the banking system therefore means researching the financial system.

Started from the bankruptcy of the Northern Rock Bank in the UK (2008, February), however, the global financial crisis and its heavily impacts have put researchers and policy makers under the requirement of re-assessment and re-evaluation the stability and performance of the global financial and banking system1.

A firm is effective when it reaches its target outputs. Similarly, a banking system is defined as effectiveness if it can fulfill its missions of providing banking services and monitoring the stability of the system. Meanwhile, if banking systems are set under similar conditions of macro- and micro-economic, the level of outcomes that a banking system can provide (in term of services and stability) is indeed its efficiency. In this sense, the problem of calculating effectiveness of banking systems all over the world becomes the problem of evaluating its efficiency with a (dummy) similar and equal input. This research is trying to define the effectiveness of the global banking system in 2010 through analysing cross-country data observed from 64 countries, using the data envelopment analysis (DEA) approach. The remainder of this paper is organized as follows. Section 2 gives some reviews on efficiency and effectiveness evaluation in the banking sector using DEA approach. Section 3 explains the methodologies and technical will be applied in the research. Section 4 shows empirical results and section 5 concludes.

Literature Review

To evaluate the efficiency of a set of firms (or banks), the most popular approaches are ratio analysis, parametric analysis and nonparametric analysis (the latter two methods belongs to the X-efficiency approach). While ratio analysis focuses on ratios between two variables (of inputs or outputs) to define the productivity and efficiency, X-efficiency analysis evaluates the efficiency of a bank through a multi-variables aspect.

DEA is a popular nonparametric method applied in evaluating efficiency in finance and banking area. After Farrell (1957) laid the foundation for a new approach in evaluating efficiency and productivity at micro-level, Charnes, Cooper and Rhodes (1978) and then Banker, Charnes and Cooper (1984) developed the CCR and BCC-DEA model, respectively, to evaluate the (relative) efficiencies of the researched decision making units (DMUs). Since then, DEA was increasingly applied in efficiency evaluation, especially in social sciences2.

There are a limited number of researches using DEA to examine banking performance at cross-country level. A study in 1997 showed that out of 130 studies on banking performance and efficiency, only six were focused on comparing the efficiency level of banking systems across countries (Berger & Humphrey, 1997, pp. 182-184). As shown in Table 1, all three DEA studies were using small sample data at institutional (bank) level to define the benchmark frontier, hence, the global banking system was left untouched.

In the 2000s, further studies which used common frontier approach were developed by add in the model

1 According to Science Direct, since 2010, there are more than 2,200 journal articles regarding banking performance after the crisis of 2007-2008 (Retrieved December 20, 2010, from http://www.sciencedirect.com). 2 Recent study of Avkiran (2010) showed that there are more than 170 articles using DEA as a main methodology to analyse the efficiency of banks and banks branches, including Sherman and Gold (1985), Peristiani (1997), Schaffnit, Rosen and Paradi (1997), and Pastor, Knox Lovell and Tulkens (2006).


some environmental/controllable variables such as banking market conditions or market structure and regulation (Kwan, 2003; Lozano-Vivas, Pastor, & Hasan, 2001; Maudos, Pastor, Perez, & Quesada, 2002; Sathye, 2005). However, as they are also mainly focused on institutional level data while macro-environment is different from country to country, they ignored that banks which are efficient in this country may not performance well if they run as foreign-owned banks in other countries (Berger, 2007, p. 125). Hence, while trying to examine the whole banking systems across countries, this study attempts to overcome the above problem.

Table 1 Studies on Banking Performance at Cross-Country Level (Prior to 1997)

Authors (date) Method used Countries included Institution Berg, Forsund, Hjalmarsson, & Suominen (1993) Data envelopment analysis Norway, Sweden, Finland Bank

Fecher & Pestieau (1993) Distribution free approach 11 OECD countries Financial serviceBergendahl (1995) Mixed optimal strategy Norway, Sweden, Finland, Denmark Bank Ruthenberg & Elias (1996) Thick frontier approach 15 developed countries Bank Bukh, Berg, & Forsund (1995) Data envelopment analysis Norway, Sweden, Finland, Denmark Bank J. Pastor, Perez, & Quesada (1997) Data envelopment analysis 08 developed countries Bank

Note. Source: Berger and Humphrey (1997).

As DEA evaluates the efficiency of each DMU based on the optimal multipliers (or weights) of inputs and outputs factors, it allows us to examine the effectiveness of a banking system by looking at the achievements of the banking sector, including both quantity (assets, deposits, credits, etc.) and quality (overhead cost, nonperforming loans, frequency of bank crises, etc.) factors of commercial banks in the economy3. They are chosen following 122 variables represent the stability of the global financial system (WEF, 2010, Appendix A). However, since DEA treats those factors dynamically (meaning each country can have its own preference on them), to be understandable in evaluating and comparing the effectiveness of the banking systems between countries, a common preference (or common set of weights) for the above analyzed factors is required. Therefore, in this research, the DEA model will be divided into three stages, in which the first stage conducts a dynamic DEA model (DSW model) to define the relatively efficiencies of the banking systems from these 64 countries; the second stage examines the determinants affecting that efficiencies (Tobit model); and the third stage defines the common set of weights for those analyzed factors (CSW model) in order to conduct the final banking effectiveness scores.

Technical Methodologies

In the first step, DSW model is produced to calculate the maximum effectiveness scores that each country can achieve with the observed (achievement) factors. Mahlberg and Obersteiner (2001) and Depotis (2004) developed an input-oriented DEA-like model which treats all factors as outputs, while input is a dummy variable (values equal to 1 for all countries). Therefore, the DSW model in this research is in fact a constant-returns-to-scale (CRS) and input-oriented DEA model. For an evaluated country j0-th, its efficiency score (DSWj0) can be expressed by the following non-negative linear problem: 3 It is important to notice that these factors are outcomes that a banking system is aiming for; hence, the DEA model in this paper will use them all as output variables.


∑∑=

0

0

0maxDSWj

kjk

mjm

xvyu

(1)

Subject to:

∑ ∑≤ kjkmjm xvyu , 1 ≤ j ≤ n

∑ = 1kjk xv

∑ = 1mu

um ≥ 0 xj = 1 {all original input values are assumed to be equal to 1}

where: um: weight of m-th output factor; vk: weight of k-th input factor; xkj: k-th input of j-th country, k = 1; ymj: m-th output of j-th country; n: number of countries; m: number of factors. Due to the fact that some countries can have the same scores in this DSW model, a super efficiency DEA

model (Zhu, 2001) is also ran to determine the ranking order of the researched countries, makes it easier to compare the effectiveness’s of the banking systems between countries.

In the next step, a Tobit regression (for more details, see Tobin, 1958) is used to determine the factors affecting the country’s banking efficiencies (Tobit model). Since the CSW scores are bounded between 0 to 1, non-censored regression models could be biased (Fethi & Pasiouras, 2010), while Tobit regression is justify as in equation (2). Variables used in this model are ones that mainly related to the financial efficient of a banking system at micro-level and are expressed in Table 2.

EF = α + β1*CONC + β2*ROA + β3*ROE + β4*CIR + β5*INF + β6*CTA + β7*NIM + β8*CII + β9*GROUP (2)

Table 2 Variables of the Tobit Model Variables Definition EF CSW-DEA scores. CONC Bank concentration (assets of three largest banks as a share of assets of all commercial banks). ROA Bank’s average return on assets (Net income/Total assets). ROE Bank’s average return on equity (Net income/Total equity). CIR Bank’s cost to income ratio (Total costs as a share of total income of all commercial banks). INF Inflation, consumer prices (annual %). CTA Bank’s capital to assets ratio (ratio of bank capital and reserves to total assets). NIM Net interest margin of banks (value of bank’s net interest revenue as a share of its interest-bearing assets).

CII Depth of credit information index (measures rules and practices affecting the coverage, scope and accessibility of credit information).

GROUP Dummy variable of income group (equals to 0 if country belongs to lower income, 1 if middle income, and 2 if high income group).


The last step is to define the optimal common set of weights which should be used for compare and ranking countries based on their banking systems’ effectiveness. It is done by applying the CSW model. It is believed that the efficient frontier found in the DSW model in the first step is the “best practice frontier” (Grosskopf & Valdmanis, 1987; Schaffnit, Rosen, & Paradi, 1997); hence, the optimal common weight set will be the one that get every countries’ performances closest to that frontier. There are several ways to define that common set of weights is based on this idea. While imposing bounds for factor weights, Roll and Golany (1993) found out that the common set of weights can be defined by maximizing the average efficiency of all DMUs or maximizing the number of efficient DMUs. Kao and Hung (2005) applied a compromise solution approach to minimize the total squared distances between the optimal objective values (found by DEA) and the common weighted values (found by using common set of weights). Jahanshahloo, Memariani, Lotfi and Rezai (2005) applied the multiple objective programming approach to simultaneously maximize the performance scores to get it closes to the “best practice frontier”. Liu and Peng (2008) applied the common weights analysis to minimize the vertical and horizontal virtual gaps between the benchmark line (slope equals to 1.0, or performance scores equal to 1.0) and the coordinate of common weighted DMUs. In this paper, we modified the model of Kao and Hung (2005) into a minimum distance efficiencies model, in which the common set of weights can be defined as the one minimizing the total distances between optimal efficiencies (DSW scores) and common weighted scores (CSW scores) of all DMUs, under the condition that each DMU’s efficiency cannot exceed its DSW efficiency4. To understand the role of each factor in CSW scores, another condition was added where the total sum of weights is equal to 1 (or 100%). The country’s banking effectiveness scores will be constructed based on that CSW scores and findings from the super efficiency DEA results in the previous step. This CSW model can be expressed as a non-negatively linear problem as follows:

( )∑ − jj ee*min (3)

Subject to:

j* DSW=je

∑∑=

kjk

mjmj xv

yue , 1 ≤ j ≤ n

*jj ee ≤ 1=∑ kjk xv

∑ = 1mu

um ≥ 0.015 xj = 1 {all original input values are assumed to be equal to 1}

where: um: weight of m-th factor; ymj: m-th factor of j-th country;

4 This constrain makes these distances non-negative, hence, they can be used directly rather than the squared distances. 5 Mahlberg and Obersteiner (2001) found that restriction weights with lower bound of 0.01 steered a middle course between too strong predetermination and too large flexibility.


n: number of countries; m: number of factors. The final effectiveness scores will then be calculated following this equation:

∑= mjCSWmj yuES (4)

where: ESj: Effectiveness score of country j-th; um

CSW: Common weight of factor m-th; ymj: Value of factor m-th of country j-th.

Empirical Results

In the first stage, countries and factors are collected from the database of Beck, Demirgüç-Kunt and Levine (2000), Laeven and Valencia (2010), the World Bank (World Development Indicator, Global Development Financial, and Doing Business databases), the International Monetary Fund (IMF, 2010), the Consultative Group to Assist the Poor (CGAP, 2010) and Annual Reports from Central Banks of such researched countries. Ten factors6 are included in this research, covering both quantitative (the first 5 factors) and qualitative (the last 5 factors) aspect of the banking sectors (see Table 3). It is important to notice that the last 3 factors are undesirable factors (as they have negative effect to the banking effectiveness), hence, they was transformed into desirable ones through the linear monotone decreasing transformation method7.

Table 3 Descriptive Statistics of Factors

Factors Mean Standard error

Standard deviation Minimum Maximum

Commercial banks’ assets/GDP 0.74 0.06 0.48 0.09 2.42 Domestic credit provided by banking sector (% of GDP) 80.21 8.74 69.92 -11.17 379.30 Commercial banks' deposits/GDP 0.60 0.04 0.36 0.12 1.80 Number of ATMs per 100,000 people 28.27 4.87 38.96 0.06 236.07 Number of branches per 100,000 people 11.47 1.23 9.86 0.53 45.60 Private credit bureau coverage (% of adults) 36.72 4.38 35.03 0 100 Public credit bureau coverage (% of adults) 8.24 1.60 12.76 0 48.50 Banks' overhead costs/Total assets 0.22 0.01 0.05 0 0.26 Nonperforming loans ratios of commercial banks 17.39 0.78 6.23 0 22.80 Frequency of banking crises 2.92 0.09 0.72 0 4.00 Note. Data of the last three variables are already transformed.

As mentioned in section 3, those factors will be treated as output variables, while a dummy-input (equals to 1) will be set for the whole 64 countries. The DSW model then produces an effective frontier built from 25 countries, while the other 39 are ineffective (see Appendix A Table A2).

Within the ineffective ones, none of them is developed countries, suggesting that the banking systems in

6 According to Dyson et al. (2001, p. 248) and Avkiran (2001, p. 68), one rule of thumb in using DEA is that the sample size has to be at least 3 times bigger than the number of total inputs and outputs to overcome the discrimination problem. As we have 64 samples over 10 variables, hence, this research is justified. 7 In this method, the transformed values will be calculated by the difference between a proper translation vector w with the original values of those undesirable factors. For more details, see Seiford and Zhu (2002) and Fare and Grosskopf (2004).


advanced economies still run better than in developing countries although they had to bear stronger effect from the current crisis. This can be explained by the difference between projected values and original values of these factors (in percentage of original values), in which the biggest differences are mainly for quantity factors, except for the case of private credit bureau coverage. The results show that, major weaknesses of ineffective countries in banking system development are the ATM network, bank deposits to GDP, private credit coverage, bank assets, and bank’s domestic credits. Those are the disadvantage of developing countries as they are still on their way developing their financial and banking systems (see Table 4).

Table 4 Differences Between Projected and Original Values for Inefficient Countries

Factors Total differences

In value In percentage of original value Commercial banks’ assets/GDP 21.72 45.56 Domestic credit provided by banking sector (% of GDP) 2,338 45.55 Commercial banks’ deposits/GDP 21.67 56.44 Number of ATMs per 100,000 people 1,373 75.88 Number of branches per 100,000 people 379.4 51.7 Private credit bureau coverage (% of adults) 1,230 52.34 Public credit bureau coverage (% of adults) 56.46 10.71 Banks’ overhead costs/Total assets 0.741 5.376 Nonperforming loans ratios of commercial banks 80.16 7.201 Frequency of banking crises 21.68 11.59 Average 552.3 36.24

In the second stage, the results from Tobit model show the relation between the banking systems’ effectiveness and various variables such as inflation level of the economy, income group that the country belongs to, concentration of the banking system, etc., as summarized in Figure 1. It is obvious that higher inflation, banking concentration, and bank’s cost-income ratio can reduce the effectiveness of the banking sector (respectively significant at 1, 5 and 10 percent), while the high level of economic development (improving to higher income group) can help increase the effectiveness of the banking system (5% significant level).

Figure 1. Determinants of the global banking effectiveness.


In the last stage, solving the non-linear problem of the CSW model (equation (3)) helped us defining a common set weight for the ten factors of every country in the research (see Table 5). Noticeably, important factors which strongly affect the performance of the banking sector in those countries are non-performing loans ratio (79.49%), public credit bureau coverage (10.47%), and number of branches per 100,000 people (3.03%). The other factors only keep minimum role (1% weight) in the final results. It shows that the effectiveness of the banking sector is mainly affected by the damage of the global crisis, the (financial) public policy of the government, and the development of the commercial bank system of each country respectively. It also suggests that the quality of the banking sector is now becoming more important than the quantity aspect, not only for countries with developed banking systems but for developing countries as well. Thus, country which focuses on improving the quality of its banking sector can have higher effectiveness and is more stable.

Table 5 Common Set of Weights for the Effectiveness Scores Factors Weight Commercial banks’ assets/GDP 1.00 Domestic credit provided by banking sector (% of GDP) 1.00 Commercial banks’ deposits/GDP 1.00 Number of ATMs per 100,000 people 1.00 Number of branches per 100,000 people 3.03 Private credit bureau coverage (% of adults) 1.00 Public credit bureau coverage (% of adults) 10.47 Banks’ overhead costs/Total assets 1.00 Nonperforming loans ratios of commercial banks 79.49 Frequency of banking crises 1.00

By applying this common set of weights, the effectiveness scores of country’s banking systems can be calculated and countries can be ranked as in Table 6. Since non-performing loans ratio became the most important factor, countries having problems with NPLs became less efficient and ranked bottom in the list, including even Denmark and New Zealand.

Table 6 The Global Banking Effectiveness in 2010 Rank Country Effectiveness score Rank Country Effectiveness score 1 Japan 23.231 33 Kuwait 17.606 2 Canada 23.231 34 Venezuela, RB 17.556 3 Chile 23.231 35 Moldova 17.504 4 Malaysia 22.275 36 Lithuania 17.394 5 Australia 22.177 37 Bolivia 17.333 6 Switzerland 22.079 38 Croatia 17.307 7 United States 22.037 39 Uganda 16.947 8 Bulgaria 21.755 40 Jordan 16.891 9 Argentina 21.671 41 Mozambique 16.853 10 Ecuador 21.461 42 Poland 16.771 11 Costa Rica 21.421 43 Colombia 16.770 12 United Kingdom 21.415 44 Armenia 16.276


(Table 6 continued) Rank Country Effectiveness score Rank Country Effectiveness score 13 Korea, Rep. 21.066 45 Thailand 16.203 14 Sweden 21.060 46 Russian Federation 16.066 15 Brazil 20.968 47 Georgia 15.859 16 El Salvador 20.232 48 Morocco 15.475 17 Dominican Republic 20.070 49 Kazakhstan 15.288 18 Peru 19.907 50 Albania 15.116 19 Israel 19.735 51 Yemen, Rep. 14.566 20 Guatemala 19.626 52 Nigeria 14.202 21 Singapore 19.326 53 Kenya 11.871 22 Estonia 19.276 54 Bangladesh 10.486 23 Panama 19.085 55 Tunisia 9.696 24 Indonesia 18.993 56 Romania 9.442 25 Turkey 18.749 57 Egypt, Arab Rep. 8.051 26 South Africa 18.538 58 Mauritius 7.601 27 Czech Republic 18.302 59 Denmark 6.519 28 Hungary 18.233 60 New Zealand 5.338 29 Saudi Arabia 18.045 61 Vietnam 4.841 30 India 17.921 62 Angola 4.761 31 Macedonia, FYR 17.842 63 Botswana 0.662 32 Slovak Republic 17.750 64 Sierra Leone 0.203

Conclusions

Using data from 64 countries in the world, this research applied the data envelopment analysis (DEA) to evaluate the effectiveness of banking systems in the World in 2010. The research was divided into three steps, in which the first stage applied data envelopment analysis method to build a common frontier for these 64 countries; the second step detected the determinants of the banking sector’s effective; and the last step defined a common set of weights for analyzing factors helping in ranking the effectiveness of the global banking system in 2010.

The research evaluated the effectiveness of the global banking systems using a dummy input and ten outputs to create a common frontier for the whole banking systems of 64 countries (while previous studies used institutional level data of smaller sample size); and after that building a common set of weights to calculate the effectiveness scores of the global banking system, applied to the DEA method. This proposes an interesting function for using DEA in examining the effectiveness (and efficiency) in the banking sector.

Findings from the research showed that banking systems in advanced economies are still more effective than in developing countries. Reasons seem to be related to the development of the banking sector in quantity (number of bank branches) and more importantly in quality aspects (including the NPL ratio, public credit bureau coverage, bank concentration, bank’s capital, and cost-income ratio). It is also included the effect of economic development, expresses through level of income (group) and inflation rates. These results partly explained the effect of the current financial crisis to the banking sector, the role of public finance (and the government) in this kind of situation, and the important role of developing commercial banking system to its efficiency and effectiveness.

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Appendix A

Table A1

Countries’ Data

Country y1 y2 y3 y4 y5 y6 y7 y8 y9 y10 Albania 0.77 66.88 0.74 2.37 2.11 0.00 9.90 0.24 16.70 3.00 Angola 0.24 9.34 0.24 9.58 0.60 0.00 2.50 0.23 5.34 4.00 Argentina 0.18 24.47 0.20 14.91 10.01 100.00 34.30 0.18 20.60 0.00 Armenia 0.20 16.66 0.12 1.37 7.59 34.50 4.40 0.22 18.90 3.00 Australia 1.29 143.75 1.14 64.18 29.86 100.00 0.00 0.24 22.80 4.00 Bangladesh 0.54 59.38 0.51 0.06 4.47 0.00 0.90 0.24 12.10 3.00 Bolivia 0.32 55.24 0.38 4.80 1.53 33.90 11.60 0.21 19.00 2.00 Botswana 0.19 -11.17 0.58 9.00 3.77 51.90 0.00 0.22 0.00 4.00 Brazil 0.91 117.85 0.66 17.82 14.59 59.20 23.70 0.14 20.20 2.00 Bulgaria 0.85 66.74 0.77 29.79 13.87 6.20 34.80 0.25 20.90 3.00 Canada 1.40 178.07 1.04 135.23 45.60 100.00 0.00 0.24 22.20 4.00 Chile 0.78 115.92 0.55 24.03 9.39 33.90 32.90 0.23 22.30 2.00 Colombia 0.51 43.26 0.22 9.60 8.74 60.50 0.00 0.21 19.30 2.00 Costa Rica 0.49 53.90 0.25 12.83 9.59 56.00 24.30 0.15 21.80 2.00 Croatia 0.90 75.09 0.77 40.10 23.36 77.00 0.00 0.24 18.40 3.00 Czech Republic 0.67 57.98 0.62 19.57 11.15 73.10 4.90 0.24 20.00 3.00 Denmark 2.42 211.45 0.72 52.39 37.63 5.20 0.00 0.23 3.30 3.00


(Table A1 continued) Country y1 y2 y3 y4 y5 y6 y7 y8 y9 y10 Dominican Republic 0.22 39.06 0.21 15.08 6.00 46.10 29.70 0.13 19.80 3.00 Ecuador 0.28 19.76 0.28 6.32 9.30 46.00 37.20 0.22 20.80 2.00 Egypt, Arab Rep. 0.56 77.70 0.75 1.78 3.62 8.20 2.50 0.22 8.50 3.00 El Salvador 0.42 49.94 0.42 11.07 4.62 94.60 21.00 0.23 20.50 3.00 Estonia 1.18 97.26 0.48 57.70 15.19 20.60 0.00 0.17 21.40 3.00 Georgia 0.40 32.87 0.22 1.17 3.14 12.20 0.00 0.18 19.20 3.00 Guatemala 0.44 40.11 0.37 20.20 10.12 28.40 16.90 0.01 20.90 4.00 Hungary 0.90 80.70 0.50 29.40 28.25 10.30 0.00 0.00 20.30 2.00 India 0.69 68.35 0.70 7.29 10.64 10.20 0.00 0.24 21.00 3.00 Indonesia 0.29 36.75 0.33 4.84 8.44 0.00 22.00 0.23 20.10 3.00 Israel 0.95 82.16 0.87 18.81 14.74 89.80 0.00 0.24 21.80 3.00 Japan 1.48 379.30 1.80 113.75 9.98 76.20 0.00 0.25 21.60 3.00 Jordan 1.29 114.92 1.09 9.38 10.02 0.00 1.00 0.24 19.10 3.00 Kazakhstan 0.89 33.51 0.39 7.01 2.47 29.50 0.00 0.23 18.20 3.00 Kenya 0.29 40.09 0.29 0.99 1.38 2.30 0.00 0.21 14.30 2.00 Korea, Rep. 1.21 112.32 0.59 90.03 13.40 93.80 0.00 0.25 22.20 3.00 Kuwait 0.81 74.92 0.71 19.69 8.27 30.40 0.00 0.23 20.20 3.00 Lithuania 0.73 64.37 0.36 28.78 3.39 18.40 12.10 0.24 18.70 3.00 Macedonia, FYR 0.55 42.70 0.56 49.97 26.79 0.00 28.10 0.22 16.50 3.00 Malaysia 0.99 115.54 1.09 16.44 9.80 82.00 48.50 0.24 18.50 3.00 Mauritius 0.88 111.78 0.86 22.04 11.92 0.00 36.80 0.24 2.50 4.00 Moldova 0.49 39.76 0.45 236.07 10.07 0.00 0.00 0.21 18.10 4.00 Morocco 0.91 95.54 0.94 9.68 15.80 14.00 0.00 0.25 17.30 3.00 Mozambique 0.22 14.14 0.29 4.90 2.92 0.00 2.30 0.20 20.50 3.00 New Zealand 1.55 156.45 0.96 50.36 28.04 100.00 0.00 0.25 1.70 4.00 Nigeria 0.45 26.73 0.26 18.63 6.42 0.00 0.00 0.23 17.00 3.00 Panama 0.86 85.41 0.88 16.19 12.87 45.90 0.00 0.19 21.60 3.00 Peru 0.21 18.51 0.26 5.85 4.17 31.80 23.00 0.23 21.10 3.00 Poland 0.55 60.06 0.42 17.31 8.17 68.30 0.00 0.24 18.90 3.00 Romania 0.52 40.91 0.32 12.47 13.76 30.20 5.70 0.18 9.50 3.00 Russian Federation 0.49 26.03 0.36 6.28 2.24 14.30 0.00 0.18 19.50 2.00 Saudi Arabia 0.55 9.42 0.53 14.70 5.36 17.90 0.00 0.25 21.90 4.00 Sierra Leone 0.09 7.35 0.15 1.14 2.76 0.00 0.00 0.16 0.00 3.00 Singapore 1.10 79.17 1.18 37.93 9.13 40.30 0.00 0.26 21.90 4.00 Slovak Republic 0.55 53.80 0.49 29.21 10.28 44.00 1.40 0.24 20.10 3.00 South Africa 0.95 215.47 0.67 17.50 5.99 54.70 0.00 0.22 19.40 4.00 Sweden 1.40 133.43 0.57 29.56 21.80 100.00 0.00 0.25 22.30 2.00 Switzerland 1.89 180.59 1.31 70.60 37.99 22.50 0.00 0.23 22.80 3.00 Thailand 0.84 145.65 0.79 17.05 7.18 32.90 0.00 0.24 17.60 2.00 Tunisia 0.62 72.04 0.52 17.69 15.51 0.00 19.90 0.24 7.80 3.00 Turkey 0.51 52.54 0.42 18.00 8.50 42.90 15.90 0.22 19.70 2.00 Uganda 0.22 11.45 0.20 0.70 0.53 0.00 0.00 0.20 21.10 3.00 United Kingdom 2.08 211.35 1.71 42.45 18.35 100.00 0.00 0.25 21.70 3.00 United States 0.73 271.64 0.83 120.94 30.86 100.00 0.00 0.22 20.30 2.00 Venezuela, RB 0.38 20.49 0.39 16.60 4.41 0.00 0.00 0.21 21.40 3.00 Vietnam 1.24 94.99 0.93 15.36 3.42 0.00 19.00 0.25 2.00 3.00 Yemen, Rep. 0.13 11.29 0.21 2.75 1.97 0.00 0.20 0.25 18.00 3.00 Note. y1, y2,..., y10 are respectively referred to ten factors in Table 3.


Table A2

Dynamic DEA Efficiencies

Rank Country DSW score Rank Country DSW score 1 Moldova 1.000 33 Thailand 0.961 2 Malaysia 1.000 34 India 0.957 3 Japan 1.000 35 Dominican Republic 0.955 4 Canada 1.000 36 Croatia 0.951 5 United Kingdom 1.000 37 Panama 0.947 6 Denmark 1.000 38 Czech Republic 0.947 7 Mauritius 1.000 39 Lithuania 0.944 8 Argentina 1.000 40 Estonia 0.939 9 Switzerland 1.000 41 Venezuela, RB 0.939 10 United States 1.000 42 Poland 0.938 11 Chile 1.000 43 Indonesia 0.937 12 Guatemala 1.000 44 Jordan 0.935 13 Singapore 1.000 45 Albania 0.931 14 Macedonia, FYR 1.000 46 Brazil 0.930 15 South Africa 1.000 47 Slovak Republic 0.929 16 New Zealand 1.000 48 Uganda 0.925 17 Australia 1.000 49 Bangladesh 0.920 18 Bulgaria 1.000 50 Kuwait 0.912 19 Vietnam 1.000 51 Turkey 0.904 20 Sweden 1.000 52 Mozambique 0.901 21 Korea, Rep. 1.000 53 Kazakhstan 0.893 22 El Salvador 1.000 54 Nigeria 0.893 23 Botswana 1.000 55 Hungary 0.890 24 Saudi Arabia 1.000 56 Armenia 0.870 25 Angola 1.000 57 Bolivia 0.867 26 Ecuador 0.985 58 Egypt, Arab Rep. 0.863 27 Yemen, Rep. 0.984 59 Russian Federation 0.855 28 Costa Rica 0.980 60 Colombia 0.846 29 Morocco 0.972 61 Georgia 0.842 30 Tunisia 0.970 62 Kenya 0.813 31 Peru 0.969 63 Romania 0.750 32 Israel 0.965 64 Sierra Leone 0.750

Note. First 25 countries are ranked based on super-efficiency DEA results.


Application of Pareto Distribution in Wage Models∗

Diana Bílková University of Economics in Prague, Prague, Czech Republic

This paper deals with the use of Pareto distribution in models of wage distribution. Pareto distribution cannot

generally be used as a model of the whole wage distribution, but only as a model for the distribution of higher or of

the highest wages. It is usually about wages higher than the median. The parameter b is called the Pareto coefficient

and it is often used as a characteristic of differentiation of fifty percent of the highest wages. Pareto distribution is

so much the more applicable model of a specific wage distribution, the more specific differentiation of fifty percent

of the highest wages will resemble to differentiation that is expected by Pareto distribution. Pareto distribution

assumes a differentiation of wages, in which the following ratios are the same: ratio of the upper quartile to the

median; ratio of the eighth decile to the sixth decile; ratio of the ninth decile to the eighth decile. This finding may

serve as one of the empirical criterions for assessing, whether Pareto distribution is a suitable or less suitable model

of a particular wage distribution. If we find only small differences between the ratios of these quantiles in a specific

wage distribution, Pareto distribution is a good model of a specific wage distribution. Approximation of a specific

wage distribution by Pareto distribution will be less suitable or even unsuitable when more expressive differences

of mentioned ratios. If we choose Pareto distribution as a model of a specific wage distribution, we must reckon

with the fact that the model is always only an approximation. It will describe only approximately the actual wage

distribution and the relationships in the model will only partially reflect the relationships in a specific wage

distribution.

Keywords: Pareto distribution, Pareto coefficient, estimation methods for parameters, least squares method, wage

distributions

Pareto Distribution

The question of income and wage distributions and their models is quite extensively treated in the statistical literature (Bartošová, 2006; Bartošová & Bína, 2009; Bílková, 2007; Dutta, Sefton, & Weale, 2001; Majumder & Chakravarty, 1990; McDonald & Snooks, 1985; McDonald, 1984; McDonald & Butler, 1987).

∗Acknowledgment: The paper was supported by grant project IGS 24/2010 called “Analysis of the Development of Income

Distribution in the Czech Republic Since 1990 to the Financial Crisis and Comparison of This Development With the Development of the Income Distribution in Times of Financial Crisis, According to Sociological Groups, Gender, Age, Education, Profession Field and Region” from the University of Economics in Prague. Diana Bílková, Ing./Dr., Department of Statistics and Probability, Faculty of Informatics and Statistics, University of Economics

in Prague. Correspondence concerning this article should be addressed to Diana Bílková, Department of Statistics and Probability, Faculty

of Informatics and Statistics, University of Economics in Prague, Sq. W. Churchill 1938/4, Prague 3, Czech Republic, post code: 130 67. E-mail: [email protected].

APPLICATION OF PARETO DISTRIBUTION IN WAGE MODELS 975

Pareto distribution is usually used as a model of the distribution of the largest wages, not for the whole wage distribution. In this article, we will consider using the Pareto distribution to model wages higher than median.

The 100·P% quantile of the wage distribution will be denoted by xP, 0 < P < 1. This value represents the upper bound of 100·P% lowest wages and also the lower bound of 100(1 – P) % highest wages. A particular quantile (denoted as xP0) which will be the lower bound of some small number of the highest wages is usually set to be the maximum wage. If the following formula (1) holds for any quantile xP, the wage distribution is Pareto distribution.

0

0

11

bP

P

x PPx

⎛ ⎞−= ⎜ ⎟−⎝ ⎠

(1)

The parameter b of the Pareto distribution (1) is called the Pareto coefficient. It can be used as a characteristic of differentiation of 50% highest wages.

We will now consider a pair of quantiles xP1 and xP2, P1 < P2. It follows from equation (1) that:

⎟⎟⎠

⎞⎜⎜⎝

⎛

−−

=PP

xx

b

P

P

11

0

1

1

0

(2)

and

11

0

2

2

0⎟⎟⎠

⎞⎜⎜⎝

⎛

−−

=PP

xx

b

P

P

(3)

From what we can derive for the rate of xP2 to xP1 that:

2 1

21

11

bP

P

PxPx

⎛ ⎞−= ⎜ ⎟−⎝ ⎠

(4)

The rate is an increasing function of the Pareto coefficient b. If the rate of quantiles increases, the relative differentiation of wages increases too. If only absolute differences between quantiles increase, only the absolute differentiation of wages increases.

It follows from the equation (1) that once the values xP0 and b are chosen, we can determine the quantile xP for any chosen P or the other way around for any value xP we can find the corresponding value of P. In the first case, it is advantageous to write the equation (1) as:

⎟⎟⎠

⎞⎜⎜⎝

⎛

−−

=

PP

xx b

PP

11

0

0 (5)

or after logarithmic transformation as:

)]1(log-)-(1[logloglog 00PPbxx PP −−=

(6)

in the second case:

b

P

P

xx

PP 00)1(1 −=− (7)

xx

P

P

1

2


or after logarithmic transformation as:

)loglog(1)1(log)(1log 0 xxb

PP PP0−+−=−

(8)

The equations (2)-(4) will after logarithmic transformation have the following forms:

11

log

log

0

1

1

0

PP

xx

b P

P

−−

=

(9)

11

log

log

2

1

1

2

PP

xx

b P

P

−−

=

(10)

It follows from the equation (9) that instead of the Pareto coefficient b we can use any other quantile xP1 of the Pareto distribution and it follows from the equation (10) that the Pareto coefficient b can be calculated using any known quantiles xP1 and xP2. Then we can also determine the value xP0 using the formulas:

,11

0

110 ⎟⎟

⎠

⎞⎜⎜⎝

⎛

−−

=PP

xxb

PP

(11)

11

0

220 ⎟⎟

⎠

⎞⎜⎜⎝

⎛

−−

=PP

xxb

PP

(12)

The model characterized with the relationship (1) will be practically applicable if the following is known: • The value of the quantile that characterizes the assumed wage maximum and the value of the Pareto

coefficient b; • The value of the quantile that characterizes the assumed wage maximum and the value of any other quantile; • The values of any two quantiles of the Pareto distribution.

Any two quantiles can be written as xP and xP+k, where 0 < k < 1 – P . Using the equation (4), we can derive for the rate of these two quantiles:

kPP

xx

b

P

kP⎟⎟⎠

⎞⎜⎜⎝

⎛−−

−=+

11

(13)

The rate (13) will be equal for such pairs of quantiles for which the following formula holds:

,1

1 ckP

P=

−−−

(14)

where c is a constant, i.e., the rate will be the same for all pairs of quantiles for which:

)(11 Pc

ck −−

=

(15)

We will use the constant c = 2 in equation (15) and we will choose gradually P = 0.5; 0.6; 0.8. Then using the equation (13) we can show the equality of rates of some frequently used quantiles:


0.75 0.8 0.9

0.5 0.6 0.8

x x xx x x

= = (16)

From the relationship (16) we can conclude that Pareto distribution assumes such a wage differentiation for which the rate of the upper quartile to median is the same as:

• The rate of the 8th to the 6th decile; • And as the rate of the 9th to the 8th decile.

If in a particular case, the observed differences of the rates of the above mentioned quantiles are negligible, Pareto distribution will be an appropriate model of the considered wage distribution. In the case, the differences are quite material, the approximation of the considered wage distribution with Pareto distribution will be more or less inappropriate. More about the theory of Pareto distribution is described in statistical literature (Forbes, Evans, Hastings, & Peacock, 2011; Johnson, Kotz, & Balakrishnan, 1994; Kleiber & Kotz, 2003; Krishnamoorthy, 2006).

Parameter Estimates

If the Pareto distribution is chosen as a model for a particular distribution we have to keep in mind that this model is only an approximation. The wage distribution will be only approximated and the relations derived from the model will also hold for the “true distribution” only approximately. Which relations will hold more precisely and for which the precision will be lower will be mostly dependent on the method of parameter estimates.

There are many possibilities to choose from. In the following text the quantiles of Pareto distribution will be denoted as xP and the quantiles of the observed wage distribution will be denoted as yP.

First we need to decide which quantile to choose as xP0. It this article we will assume that xP0 = x0.99. From the equation (1) we can see that the considered Pareto distribution will be defined by the equation:

0.99 10.01

b

P

Pxx

−⎛ ⎞= ⎜ ⎟⎝ ⎠

(17)

Then we need to determine the value x0.99 and the value of the Pareto coefficient b. Because it is necessary to estimate the values of two parameters we need to choose two equations to estimate from.

A natural choice is the equation xP0 = yP0; that is in our case x0.99 = y0.99. As the other equation we set a quantile xP1 equal to the corresponding observed quantile, i.e., xP1 = yP1. In this case, the parameters of the model will be:

yx PP 00 = (18)

and using equation (9):

P0

1

1

0

log

1 Plog1

P

yy

b

P

=−−

(19)

We can get different modifications using different choice of the maximum wage and the second quantile. If we use equation x0.99 = y0.99 and we use the median in the second equation, i.e., x0.5 = y0.5 we get a model with


parameters:

0.99 0.99yx = (20)

0.99

0.5log

0.5log0.01

yyb =

(21)

Another possibility is setting any two quantiles of the model equal to the quantiles of the observed distribution:

1 1P Pyx = (22)

2 2P Pyx = (23)

Using the formula (10), we get the following parameter estimates:

PP

y

y

b P

P

−−

=

11

log

log

2

1

1

2

(24)

and from equations (11) and (12) we get:

1 20 1 2

0 0

1 P 11 P 1

b b

P P PP

y yx P⎛ ⎞ ⎛ ⎞− −

= =⎜ ⎟ ⎜ ⎟− −⎝ ⎠ ⎝ ⎠

(25)

With this alternative we can also get numerous modifications depending on the choice of quantiles yP1 and yP2 that are used.

The third possibility is based on the request that xP0 = yP0 and that the rate of some other two quantiles of the Pareto distribution xP2/xP1 is equal to the rate yP2/yP1 of correspoding quantiles of the wage distribution observed. In this case we will estimate the parameters using equation (10):

0 0P Pyx = (26)

P2

1

1

2

log

1 Plog1

P

yy

b

P

=−−

(27)

In this case, notwithstanding that xP2/xP1 = yP2/yP1 holds, the equality of quantiles itself, xP1 ≠ yP1 and xP2 ≠ yP2, does not hold. In this case, we can also arrive to numerous modifications depending on what maximum wage is chosen and what quantiles yP1 and yP2 are chosen.

For all of the above methods the equality of two characteristics of the model and the observed distribution was required. There are also different approaches to the parameter estimates.

The least squares method is frequently used for the Pareto distribution parameter estimates as well. We will consider the following quantiles of the observed wage distribution yP1, yP2, …, yPk and corresponding quantiles of the


Pareto distribution xP1, xP2, …, xPk. The model distribution will be most precise when the sum of squared differences:

∑=

−k

iPiPi xy

1

2)( (28)

is minimized. In this case closed formula solution does not exist. Therefore sum of squared differences of logarithms of quantiles is often considered:

2iPi1

( log )log ykP

ix∑

=−

(29)

Minimizing the objective function (29), it is possible to derive the following estimates:

0 0Pi1 1 1 i

22 0 0

1 1

1 1log loglog y log y

1 1

1 1loglog

1 1

k k k

Pii i ii

k k

i ii i

P Pk

P Pb

P Pk

P P

∑ ∑ ∑= = =

∑ ∑= =

− −−

− −=

⎛ ⎞− −− ⎜ ⎟− −⎝ ⎠

(30)

011

0

1loglog y 1log

kkiPii i

P

PP

bxk k

∑∑ ==

−−

= −

(31)

In the case we use this estimating method, it is needed to keep in mind that the equality of model quantiles and observed quantiles is not guaranteed for any P. Again we can arrive to different results depending on what quantiles yP1, yP2, …, yPk are used for the calculations. Furthermore the parameter estimates also depend on the choice of the maximum wage.

Characteristics of the Appropriateness of the Pareto Distribution

For the application of Pareto distribution as a model of the wage distribution, it is crucial that the model fits the observed distribution as close as possible. It is important that the observed relative frequencies in particular wage intervals are as close to the theoretical probabilities assigned to these intervals by the model as possible.

It is needed to note that the same parameter estimation method does not always lead to the best results. It is of particular importance in “what direction” is the observed wage distribution different from Pareto distribution. Pareto distribution assumes such wage differentiation that the relations (16) hold. With real data we can encounter many different situations:

0.75 0.8 0.9

0.5 0.6 0.8

y y yy y y

< < (32)

0.75 0.8 0.9

0.5 0.6 0.8

y y yy y y

> > (33)

0.75 0.9 0.8

0.5 0.8 0.6

y y yy y y

< < (34)

0.75 0.9 0.8

0.5 0.8 0.6

y y yy y y

> >

(35)

0.8 0.75 0.9

0.6 0.5 0.8

y y yy y y

< <

(36)


0.8 0.75 0.9

0.6 0.5 0.8

y y yy y y

> > (37)

It follows from equations (32)-(37) that the observed distributions will more or less systematically differ from the Pareto distribution. In the case of equation (32) the differentiation of the observed wage distribution is higher; in the case of equation (33) the differentiation will be lower than in the case of Pareto distribution. Some bias occurs in cases equations (34)-(37) as well (but cannot be so specified). Systematical bias should be a signal for potential adjustment of the model which could be based for example on adding one or more parameters into the model. These adjustments usually lead to more complicated models. Therefore, the above mentioned bias is often neglected and simple models are preferred even though they lead to some bias.

Wage Distribution of Males and Females in the Czech Republic in 2001-2008

The data used in this article is the gross monthly wage of male and female in CZK in the Czech Republic in the years 2001-2008. Data were sorted in the table of interval distribution with opened lower and upper bound in the lowest and highest interval respectively. The source is the web page of the Czech statistical office. The following quantiles were calculated (see Table 1).

Table 1 Median y0.50 (in CZK), 6th Decile y0.60 (in CZK), Upper Quartile y0.75 (in CZK), 8th Decile y0.80 (in CZK), 9th Decile y0.90 (in CZK) a 99th Percentile y0.99 (in CZK) of Gross Monthly Wages in the Czech Republic in the Years 2001-2008 (Total and Split up to Male and Female Separated) Year y0.50 y0.60 y0.75 y0.80 y0.90 y0.99 Total

2001 2002 2003 2004 2005 2006 2007 2008

12,502 15,545 16,735 17,709 18,597 19,514 20,987 22,310

14,042 17,125 18,458 19,557 20,566 21,564 23,227 24,696

16,987 20,215 22,224 23,077 24,470 25,675 27,590 29,553

18,254 22,193 23,797 24,849 26,328 27,693 29,900 31,769

23,319 27,754 29,590 31,082 33,292 35,230 37,892 40,541

44,921 47,172 47,719 56,369 56,852 57,326 66,395 68,828

Males

2001 2002 2003 2004 2005 2006 2007 2008

14,152 16,985 18,240 19,344 20,281 21,199 22,933 24,498

15,781 18,667 20,116 21,321 22,446 23,460 25,366 27,115

19,037 22,604 24,145 25,306 26,822 28,090 30,284 32,343

20,697 24,199 26,041 27,286 28,989 30,525 32,663 35,105

26,264 31,101 34,564 34,819 37,211 39,381 42,815 46,375

46,781 48,047 48,417 57,514 57,808 58,104 70,522 72,338

Females

2001 2002 2003 2004 2005 2006 2007 2008

10,770 13,746 14,831 15,642 16,454 17,311 18,390 19,399

12,187 15,181 16,453 17,303 18,211 19,202 20,392 21,600

14,655 17,727 19,281 20,293 21,426 22,530 24,024 25,558

15,700 18,903 20,628 21,560 22,804 23,966 25,924 27,215

18,904 23,291 24,637 25,776 27,503 29,082 31,338 33,405

37,526 43,339 44,883 50,776 52,508 54,054 58,649 63,628


From Table 2, we can see that, with the exception of male in the year 2003, 2007 and 2008, all other wage distributions have lower differentiation than Pareto distribution. The systematical error occurred also in the case of male in the year 2003, 2007 and 2008. It follows from the empirical criterion (16) and from Table 2 that in all cases the differences between the rates of the considered quantiles are negligible and therefore Pareto distribution can be used as the model of the distribution.

The 99th percentile will be considered as a characteristic of the maximum wage. The parameters of the Pareto distribution are estimated using the above described methods.

First we consider the conditions xP0 = yP0 a xP1 = yP1 and we chose median as the second quantile, i.e., x0.99 = y0.99 and x0.5 = y0.5. We estimate the parameter b using the formula (21). The summary of the parameter estimates is in Table 3.

Table 2 The Rates of Quantiles y75/y50, y80/y60 and y90/y80 of the Wage Distributions in the Years 2001-2008 and Its Relations

Year 0.75

0.50

yy

0.80

0.60

yy

0.90

0.80

yy Relations between quantile rates

Total 2001 1.358815 1.299910 1.277456 (21.2) 2002 1.300422 1.295897 1.250612 (21.2) 2003 1.327994 1.289216 1.243457 (21.2) 2004 1.303112 1.270608 1.250812 (21.2) 2005 1.315815 1.280162 1.264514 (21.2) 2006 1.315734 1.284213 1.272161 (21.2) 2007 1.314623 1.287295 1.267291 (21.2) 2008 1.324653 1.286403 1.276118 (21.2) Males 2001 1.345148 1.311556 1.268936 (21.2) 2002 1.330847 1.296386 1.285203 (21.2) 2003 1.323680 1.294561 1.327273 (21.5) 2004 1.308222 1.279734 1.276084 (21.2) 2005 1.322543 1.291532 1.283632 (21.2) 2006 1.325086 1.301135 1.290146 (21.2) 2007 1.320542 1.287669 1.310810 (21.4) 2008 1.320230 1.294671 1.321037 (21.5) Females 2001 1.360723 1.288227 1.204113 (21.2) 2002 1.289624 1.245137 1.232163 (21.2) 2003 1.300019 1.253747 1.194319 (21.2) 2004 1.297375 1.246052 1.195526 (21.2) 2005 1.302189 1.252237 1.206076 (21.2) 2006 1.301488 1.248134 1.213470 (21.2) 2007 1.306362 1.271283 1.208841 (21.2) 2008 1.317491 1.259954 1.227448 (21.2)

Next we apply the conditions xP1 = yP1 and xP2 = yP2 and we choose 6th and 9th decile for yP1 and yP2. We use the formulas (24) and (25) to estimate the parameters. The summary of the parameter estimates is in Table 3.

Parameters of the Pareto distribution can also be estimated using the equations xP0 = yP0 and xP2/xP1 = yP2/yP1. We choose the 9th and 6th decile in the rate yP2/yP1. In this case we use the relations (26) and (27) to estimate the parameters. The summary of the parameter estimates is also in Table 3.


Table 3 Estimated Parameters of Pareto Distribution for Different Choices of the Estimation Equations

Equations used

x0.99 = y0.99, x0.5 = y0.5 x0.6 = y0.6, x0.9 = y0.9 0.9 0.9

0.99 0.990.6 0.6

, yxyxyx

= =

Parameter estimates Parameter estimates Parameter estimates Year xP0 b xP0 b xP0 b Total

2001 2002 2003 2004 2005 2006 2007 2008

44,921 47,172 47,719 56,369 56,852 57,326 66,395 68,828

0.326952 0.283758 0.267846 0.295969 0.299456 0.275468 0.294405 0.287978

54,143 61,890 64,800 67,096 74,095 79,614 85,426 92,352

0.365843 0.348293 0.340425 0.334192 0.347455 0.354083 0.353045 0.357552

44,921 47,172 47,719 56,369 56,852 57,326 66,395 68,828

0.365843 0.348293 0.340425 0.334192 0.347455 0.354083 0.353045 0.357552

Males

2001 2002 2003 2004 2005 2006 2007 2008

46,781 48,047 48,417 57,514 57,808 58,104 70,522 72,338

0.305624 0.265814 0.249540 0.278536 0.267749 0.257739 0.287153 0.276777

61,207 72,613 84,934 78,632 86,165 93,098

102,142 113,087

0.367449 0.368246 0.390464 0.353784 0.364658 0.373653 0.377610 0.387128

46,781 48,047 48,417 57,514 57,808 58,104 70,522 72,338

0.367449 0.368246 0.390464 0.353784 0.364658 0.373653 0.377610 0.387128

Females

2001 2002 2003 2004 2005 2006 2007 2008

37,526 43,339 44,883 50,776 52,508 54,054 58,649 63,628

0.319087 0.293539 0.283055 0.300989 0.296625 0.291062 0.296461 0.303636

39,196 47,418 48,172 49,971 54,551 57,954 63,977 68,917

0.316679 0.308749 0.291217 0.287505 0.297414 0.299456 0.309955 0.314516

37,526 43,339 44,883 50,776 52,508 54,054 58,649 63,628

0.316679 0.308749 0.291217 0.287505 0.297414 0.299456 0.309955 0.314516

In the end we also estimate the parameters of the Pareto distribution using the least squares method. We use the relations (30) and (31). In this method, we choose 5th, 6th, 7th, 8th and 9th deciles of the observed wage distribution, i.e., k = 5. Parameters estimated using the least squares method are summarized in Table 4.

Table 4 Parameters Estimated Using the Least Squares Method

Year Parameter estimates

Total Males Females xP0 b xP0 b xP0 b

2001 2002 2003 2004 2005 2006 2007 2008

56.562 64.026 67.219 69.311 76.310 81.721 88.022 94.849

0.379911 0.358469 0.351034 0.344615 0.356935 0.362626 0.362359 0.366387

63.774 73.770 85.080 80.310 88.251 95.225

103.405 114.131

0.379912 0.372825 0.391617 0.360986 0.372535 0.381012 0.383183 0.391293

42.520 49.188 51.125 52.763 57.413 60.917 67.572 72.463

0.341047 0.320682 0.309187 0.303849 0.312826 0.315022 0.325878 0.330659

The values of the sum of absolute differences of observed and theoretical absolute frequencies of all


intervals calculated for all cases considered wage distributions are in Table 5. In the case of the theoretical frequencies at first we determined theoretical probabilities using the formula (8). From these, we determined theoretical absolute frequencies.

Table 5 Sums of the Absolute Differences of the Observed and Theoretical Frequencies

Year

Equations used

x0.99 = y0.99 x0.5 = y0.5

x0.6 = y0.6 x0.9 = y0.9

x0.99 = y0.99

0.9 0.9

0.6 0.6

yxyx

= Least squares method

Total

2001 2002 2003 2004 2005 2006 2007 2008

37,459 51,358 73,388

103,625 167,946 157,094 268,740 282,396

23,255 27,327 36,520 64,422 69,930 68,849

260,786 253,373

85,795 171,404 204,535 249,348 353,661 426,442 322,437 372,117

23,859 31,658 39,722 66,249 68,679 69,104

262,224 257,050

Males

2001 2002 2003 2004 2005 2006 2007 2008

20,603 33,576 47,909 60,241 81,505 96,789

140,965 135,960

10,089 19,711 23,576 32,457 35,349 37,737

138,678 133,953

56,291 111,796 96,863

178,858 220,276 250,764 202,143 173,262

9,959 20,298 23,747 33,076 36,321 37,653

139,428 135,089

Females

2001 2002 2003 2004 2005 2006 2007 2008

24,256 23,697 37,215 45,429 51,793 58,014

138,241 140,955

23,926 16,716 30,902 41,416 41,615 41,137

128,854 132,125

23,687 42,148 40,237 45,460 52,493 74,302

150,258 155,071

21,270 18,595 30,011 40,957 41,449 41,812

127,313 131,224

Conclusions

The appropriateness of particular modifications of the Pareto distribution can be evaluated comparing the theoretic and empirical frequencies. It is possible to compare both the absolute and relative differences between the theoretic and observed empirical distributions. In this article we used the absolute differences. The values sums these differences are in Table 5. The values seem to be relatively high. The question of appropriateness of a given theoretic wage distribution in the case of large samples was described in statistical literature (Bílková, 2007). Some more general conclusions can be made from the values of the absolute differences of observed and theoretic distributions.

With the exception of the wage distribution of women in 2001, the worst results are achieved using the equation x0.99 = y0.99 and setting the ratio of other two quantiles of the Pareto distribution x0.9/x0.6 equal to the ratio y0.9/y0.6 of the corresponding empirical quantiles. This fact is less obvious for female distribution and most obvious for total distribution. This is also due to the larger sample size of the total sample (in comparison with the


sample size of the sub-groups of male and female). Again with the exception of the wage distribution of women in 2001 the second worst model is the estimate based on the equations x0.99 = y0.99 and x0.5 = y0.5. This fact is again less obvious for female distribution and most obvious for total distribution. In the case of the wage distribution of women in 2001, the worst estimate is based on the equations x0.99 = y0.99 and x0.5 = y0.5. In the case of the total group is the third worst (second best) method the least squares method (with the exception of 2005). The best results are achieved with the method based on the equations x0.6 = y0.6 and x0.9 = y0.9. In the case of the total wage distribution in 2005 is the third worst method based on the equations x0.6 = y0.6 and x0.9 = y0.9 and the best method is the least squares method. In the case of the wage distribution of male (with the exception of the years 2001 and 2006), the third worst (second best) results are again achieved using the least squares method. The best results are achieved with the method based on the equations x0.6 = y0.6 and x0.9 = y0.9. In the years 2001 and 2006 (set of men) is the third worst method the method based on the equations x0.6 = y0.6 and x0.9 = y0.9 and the best is the least squares method. In the case of the female group (with the exception of the years 2001, 2002 and 2006) is the third worst (second best) method based on the equations x0.6 = y0.6 and x0.9 = y0.9 and the most precise results are achieved with the least squares method. In the years 2001, 2003, 2004 and 2005 was for the group of women the most precise the least squares method. The very best method for the group of male in 2001 was the least squares method. In this case other methods had much higher values of the above mentioned sum of absolute differences.

From the above described comparison, it is obvious that the simplest parameter estimating methods can be in the case of the Pareto distribution competing with more advanced methods.

References Bartošová, J. (2006). Logarithmic-normal model of income distribution in the Czech Republic. Austrian Journal of Statistics, 35(23),

215-222. Bartošová, J., & Bína, V. (2009). Modelling of income distribution of Czech households in years 1996-2005. Acta Oeconomica

Pragensia, 17(4), 3-18. Bílková, D. (2007). Modeling of income distributions using lognormal distribution. In 10th International Scientific Conference

AMSE—Applications of matematics and statistics in Ekonomy. Poprad-Tatry, Slovakia, August 29-September 1, 2007, CD. Dutta, J., Sefton, J. A., & Weale, M. R. (2001). Income distribution and income dynamics in the United Kingdom. Journal of

Applied Econometrics, 16(5), 599-617. Forbes, C., Evans, M., Hastings, N., & Peacock, B. (2011). Statistical diatributions (4th ed.) (p. 212). New Jersey: John Wiley &

Sons. Johnson, N. L., Kotz, S., & Balakrishnan, N. (1994). Continuous univariate distributions (2nd ed.) (p. 756). New York: John Wiley

& Sons. Kleiber, Ch., & Kotz, S. (2003). Statistical size distributions in economics and actuarial sciences (p. 332). New Jersey: John Wiley

& Sons. Krishnamoorthy, K. (2006). Handbook of statistical distributions with applications (p. 346). Boca Rato: Chapman & Hall/CRC

Press. Majumder, A., & Chakravarty, S. R. (1990). Distribution of personal income: Development of a new model and its application to

U. S. income data. Journal of Applied Econometrics, 5(2), 189-196. McDonald, J. B. (1984). Some generalized functions for the size distribution of income. Econometrica, 52(3), 647-665. McDonald, J. B., & Butler, R. J. (1987). Some generalized mixture distributions with an application to unemployment duration. The

Review of Economics and Statistics, 69(2), 232-240. McDonald, J. B., & Snooks, G. D. (1985). The determinants of manorial income in domesday England: Evidence from Essex. The

Journal of Economic History, 45(3), 541-556.


The Chaotic Monopoly Price Growth Model

Vesna D. Jablanovic University of Belgrade, Belgrade, Serbia

Deterministic chaos refers to an irregular or chaotic motion that is generated by nonlinear systems. The chaotic

behavior is not to quantum-mechanical-like uncertainty. Chaos theory is used to prove that erratic and chaotic

fluctuations can indeed arise in completely deterministic models. Chaotic systems exhibit a sensitive dependence

on initial conditions. Seemingly insignificant changes in the initial conditions produce large differences in

outcomes. To maximize profit, the monopolist must first determine its costs and the characteristics of market

demand. Given this knowledge, the monopoly firm must then decide how much to produce. The monopoly firm can

determine price, and the quantity it will sell at that price follows from the market demand curve. The basic aim of

this paper is to construct a relatively simple chaotic growth model of the monopoly price that is capable of

generating stable equilibria, cycles, or chaos. A key hypothesis of this work is based on the idea that the coefficient,

( )( )1 1e b

m eπ

α⎡ ⎤

= ⎢ ⎥− +⎣ ⎦ plays a crucial role in explaining local stability of the monopoly price, where,

b—the coefficient of the marginal cost function of the monopoly firm, m—the coefficient of the inverse demand

function, e—the coefficient of the price elasticity of the monopoly demand, α—the coefficient.

Keywords: monopoly, price, chaos

Introduction

Chaos theory attempts to reveal structure in unpredictable dynamic systems. It is important to construct deterministic, nonlinear economic dynamic models that elucidate irregular, unpredictable economic behavior. Deterministic chaos refers to irregular or chaotic motion that is generated by nonlinear systems evolving according to dynamical laws that uniquely determine the state of the system at all times from the knowledge of the system’s previous history. Chaos embodies three important principles: (1) extreme sensitivity to initial conditions; (2) cause and effect are not proportional; and (3) nonlinearity.

Chaos theory can explain effectively unpredictable economic long time behavior arising in a deterministic dynamical system because of sensitivity to initial conditions. A deterministic dynamical system is perfectly predictable given perfect knowledge of the initial condition, and is in practice always predictable in the short term. The key to long-term unpredictability is a property known as sensitivity to (or sensitive dependence on) initial conditions.

Chaos theory started with Lorenz’s (1963) discovery of complex dynamics arising from three nonlinear Vesna D. Jablanovic, Associate Professor of Eonomics, Faculty of Agriculture, University of Belgrade. Correspondence about this article should be sent to Vesna D. Jablanovic, Vinogradski venac 20, 11000 Belgrade, Serbia. E-mail:

[email protected].

THE CHAOTIC MONOPOLY PRICE GROWTH MODEL 986

differential equations leading to turbulence in the weather system. Li and Yorke (1975) discovered that the simple logistic curve can exibit very complex behavior. Further, May (1976) described chaos in population biology. Chaos theory has been applied in economics by Benhabib and Day (1981, 1982), Day (1982, 1983, 1997), Grandmont (1985), Goodwin (1990), Medio (1993, 1996), Lorenz (1993), Jablanovic (2010, 2011), among many others.

The basic aim of this paper is to provide a relatively simple chaotic the monopoly price growth model that is capable of generating stable equilibria, cycles, or chaos.

A Simple Chaotic Price Growth Model of a Profit-Maximizing Monopoly

In the model of a profit-maximizing monopoly, take the inverse demand function: Pt = n – mQt (1)

Where P—monopoly price; Q—monopoly output; n, m—coefficients of the inverse demand function. Further, suppose the quadratic marginal-cost function for a monopoly is:

MCt = a + bQt + cQt2 (2)

MC—marginal cost; Q—monopoly output ; a, b, c—coefficients of the quadratic marginal-cost function. Marginal revenue is:

⎥⎦

⎤⎢⎣

⎡⎟⎠⎞

⎜⎝⎛+=

ePMR tt

11 (3)

MR—marginal revenue; P—monopoly price; e—the coefficient of the price elasticity of demand. A monopoly firm maximizes profit by producing the quantity at which marginal revenue equals marginal

cost. Thus the profit-maximizing condition is that: MRt = MCt (4)

Further, MCt+1 = MCt + ΔMC (5)

Or MCt+1 = MCt + αMCt+1 (6)

i.e., (1-α ) MCt+1 = MCt (7)

Thus, the chaotic model of the profit-maximizing monopoly is presented by the equations (1)-(4) and (7). Where: Q—output of the monopoly firm; MC—marginal cost; MR—marginal revenue; P—monopoly price; e—the coefficient of the price elasticity of demand; n, m—coefficients of the inverse demand function; a, b, c—coefficients of the quadratic marginal-cost function.

Firstly, it is supposed that a = 0 and n = 0. By substitution one derives:

( ) ( ) ( ) ( )2

1 21 1 1 1t t te b e cP P P

m e m eα α+ = −− + − +

(8)

Further, it is assumed that the monopoly price is restricted by its maximal value in its time series. This premise requires a modification of the growth law. Now, the monopoly price growth rate depends on the current size of the monopoly price, P, relative to its maximal size in its time series Pm. We introduce p as p = P/Pm. Thus, p ranges between 0 and 1. Again we index p by t, i.e., write pt to refer to the size at time steps t = 0, 1, 2, 3, .... Now, growth rate of the monopoly price is measured as:


( ) ( ) ( ) ( )2

21 1111 ttt pem

cepem

bep+−

−+−

=+ αα (9)

This model given by equation (9) is called the logistic model. For most choices of b, c, m, and e, there is no explicit solution for equation (9). Namely, knowing b, c, m, and e and measuring p0 would not sufficient to predict pt for any point in time, as it was previously possible. This is at the heart of the presence of chaos in deterministic feedback processes. Lorenz (1963) discovered this effect—the lack of predictability in deterministic systems. Sensitive dependence on initial conditions is one of the central ingredients of what is called deterministic chaos.

This kind of difference equation (9) can lead to a very interesting dynamic behavior, such as cycles that repeat themselves every two or more periods, and even chaos, in which there is no apparent regularity in the behavior of pt. This difference in equation (9) will possess a chaotic region. Two properties of the chaotic solution are important: firstly, given a starting point p0 the solution is highly sensitive to variations of the parameters b, c, m, and e; secondly, given the parameters b, c, m, and e the solution is highly sensitive to variations of the initial point p0 . In both cases the two solutions are for the first few periods rather close to each other, but later on they behave in a chaotic manner.

Logistic Equation

The logistic map is often cited as an example of how complex, chaotic behavior can arise from very simple non-linear dynamical equations. The logistic model was originally introduced as a demographic model by Pierre François Verhulst. It is possible to show that iteration process for the logistic equation:

zt+1 = πzt(1 - zt), π∈[ 0 ,4], zt∈[0 ,1] (10) is equivalent to the iteration of growth model (9) when we use the following identification:

t te cz p

e b m= (11)

and

( )( )⎥⎦

⎤⎢⎣

⎡+−

=11 em

beα

π (12)

Using equation (9) and equation (11) we obtain:

( ) ( ) ( ) ( )2

1 1 21 1 1 1t t t te c e c e b e cz p p p

e b m e b m m e m eα α+ +

⎡ ⎤⎛ ⎞ ⎛ ⎞⎛ ⎞ ⎛ ⎞= = −⎢ ⎥⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎜ ⎟ ⎜ ⎟ ⎜ ⎟− + − +⎝ ⎠ ⎝ ⎠ ⎢ ⎥⎝ ⎠ ⎝ ⎠⎣ ⎦

( ) ( ) ( ) ( )2

tp1e13bme

2c2etp

1e12m

ce⎟⎟

⎠

⎞

⎜⎜

⎝

⎛

+−α−⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛

+−α=

On the other hand, using equations (10)-(12) we obtain:

( ) ( ) ( )1 1 11 1t t t t t

e b e c e cz z z p pm e e b m e b m

πα+

⎛ ⎞ ⎡ ⎤⎛ ⎞ ⎛ ⎞= − = −⎜ ⎟ ⎢ ⎥⎜ ⎟ ⎜ ⎟⎜ ⎟− + ⎝ ⎠ ⎝ ⎠⎣ ⎦⎝ ⎠

( ) ( ) ( ) ( )

2 22

2 31 1 1 1t te c e cp p

m e e b m eα α⎛ ⎞ ⎛ ⎞

= −⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎜ ⎟− + − +⎝ ⎠ ⎝ ⎠


Thus, we have that iterating ( ) ( ) ( ) ( )

21 21 1 1 1t t t

e b e cp p pm e m eα α+ = −

− + − + is really the same as

iterating zt+1 = πzt(1 - zt ) using t t

e cz pe b m

= and ( )( )1 1

e bm e

πα

⎡ ⎤= ⎢ ⎥− +⎣ ⎦

.

It is important because the dynamic properties of the logistic equation (10) have been widely analyzed (Li & Yorke, 1975; May, 1976).

It is obtained that: (1) For parameter values 0 < π < 1 all solutions will converge to z = 0; (2) For 1 < π < 3.57, there exist fixed points the number of which depends on π; (3) For 1 < π < 2, all solutions monotnically increase to z = (π - 1)/π; (4) For 2 < π < 3, fluctuations will converge to z = (π - 1)/π; (5) For 3 < π < 4, all solutions will continously fluctuate; (6) For 3.57 < π < 4, the solution become “chaotic” wihch means that there exist a totally aperiodic solution

or periodic solutions with a very large, complicated period. This means that the path of zt fluctuates in an apparently random fashion over time, not settling down into any regular pattern whatsoever.

Conclusion

This paper suggests conclusion for the use of the simple chaotic model of a profit—maximizing monopoly in predicting the fluctuations of the monopoly price. The model (9) has to rely on specified parameters b, c, m, and e, and initial value of the monopoly price, p0. But even slight deviations from the values of parameters parameters b, c, m, and e and initial value of the monopoly price, show the difficulty of predicting a long-term behavior of the monopoly price, p0.

A key hypothesis of this work is based on the idea that the coefficient plays a crucial role in explaining local stability of the monopoly price:

( )( )1 1e b

m eπ

α⎡ ⎤

= ⎢ ⎥− +⎣ ⎦

where b is the coefficient of the marginal cost function of the monopoly firm, m is the coefficient of the inverse demand function, e is the coefficient of the price elasticity of monopoly’s demand, α is the coefficient.

The quadratic form of the marginal cost function of the monopoly firm is important ingredient of the presented chaotic monopoly price growth model (9).

References Benhabib, J., & Day, R. H. (1981). Rational choice and erratic behaviour. Review of Economic Studies, 48, 459-471. Benhabib, J., & Day, R. H. (1982). Characterization of erratic dynamics in the overlapping generation model. Journal of Economic

Dynamics and Control, 4, 37-55. Benhabib, J., & Nishimura, K. (1985). Competitive equilibrium cycles. Journal of Economic Theory, 35, 284-306. Day, R. H. (1982). Irregular growth cycles. American Economic Review, 72, 406-414. Day, R. H. (1983). The emergence of chaos from classica economic growth. Quarterly Journal of Economics, 98, 200-213. Day, R. H. (1997). Complex economic dynamics volume I: An introduction to dynamical systems and market mechanism. In

Discrete Dynamics in Nature and Society (pp. 177-178), 1. MIT Press. Gandolfo, G. (2009). Economic dynamics (4th ed.). Berlin: Springer-Verlag.


Goodwin, R. M. (1990). Chaotic economic dynamics. Oxford: Clarendon Press. Grandmont, J. M. (1985). On enodgenous competitive business cycles. Econometrica, 53, 994-1045. Jablanović, V. (2010). Chaotic population growth. Belgrade: Cigoja. Jablanović, V. (2011). The chaotic saving growth model: G 7. Chinese Business Review, 10(5), 317-327. Li, T., & Yorke, J. (1975). Period three implies chaos. American Mathematical Monthly, 8, 985-992. Lorenz, E. N. (1963). Deterministic nonperiodic flow. Journal of Atmospheric Sciences, 20, 130-141. Lorenz, H. W. (1993). Nonlinear dynamical economics and chaotic motion (2nd ed.). Heidelberg: Springer-Verlag. May, R. M. (1976). Mathematical models with very complicated dynamics. Nature, 261, 459-467. Medio, A. (1993). Chaotic dynamics: Theory and applications to economics. Cambridge: Cambridge University Press. Medio, A. (1996). Chaotic dynamics. Theory and applications to economics. De Economist, 144(4), 695-698. Peitgen, H. O., Jürgens, H., & Saupe, D. (1992). Chaos and fractals-new frontiers of science. New York: Springer-Verlag. Rössler, O. E. (1976). An equation for continuous chaos. Physics Letters A, 57, 397-398. Tu, P. N. V. (1994). Dynamical systems. Verlag: Springer.


Analysis of the Relationship Between Perceived Security

and Customer Trust and Loyalty in Online Shopping

Nihan Özgüven Dokuz Eylul University, Izmir, Turkey

Advancements in the internet technology triggered a line of developments in the field of marketing. As an

alternative to the conventional shopping, online shopping over the internet has gained substantial share of retail

market. Customers get used to this new shopping venue and nowadays prefer it more and more according to the

researchers, ten percent of the global population now uses internet for shopping. In this research, the author

explored the relationship between the security measures implemented by a company, very active in the online

shopping domain, and the customer trust and loyalty on the online services provided by this company. Findings of

this research are based on survey data analyzed in SPSS. This research supports the existence of a relationship

between the security of a company’s website and customer trust and loyalty on the online services of this company.

When the perception of security measures improves, customer trust and loyalty increases accordingly.

Keywords: customers, customer trust, perceived security, loyalty, online shopping, websites

Introduction

Today’s companies have to take advantage of the opportunities offered by the internet in order to be one step ahead of its competitors. Leaving aside the traditional shopping, they need to differentiate themselves via this modern communication channel as online shopping emerges as a new domain.

However, customers are confused with the increasing numbers of websites day by day. In this context, companies have to generate publicity, create user blogs and provide the most honest information about their products and services in order to shine out among the realm of websites. Only then, they can attract the attention and interest of the customers, according to Faks (2008).

Only after companies fully meet the customers’ needs and expectations, customer trust starts to build-up, according to Ural (2009). Online shopping turnover is increasing year by year, and the main drivers of this increase include the form of payment options offered to ease up the process and value-added services provided to increase the customer satisfaction. With these advancements, online shopping today has reached about four times the size of the traditional shopping for certain goods and services.

Today, from the electronic goods to car rentals to all kinds of sports materials, a wide range of goods and

Nihan Özgüven, Ph.D., Department of Business Administration, Dokuz Eylul University. Correspondence about this article should be sent to Nihan Özgüven, Dokuz Eylul University, Faculty of Economics and

Administrative Sciences, Department of Business Administration, Dokuzcesmeler Campus, 35160, Buca-Izmir/Turkey. E-mail: [email protected].

PERCEIVED SECURITY AND CUSTOMER TRUST AND LOYALTY 991

services can be purchased over the internet. Traditional retail companies are under continuous pressure of pleasing their customers and following the advancements in business to maintain their position in the market. From this perspective, easy and secure online payment applications facilitate the everyday business of these companies. A list of companies, including banks and credit card companies, have lost market share in this dynamic era as they failed to carry over the customer loyalty, brand awareness and thereby, the share of mind they used to own to the online media. Even if these companies make online payment available, their brands can get lost among numerous e-wallets. In particular, credit card and payment companies remain behind the competition when the customer accounts are linked directly to e-wallets.

In the study, the literature reviewed is primarily about online shopping and its effects on the perceived reliability, and the trust and loyalty variables are explained and the relationship between these variables and online shopping are revealed.

Literature Overview

In the study which researched the impact of customer trust on e-commerce, Kim, Chung and Lee (2011) concluded that internet security measures have positive impact on customer trust and no impact on transportation costs while customer satisfaction has positive impact on trust and commitment. Bellman, Lohse and Johnson (1999) explored the relationship between customers’ demographic characteristics, personality traits and attitude towards online shopping; they identified that customer lifestyle is effective on attitude towards online shopping and customers with time limitations tend to do more online shopping. Separately, Jarvenpaa, Tractinsky and Vitale (2000) explored the setup of online shopping website and company reputation in relation to risk perception, customer trust and attitude and demand; they emphasized that there is a positive relationship between company reputation and consumer trust and as trust improves, risk perception decreases.

Ou, SIA and Banerjee (2007) explored the Chinese market and identified the mistrust in the websites, lack of regulatory framework and limited product offer as the reasons behind the slow development of online shopping over there. Teo (2002) examined customer attitude towards online shopping and Internet and concluded that companies do not encourage customers to shop online and customers do not embrace the idea of online shopping. In addition, he emphasized that customers do use internet to collect information, rather than shopping.

Perceived Security, Trust and Loyalty

In the online shopping domain, website security is important for the sense of trust and loyalty. The security of the website is essential to attract customer traffic and this is only possible with the security measures put in place.

Perceived security. Security is the fundamental concern of the customers who want to shop over the internet, according to Suh and Han (2003). Failure to put in place adequate security measures that assure the confidentiality of the customer data is the major barrier in front of the e-commerce development, according to Furnell and Karweni (1999). In the online shopping domain, perceived security depends on the reliability of the payment methods as well as the data transmission and storage. In other words, perceived security is the customer perception on the quality of tools and processes used for personal information transmission and storage, according to Kolsaker and Payne (2002).


Trust. In the online shopping, companies with online sales services thorough their websites focus on the customer trust and online purchasing experience. In traditional shopping, customer trust depends on the salesperson and company image whereas in online shopping, it depends on the reaction of buyers, their e-commerce experience and purchasing style, according to Kim, Ferriand and Rao (2008). Trust is a relationship of exchange between the uncertainty, sensitivity and commitment, according to Jarvenpaa, Noam, and Vitale (2000). Trust is also considered in connection with the communication, commitment, satisfaction and relationship marketing theories, according to Flavian and Guinaliu (2006).

Loyalty. Loyalty in online shopping means customers continuing to shop at a website that they have shopped before and recommending it to their friends, according to Cyr (2008). Loyalty is a result of consistent satisfaction the customer gets from a product or service the purchases for himself and his family, according to Assael (1990) loyalty is also defined as a “saturation in satisfaction”, according to Altıntas (2000) to develop loyal customers, companies create online virtual communities; by focusing on online virtual communities, they both gain potential customers and retain the existing ones, according to Kim, Lee, and Hiemstra (2004, p. 343).

Methodology

As part of this study, a questionnaire was prepared, collected data were analyzed using SPSS 16 program and the results were interpreted. Studies of Chen (2006), Kim, Chung and Lee (2011), Wu and Chang (2003) were used as references while preparing the basic scale expressions in the survey form.

Objective of the study. This research aims to understand the relationship between perceived security and customer trust and loyalty towards online shopping and different websites. The study covers online shopping customers in Turkey.

Findings of the study. Findings of the research, as the outcome of the analysis conducted, are shown below. Reliability of the scale statements has been also analyzed.

As the result of reliability analysis, the overall average of the scale statements is found as 2.8670 and the correlation between questions is 0.4501. These findings show that the correlation between questions is low. The analysis of the reliability value is obtained as 0.8986 accordingly, indicating a high reliable scale (0.80 < α <1).

Table 1 shows the demographic characteristics of people who filled in the questionnaire. Among the participants of this survey, 42% were female and 58% were male. According to the data

collected, the larger portion of the survey respondents were male and men use online shopping more. The distribution of respondents by age groups are as follows: 33% of respondents are aged 18-25 years, 23% are aged 26-35 years, 21% are aged 36-45 years, 8% are aged 46-55 years, 8% are aged 56-65 years and 7% are more than 65 years old. According to these findings, most respondents are aged 18-25 years and young. This is a well-expected finding as younger people use the Internet more frequently. Seven percent of survey respondents are primary school graduates, 7% are secondary school graduates, 22% are middle school graduates, 13% are associate degree graduates, 40% have undergraduate and 11% have graduate degrees. Accordingly, most respondents have a graduate degree which indicates that online shoppers have relatively high levels of education. Sixty percent of respondents are married and 40% of them are unmarried. Among the respondents of survey, 3% earn 500-1,000 TL, 14% earn 1,001-1,500 TL and 1,501-2,000 TL, 9%, earn 2,001-2,500 TL, 15% earn 2,501-3,000 TL, 18% earn 3,001-3,500 TL, 8% earn 3,501-4,000 TL, 9% earn 4,001-4,500 TL, 4% earn


4,501-5,000 TL and 6% earn 5,001 TL or more than on monthly basis. This finding shows that the majority of the respondents in the range of 3,001-3,500 TL income level have a high level of income compared to the overall country average. Six percent of the surveyed work in public sector, 19% of them work in private sector, 5% are housewives, 8% are retired, 12% of them are students, 32% are self-employed and 13% are trader. Most of the participants are self-employed.

Table 1 Demographic Characteristics Frequency % Occupation Frequency % Gender

female 175 42.16 Businessman, top executive 24 5.78 male 240 57.84 Public sector worker 25 6.03

Age Private sector worker 80 19.28 18-25 135 32.53 housewife 20 4.81 26-35 95 22.89 Retired 31 7.47 36-45 85 20.49 Student 50 12.05 46-55 35 8.43 Self-employment 134 32.29 56-65 35 8.43 Tradesman 51 12.29 65 and more 30 7.23 Revenue

Education 500-1,000 13 3.1 primary 30 7.23 1,001-1,500 56 13.5 secondary 30 7.23 1,501-2,000 58 14.0 collage 90 21.68 2,001-2,500 38 9.2 two-year degree 55 13.25 2,501-3,000 61 14.7 university 165 39.76 3,001-3,500 75 18.1 master degree 45 10.85 3,501-4,000 32 7.7

Marital status 4,001-4,500 38 9.2 married 250 60.24 4,501-5,000 17 4.1 single 165 39.76 5,001- and more 27 6.5

Total 415 100 Total 415 100

Table 2 Results of Factor Analysis Factors definitions Trust Perceived security Loyalty G1 0.604 G2 0.779 G3 0.748 S1 0.753 S2 0.683 S3 0.733 S4 0.637 B1 0.882 B2 0.874 B3 0.888 B4 0.823

As shown in Table 2, the first factor, trust has 3; the second factor, perceived security has 4 and the last factor, loyalty has 4 questions. Factor loadings of the questions for the first factor are between 0.604 and 0.779;


for the second factor are between 0.637 and 0.753 and for the third factor are between 0.888 and 0.823. All factor load values high. The first factor explains 30.566% of the total variance, the second factor explains 23.747% and the third factor explains 25.277% of the total variance. According to the obtained findings, the first factor, trust is more explanatory than the other factors.

Table 3 shows the correlation between the scale dimensions.

Table 3 The Correlation on the Scale Dimensions Trust Perceived security Loyalty Trust Pearson correlation 1 0.715 0.637 Sig. (2-tailed) 0.000 0.000 No. 415 415 415 Perceived security Pearson correlation 0.715 1 0.871 Sig. (2-tailed) 0.000 0.000 No. 415 415 415 Loyalty Pearson correlation 0.637 0.871 1 Sig. (2-tailed) 0.000 0.000 No. 415 415 415

There is a strong direct correlation between trust, perceived security and loyalty dimensions.

Table 4 T-test Results of the Scale on the Statements Definitions No. Mean Std. deviation Std. error mean Trust The web sites which provides online shopping are honest 415 2.7590 1.00470 0.04932 The web sites that offer online shopping are reliable 415 2.7012 0.94146 0.04621 Web sites are safe 415 2.7060 0.93784 0.04604 Perceived security The web site which I give credit card number to get my product, is safe 415 2.8627 1.08031 0.05303 In general, making online payment is risk-free 415 2.6747 1.05533 0.05180 Online sales firms, honest about my personal data is kept private 415 2.9012 0.98901 0.04855 Online sales firms offer a guarantee of confidentiality in all matters 415 2.9205 1.02667 0.05040 Loyalty Web sites easy to think that the process of purchasing 415 3.6241 1.03951 0.05103 I would recommend to friends online shopping 415 3.3446 1.15859 0.05687 I prefer online shopping and traditional shopping methods 415 2.6096 1.16590 0.05723 Most of my purchases are in online shopping 415 2.4337 1.06767 0.05241

When the scale expressions are evaluated in 5-point Likert scale, response 3 means that customers are undecided on this specific point. Accordingly, test value was taken as 3. In Table 3, the average values of the scale are given. If the average value of the expressions is more than 3, then it means that the respondents agree. However, when the t values in Table 4 interpreted together with the values in Table 5, respondents do agree in the statements 8 and 9. These statements are as follows: “I think the online purchasing process is easy” and “I would recommend online shopping to my friends”. Respondents do not agree on the other statements about perceived


security and trust. The two expressions respondents agree are about with loyalty. Accordingly, it can be concluded that respondents are more loyal to the online shopping than the average.

Table 5 Levels of Significance on the Statements of Scale Test value = 3

t df Sig. (2-tailed) Mean difference 95% trust interval of the difference Lower Upper

G1 -4.886 414 0.000 -0.2410 -0.3379 -0.1440 G2 -6.465 414 0.000 -0.2988 -0.3896 -0.2080 G3 -6.386 414 0.000 -0.2940 -0.3845 -0.2035 S1 -2.590 414 0.010 -0.1373 -0.2416 -0.0331 S2 -6.279 414 0.000 -0.3253 -0.4271 -0.2235 S3 -2.035 414 0.042 -0.0988 -0.1942 -0.0034 S4 -1.578 414 0.115 -0.0795 -0.1786 0.0195 B1 12.231 414 0.000 0.6241 0.5238 0.7244 B2 6.059 414 0.000 0.3446 0.2328 0.4564 B3 -6.821 414 0.000 -0.3904 -0.5029 -0.2779 B4 -10.805 414 0.000 -0.5663 -0.6693 -0.4632

In this study, the following hypotheses are formed to explore the relationship between perceived security for online shopping, customer trust and loyalty.

H1: There is a relationship between trust and perceived security; H2: There is a relationship between trust and loyalty; H3: There is a relationship between perceived security and loyalty. When the hypotheses were tested with regression analysis, the relationship between trust and perceived

security was found to be statistically significant (p < 0.05). The relationship between trust and perceived security is a very strong and positive one (r = 0.890). In addition, the correlation coefficient (r2) was calculated as 0.792, which means that 79.2% of the variation in trust depends on the perceived security. As the perceived security of online shopping improves, customer loyalty increases. Hypothesis H1 is accepted.

The relationship between trust and loyalty was significant (p < 0.05). The relationship between trust and loyalty is a positive one (r = 0.737). However, the correlation coefficient (r2) was calculated as 0.543; i.e., 54% trust variability depends on the loyalty. H2 hypothesis was also accepted. Customer loyalty in online shopping increases in line with the trust.

The relationship between perceived security and loyalty variables found to be significant (p < 0.05). There is a positive relationship between perceived security and loyalty (r = 0.871). In addition, the correlation coefficient (r2) was found to be 0.75, i.e., 75% of variation in the loyalty depends on the perceived security. Accordingly, customer trust towards online shopping depends on perceived security and trust leads to loyalty.

In the online shopping domain, website security measures improve customer trust and this trust results in a customer loyalty.

Results

This study considered three factors associated with online shopping: perceived security, trust and loyalty.


Respondents of the study questionnaire in general argued that the websites have not taken adequate security measures and thereby, they do not have trust in online shopping. However, customer trust and loyalty are very important in online shopping, and customers do continue to shop at the websites which they have shopped before and recognized as trustable.

Following conclusions are derived with hypothesis testing in this study; as a company’s perceived security of online shopping site increases, also does the customer trust. With increasing level of customer trust in online shopping, loyalty also increases. All in all, customer loyalty depends on the security measures provided by online shopping websites; these measures improve the perceived security and consumer trust, which in return increases the loyalty.

Discussion

In recent times, online shopping is more and more gaining edge towards the traditional shopping. As of today, approximately one-tenth of the world’s population buys and sells over the internet. Customers purchase more books, video games and plane or bus ticket over the internet than they do over the counter.

To succeed in online shopping, companies have to own a website which carries certain features. For instance, the website should be simple but eye-catching, easy to access and navigate through. All in all, perceived security of the website is fundamental as it directly affects the consumer trust and loyalty. Customers need to disclose sensitive information, such as personal and financial information, while shopping online; accordingly, companies should to take stringent security measures to ensure the confidentially of disclosed information, especially in their payment processing systems in use.

Businesses should clearly treat security as a priority as consumer trust is the key to success. Customers, not surprisingly, prefer to only trustable website. In recent years, among the multiplying number of companies with online sales services, the ones that have invested more on security measures attracted more costumer interest.

The navigation functionality metric, comprised of operational efficiency, the speedy transmission of words and images, and modern technology, has a significantly positive effect on a site’s perceived trustworthiness and reliability. Security also had a significantly positive influence on satisfaction. These and other relationships have been tested in previous studies and our findings are consistent with other reports (Kim & Lim, 2005; Shankar, Urban, & Sultan, 2002; Suh & Han, 2003). Our findings indicate that increasing customer trust in online shopping results in increased loyalty.

Findings of this study are consistent with the prior researches, such as Kim and Lim (2005); Shankar, Urban and Sultan (2002); Suh and Han (2003), which have explored the relationship between security and loyalty; depending on the security measures provided by online shopping websites, customers become more loyal to the site.

Limitations and Future Research

This study has a few limitations that need to be pointed out and recognized when interpreting the results. One obvious limitation is that the study covers customers using the online shopping in one province of Turkey. However, to reach all customers nationwide who shop online would necessitate a larger budget, more staff and longer time—all of which could not be afforded due to the economical constraints. Convenience sampling


method was applied; 450 survey forms were distributed and recollected in the scope of the study—out of which, 35 of them were missing or filled in with contradictory and erroneous information; these were excluded from the scope of research. The final number of valid responses was 415.

Another potential limitation is the use of behavioral intention to measure the behavioral component of attitude. In addition, this research only explored the customers in Turkey, and future studies can be performed in other countries to compare similarities and variations among different countries. Such reviews and summaries provide a solid foundation on which we, as researchers, can build future studies.

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web site. Industrial Management and Data Systems, 106(5), 601-620. Furnell, S. M., & Karweni, T. (1999). Security implications of electronic commerce: A survey of consumers and business.

Electronic Networking Applications and Policy, 9(5), 372-382. Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an internet store. Information Technology and Management,

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Industrial Managementand Data Systems, 7(105), 937-954.


Growth Potential and Profitability Analysis of Insurance

Companies in the Republic of Serbia

Dragana Ikonić, Nina Arsić Higher School of Professional Business Studies, Novi Sad, Republic of Serbia

Snežana Milošević Economic and Trade High School, Senta, Republic of Serbia

Economically developed countries hold much of its total wealth as financial savings, and they should faster

experience higher rates of overall economic growth in the long run. Given the level of income made by economic

entities and according to such correlation, their propensity to save can be generated. As a clear reflection of the

development of the financial sector, insurance companies as financial intermediaries, through the mobilization of

savings, contribute to the development of the entire financial sector. Analyzing the performance of insurance

companies in Serbia, CARMEL method will be applied, which includes indicators for the presentation of

quantitative criteria for the purpose of monitoring and analyzing the profitability of insurance companies consisting

of a model that is the current methodology of the MMF. In addition to traditional financial instruments, derivative

securities are traded in financial markets, promoting the development of financial markets, such as options, which

are generators of potential growth of profitability. The aim of this paper is to show the growth potential of

profitability in insurance companies, as well as decreasing risks which are connected to the business activities by

the use of options.

Keywords: growth, profitability, insurance companies, options

Growth Potential of Insurance Sector

As far as modestly developed Serbia’s insurance market is concerned, the premium from credit portfolio of insurance is insignificant because credit insurance is widespread among developed economies. The consequences of global financial crisis that are largely seen in our country are characterized by limited supply of capital, more expensive loans and decreased demand. With the present problem of getting receivables, it is clear that there are no signs of developing credit insurance sector in Serbia. From the perspective of financial markets, insurance companies and pension funds play the significant role as institutional investors in various securities. So with these

The Development of Insurance Sector

Dragana Ikonić, MA of Economics, Research Associate, Higher School of Professional Business Studies. Nina Arsić, MA of Law, Research Associate, Higher School of Professional Business Studies. Snežana Milošević, MA of Economics, Professor, Economic and Trade High School. Correspondence concerning this article should be addressed to Dragana Ikonić, Vladimira Perica Valtera 4, 21000 Novi Sad,

Republic of Serbia. E-mail: [email protected].

GROWTH POTENTIAL AND PROFITABILITY ANALYSIS OF INSURANCE COMPANIES 999

investments, they enable a significant and major increase in the liquidity of the market, as well as its overall performance. Sales of insurance policies to residents and businesses represent and create a long-term source of funds. These activities can be used to purchase long-term financial instruments—stocks and bonds, and short-term securities. The basic and the key form of insurance in developed countries, like the United States, is life insurance, while in less developed countries like the Republic of Serbia non-life property insurance is dominant.

The banking sector dominates the financial market in Serbia and it is followed by the insurance sector. It cannot be said about the fund industry which is just in the state of approximate trend. By the fact of delaying the development of domestic investors created a significant gap, which was filled with foreign portfolio investors. Regarding fund industry, the first and the crucial steps were made by voluntary private pension funds supervised by the National Bank of Serbia (Ikonić, Arsić, & Milošević, 2011).

In the total assets of the financial sector in the year 2010, which amounted to 2,759 billion dinars, banks accounted for 91.8% and the insurance company with 4.2%, as shown in Table 1 (National Bank of Serbia, 2010).

Table 1 The Share in the Total Financial Sector in Percent

Banks Leasing Insurance DPF

2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010 Total assets 89.3 90.8 91.8 6.2 4.7 3.6 4.3 4.2 4.2 0.2 0.3 0.4 Capital 93 92.1 92.5 1.4 1.9 1.5 5.6 6 6 Number of employees

72.2

72.5

71.8 1.2

1.1

1.1 26.2

25.9

26.8 0.5

0.4

0.3

The structure and process of forming of financial institutions largely depend on the extent of development of financial market. Apart from legal limitations, there are other factors influencing the development of financial market, such as, political and economic conditions, currency stability, appropriate level of savings, etc.. Contemporary financial markets should have tendency to create business environment both for classic financial institutions and for new ones, which will offer a wide selection of financial services.

It can be stated that insurance sector is inadequately developed in Serbia. Not only is the level of its development below EU average, but there are also other indicators of development (the relationship between total premium and gross national product, and total premium per capita).

By influencing the rise in the price of risk and fall in the investment income, financial crisis causes the need for increasing the insurance premium. Figure 1 shows the development of insurance in some European countries, which can be analyzed in terms of share of premium in gross national product (Swiss Re, Sigma No. 2/2005, No. 5/2006, No. 4/2007, No. 3/2008, No. 3/2009). In the period between 2004 and 2008, Serbia held the 62nd position in the world, and comparing with the group in which it has been placed it can be concluded that Serbia has the satisfactory position since the countries like Romania and Turkey are behind Serbia. Switzerland has the highest percentage of share (with the tendency of decreasing the share), followed by Germany and Spain (Swiss Re, Sigma No. 2/2005, No. 5/2006, No. 4/2007, No. 3/2008, No. 3/2009).

The information about total number of insurance companies states that there were 26 insurance companies in the first quarter of 2010 (National Bank of Serbia, 2010). There are 22 companies involved into insurance affairs, and only four companies have re-insurance services included (Law on Insurance, The Official Gazette of


the Republic of Serbia, 2004). Among companies dealing with insurance, there are seven companies involved in life insurance, nine companies working exclusively with non-life insurance, and there are six companies dealing with both life and non-life insurance. Breakdown by ownership shows that 19 insurance companies were in majority foreign and seven in majority domestic ownership as of 2009.

Figure 1. The level of development of insurance in some European countries: The share of premium in GNP.

The sector grew at a much slower pace (16.5% in 2008 vs. 2.6% in 2009), but its overall performance may be assessed as encouraging given the crisis environment. The total premium in 2007 ($ 44.8 billion) rose by 16.9% compared to the premium in 2006, whereas the increase in the total premium in 2006 was 10.3% compared to 2005. If we observe the first quarters in the period between 2006 and 2010, the rise in premium can be noticed (16%, 17.9%, 1.09%, and 2.41% respectively). Observing the changes of total premium in the period from 2005 to the first quarter of 2010, it can be concluded that it had the tendency of rise, which is seen in Figure 2 (National Bank of Serbia, 2009).

Observing the premiums per capita in 2008 it can be seen in Figure 3 that Serbia holds 62nd position in the world with $ 126.1, whereas the same indicator for EU-27 countries is $ 3,061. The UK holds the first place with $ 6,858, followed by the Netherlands with $ 6,849 and Switzerland with $ 6,979.4. Hungary and Croatia are in the 41st and 42nd position with the premiums per capita of $ 501.4 and $ 430.7 respectively, whereas Turkey holds the 65th position with $ 116.1.

In the period between 2004 and 2008 Serbia on average holds the 65th position in the world with the decreasing tendency of premium per capita. Turkey holds the 61st position on average with the average premium per capita of $ 115 in the given period. Hungary and Croatia hold on average the 38th and 41st position with the average premium per capita of $ 398 and $ 326 respectively. The Netherlands holds the 5th position with the average premium of $ 4,855 per capita. The UK has the 1st place in the world, with the average premium of

0

2

4

6

8

10

12

14

2008

2007

2006

2005

2004


$ 5,909 per capita (Swiss Re, Sigma No. 2/2005, No. 5/2006, No. 4/2007, No. 3/2008, No. 3/2009).

Figure 2. Quarterly movements in total premium (2005-2010) in billions of Serbian dinars (RSD).

Figure 3. Premium per capita in European countries in dollars (2004-2008).

The development of insurance sector in its full potential would create a proper framework for appliance and use of other financial instruments such as financial derivatives.

Options in the Function of Profitability Growth of Insurance Companies The main role of creating products is protection against risk, or reduction and elimination of harmful

consequences of a financial risk. Traditionally, the public discourse on derivatives mentions hedging and speculative activities as complementary concepts. Modern approaches do not place hedging in the foreground but point out that derivative instruments are tools that should serve companies in a better assessment of financial risk, and they undoubtedly contribute to the possibility of generating higher profitability. Financial derivatives are controversial instruments for many reasons. First they are complex and thus seen as unclear to use, but where theorists and practitioners agree on is the fact that their use is subject to their full understanding; otherwise, the outcome is not certain.

9.9 11.5 13.6 13.7 14.118.521.3 24.1 28.7 28.526.5

29.834.4

40.1 40.934.7

38.344.8

52.2 53.5

2005 2006 2007 2008 2009 2010

I II III IV

0%

20%

40%

60%

80%

100%

United Kingdom

Netherlands Switzerland Hungary Croatia Serbia Turkey

4,508 3,599 5,716 287 248 45 65

4,599 3,7415,558

334 27549 79

6,467 3,8295,562

376 30877 89

7,114 6,2635,741 492 371

103111

6,858 6,849 6,379 501 431 126 116

2004 2005 2006 2007 2008


If we take into consideration the degree of development of domestic financial markets, there is an obvious significant lagging behind the international market of financial derivatives. During the last years, there has been removal of a number of factors critical for this lag in the development of domestic financial market, but the consequences of these factors still exist and can be felt. It is essential to have intense involvement of economy and banks in international financial markets in order to achieve the development of financial derivatives market in Serbia. Encounter between interest rates and exchange rates from foreign markets and local entities involved in these flows will result in risks from international financial environment.

In order to protect themselves against currency and interest rate risk, domestic entities must know of instruments, techniques and strategies of trading on uncertain foreign market derivatives. Positive legislation in the Republic of Serbia provides enough space for the development of this market, but so far important results have not been achieved in this segment. Experts say that there are many factors influencing the development of derivative markets in our country. The most important factors are as follows: faster development of spot financial markets, efficient protection of creditors’ rights, active role of government in this segment, transformation of banks and economy and appropriate measures of monetary and fiscal policy. If the factors of development of derivative markets are rapidly implemented and brought into effect, dynamics of financial markets will be automatically more noticeable. There is no doubt that the current situation in our market cannot be compared with the situation that existed just a decade before. In fact, long-term credit instruments lacked in the market ten years ago, but today there are foreign currency savings bonds with long maturity, and the stock market is much better organized (Skakavac, 2008). A similar development path as in developed markets is expected and it will surely start with the classic futures forward contracts as the simplest financial derivative, but later more sophisticated financial instruments will occur, such as options, futures and swaps.

It is possible to predict that the market of financial derivatives in our country at an early stage in its development will have inter-bank character, with sporadic participation of some highly rated companies, whereas the share of the corporate sector and the citizens can be expected with the institutionalization of the clearing house and establishment of appropriate mechanisms to guarantee the performance of the contract.

A popular segment of the financial markets in the world is the market of financial derivatives. There are trade operations with derivatives such as futures, options, forwards and swaps. The basic function of derivative financial products is the protection from risk. The fact that applies to developed countries is that the number of investors trading with options tends to increase in contrast to the total number of investors. It is believed that there are significant opportunities to expand benefits and options for switching activity from over-the-counter market to stock market. The volume of options trading at CBOE is shown in Table 2 (Retrieved from www.cboe.com).

Table 2 The Volume of Options Trading at CBOE 2010 2009 2008 Shares 572,688,137 634,710,477 604,024,956 Indexes 269,989,511 222,787,514 259,499,726 Trading instruments 276,362,700 277,266,218 329,830,388 Total 1,119,040,348 1,134,764,209 1,193,355,070


Table 3 Global Options Markets

Exchange

Volume traded Notional value Open interest Number of trades Option premium

(Nber of Contracts) (USD millions) (Nber of Contracts) (USD millions)

2009 2008 2009 2008 2009 2008 2009 2008 2009 2008 Americas

BM&FBOVESPA 546,547,550 350,046,283 931,053 855,086 7,299,503 2,847,679 14,842,470 11,877,646 28,676 21,956

Boston Options Exchange (2)

137,784,626 177,600,467 24,902 44,463 NA NA 7,869,962 9,544,517 24,902 44,463

Buenos Aires SE 25,132,711 25,165,308 NA NA 747,190 344,528 535,375 578,555 241 339

Chicago Board Options Exchange (CBOE)

634,710,477 604,024,956 2,187,581 2,717,661 188,281,057 187,131,615 46,078,979 35,461,401 111,455 172,815

International Securities Exchange (ISE)

672,429,815 687,165,942 NA NA NA NA 44,122,185 NA NA NA

MexDer 345,718 585,037 73 154 3,960 17,486 3,288 6,104 NA NA

Montréal Exchange(1)

14,507,261 14,633,599 76,246 73,732 1,547,120 1,453,365 839,596 765,794 2,060 3,182

NASDAQ OMX PHLX

426,245,722 537,954,692 NA 225,858 193,253,211 235,799,395 23,782,783 36,343,109 123,339 225,859

NYSE Amex 170,978,207 121,342,636 NA NA NA NA NA NA NA NA

NYSE Arca Options

273,769,123 270,939,723 NA NA NA NA NA NA NA NA

Asia Pacific

Australian Securities Exchange (Inc. SFE) (4)

15,242,798 17,043,125 196,892 262,171 1,451,359 1,328,769 1,460,904 1,509,062 23,405 32,629

Hong Kong Exchanges (1)

41,863,995 48,038,651 127,339 168,772 3,836,130 3,978,418 NA NA 9,623 16,419

Korea Exchange 982 21 0 0 0 0 21 19 0 0

National Stock Exchange India

14,066,778 11,067,082 88,173 50,851 41,012 153,609 10,928,922 7,973,108 2,998 1,860

Osaka Securities Exchange

408,612 534,954 NA NA 20,897 86,764 78 601 110 134

TAIFEX 8,240,390 872,880 14,824 5,319 2,584 574 110,547 29,666 19 13

Tokyo Stock Exchange Group

660,875 88,256 NA NA 102,789 44,628 NA NA 46 4

Europe, Africa, Middle East

Athens Derivatives Exchange (3)

67,590 182,757 133 677 1,615 6,272 3,218 2,728 10 55

Borsa Italiana 20,462,240 20,056,426 71,873 112,613 2,719,744 2,748,370 459,087 545,541 NA NA

Eurex (1) 146,286,451 197,338,587 353,285 881,388 NA NA 2,822,091 2,814,787 NA NA

Johannesburg SE 15,670,869 19,591,351 NA NA 2,814,565 32,236,246 6,960 9,079 984 1,346

MEFF(1) 35,527,914 18,317,249 56,253 35,357 7,728,251 4,669,410 77,754 59,053 3,290 2,091

NASDAQ OMX Nordic Exchange

28,775,091 42,767,407 399,648 47,388 3 844 093 4,913,148 NA NA 1,873 2,866

NYSE Liffe (European markets) (1) (5)

141,604,421 142,684,583 325,405 461,824 32,661,287 33,374,165 3,407,139 3,676,891 24,969,263 39,222,710

Oslo Børs 2,219,926 3,976,223 1,493 5,377 NA NA NA NA NA NA

Tel Aviv SE 321,735 0 1,200 0 23,192 0 5,165 0 84 0

Wiener Börse 474,697 848,021 596 3,946 70,363 78,631 14,290 17,510 55 163

Total 3,374,346,574 3,312,866,216

The largest volume of trading in global markets is conducted in CBOE Stock Exchange, (which is shown in Table 3) with nearly one billion contracts in 2008 (Retrieved from www.world-exchanges.org), which is ahead of other Asian and European stock markets. CBOE also had the largest number of trade operations as


well as the largest amount of premiums (Alijanović, Poklepović, & Šego, 2009). The prerequisites for the survival of derivates market are transparency and regularity.

In order to provide the unique market at the level of the European Union, the latest framework for regulation is Solvency II. This act will be applied in Serbia in 2012. Solvency II acknowledges the influence of all risks that insurance companies face while determining the level of capital adequacy. For European insurers it is particularly significant that Solvency II regulations will enable long-term sustainability of the insurance sector as a whole, bearing in mind the key experience gained during the crisis. Solvency II will have a significant role in the field of determining the adequacy and efficient allocation of capital, which has a direct influence on the reduction of costs for the insured, better protection from failure because the capital is adapted to the appropriate risk and on the promotion of good examples of risk management (Swiss Re, Sigma No. 4/2006).

Global structure of balance sheet of insurance companies in Serbia is not stable. One of disadvantages of insurance companies is the fact that the value of fixed assets exceeds the value of working capital. Thus in 2008 and 2009 the value of fixed assets was about 35 and 41 billion dinars respectively, whereas the value of working capital was about 20 and 22 billion dinars. The relationship between fixed assets and capital are similar in 2007, 2006 and 2005 (30.1: 24.7 bn dinars, 24.9: 20.9 bn dinars and 22.5: 17.6 bn respectively). Immobile assets in the form of intangible assets show that it is difficult to make distinction between a non-insurance company and insurance company, or in other words, insurance companies recognize only those funds that are easy to be dealt with and are called approved funds. All these should be included in the balance sheets of insurance companies, whereas the permanent assets should be excluded from the balance sheet and thus property part of the balance sheet would be underrated (Ostojić, 2004). The above-mentioned problem and new institutional regional decisions make insurance companies transfer to property and life insurance by high capital census and strict division.

Despite the potential that financial derivatives (options) have, they are not used in the Republic of Serbia. The reason is that financial markets and financial institutions are at a low level of development and that financial derivatives still have only theoretical but not practical potential. The involvement in international financial flows would create the need for using the options, and thus there will be their contribution to profitability growth of appropriate insurance institutions.

An Overview of Determinants of Profitability of Insurance Companies

Theoretical and Practical Framework of the Analysis of Profitability Indicators The National Bank of Serbia, as a regulatory body, set out six guidelines from the field of insurance, whose

aim is to protect the interests of the insured and insurance beneficiary, create trust of citizens in financial and insurance sector in order to establish a safe and stable insurance market. These guidelines include different fields necessary for business operations, supervision, reporting and development of corporative managing of insurance companies. Their aim is to suggest a way of organizing and carrying out the business activities to insurers, so the efficiency can be improved.

The National Bank of Serbia created the guidelines (Carmel indicators) following IMF methodology so the performance assessment of insurance companies is not only standardized but simplified. They are criteria for quantitative monitoring and analysis of financial stability of insurance companies. The indicators of capital


adequacy are the first to be applied in determining profitability of a certain insurance companies. The analysis of indicators of capital adequacy shows how a certain insurance company is profitable.

Determining capital adequacy according to Carmel methods consists of the following subgroups of indicators: C1: Self-insured retention premium/Total capital. This indicator measures the relationship between

self-insured retention premium and total capital of an insurance company. Self-insured retention premium is the approximation of risks considered in insurance contracts by insurance companies involved in non-life insurance. The significance of this premium is reflected in its capability to absorb inadequate price level of premiums and potential unexpected damage covered by insurance. More precisely, self-insured retention premium measures the insurance risk.

If the total value of this indicator is high, it can be concluded that the total capital is inadequate comparing to taking risks considered in insurance contracts (which is measured by the level of premium). Conversely, a low value after comparing self-insured retention premium and total capital brings to conclusion that capital resources are not used properly or that the insurance company has problems and it cannot generate its portfolio.

C2: Total capital reduced by loss/Total assets. This indicator measures the relationship between the total capital reduced by loss and total assets of the insurance company. This indicator measures the exposure of insurance company to market, investment and credit risk. The low value of this indicator may point out to the high exposure of the insurance company to these types of risks.

C3: Total capital reduced by loss/Technical reserve. If C3 indicator shows very high levels, there is inadequacy of total capital compared to take risks according to insurance contracts (measured by the level of technical reserve). The high level of indicators may signal a bad use of capital resources or failure to generate its portfolio.

An insurance company is obliged to determine, at the end of accounting period, the technical reserve for settling liabilities from insurance contracts (Law on Insurance “Official Gazette of RS”, No. 55/2004, 70/2004-red. and 61/2005.) and they serve for settling liabilities set forth in the issued insurance policies. Technical reserve is generated from the technical premium funds. Their level is determined by actuarial methods and it depends on future liabilities and structure of insurance portfolio.

In order to have more active insurance companies in financial market, there is an institutional framework provided where free financial funds can be placed. According to the Law on Insurance there is a clear picture what portion of technical reserve can be placed by insurance companies (Official Gazette of RS, No. 83/2005), but not to cause non-liquidity problems.

C4: Collateral reserve/Solvency margin. This indicator shows the relationship between collateral reserve and solvency margin. An insurance company in its business operations, i.e., settling its liabilities, does not use premium gains or placement from invested funds. The reason for that is the difference in business operations among insurance companies. That is why forming the reserve is necessary for the insurance companies. The reserve is formed by taking financial funds from gains, premium and start-up capital.

Collateral reserve is a form of guarantee that the insurance company will settle liabilities on the basis of insurance. It is the indicator of solvency. According to the Law on Insurance, collateral reserve must always be higher than the calculated solvency margin. An insurance company must have collateral reserve or capital in order to settle its liabilities. The insurance company is obliged to deposit and invest collateral reserve (Official


Gazette of RS, No. 83/2005) in accordance with the insurance rules and good business customs. Likewise, the collateral reserve should be defined in the methods and amounts prescribed by the Law and with the aim of keeping and protecting its real value.

An insurance company must provide prescribed solvency margin. The solvency margin represents the quantitative indicator of solvency, i.e., the surplus of liquidity assets over the liabilities of the insurance company. The level of collateral liquidity must be higher than established solvency margin, i.e., its amount cannot be less than fixed assets. If there are variations, or in other words, if collateral reserve does not reach the amount of calculated solvency margin, the insurance company shall launch the harmonization programme within 30 days from the day of stating irregularities. Solvency margin is a guarantee that the liabilities of paying insured amount and indemnities will be settled in case the insurance company has financial problems. Solvency margin also represents the signal for supervisory board to take certain measures in case there are threats to solvency margin.

The analysis of profitability indicators brings to a clearer image of success of certain insurance companies. More detailed analysis of this indicator into parts refers to successful business operations of insurance companies. The necessary information is obtained from balance sheet, income statement and notes from financial reports as well as from consultations from the heads of insurance companies. The notes for 2009 and 2008 at the example of Dunav Insurance and DDOR Insurance will be presented hereinafter (see Table 4).

Table 4 Overview of Subgroups of Indicators for Dunav and DDOR Insurance

Group Indicator Amount in thousands

2009 2008 C1 Self-insured retention premium/Total capital 122.1% 111.1% C2 Total capital reduced by loss/Total assets 40.9% 40.7% C3 Total capital reduced by loss/Technical reserve 81.1% 81.8% C4 Collateral reserve/Solvency margin 329.4% 298.5%

By comprising the previously stated indicators of capital adequacy that have been practically applied, it can be concluded that there are signs of success, i.e., profitability of the insurance companies. Namely, by analyzing and interpretation of the capital adequacy indicators it is noticed that DDOR Insurance creates a lower level of profitability compared to Dunav Insurance.

Conclusion

A strong competition among the business entities participating in the market is more and more present in our region as well so the right observation and analysis of the business success is of paramount importance. The reason for that lies in the need for better understanding of the current position and better design of future business operations. Only companies that make right decisions are able to quick and efficient implement those decisions and they are characterized as successful companies.

In the first parts of papers, we attempted to show development of the insurance sector in the Republic of Serbia in comparison with other developed countries. Insurance is today one of the most profitable activities in the economies of European countries, and such tendency is seen in Serbia. The results of the research in the first part conclude that the insurance market in Serbia is among so-called developed markets with the chance to grow


and be more prosperous. The conclusion of the National Bank of Serbia is that the insurance market and the level of its development are not at the satisfactory level. As indicators of the level of development of insurance market, in the first part of the paper are given the following: the share of the premium in gross national product in the period between 2004 and 2008, and here Serbia is on average at the 62nd position. Therefore it can be said that Serbia is at the satisfactory level since Romania and Turkey are behind according to this ranking. The movement of the total premium from 2005 to the first quarter of 2010 has been shown and it is seen that it had risen. The premium per capita for the period between 2004 and 2008 has been observed, and here Serbia holds 65th place in the world with rising tendency which is now $ 80 on average. For example, Hungary and Croatia hold 38th and 41st place respectively with the average premium per capita of $ 398 and $ 326 respectively in the given period. Most reputable experts dealing with the analysis of business operations of insurance companies point out that Serbia will, after overcoming the financial crisis, have an increase in the insurance premium that will exceed the growth of the gross national product.

Developed financial markets show a tendency to increase the number of option contracts as well as other financial instruments. Through greater regulation and transparency of capital market in the Republic of Serbia, trading derivative securities, including options, should be introduced in the future and this introduction will be beneficial to the growth of profitability of insurance companies. Also the introduction of options on our stock exchange would be of great importance for capital market in Serbia because it would announce new possibilities for placing the funds.

The results of the research in the latter part of the paper point out that an insurance company may achieve and keep desirable level of profitability if it has an adequate level of capital. Transparency of business operations has been promoted since annual reports of insurance companies are available to the public on the Internet. It has been emphasized that this analysis is based on the indicators of CARMEL methods adapted to insurance companies. By this method it is possible to increase the extent of transparency and comparability because the National Bank of Serbia automatically takes all the indicators of CARMEL methodology into consideration. Within the analysis of profitability the indicator of capital adequacy has been used and it is undoubtedly the essence of today’s business operations of insurance companies because its function is to absorb the risks, create security for the insured and provide the survival on the insurance market. The capital of insurance companies should satisfy internal capital requirements as well as the requirements of regulatory bodies or ranking agencies. The above-mentioned theoretical assumptions have been applied at the example of DDOR and Dunav Insurance.

Insurance companies thus will be able to utilize serious and scientifically based and practically proved ways and to fulfil their inclination towards successful business operations in comparison with their rivals—now and in the future.

References Alijanović, Z., Poklepović, T., & Šego, B. (2009). Trading with options on world markets. Računovodstvo i finansije, Zagreb, No.

10, 123. Ikonić, D., Arsić, N., & Milošević, S. (2011). Hedging with option as a contemporary concept and initiator of domicile financial

market: The First International Symposium Engineering Management and Competitiveness. Zrenjanin, Republik of Serbia. National Bank of Serbia. (2007). Annual Report. National Bank of Serbia. (2009a). Total insurance premium by insurance companies and types of insurance. National Bank of Serbia. (2009b). Annual Report.


National Bank of Serbia. (2010). Insurance sector in Serbia—First quarter report. Official Gazette of the Republic of Serbia. (2004). Law on insurance. No. 55/2004. Official Gazette of the Republic of Serbia. (2005a). Decision on limiting certain forms of deposit and investing of technical reserve

and on the highest amount of certain deposit and investing of collateral reserve of insurance companies. No. 83/2005. Official Gazette of the Republic of Serbia. (2005b). Decision on methods for determining the level of solvency margin. No. 31/2005 Ostojić, S. (2003). Applicative aspects of bank’s financial reporting: Analytical framework of a single banking report. Privredna

izgradnja, 1-2. Ostojić, S. (2004). The necessity for restructuring insurance companies in Serbia. Privredna izgradnja, 1-2. Paul, N., & Bill, Y. (1999). A financial approach for determining capital adequacy and allocating capital for insurance companies.

Bermuda: Hamilton. Society of Actuars. (2004, March). Speciality guide on economic capital. Schaumburg: Illiniois. Swiss, R. (2006). Solvency II: an integrated risk approach for European insurers. Sigma No. 4/2006. Žarković, N. (2009). Insurance in the world and Serbia under the conditions of economic crisis. Tržište, Novac, Kapital Journal,

Chamber of Commerce of Serbia, Belgrade.


Sustainable Consumption and Production

in the Baltic Sea Region

Janis Brizga University of Latvia, Riga, Latvia

Dzintra Atstaja BA School of Business and Finance, Riga, Latvia

Dzineta Dimante University of Latvia, Riga, Latvia

Economic activity always has an impact on the environment, but the potential degree of this impact depends on

consumption and production patterns. The aim of this paper is to analyse the environmental and well being impacts

of consumption and production systems in Baltic Sea Region and draw conclusions about transferring of best

practises in Latvia. This study is based on indicator analyses, focusing on data of environmental impacts from

consumption and production in the region, and analyses drivers behind these impacts. The paper concludes two

trends—Scandinavian countries and Germany which have more advanced economies demonstrate much higher

ecoefficiency and environmental management practices compared to the new EU member states. The example of

the Baltic Sea region shows that high income levels and a stable development path in the old EU member states

provide grounds for technology advancement to reduce the environmental impact of production. However Baltic

States and Poland on average demonstrate much more sustainable consumption patterns. But the trends in these

countries are negative—they try to copy lifestyles and consumption patterns of more advanced economies with

higher ecological footprint. Challenge for Latvia is to improve its ecoefficiency but at the same time develop more

sustainable consumption patterns.

Keywords: Baltic Sea Region, economy, environmental impact, efficiency, environmental management,

sustainable consumption and production

Introduction

The purpose of this paper is to analyse the impact of economies in different stages of development on state of the environment and well being of the population, using the example of the Baltic Sea Region (BSR) countries and drawing conclusions about the possibilities of introducing best practises from the region in Latvia. Janis Brizga, Ph.D. candidate, Department of Environmental Management, University of Latvia. Dzintra Atstaja, Professor, Department of Entrepreneurship and IT, BA School of Business and Finance. Dzineta Dimante, Ph.D. in Economics, Assistant Professor, The Chair of Economic Systems Management Theory and Methods,

University of Latvia. Correspondence concerning this article should be addressed to Dzintra Atstaja, K.Valdemara Street 161-407; Riga, LV 1013,

Latvia. E-mail: [email protected].

SUSTAINABLE CONSUMPTION AND PRODUCTION IN THE BALTIC SEA REGION 1010

The Baltic Sea Region is made up of nine countries and a number of metropolitan areas. The region encompasses Estonia, Latvia, Lithuania (The Baltic States), Sweden, Denmark, Finland, Germany, Poland, and North-West Russia, with St. Petersburg and Kaliningrad Oblast, the Russian exclave between Poland and Lithuania (see Figure 1). All countries except Russia are members of the European Union. The paper examines only those BSR countries which are EU member states—Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden.

Figure 1. Map of Baltic Sea Region. Source: UNEP/GRID.

BSR is rich and diverse in ecosystems as well as in economic activities. It inhabits around 100 million people and produces many services and industrial and agricultural goods. However consumption and production patterns in the BSR have an increasing influence on global resources and ecosystems. The earth has entered into a new epoch where humans constitute the dominant driver of change to the Earth System and abrupt global environmental change can no longer be excluded (Rockström et al., 2009).

Current economic downturn in many Baltic Sea countries can be used as a starting point for making considerable changes in these patterns, paying more attention to the environmental constraints, economic efficiencies and social wellbeing. To ensure this kind of economic development or sustainable consumption and production there are three types of strategy to apply (Shove, 2004; Sayfang & Paavola, 2007; Bauler et al., 2009; Paredis, Crivits, Bauler, Mutombo, Boulanger, & Lefin, 2009): (1) Ecoefficiancy strategy aims to reduce the intensity in materials (including the non-renewable sources of energy) throughout the life-cycle of products and services; (2) Structural change strategy aims at changing supply side; and (3) Sufficiency strategy aims to de-linking the product functions from the wellbeing they generate1. 1 Different authors use different terms for these strategies. For example, Sayfang and Paavola (2007) talks about market (ecological modernization), hierarchical (systems of provision) and egalitarian (social marketing) approaches, Shove (2004) proposes to focus on promoting efficiency, restructuring supply and restructuring demand, but Paredis et al. (2009) calls them eco-efficiency, de-commodification and sufficiency strategies.


There are many regional initiatives executing these strategies in the BSR and several intergovernmental institutions like Council of the Baltic Sea States (Baltic 21), HELCOME and the EU strategy for the Baltic Sea Region which amongst other things try to solve the conflicts arising between environmental protection, economic development and social welfare. Most of these governmental and intergovernmental initiatives focus primary on the efficiency strategy and use of economic instruments. These instruments are especially effective in circumstances of market economy and influence producers’ possibilities and consumers’ behaviour in the market (Central Intelligence Agency, 2008). Hoverer, this approach alone cannot deliver sustainable consumption and production (Greening, Green, & Difiglio, 2000; Fuchs & Lorek, 2005; Rubik et al., 2009; Jackson, 2009), as it does not take into account absolute numbers and scale and in many cases ignores possible rebound effects.

Assessing how green the economies of BSR are, we analyse data reflecting environmental impacts from consumption and production in the region. There are many drivers behind these impacts and that’s why we used variate of indicators which characterises these diverse relationships between divers, pressures and impacts on environment and human prosperity.

Sustainable Consumption Patterns

BSR countries differ considerably according to the GDP per capita in comparison to industrially developed countries and transition economies. Old EU member states weighted average GDP per capita in 2008 was around 31.8 thousand EUR in current prices with decrease in 2009 around 4.6 per cent. New EU member states or transition countries weighted average GDP per capita in the same period was around 9.6 thousand EUR in current prices with decrease around 15 per cent in 2009. So in 2009 average income difference between old and new member states is 3.7 times. Household spending accounts for a significant proportion of GDP, averaging just around 57 % in the BSR (Eurostat).

Also the inequality of income distribution reflected by Gini index is higher in transition economies (see Table 2), which means that there is considerable share of people living in poverty. This causes a dilemma between economic growth and environmental protection to be even more complicated.

Having different consumption patterns in various countries the environmental impact from consumption can differ considerably. Food, housing and mobility are the three main consumption clusters with the highest environmental impacts (Tukker et al., 2006; Lähteenoja & Lettenmeier, 2007; Moll & Watson, 2009). Household expenditures are increasing not only in eastern countries of the BSR, but also in Scandinavia and Germany where absolute per capita expenditures are 3 to 4 times higher than in Baltic States and Poland. In the time period between 2002 and 2009 household expenditures increased by 6%, but the increase in the consumption clusters with the highest environmental pressures (food, housing and mobility) in the same period was only 2.7% with the highest increase in the Baltic States and Poland and some decrease in other BSR countries (Denmark and Germany in this period has experienced decreasing household expenditures in these sectors).

Biggest environmental pressures related to the food consumption are linked with the consumption of animal-based products. Meat consumption in the BSR is similar to the rest of EU, but households in Denmark, Germany, Sweden and Poland consumes on average more meat products than consumers in the Baltic States (see Figure 2).

There are significant differences in the transportation infrastructure and patterns in the BSR. Train network


is most developed in Sweden, Denmark and Germany and in these countries it represents 8%-9% of in total inland passenger-km. Number of cars per household also differs significantly (see Figure 3). In those countries with the highest number of cars per 1,000 inhabitants car travel also represents the higher share in total travel.

DenmarkGermany

SwedenPoland

FinlandEstonia

LatviaLithuania

0

20

40

60

80

100

120

Figure 2. Consumption of meat per inhabitant (2007). Data: Eurostat.

Figure 3. Cars per 1,000 inhabitants and car share in total inland travel. Source: Eurostat.

Also final energy consumption by households differs very much in the Region. Most of the countries over the last years have experienced slight increase in the total energy consumption (see Figure 4). But at the same time electricity consumption has increased very rapidly, in Latvia by 50%. Main drivers of increasing electricity consumption are growing number of appliances (e.g., freezers, washing machines, dishwashers, PCs and other small appliances) utilized in households as well as increasing diversity of electricity use (not only for lighting, food storage and entertainment, but also food preparation, air conditioning and hot water preparation).

Housing which represents significant share in the total household expenditures is also responsible for the biggest share of total energy consumption (in Sweden 60%). BSR is experiencing several trends which facilitate increasing energy consumption by housing sector. There is increasing number of dwellings, also the size of

78 80 82 84 86 88 90 92300

350

400

450

500

550

Denmark

Germany

Sweden

Poland

Finland

Estonia Latvia

Lithuania

R² = 0.2913778635

Car % in total inland passenger-km

Car

s pe

r 100

0 in

habi

tant


dwellings is increasing over the years. But there are also positive trends. Rising energy prices, increasing taxes on fossil fuels and information campaigns have shifted household energy consumption away from oil and coal to other energy carriers—mostly biomass and natural gas, but also solar and wind energy is more and more available and used by households.

Figure 4. Household final energy consumption (toe). Source: Eurostat.

Sustainable Production Patterns

Economies of BSR countries which have not undergone the change of economic system have considerably more developed production sector and are more advanced in technological development. These countries have also succeeded to be the frontrunners in the development of ecotechnologies—Denmark is well known for its cluster of wind power generator production, Germany—for developments in wind, solar and geothermal energy production equipment and components, Sweden—for its use of hydro power and biomass for energy production. Sweden is the first advanced western economy trying to become oil free for energy production until 2020 without building a new generation of nuclear power stations.

Considering the great environmental impact of climate change, energy efficiency and the use of energy resources with less or zero greenhouse gas emissions (GHG) are very important factors assessing economy’s impact on the environment. Figure 5 shows that all BSR countries have improved their energy efficiency from 1996 until 2008. New EU member states have succeeded reductions by factor 2, but still their average energy intensity is 2.7 times higher than in the old member states. This can be explained by advanced technologies of the old member states and new member states’ bad heritage of energy inefficiency from Soviet times especially in the housing sector. Denmark and Sweden has vast range of environmentally motivated subsidies besides the traditional economic instruments—charges and taxes (European Environment Agency, 2010).

Not only the old EU member states but also Latvia has had a positive experience in using renewable resources for energy production. Sweden, Latvia, Finland and Denmark have the biggest share of renewable resources in

Denmark Estonia Finland Germany Latvia Lithuania Poland Sweden 0

0.2

0.4

0.6

0.8

1

1.2

20022008

toa

per c

apita


total energy consumption (see Figure 6) and these countries have also the highest targets for 2020 set by EU Directive on renewable energy. Finland, Sweden and Latvia are leaders in EU in biomass production per capita.

There is a continuous debate over economic and environmental impacts of biofuels. Mainly, because biofuel production compete with food production and may cause an increase in fertiliser and pesticide use which have adverse negatively effect on ecosystems and biodiversity. Use of renewable resources for energy production is a very important factor for development of the local economy. The renewable energy sector provides jobs, reduces transportation volumes, increases energy independence and for many countries improves import-export balance. These benefits favour development of biofuel industry, but with great attention to sustainable practices and high environmental standards. According to studies commissioned by the German Ministry of Environment, Germany had 166 thousand jobs related to renewable energy in 2004 and estimated considerable increase in the future (UNEP, 2008).

Figure 5. Energy intensity of the economy in BSR countries from 1996-2008 (kg of oil equivalent per 1000 Euro). Source: Eurostat.

Figure 6. Electricity generated from renewable sources in BSR countries from 1998-2010, % of gross electricity consumption. Source: Eurostat.


To improve energy efficiency and increase the share of energy produced from renewable resources, new member states should use EU Structural Fund financing and also revenues from Kyoto Protocol emission trading system. As the restructuring of economies in transition countries has led to a sharp decrease in production sector and improvement of technologies, the GHG reductions in three Baltic States are even bigger than countries have committed by Kyoto Protocol (see Figure 7). Therefore the new member states are able to obtain assets from emission trading and invest them in technologies for reduction of GHG emissions. For example, in 2009 and 2010 Ministry of the Environment of the Republic of Latvia organized contests for investments in energy efficiency and technology development for 81 million EUR. There is a good cooperation between BSR countries in joint implementation projects as well. The BSR as a testing ground was an early stage of the overall process of following and implementation of the Kyoto Protocol.

Figure 7. GHG emissions in CO2 equivalent reductions in BSR countries 1990-2006. Source: United Nations Framework Convention on Climate Change.

Technological improvements are of vital importance not only in energy use, emissions reduction but also in saving other resource. These improvements in resource use can be obtained through reductions in material input, minimisation of waste, reuse, recycling of waste and improved durability of goods. Figure 5 shows that waste sorting and management system in the new member states has not been developed properly, because on average in 2008 there is 3.6 times more waste landfilled per capita compared to old member states. Comparing municipal waste created and landfilled from 2001 to 2008 old member states have landfilled on average 19 percent of their municipal waste but new member states 79 percent. An analysis of reasons for such disparities revealed that old member states have more developed waste management systems and also landfill charges are much higher ranging from 30 to 100 EUR per ton of waste, while new member states have very low landfill charges, for example, 4 EUR per tonne in Latvia. Estonia has managed to achieve a considerable reduction of municipal waste landfilled from 95 % in 2000 to around 60 % in 2006 owing to landfilling cost increase by 700 percent. Since 2002 in Sweden and since 2005 in Germany it is not allowed to landfill the organic waste. The graphs in Figure 8 show that it has caused an obvious decrease in weight of lanfilled waste per person. EEA study finds that to be effective landfill tax rates should be relatively high, although in Estonia rapid increases to a relatively low landfill tax have achieved a similar effect (European Environment Agency, 2009).

These examples show that in BSR countries with higher per capita income levels using economic


instruments and technology advancements do reduce impact of their economy on the environment. Figure 9 shows the relation between GDP per capita (horizontal axis) and energy intensity (vertical axis) in 2007. Coefficient of determination 0.8 shows that the exponential equation describes the relation between these factors is quite close.

From green economics perspective it would be very important to strengthen cooperation between BSR countries, facilitate technology transfer and share best environmental management practices to decouple growth of transition economies and their impact on environment. As the Baltic Sea is one of the common goods of the region and it suffers a lot from pollution caused by surrounding countries’ economies such common effort would improve the well being of inhabitants of all BSR countries.

Figure 8. Municipal waste landfilled (kg per capita) in BSR countries 1997-2008. Source: Eurostat.

Figure 9. Relation between GDP per capita in current prices and energy intensity in BSR countries during 2003-2009.

Source: Eurostat.

Environmental data of BSR countries reveals that slower growth in transition economies has been beneficial for some environmental issues, such as biodiversity and protected areas. According to Eurostat, Estonia has highest percentage of areas protected for biodiversity—17 percent of its territory, Latvia has highest common bird index 109.7 in comparison to 1990.


Many authors have stressed that there is a necessary drastic reduction of environmental impact of economic activities to avoid the collapse of civilization and change should come from society by transforming dominant cultural patterns, changing attitudes and behaviour (Assadourian, 2010; Jackson, 2009; Daly, 2008). Therefore there is a need for transition not only economic sector and technologies, but also institutional framework which should encourage prosperity also outside of the market and culture—social-psychological mindset should shift towards less materialistic values and lifestyles.

While transition countries do not have enough capacity to develop new technologies for decoupling the growth, they would need to pay more attention to education, awareness rising and promotion of green lifestyles. In order to find out the real possibilities of involving society in the introduction of environment protection activities and to clarify a real situation regarding society’s attitude towards environmental problems, we carried out a survey of the entrepreneurs in Latvia, which could serve as an example for situation in the Eastern part of the region.

Performance Indicators

To assess how a state of the environment, technological advancements and also public opinion have contributed to the quality of life and wellbeing of the inhabitants in BSR countries, we use such well developed indicators as Environmental Performance Index (EPI) and Happy Planet Index (HPI). Environmental performance index was elaborated by a team of environmental experts at Yale University and Columbia University. EPI ranks countries on their performance across 25 metrics aggregated into ten categories including: environmental health, air quality, water resource management, biodiversity and habitat, forestry, fisheries, agriculture, and climate change. Analysis of the policy drivers underlying the 2010 rankings suggests that income is a major determinant of environmental success. At every level of development, however, some countries achieve results that exceed what would be anticipated, demonstrating that policy choices also affect performance (Yale Center for Environmental Law & Policy Yale University, 2010). Table 1 shows that in comparison to 163 countries all BSR countries occupy ranking in the first half while the old EU member states from BSR and Latvia have higher scores. Owing to changes in the data and methods used in 2010, the results cannot be directly compared to 2008.

Table 1 Environmental Performance Index Ranks and Scores for BSR Countries in 2008 and 2010

2010 2008

EPI rank EPI score EPI rank EPI score Sweden 4 86 3 93.1 Finland 12 74.7 4 91.4 Germany 17 73.2 13 86.3 Latvia 21 72.5 8 88.8 Denmark 32 69.2 26 84.0 Lithuania 37 68.3 16 86.2 Estonia 57 63.8 19 85.2 Poland 63 63.1 43 80.5

Note. Source: EPI.


The Happy Planet Index (HPI) report identifies health and a positive experience of life as universal human goals, and the natural resources that human systems depend upon as fundamental inputs. A successful society is one that can support good lives that don’t cost the Earth. The HPI measures progress towards this target—the ecological efficiency with which happy and healthy lives are supported (The New Economics Foundation, 2009).

HPI scores range from 0 to 100—with high scores only achievable by meeting all three targets embodied in the index—high life expectancy, high life satisfaction, and a low ecological footprint. The ecological footprint measures our use of ecological resources and represents the amount of biologically productive land and sea area needed to regenerate the resources a human population consumes and to absorb and render harmless the corresponding waste. The earth currently has just 1.8 global hectares available per person. From BSR countries Lithuania and Latvia have the smallest ecological footprints but still they are almost twice as big as fair share for each person on Earth. Estonia’s big footprint can be explained by the fact that it produces electricity from oil shale which is very polluting (Streimikiene & Roos, 2009). Nevertheless, shorter life expectancy and lower life satisfaction ranks new member states behind the old ones according to HPI.

Whilst the HPI confirms that the countries where people enjoy the happiest and healthiest lives are mostly richer developed countries, it shows the unsustainable ecological price we pay. It also reveals some notable exceptions—less wealthy countries, with significantly smaller ecological footprints per head, having high levels of life expectancy and life satisfaction. In other words, it shows that a good life is possible without costing the Earth (The New Economics Foundation, 2009).

In case of BSR only Denmark lags behind other old EU member states, but in overall higher life satisfaction and life expectancy offsets drawback of bigger footprints and Germany, Sweden and Finland have better HPI scores than transition countries (see Table 2).

Table 2 Performance Indicators of BSR Countries

Country Life satisfaction (0-10)

Life expectancy (years) 2010

Foot-print (g ha/cap) 2007

HPI HPI rank GDP per capita (EUR PPP) 2008

HDI (2010)

Gini coefficient(2008)

Germany 7.2 80.2 5.1 48.07 51 29,000 0.885 30 Sweden 7.9 81.3 5.9 47.99 53 30,700 0.885 24 Finland 8.0 80.1 6.2 47.23 59 29,300 0.871 26 Poland 6.5 76.0 4.3 42.75 77 14,100 0.795 32 Lithuania 5.8 72.1 4.7 40.90 86 15,500 0.783 34 Latvia 5.4 73.0 5.6 36.67 101 14,300 0.769 38 Denmark 8.1 78.7 8.3 35.47 105 30,100 0.866 25 Estonia 5.6 73.7 7.9 26.42 131 16,900 0.812 31

Note. Source: HPI, Eurostat.

Combining HPI, EPI, Human Development Index and Gini coefficient ranks, we conclude that Sweden has achieved the best results from BSR, followed by Finland, Germany and Denmark. This shows that advancements in technology, high income levels and well coordinated legislation base, use of economic instruments in old EU


member states have provided good results not only to inhabitants of these countries but also for the environmental situation.

Conclusions

BSR countries can be considered as good perspective for implementation of green economics because of considerable achievements in several countries of the region using renewable energy, improving technologies, preserving environment, reducing inequality, improving well being. Although each country has its own traditions, history, culture and politics, this diversity can be mutually beneficial in case of good cooperation.

In total the old EU member states from the BSR have managed to achieve better results in ecoefficiacy and decoupling of resource consumption and pollution from economic growth. Energy intensity of economy, GHG emission intensity of output and waste management measures are examples of this. The new member states and whole region can benefit from technology transfer, knowledge sharing and other forms of partnership.

However old EU member state have much higher per capita consumption levels and this leads also to the higher household direct and embedded energy consumption, waste generation and at the end higher ecological footprint from consumption. But the trends in the new member states are alarming, as increasing income leads towards higher resource consumption and pollution levels linked to the life cycle of the products and services.

The ecological situation in transition economies improved considerably when industry output reduced and policy changed along with the collapse of the Soviet Union. EU accession process also contributed for better environmental situation as EU Environmental standards and basic environmental management principles were introduced.

High income, sophisticated environmental policies and technology advancements improve environmental health, air quality, resource management, higher life satisfaction and life expectancy which offset drawbacks of bigger consumption in the old EU member states and results in higher rankings in Environmental Performance Index and Happy Planet Index with some exceptions.

Common resource—the Baltic Sea and good neighbouring relations serve as facilitators for active cooperation in environmental issues in the region.

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Motifs and Impediments for the Harmonization

of Accounting Regulations for Small and

Medium-Sized Companies in the EU

Tamara Cirkveni RRiF High School for Financial Management, Zagreb, Croatia

Small and medium-sized companies in most EU countries form a considerable share in the total number of

companies and are also an important development impeller of the entire economy. Therefore, one of the most

essential goals of accounting authorities in the EU is accomplishing the harmonization of accounting regulations

for these companies. In this paper, the author have discussed and explained the main motifs and impediments for

this harmonization. One of the main motifs is a big span and complexity of international standards of financial

reports which is allowed and even prescribed in many countries. Some of the main impediments are a lack of

uniformity as far as criteria for classification of small and medium-sized companies according to size are concerned

as well as the determining of limitations up to which the requirements in accounting standards for small and

medium-sized companies should be set.

Keywords: IFRS for SMEs, accounting regulation, small and medium sized entities, motifs, impediments

Introduction

Efforts to “harmonize” accounting around the world began even before the creation of the International Accounting Standards Committee. Companies seeking capital outside of their home markets and investments internationally faced increasing problems resulting from national differences in accounting measurement, disclosure, and auditing (Choi, Frederick, Meek, & Gary, 2008). In the last thirty years, this process has been mostly oriented on large entities. The bases of accounting regulation were made by the fourth and the seventh directive of the EU. However, they failed to obtain a desirable and expected level of financial reporting transparency and comparability.

The process of adoption of international financial reporting standards (IFRS) in both EU and non-EU countries has created further bases for establishing accounting regulations, especially for well-rated entities. The Regulation of the European Parliament and of the Council (1606/2002/EC dated July 19, 2002) (Retrieved July 20, 2010, from http://www.eur-lex.europa.eu) has had an important role in this process and it has also prescribed a required application of the IFRS for all entities which are rated on the EU financial market and which have been Tamara Cirkveni, MSEc, Economy Department, RRiF High School for Financial Management. Correspondence concerning this article should be addressed to Tamara Cirkveni, Vlaška 68, 10 000 Zagreb, Croatia. E-mail:

[email protected].

MOTIFS AND IMPEDIMENTS FOR THE HARMONIZATION 1022

preparing consolidated financial reports since May 1, 2005. This requirement has substantially influenced the acceptance of the IFRS as a frame of financial reporting for other (both well-rated and non-rated) entities in the EU member states as well as in African and Asian countries. Although these EU and IFRS directives have played a vital part in the establishment of the entire accounting regulation, their requirements are adjusted mostly for large entities which manage a sufficient number of professional accountants and whose beneficiaries of financial reports need more information about their management. The requirements for small and medium-sized entities, which account for 95% (Klikovac, 2009) of all entities in most EU countries, were therefore placed in the background, i.e., they were left to national accounting regulations. Due to those reasons, some countries accepted the IFRS even for small and medium-sized entities (e.g., Malta, Cyprus), while other countries have created national standards in order to reduce the requirements in the financial reporting for small and medium-sized entities (e.g., Great Britain, Slovenia, Ireland, Sweden). Due to the fact that it is obvious that the IFRS are too complicated to be applied for small and medium-sized entities, the motifs for the harmonization of the accounting regulations for small and medium-sized entities in the EU are numerous. Seven years ago International Accounting Standards Board (IASB) has therefore started creating global accounting standards for those entities as a part of the project “International standards for small and medium-sized entities” (IFRS for SMEs). A lot of problems occurred in that process, the most important were the lack of uniformity as far as criteria for classification of small and medium-sized entities are concerned as well as the determining of limitations up to which the requirements in accounting standards for small and medium-sized companies should be set. Nevertheless, the IASB published the IFRS for SMEs in July 2009. Ultimately, the open question that still remains to be answered is whether the European Commission will and in which scope adopt these standards as a constituent part of accounting legal regime in the EU.

The Characteristics of Accounting Regulative in EU

The European Union (the EU) is a regional organization of European states through which its members accomplish common goals such as well-balanced economic and social development, high rate of employment as well as the protection of citizens’ rights and interests. Since January 1, 2007, the EU consists of 27 member states with the population of approximately half a billion people (Retrieved July 20, 2010, from http://www.entereurope.hr). The accounting legal regime in the EU is comprised of directives and regulations, and regulatory bodies that regulate accounting at the EU level are: European Parliament, Council of the European Union, European Commission, European Financial Reporting Advisory Group and Accounting Regulatory Committee.

The accounting system of every EU member state as well as of those states which aspire to that status is based on regulations and directives of the EU. Beside them, an important role is played by decisions, recommendations and opinions which are passed by the EU legislation. Regulations which are passed at the EU level are binding for application in all EU member states, i.e., individual adoption for their application is not needed in the EU member states. At the EU level, several regulations of the European Parliament and of the Council, as well as of the European Commission have been passed and are referred to the accounting regulative. The regulation that defined the beginning of harmonization of the accounting regulative in the EU is the Regulation of the European Parliament and of the Council (1606/2002/EC dated July 19, 2002). According to this


regulation all entities which are rated in the financial market of the EU and which prepare consolidated financial reports are bound to apply the IFRS since January 1, 2005.

The EU directives are adopted by the legislation of every member state. Although all EU member states are bound to adopt the directives, it does not mean that the institutions within the member state have to comply with the directives if their content is not prescribed by their legislature. The most important directives which edit accounting area are the fourth and the seventh directive, as well as the directives which define the financial reporting in the banks and insurance companies. The fourth directive has harmonized the appearance of balance, as well as of the profit and loss account, and it has also defined the minimum of information that the notes to the financial statements have to contain. An important base for the comparability of information in the financial reporting has therefore been created. The seventh directive has defined the entities which should prepare the consolidated financial reports and that has standardized the requirements which are referred to those reports. However, the success of EU harmonization efforts has been debated. For example, member states generally did not scrap their existing accounting rules when adopting EU directives. Another issue is the scope to which member states enforced compliance with the directives (Walton, 2007).

The prerequisite for a complete acceptance and spread of the IFRS and which is published by the IASB was made by the directive. Current application of the IFRS in the world shows that the IFRS are accepted world-wide, that many countries use them as a basis for their national standards and that they are accepted by numerous stock-markets and controllers which allow domestic or foreign entities to deliver the financial reports prepared according to the IFRS (Choi, Frederick, Meek, & Gary, 2008). The application of the IFRS during the preparation of consolidated financial reports for non-rated entities is allowed by/in the majority of EU member states. For the individual financial reports of the EU member states, the application of the IFRS is somewhat different. Therefore, in ten EU member states the use of IFRS is not allowed (e.g., Austria, Belgium, the Czech Republic, France etc.). The above application suggests that in the majority of the EU states, IFRS are accepted when consolidated financial reports are prepared, and to a lesser scope when individual financial reports for non-rated entities, i.e., for small and medium-sized entities, are prepared.

The directive provides the member states to allow the application of the IFRS to the entities during the preparation of the individual financial reports, as well as to entities which are not rated in the regulated capital market (Tadijančević, 2005), i.e., small and medium-sized entities. Such a demand can be justified due to the fact that the IFRS meet the requirements of the external users with the goal of truthful and fair display of properties, management liabilities and results. However, the complexity of their requirements and solutions in some issues are not appropriate for the usage in the small and medium-sized entities. Therefore, in the majority of countries national legislature for the financial reporting of the small and medium-sized entities is applied. The countries which possess prescribed standards for small and medium-sized entities, and the EU members are Great Britain and Slovenia. Unlike the IFRS, the EU directives refer to all entities, even the small and medium-sized entities. The essential role in the financial reporting of the small and medium-sized entities is played by the fourth directive that beside the rules for the preparation and publication of the financial reports, recommends abbreviated financial reporting for those entities. Unfortunately, that proposal was not sufficient for solving the problem of financial reporting for small and medium-sized entities.


The Harmonization of Accounting Regulative for Small and Medium-Sized Entities

Small and medium-sized entities are an important promoter of the entire EU economics, and it is understandable that for some time a question is asked whether it is needed and how to harmonize the accounting regulative for those entities. Numerous accounting organizations have tried to answer these questions, but the central role was held by the IASB which has recognized the complexity of the application of the complete IFRS for small and medium-sized entities and which has also started the project to create the standards of financial reporting for small and medium-sized entities. For the main motifs of this action, the IASB has, beside the complexity of the IFRS, highlighted the fact that the adoption of global standards for small and medium-sized entities is necessary due to better protection of foreign suppliers, foreign banks which grant them loans, and due to foreign investors to whom the global accounting standards will ensure a desired compatibility (Retrieved July 18, 2010, from http://www.iasb.org). Despite all that, during the creation of global accounting standards there were numerous obstacles which had to be overcome.

The basic problem which complicates the harmonization of financial reporting for small and medium-sized entities is the criteria for classification of entities according to their size. It is enough just to be reminded that the fourth directive, the European commission and the national legislature of EU member states prescribe different amounts for the quantitative classification of entities (the sum of the balance sheet, total income, number of employees). On the other hand, the IASB has, during the defining of the standards scope for small and medium-sized entities, chosen the qualitative characteristics, i.e., the defining of the public liability during the classification of small and medium-sized entities. The usage of different terminology which denotes the same term (small and medium-sized entities) is equally indisputable. Besides, numerous authors as the main argument against separation of financial report for small and medium-sized entities from the one for large entities state the need for universality, comparability and reliability of the financial reports for all categories of entities. It is also vital to take into account that in some countries (e.g., Germany) financial reports traditionally serve also for the needs of informing and determining the profits (for distribution), and the IFRS are inappropriate for that function, especially because they are not oriented towards the precautionary principle, whose goals are the maintenance of capital and the protection of investors (2005).

In the process of harmonization of financial reporting an important role belongs to the IASB which has already in 2001 with Standards Advisory Council (SAC) for the first time considered the need for creating accounting standards for small and medium-sized entities, and two years later (i.e., 2003) it launched their creation. In the process of developing the IFRS for SMEs, the IASB conducted an extensive world-wide debate. Working group comprised of forty members—experts cooperated with the IASB on the structure and content of the IFRS during different development stages. Standards draft was published in 2007 and it was translated into five languages which contributed to the widening of the circle of experts involved in the debate1. It has also been tested on more than 100 small entities in 20 countries resulting in a further simplification of standards.

Final version of the IFRS for SMEs was published in July 2009. The bottom line is that the SMEs standards actually represent a shortened form of the IFRS (the scope is reduced for 90%). Certain requirements which are considered inappropriate for the application in small and medium-sized entities are not contained in the IFRS for

1 Mrša, Josipa. Iz odbora za MRS-Objavljeni su IFRS-a za mala i srednje velika poduzeća. RRiF, 2009., br. 08/09., str. 49.


SMEs (see Table 1).

Table 1 IFRS Requirements Which Are Not Included in the IFRS for SMEs IAS 33 Earnings per share IAS 34 Intern in financial reporting IFRS 5 Non-current assets held for sale and discontinued operations

Besides, in the IFRS for SMEs simpler variants are involved in subsequent valuation of tangible fixed assets as well as simplified recognition and establishment of financial assets.

The recognition of tax assets and deferred tax liabilities is also simplified. The IFRS for SMEs consist of 35 sections and a glossary (Retrieved July 25, 2010, from http://www.iasb.org), and they should be applied by the entities which do not have “public liability”.

Obstacles for a Possible Application of the IFRS for SMEs

Despite the fact that the IFRS for SMEs are supported by numerous international organizations, the EU support is still debatable. In fact, in September 2007 Charlie McCreevy, the European Commissioner for Internal Market and Services declared that the IFRS Draft for SMEs was not simplified enough to be appropriate for application in most small and medium-sized entities. Due to these reasons numerous efforts were subsequently made in order to simplify and adjust the accounting requirements according to the requirements of small and medium-sized entities. The EU commission has decided to conduct a consulting research (Retrieved June 20, 2010, from http://www.ec.europa.eu/internal market/consultations/2009/ifrs for sme en.htm) about the need to simplify the directives’ demands in order to create the basis for the application of the IFRS for SMEs. One of the important questions of the research was to determine whether the IFRS for SMEs appropriate for the application in the EU. The majority of respondents answered affirmatively (13 of 22 countries). The countries which support the application of the IFRS for SMEs underline the enhanced comparability of information in financial reports since the application of these standards, the attraction of foreign capital, and therefore the reduction of capital expense due to application of universal accounting standards as main arguments for their application. On the other hand, some respondents think that the IFRS for SMEs are too complex for application in small entities, i.e., that the consequence of the application of these standards will be contradictory due to high expenses of the preparation for their application. An overview of the most important arguments for and against the application of the IFRS for SMEs is shown in Table 2.

Table 2 An Overview of Arguments for and Against the Application of the IFRS for SMEs According to the Respondents Arguments for IFRS for SMEs Arguments against IFRS for SMEs enhanced harmonization and comparability of information in financial reports the duplication of administrative burden for those entities

reduced capital expenses the cohesion of accounting and tax regulative in some countries can result in double financial reporting

the usage of an “unique accounting language” they are not useful to the entities which do business “locally” the frequency of changes in the accounting regulative

Respondents also held a wide range of views on how to deal with incompatibilities between the Accounting


Directives and the IFRS for SMEs. Some countries implied that a mechanism should be formed which would maintain the compatibility of accounting standards and directives and enable their alternations. Others suggested that conflicts should be resolved on a case by case basis by national authorities, or that priorities should be established in the framework of the Directives. Finally, some respondents considered that the IFRS for SMEs should not be applied in case of incompatibility.

Due to all these reasons the European Financial Reporting Advisory (EFRAG) conducted a research (Retrieved July 20, 2010, from http://www.efrag.org/newa/detail.asp?id=548) which was directed to analyse the compatibility of the IFRS for SMEs and of the fourth and the seventh directives. The aim of this research was to determine the areas of incompatibility of the IFRS for SMEs and of the directives. According to the conclusion of the EFRAG the incompatibilities in the IFRS for SMEs are determined in numerous areas (see Figure 1).

Figure 1. An overview of requirements for the IFRS for SMEs which are incompatible with the EU directives.

Data about the requirements for the modernization of the directives were gained due to the consultations conducted by the EFRAG and IASB. Numerous interest groups consider that the directives should continue to be the framework of the financial reporting in the EU and that they should prescribe the preparation of reports about the money flow and minimal information which should be presented in the notes. Other interest groups intercede for the making of directives which are drafted on the principles and not on the detailed elaboration of the financial reports’ structure. When defining the value of the items which are shown in the financial reports, numerous groups consider that the application of fair value method represents a great burden for small entities and that it is in contradiction with the basic principle “think small first” on which reviewed assets should be based. In order to enable quality accounting information, many who are involved think that the extraordinary items should again be placed in the financial reporting frame. All the provided requirements refer to the need for further consultations and debates in order to coordinate the directives’ prescriptions with the IFRS requirements and the IFRS for

Requirements for the IFRS for SMEs which are incompatible

with the EU directives

1. The prohibition to present “extraordinary items”.

2. The requirement to measure financialinstruments (non-basic financial instruments) atfair value.

4. The requirement to recognise immediately inprofit or loss any negative goodwill.

3. The requirement to presume the useful life ofgoodwill to be ten years if can’t be estimatedreliably.

5. The requirement to present the amountreceivable from equity instruments issuedbefore the entity receives the cash as an offset toequity and not as an asset.

6. The prohibition to reverse an impairment lossrecognised for goodwill.


SMEs requirements, all with the purpose of creating a unique accounting regulation for all entities.

Conclusion

Motifs for the harmonization of the accounting regulation for small and medium-sized entities are multiplying due to the process of globalization. However, there are also many obstacles which have appeared in this process. One of the obstacles is the acceptance of new solutions in the countries which have solved the problem of the requirements’ scope in the IFRS by adopting national accounting standards for small or small and medium-sized entities. Another obstacle is the act of defining the criteria for classification of small and medium-sized entities, i.e., defining whether those are just the entities which do not have the public liability, as the IASB suggests. The application of fair value and extraordinary items in the accounting standards for small and medium-sized entities is also relevant in determining the requirements which are appropriate for the application in these categories of entities. The determination of scope and limitations is a very complex work, therefore it is not surprising that the process of adopting the IFRS-a for SMEs has lasted for seven years and that it has not resulted in the standards whose requirements were entirely accepted by the European commission and numerous interest groups which were involved in the debates related to the requirements of those standards. The demand of coordination of the accounting regulations has imposed the demand of coordination of the IFRS for SMEs with the directives whose prescriptions are based on the fundamental accounting principles which have created the basis for the harmonization of the accounting regulation.

References Anonymous. (2005). Problems and opportunities of an international financial reporting standard for small and medium-sized

entities. The EAA FRSC’s Comment on the IASB’s Discussion Paper. Accounting in Europe, 2, 23-45. Anonymous. (2010). EFRAG Compatibility analysis: IFRS for SMEs and the EU Accounting Directives. Retrieved July 20, 2010,

from http://www.efrag.org/newa/detail.asp?id=548 Basis for Conclusions on Exposure Draft. (2007). London. IASB. Retrieved July 18, 2010, from http://www.iasb. org Choi, F. D. S., & Meek, G. K. (2008). International accounting. Pearson Prentice Hall. Klikovac, A. (2007). Financijsko izvještavanje u Europskoj uniji—komparativan prikaz. Ekonomski pregled. Mikrorad. Zagreb. Klikovac, A. (2009). Financijsko izvještavanje u EU: Harmonizacija financijskog izvještavanja za mala i srednja društva. Mate:

Zagreb. Mrša, J. (2009). Iz odbora za MRS-Objavljeni su IFRS-a za mala i srednje velika poduzeća. RRiF, 08/09. Ramljak, B., & Žager, K. (2002). Potreba i iskustva drugih zemalja u razvoju računovodstva malih i srednjih poduzeća. zbornik

radova XXXVII. Simpozija Pula, HZRIFD, Zagreb. Smrekar, N. (2009). Usklađivanje nacionalne i međunarodne regulative financijskog izvještavanja malih i srednjih poduzeća.

zbornik Ekonomskog fakulteta Zagreb. Mikrorad, Zagreb. Tadijančević, S. (2005). Usklađenost financijskog izvještavanja i revizije u Hrvatskoj s pravnom stečevinom EU-a. zbornik

radova XL. Simpozija Pula. HZRIF. Zagreb. Walton, P. (2007). European Harmonization, International Finance and Accounting Handbook. 55. Žager, K., et al. (2009). Računovodstvo malih i srednjih poduzeća. Mikrorad. Zagreb.


Change of Management Values in Estonian

Business Life in 2007-2009

Anu Virovere Tallinn University of Technology, Tallinn, Estonia

Estonian Entrepreneurship University of Applied Sciences, Tallinn, Estonia

Mari Meel Tallinn University of Technology, Tallinn, Estonia

Eneken Titov Tallinn University of Technology, Tallinn, Estonia

Estonian Entrepreneurship University of Applied Sciences, Tallinn, Estonia

The paper deals with the change of management values in Estonian business life in the year of the rapid growth

(2007) as compared with the year of hard decline (2009). The hypothesis is set that company managers do not have

permanent values but they change accordingly to the change in economic conditions: in economical welfare

situations business-managers more eagerly take larger responsibilities on ethical and philantrophical stages but in

crisis only the lower stages (economical and legal ones) could be detained. In the paper, we firstly observe if values

change in general and secondly we study if our pre-stated hypothesis holds. As the research method we use the

method of critical incidents.

Keywords: core values, organizational values, economical crisis, sustainability, change of values

Introduction

In 2001, Drucker wrote:

The half century after the Second World War, the business corporation has brilliantly proved itself as an economic organization. In the next society, the biggest challenge may be in its social legitimacy—its values, its mission, its vision. The wave of distrust of business generated by the recent financial crisis has proved how right it was. (as cited in Paschek, 2009)

Importance of CSR During the last decades, corporate social responsibility has become a more important topic in countries with

developed economies. Discussions about it intensified already in the end of the 1960s with the rise of Milton

Anu Virovere, Ph.D. candidate, Lecturer, Chair of Marketing, Tallinn University of Technology; Management Institute, Estonian

Entrepreneurship University of Applied Sciences. Mari Meel, Ph.D., Associate Professor, Chair of Operations Management, Tallinn University of Technology. Eneken Titov, Ph.D. candidate, Department of Business Administration, Tallinn University of Technology, Lecturer and

Director of studies in Management Institute, Estonian Entrepreneurship University of Applied Sciences. Correspondence concerning this article should be addressed to Eneken Titov, Estonian Entrepreneurship University of Applied

Sciences, Suur-Sõjamäe 10a, Tallinn, 11415, Estonia. E-mail: [email protected].

CHANGE OF MANAGEMENT VALUES IN ESTONIAN BUSINESS LIFE 1029

Friedman’s (1963, 1970) ideology: “There is one and only one social responsibility of business—to use its resources and engage in activities designed to increase its profits so long as it stays within the rules of the game”. In accordance to globalization and strengthening of citizenship movement the self-consciousness of societies has risen and that has brought along the broadening of meaning of corporate social responsibility and also, sustainability has gained the leading position. The issue of sustainability has also become important due to the constant deterioration in environmental conditions and to the growth of exploitation of poor countries’ resources.

On the other hand, at international climate conferences, the views of wealthy and underdeveloped countries often collide in the question of social responsibility towards nature: representatives of underdeveloped countries declare that wealthy countries have higher responsibility and must bear higher costs in protection of environment, while poor countries just cannot do it—they are not able to do more than stick to the basic survival game. The authors of this article were fascinated with the thought, how suggestible and changing are people’s attitudes and way of thinking towards the change of economic conditions, for example, does the economic crisis, growing debt-load and poverty weaken the European Union’s usually heightened responsibility towards nature and traditional efforts to lessen social inequity?

Importance of Values Values are the ideas and beliefs that influence and direct our choices and actions (Gini, 2004). Values

perform three functions for individuals and organizations—to defend against perceived threats (defensive values), to adjust to society (stabilizing values), and to foster movement toward self-actualization (growth values). All these three types of values are necessary and leadership definitely carries an important role in supporting these values and creating opportunities to do that (Hultman & Gellerman, 2002). Effective leadership is about finding balance between economic success and well-being of your employees, and at the same time, it is about balance between society and the owners’ demands. Therefore there are values by nature dynamic and influenced by economic environment. Other authors have also drawn attention to the change of values, for example, professor Lauristin (2008) has indicated the negative change of values in Estonian liberal society where borderless market economy has turned into total sales ideology, democracy has turned into egoistic competition between political parties and state-of-law has opened its doors to large-scale bureaucracy. Prevalently, Estonian manager’s leadership style does not based on long-term management values. However, the enduring leadership is important in order to assure the sustainability. Enduring leadership is leadership that outlasts and transcends the individual—has been shown by research to be a predictor of long-term success (Moon, 2001).

Influence of crises to management. Today’s managers are under strong pressure, especially during the economic crisis, because the rapid development of technology is forcing continuous change and new knowledge economy requires people who are devoted to their work. This can be considered a conflict situation where successful conflict management, turning the conflict into something productive, could help implement changes faster. Empirical research in Estonian organizations indicates that the best predictors of attitude towards change are ethical values and business ideological values (Alas, 2009). The ability to use crisis as a productive conflict and to base on true business ideological values in practice, would enable the organization to do the right changes as well as to be sustainable. To understand productive conflict we should consider conflict management strategies because they strongly influence subsequent interactions and outcomes, and conflict issues because they impact on


conflicts management strategies through thoughts and feelings (De Dreu, 1997). Conflict studies, carried out in Estonia show that Estonian leaders are lacking the knowledge of ethics and

the will to resolve conflicts and understand the usefulness of a good and motivating work atmosphere. They do not realize that resolving conflicts and assisting the employees will be beneficial to the company and thereby make a major contribution to a more positive environment at work which significantly improves the employees’ motivation and loyalty and the companies market position (Virovere, Kooskora, & Valler, 2002).

Influence of working environment to job satisfaction. During the time of fast changes every organization needs creativity and innovation and the will of employees to go along with the changes. That means creating an environment where creativity is made possible. Organizational culture and microclimate are directly influenced by a manager’s leadership style and leadership values. Studies carried out in Estonia show that especially people with an university education were most less satisfied with management and work satisfaction was the lowest among employees who had worked for the company for four and five years (Alas, 2009). Based on these results, it is possible to conclude that there is a lack of appreciation of the working environment and workers in Estonian organization.

The Change of Management Values In this article, we tried to follow, how has the economic crisis influence the attitudes and management values

of Estonian managers: Estonia’s relatively fast and successful emerge into West-European (capitalist) society has often been explained by Estonian liberal-friedmanistic economic policy. After joining EU (in 2004) both the state and society here have started to force the businesses towards broader social responsibility and triple-bottom-line way of thinking is emerging. That means that a business (its management) should feel a broader responsibility towards social and ecological environment than just a legal one. It is logical to assume that during fast economic growth and relative wealth, the managers of companies were susceptible towards that new approach. But how are things now when companies have to concentrate on survival?

Theory and Hypothesis The Hypothesis

Traditionally, corporate social responsibility is divided into four stages (look for, e.g., Carroll & Buchholtz, 2009; Ferrell, 2008; Crane, 2010; etc.). Initially the model was proposed by Carroll soon in 1979 and advanced later (1999, 2009). The stages are differentiated as the ground ones—economical and legal, and the upper ones—ethical and philantrophical responsibilities. Logically, it could be supposed that in the situation of economical welfare business-managers are more eager to take more larger responsibilities on ethical and philantrophical stages and vice versa, in hard conditions of economical crisis it would be well enough if only the lower stages could be detained: at times of economic decline companies do not have means for philantropic causes and also in the case of ethical considerations it is observed that they would not cause additional expenses to the company.

The Base of the Hypothesis That hypothesis seems to be supported by several earlier researches about the behavior of international

organizations while locating territories of production. Reich (1992) shows that already since 1970s a trend is emerging where multinational enterprises, which are operating in the conditions of severe global competition and


therefore are forced to innovate their production continuously keeping at the same time prices low, have nothing to do but to organize their work in the way as by placing their innovative units (research and development) in developed country, with highly educated and expensive work force, and their mass production in underdeveloped countries where the cost of work is low (as usual the lower cost of work force is accompanied with poorer labor conditions, absence of trade unions, lower safety protection etc.). This means that while locating their organization they follow (in territorial sense) Carroll’s 4-level model, that higher-level responsibilities are considered only in the economically developed mother country. In poor countries, where production units are located, it is well if legal obligations are met at minimal range (according to the looser legislation base of under-developed countries) and the goal is making maximum profit. Several researches show that this is a continuous trend both in the US and EU. Also, it is mentioned that in the case of international competition it is inevitable (for example, Meel & Saat, 2000). Crane (2010) shows that a growing number of multinationals as for example major European brands (Adidas, Reebok, Marks and Spencer etc.) as well as high-profile US brands (Disney, Levi’s, Nike, Wal-Mart etc.) are involved in these location-based ethical conflicts.

The influence of crisis to an organization. Talwar (2009) wrote also that, in an era of global transformation, a narrow focus on strategies for enhancing profitability will no longer be sustainable, and organizations will need to seriously address long-term geopolitical social issues to attain sustainability with the adoption of universally acceptable ethical work standards. Practicing values is an important aspect for building a successful strategy and corporate culture. Based on the banking crisis it is also possible to draw parallels between organizational values and success. For example John Holland (2010) writes in his article that:

Top management weaknesses in the failing banks were important in undermining bank SCA and increasing relative vulnerability to crisis. Top management weakened other key resources such as risk management skills at middle management and operational levels by downplaying relevant knowledge. They appeared not to have had an explicit strategy to develop human capital, structural capital and relational capital at all levels in the bank or how to use it to improve risk control and intermediation. They downplayed ideas of adequate equity, and of sufficient cash. They sought to gain the maximum benefits of leverage ignoring the impact on bank functions and risk exposure.

Values and Maslow’s Hierarchy. It can be logically assumed that the same tendency that works locally (territorially) should work in the time dimension, according to the change of economic conditions. During economic recession while most of any country’s population fall to lower levels of Maslow’s hierarchy of needs (main problems are making a living, lack of jobs is increasing) fundamentalistic claims rise also in managerial values: compared to developed societies only legal obligations are met, philantropic and ethical obligations will be left waiting for better times. In order to manage economical crises, there is a need to actualize Maslow’s hierarchy upper needs—self-actualization and commitment, which would help to manage changes in the organization as well as to become innovative and sustainable. Based on the same logic, it can be assumed that company managers do not have constant moral certainties or values, but they shift according to the changes of economic conditions: During the good times, they tend to behave according to virtues—show up more caring, respect, valuing the employees etc.. During the recession, employees are fired more easily, in communication with the employees the managers are stricter, aggressive and autocratic. Only these values are considered that are connected to the company’s economic success and sustainability.

Stability of values. On the other hand, researches that prove exactly the opposite (Collins, 2001) show that


not all managers let their moral values to be shaken by the outside environment. Especially in times of recession like in 1929, just those companies that did not cross the line beyond their main values survived. Different researches (Collins, 2003; Drucker, 1972) even prove that sticking to core values is the key issue in an organization’s sustainability. In really remarkable companies change is a constant factor, but they distinguish issues that should never be changed and those that should be opened to change. They distinguish their timeless core values and constant mission (that should never change) from ways of action and business strategies that have to be changed according to the changes in the world (Collins, 2003). Due to Fukuyama (2001), the sustainability of an organization is directly linked to the question of core values, although we have shared values, they may not yet produce social capital if the values are wrong. Profit orientation as a value has been replaced with a new value of sustainability (Drucker, 2003). Also, a research by Wilson and Eilertsen about strategic planning and survival during economic recession produced results that show the importance of core values. Although in 2009, organizations have more focus on cash flow and liquidity than they did a year ago, managers are experiencing greater internal pressures or conflicts inside the organization because of the changes in business environment, leadership is using the situation to make difficult decisions, and there is more leadership steering than managers had experienced in the past, despite these pressures, two-thirds of managers are convinced that their actions during the crisis remain aligned with the values and vision of the organization (Wilson & Eilertsen, 2010).

The association between values and organization’s success has also been researched as an important aspect. With reference to corporate ethical values, Hyman (1990) contendes that positive employee perception of top management’s values and beliefs will lead to higher performance outcomes. Bergeron (2007) concludes that individuals that perceive high congruity between an organization’s ethical values and their own will feel more motivated. Schwepker (2003) suggests that congruity between the ethical values of an employee and their organization will positively influence employee’s performance.

Flowingly we are trying to research how constant the organizations’ management values have been in Estonia during the last abrupt changes in the economical environment: At first, we observe if values change in general; as for second, we study if our pre-stated logical assumption holds—that while the economic situation deteriorates drastically, the basis of management values change and socially responsible and ethical behavior receives less consideration.

Organizational Effectiveness vs. Values One important aspect that draws attention to the importance of values in an organization is the connection

between organizational values and organization’s success. Several modern researchers have pointed out that the constancy and direction of organizational values are some of the most important aspects to predict a company’s success. For example, Kotter and Heskett have written in their book Corporate Culture and Performance, that companies with strong adaptive cultures based on shared values outperformed other companies by a significant margin. For example, they show how valuing interest groups influence success—companies that emphasized all stakeholders—employees, customers and stockholders, and focused on leadership development, grew four times faster than companies that did not. They also found that these companies had job creation rates seven times higher, had stock prices that grew 12 time faster and profit performance that was 750 times higher than companies that did not have shared values. Collins and Porras (2003) confirm the same tendency in their book Built to Last, where


they compared organizations with gyroscopes which keep the organizations in balance—the main values stay changeless, but other organizational processes continue to change. They show that companies that consistently and in long-term focused on building strong corporate cultures outperformed companies that did not by a factor of six and outperformed the general stock market by a factor of fifteen. Beu, Buckley and Harvey (2003) set the organizational values even on a higher position while they say that business, as a type of society, is possible only within a certain social context of institutions, agreements, understandings and shared values.

Shared Values and Job Performance In the case of value-based leadership, it has been discussed that in reality, all organizations are value-driven.

But what is important is the fact whether the values are conscious, shared and lived, or unconscious and undiscussed. When values are unconscious and undiscussed, the culture of the organization usually reflects the personality of the leader. Unless the organization has a very evolved leader, it is unlikely that there will be an alignment between employees’ personal values and the leader’s values (Fitzgerald & Desjardins, 2004). At the same time, a high consensus in followers’ perception of their leader does not assure that performance is in line with company expectations. Consequently, it is proposed that high work values moderate the relationship between consensus and performance (Schyns, 2006).

When values are conscious and discussed, it is likely that they are shared and lived. In this case, there is a stronger possibility that that there is an alignment between employees’ personal values and the organization’s values (Fitzgerald et al., 2004). Westerman and Cyr (2004) analyzed personality and work environment congruence and found that value congruence was the best predictor of job satisfaction. Verquer, Beehr and Wagner (2003) also found that value congruence and turnover intent are in strong positive correlation with each other. One other important result was that when individuals’ values match those of their organization, they are less likely to leave.

A whole theory has been created to explain the connections between organizational environment and the individual (the person-environment fit theory), that assumes that individuals prefer an environment that possesses characteristics (e.g., values, beliefs) that are similar to their own (Kroeger, 1995). The theory says that if people fit well with an organization, they are likely to exhibit more positive attitudes and behaviors.

Leadership and Shared Values Therefore it is important to understand while connecting values and organizational success to each other

whether the behavior of the organization is based only on the manager’s or the organizations shared values. It is also important that the organizational values cannot be seen separately of leadership and management behavior. Terrence Deal and Allan Kennedy found out that leaders should not hesitate to communicate their values widely and advocate for them vigorously. They considered important that leaders create a guiding vision and shape shared values. James MacGregor Burns believes that leaders should help followers reframe their understanding of core values from self-interest to a broader view of the common good (Whitmire, 2005). Peter Drucker (2003) wrote:

The leader is visible; he stands for the organization. He may be totally anonymous the moment he leaves that office and steps into his car to drive home. But inside the organization, he or she is very visible, and this isn’t just true of the small and local one, it is just as true of the big, national, or worldwide one. No matter that the rest of the organization doesn’t do it; the leader not only represents what we are, but, above all, what we know we should be.


Also, Alas and Tuulik (2004) emphasized the importance of managers in strengthening the values and believed that common values can be attained through improved training and improved management practices and also by having the right leaders for the job.

We have no reason doubting the importance of behavior of managers in influencing the values of an organization but more important become the question—how important are their actions in forming organization’s values in the eyes of the managers themselves. For example, based on the research of McKinsey and Co in 2009 (763 executives who responded) two most important activities for managers were “leadership (shape and inspire the actions of others) 49% of respondents and “direction” (capacity to articulate where the company is heading and how to get there) 46 % of respondents, but activity “foster a shared understanding of values” was important for only 8% of respondents. Researchers claim that ensuring shared values has become less important since the economic crisis began, while the other two qualities have become more significant (Wartzman, 2009).

Therefore, of critical importance is how much do manager’s value spreading and following the organizational values inside the organization. While getting over the crisis those organizations survive that have kept to the same core values in the long run.

Consultant Kane (2009) has described how core values affect performance and managers definitely have an important role in that process. She believes that: “Managers and others throughout the organization give priority attention to what is stressed in the corporate values system and this in turn supports producing the priority results”. If the employees have acknowledged the core values they make better decisions, because they are guided by their perception of the shared values. Also, if employees share the values then they are more likely to recognize that they are an important part of the organization. They are more motivated because life in the company has more meaning for them. They work harder because they are dedicated to what is expressed in the organization’s core values.

Values Which Predict Success Peters’ and Waterman’s seven values of excellence. Several authors have investigated which

organizational shared values predict success. Many researchers have been carried out where connections between different shared values and organizational success have been investigated. Boxx, Odom and Dunn (1991) used Peters’ and Waterman’s seven values of excellence, stated in 1982 (superior quality and service, innovation, importance of people as individuals, importance of details of execution, communication, profit orientation, and goal accomplishment) and analyzed their correlation to work satisfaction. Although positive correlation was found among highway and transportation managers, the results can be generalized because later researches also confirm correlations between values and work satisfaction.

Hultman’s 15 values. Hultman has brought out 15 values (self-directed learning, adapting to change, balance, seeking opportunities in the midst of uncertainty, utilizing ability, distributing rewards fairly, finding satisfaction in work, serving mutual interests, working as an owner, prizing wisdom, being authentic, seeking truth, celebrating differences, accepting people and viewing people as ends in themselves), that in his opinion are particularly relevant for success in this current business climate of global competition and instant communication. Those values also happen to be humanistic values that foster wholeness and integration (Hultman & Gellerman, 2002). Hultman also stresses the importance of connection between organizational and individual values: “Effective culture is one that successfully balances individual and organizational values, that is, walking the


tightrope to success” (Hultman & Gellerman, 2002). Based on research he also claims that profits are higher when individual and organizational values are aligned. He writes that many organizational problems can be traced back to people’s values (Hultman & Gellerman, 2002).

Risk-taking value and success. Organizational success has been also tied to risk-taking. Zukerman and Kuhlman’s (2000) study show that generalized risk taking is related to scales for impulsive sensation seeking and aggression. Logically, it could be guessed that risk-taking is rather positively connected to organization’s success but based on several researches the connection seems to be indeed negative. Rauch and Frese (2002) show that high risk-taking is negatively associated with business success, Estola (2004) found that risk-taking is a contributory factor to the unethical in business. Based on theory another value that is negatively correlated to organization’s success is concentrating of profit—Amos and Weathington found that there are general negative connotations associated with organizations that individuals perceive as only valuing profit (Amos & Weathington, 2008).

Ethical Values and Success Correlations between ethical values and different constructs (devotion, work satisfaction) have been studied

relatively much also they have proven to have positive correlation with organization’s success. For example, Hunt, Wood and Chonko (1989) discovered a positive association between corporate ethical values and organizational commitment, Singhapakdi, Kraft, Vitell and Rallapalli (1995) proved that those employees who exhibited a greater degree of belief in corporate ethical values placed more importance on ethical approaches and social responsibility, thus leading to the overall increased effectiveness of the organization. In the next study Singhapakdi, Rao and Vitell (1996) found that an organization that appears to have ethical values shared by its employees is relying on the ethical reasoning of its decision makers.

DeGeorge ties organization’s success to ethical values more directly, assuming, based on the study, that the freedom of business to make profit is limited by the values of fairness, equal opportunity, honesty and truthfulness (DeGeorge, 1999) and therefore setting ethical values on the first place above all other values. Others have also mentioned the importance of ethical values. Barnow, King and Krumina (2003) tied ethical behavior to social capital, based on the fact that making human relations more ethical directly increases the value of social capital. Alas and Tuulik (2004) develop the idea of importance of ethical values further, stressing organization’s ethical competencies by which they mean a company’s ability to change its activities so they conform to a set of ethical standards, and so, to manage its own values and commitments. Therefore, when an organization bases its actions of ethical values they also appear in organizational behavior as ethical competencies and thereafter the behavior of the organization as a whole influences the employees to work harder and finally the performance of the organization rises.

In different researches especially one value has been demonstrated as an important ethical value, which is fairness (Moorman, Niehoff, & Organ, 1993; Clemmer, 1993; Oliver & Swan, 1989). On one hand fairness is important as an organization’s core value, but employee’s perception of how fairly he or she is treated can become even more important. Perceived fairness is a key antecedent to commitment, job performance and job satisfaction. The value of employee-centeredness can also be discussed through two aspects. The importance of people as individuals’ value facet significantly related to job satisfaction. This circumstance indicates that


employees who perceive their organization as valuing employees as individuals report higher job satisfaction (Amos & Weathington, 2008).

Research

Research Methodology This research can be called critical discourse analysis (more information about this in Laherand, 2008, pp.

329-330, or Fairclough, 2002, pp. 91-116). The same principles have been used in other researches in Estonia by Lauristin (2000)—investigating articles appearing in two newspapers during 10 years that were collected out of certain two month issues of each year (Lauristin’s analysis is centered on typical metaphors that carry the means of translating social changes).

In a similar way, we use documents, namely business magazine Director’s 2007 and 2009 issues as the database for our qualitative study. In 2007, Estonian economy was in the phase of fast growth, quite fast inflation accompanied that also. Wages (and prices) rose, there was lack of work force, not lack of work. It could be guessed that in that kind of environment the managers of companies were considerate towards their employees (valued them relatively highly) and acted also more broadly responsible towards other interest groups (taking higher stages of model of Corporate Social Responsibility).

In 2009, Estonia was already in deep economic crisis, lack of work was serious, companies had hard time selling their products both here and outside markets, several companies had gone into bankruptcy, both wages and prices had stagnated—we guessed that in that kind of situation the values of entrepreneurs (in Estonia: managers of companies but also co-owners) would comply with lower stages of model of Corporate Social Responsibility.

As it can be seen we used magazine articles in our study. The articles were interviews with managers of companies—that kind of database can be named as documents. Hirsjärvi (2005) suggests data gathering method based on documents, mostly along with other data gathering methods but it can be used as an independent method also (Flick, 2006, pp. 245-246).

To ensure validity and reliability of our investigation we used Creswell’s (2003, pp. 196-197) proposed researcher triangulation which means using different observers to discover or minimize mistakes that come from the researcher’s person, like it was said above, we were reading the articles from business magazine director, issues of 2007 and 2009. Each of them included about 10-30 business related articles that in our view represented important values of that particular time in our business world. Two researchers read independently each article and wrote down the values that the article carried. One hundred and fifty seven articles in 2007 issues were read and 401 values were written down. One hundred and sixty five articles in 2009 issues were read and 340 values were written down.

Next the discovered values were analyzed. Values inside the article that we agreed upon us added to the database. If different values appeared, our third researcher read the article, too. If her opinion was the same as either of the two others those values were added to the database, if not, then these values were not added. In 2007, there were 27 and in 2009, 30 articles that did not show any clear values. The values added in the database were analyzed and similar were gathered together. If necessary the same articles were re-read to make sure that similarly named values would actually represent values with the same meaning. The results of research are shown in the Appendix A.


Discussion This research showed an important change of values in the period of 2007-2009 (see Appendix) that can be

described by Estonian economy reaching deep economic crisis, coming from very fast economic growth. That was also accompanied by very fast growth of unemployment (the number of unemployed people doubled in a year—2008 IV quarter, 53,500 people, and 2009 IV quarter, already 106,700 people. Estonian population is approximately 1.3 mil). In the beginning of 2010, unemployment continued to rise. This has been the highest level of unemployment in Estonia in 12 years (Toompark, 2010).

For many companies, it was more useful to go into bankruptcy than to continue working. In 2009 in Estonia 1,055 businesses and 14 non-profit organizations were estimated unable to pay their debt which meant that the number of bankruptcies rose compared to 2008, 2.5 times, in numbers 623 companies. Statistics show that every 133th business, that is 0.75% of all businesses in Estonia went into bankruptcy (Karner, 2010).

Innovation and creativity. If we analyze the change of values (see Appendix A), then we can bring out both important changes and also those values that were left at the same level and were mutually important both in 2007 and 2009. Innovation and creativity turned out to be very important. They are directly connected to fast changes in the society and the need to stay in competition and keep up with the fast development in technology.

Innovativeness, creating something new is also named as most important by professor Lauristin (Raun, 2010), who states that these are the keys of bringing a country and an organization of the crisis. In her words, it is clear that innovativeness is needed in Estonia, but it is another question if we can meet those needs. According to our research, creativity and innovation are important values by the number of times they appeared, but their change in time was not noted. If we talk about knowledge management as a management instrument in a modern organization, innovation being presented as a value must be considered as an important issue, because the innovation views and creativeness are the significant parts in process of knowledge management development.

Risk-taking. Economic crisis brings out the need to rising professionalism and risk-taking. If in economy taking risks is seen as a possibility to achieve higher results, then this study also confirms that in difficult economic conditions taking risks may mean ignoring ethical principles and laws. In order to use the risk to come out of the crisis one must in full awareness use the principles of risk management. Risk management can thus be defined as a systematic application of management practices to identifying, analyzing, treating, and monitoring uncertainties to better advice crisis management (Robert & Lajtha, 2002).

The rise of professionalism and courage to risk as values and using knowledge management is connected to the opportunity to use the situation for one’s own advantage, and therefore be more competitive in the market. The point of view is the courageous survive. The crisis gives an extraordinary possibility to change both organizations and economic structure. Managers who miss the opportunity to use the crisis for long-term changes not only waste a good possibility, but also make re-appearance of other crises possible (George, 2010).

Teamwork. The possibility for long-term changes is connected to crisis management and knowledge management. Knowledge management itself will not solve the problems. The active involvement of top management and the board and the exercise of their power on these knowledge matters are vital. As knowledge is vital the organizations need active teamwork by employees and management to implement changes. At the same time, research showed that in times of crisis, the importance of teamwork as a value has diminished greatly. Therefore, it is contradictory that knowledge management is important for coming out of the crisis but at the same


time Estonian managers do not value one of the main competencies of using it—teamwork. The reasons of lack of teamwork can be uncertainty and fear of losing one’s job. Therefore, everybody is concerned about keeping the status quo instead of actively searching for new opportunities. The same results are backed up by the fact that communication as a value diminished because teamwork means communication. It is difficult to conceive of how such learning, knowledge and regulation can control or change human nature, especially greed.

Motivation and valuing the employee. Analyzing these values that changed remarkably in negative direction, motivation and valuing the employee must be pointed out. The diminishing of these values can be explained by the fact that having a job became a value of its own during the time or crisis and being motivated while having a job was elementary. Simply put it means that for employees the content of the job, job environment, management activities and other factors that influence work motivation and satisfaction became less important because lack of work-force that described the earlier period had been replaced by massive lack of work. Changed economic conditions brought out sparingness and saving as values that represent in general the whole operations of an organization—the main savings were made in employee wages (in 2009 III quarter, Estonian average salary was 11,770 crowns. The drop in annual average salary was 5.9%. Still in 2008, the rise in average salary was 14.8%, average salary began to drop in the I quarter of 2008 (Toompark, 2010)), number of jobs, expenses on trainings and other employee-related costs. Because of that responsibility for the employees diminished as the employers often felt they had power over them (many possible new employees around). Although courage and risk as values appeared more often, it seems contradictory that aggressiveness and competition diminished. This tendency can be explained by several cartel agreements occurring during these times (Prangli, 2008).

Crisis management with full awareness. To use crisis as a possibility to develop and change economy, it is necessary to use crisis management with full awareness. Crisis management is broader in scope and can be defined as a set of ongoing and systematic processes for identifying, analyzing, and treating business crises by applying management practices (Mitroff, 1994). Crisis management frameworks can be categorized according to those that focus on why crises happen, which is termed operation-oriented frameworks, and those that focus on how crises impact organizations and the tasks that need to be performed in order to lessen their impact, which is termed process-oriented frameworks (Wang, 2009).

If we analyze the differences among negative values that appeared it shows that in the earlier period overbuying and overbidding, brutality and shrewdness were condemned. But in 2009, more organization-centered behaviors were brought out as negative values—too much profit-centeredness, lack of mission, not trusting employees and too little creativity.

Results and Conclusion

In this paper, we researched the constancy of management values in times of economic crisis. We started out with the hypothesis that in hard economic conditions less attention is paid to ethical values and economy-based values will take their places. At the same time, several earlier researches made us doubt that hypothesis. They said that those companies whose core values and mission stayed constant in long term survived any crisis better. In this research we followed the change in management values in 2007 (time of rapid economic growth) and 2009 (deep crisis in economy).


Moorman points out that the most important value is fairness and it should even be one of the core values of the organizations, but at the same time our research shows that the fairness as a value is decreased at the time of crisis. Comparing the values discovered by our research to values brought out by Peters, Waterman and Hultman, we can admit that four values of Peters et al. were also discovered in our study—superior quality and service, innovation, importance of people as individuals, communication. But in our study communication and importance of people diminish during the crisis. Other values, important by Peters et al.—importance of details of execution and goal accomplishment did not show up as significant in our study. Comparing our results to Hultman’s important values we can mention fairness and honesty, whereby the occurrence of honesty is increased and occurrence of fairness is significantly decreased-it confirms the decrease of importance of ethical values in the time of crisis.

The management values analysis 2007 versus 2009 shows a certain change in values but does not bring out the need for knowledge management and learning as a value. Also Holland (2010) claims that knowledge and lack of it was also deeply implicated in the crisis and in many of the above problems, and hence addressing these issues will be part of the solution.

What are the conclusions of that research? We must admit that there has been an important shift among management values in the period of 2007-2009. In the centre position, there is survival, not so much competition but still sustainability is tied to innovation and creativity.

Sustainability in a society, in Estonian economy coming out of the economic crises means that our economic structure also needs a change to be competitive. If Estonia has clearly approached the EU and developed countries economies characteristics in some ways, then we cannot say that about our economic structure’s dynamics unfortunately (Terk, 2007). James Collins and Jerry Porras of Stanford University (2003) found that the main differences between the visionary companies (companies that survived the economic crisis) and the control group with which they were compared were in their approach to values. All the visionary companies had a powerful sense of their identity and what they wanted to achieve. Managers in global business can help their firms to be successful and to minimize ethical conflict in several ways. The most important in sustainability of an organization is that the core values stay the same.

Surviving is also connected to opposite values, saving and frugality on one side but also courage and risk on the other. Diminishing competition seems illogical but it can be explained by making cartel agreements that represents growth in unethical behavior. Cartel agreements are connected to the need to lessen the competition on the market and therefore ensure the survival of your own organization but at the same time this activity shows ignorance of ethical values. At the same time, other researches (Alas, 2009) show that having ethical values present in the organization is an important prerequisite for employees to go along with changes.

As the research confirms the importance of ethical values like respect, valuing of employees, justice and responsibility has diminished remarkably, the hypothesis that was set—in hard times economic concerns prevail over ethical and philantropical ones—is proved right. At the same time the will of an organization to keep the status quo and not to use the crisis as an opportunity for positive changes points out.

In conclusion, it can be said that the year 2007 is described by innovation and creativity, communication and caring as values, also valuing the employee, stability and intentionality. In 2009 innovation, creativity and caring remain important but ethical values as fairness, respect and valuing the employee lost their significance.


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Appendix A

Figure A1. Change of management values in Estonia in business life between 2007-2009, by the frequencies of the occurrence of values.

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0 10 20 30 40 50 60

Innovation and creativity communication

trustefficiency

caringprofesionalism

stabilityvaluing the employee

fixity of purposedecision-making ability

motivationcooperation

visionenterprisingness

fairnesshonesty

transparencyaccuracy

responsibilityagressiveness

teamworkopenness

commitmentflexibility

client orientationcontinuous learning

genialityoptimism

respectself-confidence

franknessloyaltyquality

risk-takingself-analyzing

economypatience

carefulness

2007 2009


The Impact of Tax Policies on Taxpayers Budget in

Terms of Risk, Sensitivity and Volatility

Boloş Marcel Ioan, Otgon Cristian Ioan, Pop Răzvan Valentin University of Oradea, Oradea, Romania

Local and central governments are concerned to develop fiscal policies that are based on principles already enshrined

in the literature as the principle of equity and/or the principle of fiscal appropriateness. Beyond these principles, the

governments want to make sure that all taxpayers have the capacity to pay at maturity the tax debts owed to the

public budget. In crisis situations, as recent experience has shown, governments adopt fiscal policy measures, with

the sole purpose of procuring financial resources to cover the huge government budget deficits. In this situation, a

natural question arises: Do governments need, for the elaboration of their fiscal policy, an analysis that takes into

account the taxpayer’s budget? Or is it sufficient that they confine only to the theoretical principles enshrined in the

literature or the tax paying ability of the taxpayers? The answer can only be affirmative, because any taxpayer’s

budget is an inexhaustible source of resources for the public budgets. It is undisputed that in the taxpayer’s budget,

the tax expenditures coexist with other categories of expenditures such as consumption expenditures, durable

expenditures and public utilities expenditures. Each expenditure type is risk-bearing. To study the structure of budget

expenditures within the taxpayer, the authors suggest the use of three indicators innovative for the science of public

finance: the risk, the sensitivity coefficient and the coefficient of volatility. Depending on the values registered by the

three indicators of fiscal policies, expenditures can be classified as risky, volatile and sensitive which may lead to

risks of failure to collect the taxes and/or to tax evasion. Innovative for the science of public finances is that the

fundamentation of the fiscal policies is realized using the three indicators, the budget of the taxpayer and the

networking between the categories of expenditures that fall within its budget structure.

Keywords: fiscal policy, risk, volatility, sensitivity, taxpayer budget, expenditure

Introduction

Nowadays the local and central governments in Central and Eastern Europe are preoccupied to elaborate measure plans which can lead to new sustainable economic development and also to get out of crisis. The economic crisis has hit the national economies. The aggregate demand has been severely damaged. Companies had to adjust their activities, many of which bankrupted. Along with these, budget deficits have appeared because

Boloş Marcel Ioan, Associate Professor, Department of Finance-Accounting, University of Oradea. Otgon Cristian Ioan, Master, Department of Finance-Accounting, University of Oradea. Pop Răzvan Valentin, Bachelor, Department of Finance-Accounting, University of Oradea. Correspondence concerning this article should be addressed to Boloş Marcel Ioan, Oradea, Romania, Linistei street, 14, bl. PC 7,

ap. 3. E-mail: [email protected].

THE IMPACT OF TAX POLICIES ON TAXPAYERS BUDGET 1044

the national economies could not provide their financial resources in order to support the public expenditures. But these budget deficits, some of them out of control, have given serious headaches to the local and public governments. The measures taken to rationalize the public expenditures were quite unpopular. The salaries have been considerably diminished, for example Romania has decreased the salaries by 25% and increased the consumption taxes (VAT has increased in the majority of Central and Eastern Europe countries).

The IMF intervention was necessary in order to give “last resort” credits to avoid financial collapse or even the default of states. For example, Greece borrowed 100 billion euro in order to avoid the financial difficulties determined by the budget deficit financing, while Romania has contracted a credit worth 20 billion euro with the same destination. Many of the rationalizing measures determined a series of fiscal innovations. Hungary, for example, resorted to different taxation for banks and monopolies. And the examples can go on. Every country had a specific strategy to get out of problems. The common point of these strategies was: rationalizing the public expenditures, fiscal innovations, and financing budget deficits through capital infusions from IMF, EU, World Bank or BERD.

A natural question arises: What was the cause of these excessive deficits acted like a real tsunami in times of financial crisis? The answer is very simple. Influenced by the economic growth miracle Central and Eastern Europe countries had increased the public expenditures that were not based on a sustainable economic growth. The oversized expenditures were not matched by financial resources of the same level. The consequences did not occur when the economic crisis started. This is how public debts have exponentially increased so the imminent danger of this period, for the most of the Central and Eastern European countries, is a new type of crisis: “sovereign debt crisis”.

The economic growth period in Central and Eastern Europe has brought a mentality change regarding the consumer’s behavior. Until recently, it was impossible to overcome the CEE consumer’s behavior, whose golden rule was that 35-45 years old consumers would buy durables from their savings. The American consumer’s behavior, which resorts to credits to buy a house or a car, was now adapted. There are several implications regarding this behavior, the consumer can enjoy his purchased goods without expecting to save the necessary money. The workforce is permanently stimulated to seek new job opportunities in order to pay the credit annuity. The economy is based on goods and services demand stimulated and supported by the banks through credits.

Changing mentality by resorting to credit in order to buy durable goods has determined the appearance of a new category of expenditures. This refers to the expenditure with the credit annuity which is additional to the already mentioned consumer expenditures, tax expenditures and public services expenditures.

A portfolio of consumer spending was formed, in which consumer goods spending has an important percentage, approximately 60% (see Figure 1), followed by expenses for taxes and charges, that account for 15%-16%. What is noticeable in the consumer’s budget is that in the growth period, until the emergence of the global economic crisis, there was a new type of expense, that of durable goods, with an average of 14% share in the total budget, which confirms that, consumers have turned to loans to purchase durable goods and thereby there was a change in lifestyle and consumption mentality generating a continuous improvement of living conditions. Another important category of expenditure as a share of the consumer’s budget is the expenditure on public services, about 15%, which has an upward trend in the period under review due to the rising prices of public utilities (electricity, water, heat etc.).

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needed; collective, since each country that has fiscal space should contribute; and sustainable, so as not to lead to a debt explosion and adverse reactions of financial markets.

Fiscal policy is also affecting the markets, the impact of fiscal policy from a different approach should be taken into consideration, the appetite for fiscal discipline has been steadily declining among most industrial countries (Ricardo, 2005). Even after controlling for cyclical effects, budgetary balances have been deteriorating both in the US and in Europe. In Japan, a string of large fiscal imbalances has severely undermined the sustainability of the fiscal stance.

In the past, fiscal profligacy would have been punished by markets with higher interest rates and, in some cases, also exchange rate depreciation. This is another good reason to find a way to calculate the taxpayers affordability.

Fiscal policy, the main instrument for the public authorities, has a great influence on economic cycles (Lopez-Pinto, 2001). The conclusion of a research that takes into consideration the effects of fiscal policies on capital accumulation and economic performance in a simple endogenous growth model with elastic labor supply by focusing on the implementability of a competitive equilibrium with productive public spending and distortionary taxation is that given a feasible exogenous fiscal policy, productive public spending can, at first, lead to positive short-run and long-run growth in the unique competitive equilibrium (Hyun, 2009). However, although strictly positive growth is possible in the short run, a Ramsey policy with productive public spending does not implement positive capital accumulation in the long run. Also, the local indeterminacy of Ramsey allocations, in conjunction with the global multiplicity, arises as an implementable competitive equilibrium with Ramsey policies: namely, a continuum of transitional dynamics and multiple balanced growth paths.

Extending income tax cuts and reducing the growth rhythm of government spending (excluding Social Security and Medicare), assuming that government expenditures are cut to avoid dramatic increases in government consumption relative to GDP in comparison to historical norms, would increase investment, employment, and output. However, postponing the implementation of tight spending controls would more than offset the positive benefits of lower tax rates on the size of the economy and leave future generations with fewer resources for private consumption and production (Diamond, 2005).

Volatility and Sensitivity Calculation in the Study of Fiscal Policy Impact Over the Public Budget

As already seen, in the Central and Eastern Europe the taxpayers’ budget is characterized by a series of features specific to the economic boom period, but also by the constraints determined by the well-known financial crisis. As a consequence of economic boom met in the former communist countries but perhaps as a result of changing attitude of taxpayers, a significant proportion of expenses is starting to be held by those for durable goods. The latter takes the form of reimbursement credit rates and interest rates contracted by the taxpayers from banks in order to buy houses or durable goods.

The volatility and sensitivity calculation in order to study the impact of fiscal policies over the taxpayer’s budget involves a series of hypotheses which represent the base of calculation and have as a goal the analysis of the inherent risk each expenditure category included in the taxpayers budget but also of the risk determined by the variation of weight held by some expenditures in the total budget.


A natural question arises: What is the significance of total budget risk and how can this category of risk affect the fiscal policies which the governments are elaborating in accordance with the national development strategies?

There are several matters which we are trying to cover, supported not only by the theoretical formulations which will be found in this research paper but also by the elaborated calculation of the volatility and sensitivity within the study of fiscal policy.

In the terminology used in this research paper, global risk designates the risk that an expenditure, part of the total taxpayers budget, cannot be realized due to lack of funding source or other endogenous or exogenous factors which characterize the taxpayer’s behavior. The greater the risk, the higher the probability for an expenditure not to be made. If this probability affects the tax expenditures the public budget can be put in difficulty on short and medium term by the taxpayer’s risk of non-payment. As a consequence, fiscal policies make more sense if analyzed from the perspective of the inherent risk of each category of expenditure which constitutes the taxpayer’s budget and also from the perspective of sensitivity analysis determined by fiscal policies when they produce an effect on the proportion of taxes in the taxpayer’s total budget.

In order to test the impact of fiscal policies over the taxpayer’s budget there were drawn a series of hypotheses, which are the basis for the sensitivity and volatility calculation and are characteristic for any consumer’s budget.

First hypothesis starts from the idea that each group of expenditures, no matter if they are consumption expenditures )( cCh , tax expenditures )( ,taxeimpCh , durable expenditures ( )bfiCh , or public utility expenditures

)( upCh , registers expenditures growth rate between two consecutive periods,0t respectively

1t , determined

according to a relation of the following form:

1000

01 ×−

=t

ttch Ch

ChChR (1)

Any positive values of the expenditures growth rhythm may reveal the taxpayer’s propensity for a category of expenditure and hence a sort of behavior which can be based on consumption expenditures and/or durable expenditures, while the negative values signify a decreasing pace of allocating financial resources for that category of expenditure. In any situation the taxpayer’s budget must be balanced, even if loans are contracted in order to provide the budget balance.

The second hypothesis is based on the fact that the sum of weights of every category of expenditure in the total budgets equals to one. It means that the taxpayer’s budget can be written as a sum of expenditures consisting in consumer goods expenditures, tax expenditures, durable goods expenditures, public services expenditures, according to the taxpayer’s budget equation of the form:

,c c imp taxe bfi upB Ch Ch Ch Ch= + + + (2)

If equation (2) is divided to taxpayer’s budget )( cB , it results a sum of weights in the total budget, formed by the weight of consumption expenditures )( cp , the weight of tax expenditures )( fp , the weight of durable expenditures ( )bfip and also the weight of public utility expenditures )( upp , according to the following relation:

1 c f bfi upp p p p= + + + (3)


In order to substantiate the global risk of taxpayer’s budget, it is necessary to use a series of specific indicators which start from the average rhythm of total expenditures growth which is registered by the taxpayer

)( chR−

and also from the variance of total expenditures which form the taxpayer’s budget structure )( chσ . The average rhythm of total expenditures growth is obtained depending on the weight of expenditures specific to the taxpayer’s behavior in his total budget )( ip and also on the average rhythm of specific expenditures between

two consecutive periods ( ChiR−

). Also the variance of total expenditures which forms the taxpayer’s expenditure structure is obtained depending on the weight )( ip of every category of specific expenditures, on the standard

deviation (the inherent risk of each category of specific expenditures in taxpayer’s budget), 2Chiσ , and on the

covariance between two pairs of specific expenditures )( , fcσ . We, thus, obtained the global risk equations which characterize the taxpayer’s behavior. These equations are

at the base of the study of the impact that fiscal policies have over the consumption goods budget, tax budget, durable goods budget and public utility budget and can be expressed as follows:

upbfifc

bfiupupbfifupupffbfibfif

CupupcCbfibficCffcupupbfibfiffCcCh

upupbfibfiffCcCh

pppppppppp

pppppppppp

RpRpRpRpR

+++=

++

+++×+×+×+×=

×+×+×+×=−

1222

222222222222

____

σσσ

σσσσσσσσ

(4)

The above equations can be rewritten in the following general form:

∑

∑ ∑∑

∑

=

= = =

=

−

=

+×=

×=

4

1

4

1

4

1

4

1

222

4

1

_

1

2

ii

i i jijjiChiiCh

iChiiCh

p

ppp

RpR

σσσ (5)

The study of fiscal policies’ impact over the taxpayer’s budget will be performed by measuring the sensitivity of consumer’s global risk )( Chσ according to the changes in the tax expenditure weight )( cp , according to the expression:

c

Ch

p∂∂

=σ

γ (6)

In order to determine the sensitivity coefficient (γ ), it is necessary to establish the final form of consumer’s global risk based on the general risk equation depending on expenditure’s weight of consumption goods, durable goods, taxes and public services and also the specific risk determined through the medium of standard deviation

)( 2Chiσ for each expenditure categories:

2 2

2

2

2

( )

( )

( )

( )

C h c c c f c f b fi c b fi u p c u p

f f f c c f b fi fb f i u p fu p

b f i b fi b f i c c b fi f fb fi u p b f iu p

u p u p u p c c u p f fu p b fi b fiu p

p p p p p

p p p p p

p p p p p

p p p p p

σ σ σ σ σ

σ σ σ σ

σ σ σ σ

σ σ σ σ

= + + + +

+ + + +

+ + + +

+ + +

(7)


The analysis of the expression of the consumer’s global risk equation (5) from above reveals that global risk is depends on expenditures weight in the taxpayer’s total budget )( ip and the risk specific to each expenditure category related to the taxpayer’s total budget )( iChσ , which leads to the global risk evaluation of the form:

2Ch c CCh f fCh bfi bfiCh up upChp p p pσ σ σ σ σ= + + + (8)

In these conditions and taking into account the possible changes in the tax expenditures, the sensitivity coefficient shall be determined starting from expression (6):

( ) ( )

( ) 12

1 12 2

c CCh f fCh bfi bfiCh up upCh fCh bfiCh upChCChc f bfi up

c Ch c c c c

c CC f fC bfi bfiC up upC CCh CChCh Ch

p p p pp p p p

p p p p p

p p p p

σ σ σ σ σ σ σσγσ

σ σ σ σ σ σσ σ

∂ + + + ∂ ∂ ∂⎛ ⎞∂= = + + +⎜ ⎟∂ ∂ ∂ ∂ ∂⎝ ⎠

= + + + = +

(9)

The final form of the sensitivity coefficient which will be used in the analysis of the impact of fiscal policies over the taxpayer’s budget is given by a relation of the form:

Ch

CChC σ

σγ = (10)

The expression (10) provides a major advantage because the sensitivity analysis of central and local governments fiscal policies can be made taking into account the taxpayer’s global risk which consider every expenditure categories specific to the taxpayer’s needs for either consumption or durable goods.

In order to measure the taxpayer’s global risk there shall be used the taxpayer’s budget equations written in a matrix form, using the variance-covariance matrix ( mn ×Ω ) and the column vector of every expenditure weights in the taxpayer’s budget )( T

ip which in a simplified form can be written as:

cc cf cbfi cupCCh c

fCh ffc ff fbfi fup

bfiCh bfibfic bfif bfibfi bfiup

upCh upupc upf upbfi upup

pp

p

p

σ σ σ σσσ σ σ σ σσ σ σ σ σσ σ σ σ σ

⎛ ⎞⎛ ⎞ ⎛ ⎞⎜ ⎟⎜ ⎟ ⎜ ⎟⎜ ⎟⎜ ⎟ ⎜ ⎟= ×⎜ ⎟⎜ ⎟ ⎜ ⎟⎜ ⎟⎜ ⎟ ⎜ ⎟

⎜ ⎟ ⎜ ⎟⎜ ⎟⎝ ⎠ ⎝ ⎠⎝ ⎠

(11)

With these calculation judgments, the sensitivity coefficient can be determined for each expenditure category which is part of the taxpayer’s budget, in order to measure the risk specific to each expenditure category, compared to taxpayer’s global risk. In contradistinction to the inherent risk also specific to each expenditure category, which is related to the values registered by each expenditure category in a previous period of time and is determined by the standard deviation, the sensitivity coefficient is influenced also by the covariance between the expenditure pairs which are part of the taxpayer’s portfolio.

High values of sensitivity coefficient, specific to the tax expenditures, determined above, will indicate an increased level of risk of these expenditure categories not to be paid in time, while low values of this coefficient can be an expression of a high potential of financial resources, which can be fructified by the governments through additional revenues for the public budgets.

The sensitivity coefficient is highly dependent on two specific notions, which are innovative for the public finance domain, namely the expenditure risk and taxpayer’s global risk. Explained in simple terms, the


expenditure risk appoints the risk that an expenditure is not made by the taxpayer due to: lack of financial resources, taxpayer’s specific behavior etc.. For public budgets, the taxpayer’s risk of tax expenditure is equivalent to the risk of not collecting the tax revenues. If this risk is amplified by a certain intensity of financial crisis, the probability that the public budget shall register deficits or liquidity crisis is quite high.

The risk of a specific expenditure relative to the taxpayer’s total budget is the second form of the specific risk for each expenditure category which is a part of taxpayer’s total budget. The advantage of studying this form of risk is that it depends on the intensity of the connections between a studied expenditure and the other categories of expenditure. These connections are studied through the statistical covariance and indicate the “behavior” of a certain expenditure category as compared to the taxpayer’s total expenditures. The major advantage of this category of risk is given by the fact that, by the help of covariance, one can study the way a certain category of expenditure behaves as compared to the other expenditure categories.

As regards the taxpayer’s global risk, it offers information related to the taxpayer’s risk of not his budget. When taxpayer’s budget is risky, the central and local fiscal policies are more exposed to the risk of not collecting the tax debts. That is why a fundamental element, even strategic, in the substantiation of fiscal policies, will be the very intensity of the global risk of the taxpayer’s budget in order to detect in due time potential risks of not realizing the planned budget.

It can be noticed that taxpayer’s global risk is a homogeneos function that depends on the weight vector

( ), , ,c f bfi upp p p p , which means that the Euler formula can be applied and the taxpayer’s global risk equation

can be rewritten as:

fCh bfiCh upChCCh Ch Ch Ch ChCh c f bfi up c f bfi up

c f bfi up c f bfi up

p p p p p p p pp p p p p p p p

σ σ σσ σ σ σ σσ∂ ∂ ∂∂ ∂ ∂ ∂ ∂

= + + + == + + +∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂

(12)

Taking into account the sensitivity coefficient established through expression (9) the taxpayer’s global risk can be written depending on the coefficients )( iγ and the weights of specific expenditures in the taxpayer’s total budget )( ip , in the following formula:

Ch c c f f bfi bfi up upp p p pσ γ γ γ γ= + + + (13) If expression (8) is divided by

Chσ and the sensitivity coefficient is replaced with the ratio between the risk specific to each category of expenditure )( iChσ and the taxpayer’s global risk )( Chσ , a new form of taxpayer’s

global risk is obtained:

2 2 2 21 fCh bfiCh upChCChc f bfi up

Ch Ch Ch Ch

p p p pσ σ σσ

σ σ σ σ= + + + (14)

The coefficients in expression (14) are called volatility coefficients and are determined as a ratio between the specific risk of a certain risk category in the total budget )( iChσ and the standard deviation of taxpayer’s expenditures )( 2

Chσ according to the relation:

2Ch

iChi σ

σβ = (15)

The volatility coefficients determined for each expenditure category which is part of the taxpayer’s budget offer information related to the risk of alterations in the level (value) registered for an expenditure in a short


period of time. High values of the volatility coefficient will reflect a high risk for a category of expenditure that is part of the taxpayer’s budget, which can modify its value in a short period of time, while the low (diminished) values of volatility coefficients reveal a low risk and thus a low probability that a category of expenditure, that is comprised in the taxpayer’s structure, could modify its value in a short period of time.

Sensitivity and volatility are two coefficients which provide the local and central governments with information regarding the taxpayer’s risk of not paying his taxes. This category of risk is extremely important for every government that is substantiating its fiscal policy. If the taxpayer is registering high sensitivity coefficients then the fiscal policy turns to be quite risky.

Types of Fiscal Policies Established With Respect to the Taxpayer’s Risk

The calculations, the hypotheses, and the rules exposed above lead to the conclusion that every fiscal policy made by central or local governments has to be substantiated not only on the affordability of taxpayers but also on the risk of not paying. This risk occurs because the taxpayer doesn’t finance sole a category of expenditure that regards the taxes. The latter is added to by the consumption goods, durable goods, public utility expenditures which represent nothing more than expenditures for meeting the needs of a regular taxpayer. This way, the taxpayer is acting in the market, in his bivalent nature from two points of view, as a consumer and as a taxpayer. The constraints resulted from financing the expenditures are limited to the taxpayer’s income over a certain period of time. These constraints often generate the occurrence of risk of non-payment as the income growing speed is inferior to the expenditure growing speed.

There are three categories of indicators which are at the basis of fiscal policy substantiation depending on the risk which appears in the taxpayer’s budget. The indicators result from the above hypotheses and calculations, and they are: the inherent risk of an expenditure category, the sensitivity coefficient and the volatility coefficient of expenditures which are part of taxpayer’s budget structure.

The inherent risk of each expenditure category, determined by the standard deviation, offer the local and central governments information related to the taxpayer’s risk of not paying. The higher the values of this risk, the more intense the risk of not paying is acting. The major disadvantage of this indicator is the fact that it doesn’t take into consideration other expenditure categories which are part of taxpayer’s budget and moreover it does not measure the specific risk for each expenditure relative to the total budget.

In order to offer complete information about the taxpayer’s risk, which local and central governments cannot neglect, there were introduced two specific notions regarding the global risk and the specific risk for each category of expenditure part of taxpayer’s budget. The global risk, as shown before, represents that certain category which can help in obtaining information related to the probability of the taxpayer’s budget to collapse. The specific risk of an expenditure category provides information about the “behaviour” of this expenditure as compared to the other ones which compose the taxpayer’s budget. Regardless of the calculation and the interpretation of the indicators related to the taxpayer’s risk, these indicators can succesfully be used with success in the sensitivity and volatility calculation of the coefficients, used by the local and central governments for fiscal policy substantiation. While the sensitivity coefficients contribute to testing the way a expenditure category behaves relative to the taxpayer’s total budget when a percent of the weight of these expenditures in the total budget changes, the volatility coefficient provides information about the probability of an expenditure to change


in a short period of time. Depending on the values which are registered by the inherent risk of expenditures and the values of

sensitivity and volatility coefficients for these expenditures, we can distinguish the particularities of the types of fiscal policies.

(1) If 2 2

, ,( )f c bfi upσ σ≥ , ( ), ,f c bfi upγ γ≥ , , ,( )f c b fi u pβ β≥ , the fiscal policy is risky and unstable and the fiscal expenditures are volatile in comparison with the other expenditures. The volatility is high. The risk of not collecting the fiscal debts is maximum. The government has to review the fiscal policy to monitor and control the risk of not collecting the tax debts.

(2) If ( )2 2, ,f c b fi u pσ σ≥ , ( ), ,f c b fi u pγ γ≤ , ( ), ,f c b fi u pβ β≥ , the fiscal policy is also risky, stable, with high

volatility. The tax expenditures behave quite well as compared to the other expenditures due to the low level of sensitivity. The risk of not collecting the tax debts is high. Volatility registers high levels. The government’s fiscal policy has to be monitored because there is a perspective of increasing tax expenditures on short term.

(3) If ( )2 2, ,f c bfi upσ σ≥ , ( ), ,f c bfi upγ γ≤ , ( ), ,f c bfi upβ β≥ , the fiscal policy is risky, stable, with low

volatility. Regarding the global risk, tax expenditures behave quite well as compared with the other expenditures. The risk of not collecting the tax debts is in acceptable limits. Volatility is low. The government’s fiscal policy has to be monitored from the perspective of the evolution of the inherent risk of tax expenditures.

(4) If ( )2 2, ,f c b fi u pσ σ≥ , ( ), ,f c b fi u pγ γ≤ , ( ), ,f c bfi upβ β≥ , the fiscal policy is also risky, unstable, but with

low volatility. The tax expenditures are extremely sensitive in report to the other expenditures which means that an increase by one percent in tax expenditure is answered by an increase in the global risk. The volatility is quite low; yet, the risk of not collecting the tax debts stays high.

(5) If ( )2 2, ,f c bfi upσ σ≥ , ( ), ,f c bfi upγ γ≤ , ( ), ,f c bfi upβ β≥ , the fiscal policy is characterized by a

diminished risk, unstable and highly volatile. There is a problem in these situations due to the unstable characteristic of fiscality. It is possible that for short-term periods of time the tax expenditures register high values, due to the high volatility. The risk of not collecting the tax debts can be a major problem when the tax expenditures grow.

(6) If ( )2 2, ,f c bfi upσ σ≥ , ( ), ,f c b fi upγ γ≤ , ( ), ,f c bfi upβ β≥ , the risk of fiscal policy is still diminished, the

fiscal policy is stable due to the low level of sensitivity and high volatility. The behaviour of tax expenditures compared with the other expenditures is good due to the low sensitivity. Volatility is high. The fiscal policy has great chances to be succesfully implemented even if there is a perspective of increasing tax expenditures for short-time periods.

(7) If ( )2 2, ,f c bfi upσ σ≥ , ( ), ,f c bfi upγ γ≤ , ( ), ,f c bfi upβ β≥ , the fiscal policy risk is also diminished, but the

fiscal policy is stable, due to low level of sensitivity which tax expenditures register. The volatility is low. The behaviour of tax expenditures as compared to the other expenditures is good with respect to the taxpayer’s global risk. It’s the type of fiscal policy with the greatest sensitivity and volatility indicators, with great chances to be succesfully implemented, and a low risk of not collecting the tax debts.

(8) If ( )2 2, ,f c bfi upσ σ≥ , ( ), ,f c bfi upγ γ≤ , ( ), ,f c bfi upβ β≥ , the risk of fiscal policy is low and unstable. The

volatility is also low. The tax expenditures behave rather undesirably as compared with the other expenditures,


due to high level of sensitivity. There is a risk of not collecting the tax debts when the weight of tax expenditures in the taxpayer’s total budget changes.

The combination between risk, sensitivity and volatility coefficients, offer the governments further information in order to substantiate their fiscal policies, so that the risk of not collecting the tax debts could be controled. It is noticeable the fact that the risk, the sensitivity and the volatility of fiscal policies could not always register values which can be framed in the eight fiscal policy typologies. In these situations the values of the indicators should be analyzed in correlation with the values obtained for each expenditure category which is part of taxpayer’s total budget. The combination between sensitivity and volatility coefficients is also useful to detect the tax evasion which can be active in the circumstances when the risk is high and the sensitivity and the volatility levels are high as well.

Nowadays, the risk of not collecting the tax debts and tax evasion are major concerns for the local and central governments all over the world. There is a question which has to be answered: To what extent do fiscal policies need to be reviewed in order to keep the taxpayer’s fiscal comfort? It is a question and also a research subject which will be treated in our future research activities.

Testing the Types of Fiscal Policies for the Taxpayers From Central and Eastern Europe

In order to test the impact of fiscal policies over the taxpayer’s budget, the expenditures of the taxpayer were grouped in four major categories, namely the consumption expenditures, tax expenditures, durables expenditures, and public utility expenditures. The database of this analysis is made of information provided by the national institutes of statistics. The calculation of risk, sensitivity coefficient and volatility coefficient can be applied for each series of data constituted with the purpose of analyzing the sustainability of local and central government’s fiscal policies.

The first indicator calculated was the growth in the rate of expenditures between two consecutive periods, the time slot for the analysis being 2008-2010. The results are presented in Appendix A. It is noticeable that the most spectacular growth rhythm was registered by the durables, which after an ascending trend in 2008-2009 it is start to register a decrease in the late 2010. The consumers abandoned the idea of buying durables as a result of the fact that the consumer’s income was constant, in the analyzed period, with a slight decrease. The durables were a disposable variable as their income was diminished. The general characteristic of growth rhythms, in periods of economic crisis, for the analyzed expenditure categories was the emergence, as an increasing rhythm was followed by a descendent evolution, even for short period of time. Regarding the public utility expenditures they had an increasing trend due to the fact that in Central and Eastern Europe the prices of public utilities are established in monopoly conditions. An emergence of fiscal expenditures was observed in the period analyzed and that was due to increased tax rates, as a last resort solution to avoid financial collapse or excessive budget deficits.

The risk of expenditures is the second indicator which has been calculated and analyzed for each expenditure category that was part of taxpayer’s budget. The less risky expenditure turns out to be the consumption expenditures, which are the most significant part of the total budget. The reason is that in the analyzed period the consumption expenditures are almost constant and the growth rhythms of this type of expenditures registered the same trend. The durables expenditures proved to be extremely risky because, besides the fluctuant growth rhytms, they have registered high values of risk (in quarter IV 2 4, 293 .04209bfiσ = ).


The situation is explained by the fact that during economic boom, the population resorted to credits to purchase durables, and then the economic crisis changed the behaviour of the consumer who abandoned the idea of buying durables, because it was the only disposable type of expenditure. Regarding the tax expenditures they registered high values of risk especially in the last period analyzed (year 2010). The tax expenditures were ranked in the third place after durable expenditures and public utility expenditures. The risk evolution for each expenditure is presented in Figure 3.

Figure 2. The growth rythm of consume expenditure (% from a trimester to another).

Figure 3. The evolution of the risks for each expenditure (% from a trimester to another).

-40

-20

0

20

40

60

80

1 2 3 4 5 6 7 8 9 10 11

Growth rhythm for consumer expenditure Growth rhythm for taxes expenditure

Growth rhythm for durables expenditure Growth rhythm for public utility expenditure

Total expenditure

0500100015002000250030003500400045005000

0

100

200

300

400

500

600

700

800

900

1 2 3 4 5 6 7 8 9 10 11

The risk for all expendituresThe risk for the consumer expenditure The risk for the taxes expenditureThe risk for the public utility expenditureThe risk for the durables expenditure (represented on the secondary axis)


The sensitivity and volatility coefficients for each expenditure category are the third category of indicators analyzed, the values of which are presented in Table 1.

Table 1 The Situation of Sensitivity and Volatility Coefficents for Each Expenditure Category Specification Risk at the level of period Sensitivity at the level of period Volatility at the level of period Total expenditures 22.0287846 Consumption expenditures 20.87507 0.10530504 0.00079995 Tax expenditures 116.6408 0.25906198 0.00196797 Durables expenditures 597.26563 0.53432052 0.00405898 Public utilities expenditures 248.107557 0.10131246 0.00076962

The most sensitive expenditures for the period analyzed remained the durable expenditures. The calculation leads us to the conclusion that a one percent change in the weight of durables expenditures determines an increase of 0.53% in the global risk of the taxpayers budget. The weight of tax expenditures in the total budget will itself determine an increase of the global risk of 0.25%. Finally, the sensitivity calculation shows that even if public utility expenditures are quite risky, they behave better compared to the other expenditures due to low level of sensitivity which is registered in the analyzed period.

The volatility coefficient registered the highest values for the durable expenditures. It means that the probability of changing the values of durables expenditures in the total budget is very high. The hypothesis of this change in value is confirmed by the emergent growth rate which was registered during the analyzed period (2008-2010).

The tax expenditures register quite high levels in what volatility is regarded after durables expenditures. Any increase of tax expenditures will have consequences in the volatility of this type of expenditure. The causes for a high volatility can be many. One of them can be the stagnation or even the reduction of the income which taxpayers earn during the analyzed period.

The consumption expenditures remained the less volatile. The explanation consists in the low level of risk which consumption expenditures registered but also in the low level of sensitivity registered as compared to the other expenditure categories.

The general characteristic of Eastern Europe fiscal policies related to the taxpayer’s total budget is that it was quite risky registering the third highest level of risk, after durable expenditures and public utility expenditures. The volatility is quite high which means that any modification of tax expenditure weight in the total budget becomes risky. Central and local governments must be prudent in the elaboration of fiscal policies to avoid the risk of not collecting the tax debts or the phenomena of tax evasion which can manifest among the taxpayers. Besides the high sensitivity of fiscal policies, Eastern Europe registers an interesting particularity determined by the high volatility of tax expenditures. This means that the latter are likely to change their values on short-term. Any modification of fiscality as a weight in taxpayer’s budget is followed by a certain response which can manifest under the form of not collecting the tax debts as they were projected. The greatest constraint regarding fiscality is manifest when the income evolution is flat or decreasing especially in the time of economic crisis. The influence of income stagnation on the fiscal risk and on sensitivity and volatility of risk with the tax expenditures is a future reseach direction which shall be explored within further research activities.


From the perspective of risk, sensitivity, volatility the tax expenditures were analyzed on their structure. In order to perform this analysis tax expenditures were grouped in four major subgroups, namely, wage tax expenditures, pension contribution expenditures, health contribution expenditures and unemployment expenditures. The results are presented in Table 2.

Table 2 Risk, Sensitivity and Volatility Calculation for Eastern Europe Tax Expenditures Specification Risk at the level of period Sensitivity at the level of period Volatility at the level of periodTax expenditure 11.65603 Wage tax expenditure 18.5823 0.3962421 0.0108352 Pension contribution expenditure 8.781152 0.2362452 0.0064601 Health contribution expenditure 12.16907 0.3200744 0.0087524 Unemployment expenditure 10.97704 0.0474382 0.0012972

The most risky expenditures remained the wage tax expenditures with a level of risk of 5823.182 =sσ , which simultaneously register the highest levels of sensitivity, 3962421.0=sγ , and respectively of volatility,

0108352.0=sβ . This means that any modification in central government’s fiscal policy, in the sense of a transition from a fiscal policy based on flat tax to a fiscal policy based on progressive tax may lead to a great risk of not collecting the tax debts. Also a high risk level was registered by the health contribution expenditures. The level of sensitivity and volatility of this subcategory makes the modification of weight in the total budget lead to a risk of not collecting the specific tax debts owed to the social security budget.

The structural analysis of tax expenditure structure based on risk, sensitivity and volatility coefficients provides the governments with additional regarding the most sensitive, risky and volatile expenditure, so that they could be more cautious in the elaboration of fiscal policies.

Conclusions, Future Research Directions

The fiscal policy of central and local governments should not be based only on equity principles and/or fiscal rightness. It is not sufficient to produce a fair wealth taxation or a fair taxation of the work and of the capital if these are not accompanied by a detailed analysis of taxpayer’s budget. And this budget has a series of constraints determined by the income level which taxpayers register and also by the behaviour of the taxpayer acting as a consumer on the products and services market.

Each expenditure category is included in the taxpayer’s budget regardless of its nature: consumption expenditures, durables expenditures, tax expenditures and/or public utility expenditures registering a certain level of risk. This risk can be manifested under two forms: when the taxpayer involves in the expenditure and the public budget collects the tax debts or on contrary when the taxpayer does not make the whole expenditure in which case the tax debts register an increasing trend. The measurement of each expenditure risk was performed using the standard deviation, and the results obtained in the analysis period 2008-2010 lead to the hypothesis that the riskiest category of expenditure remains the durables expenditure followed by the public utility expenditures. On the third place as size, it turns out to come the tax expenditures, that register a risk of 6408.1162 =fσ which implies that Eastern Europe countries must be cautious in the elaboration of fiscal policies, because there is a risk for taxes not to be collected totally at their maturity.


This form of risk measurement is not sufficient, because the expenditure categories are interdependent. The measurement of the interdependency between the expenditure categories leads to another indicator for the analysis of the fiscal policies, known as sensitivity coefficient. The indicator whose formula was calculated in this research paper measures the risk of an expenditure category relative to the total taxpayer’s budget when there is a modification of one percent in the weight of a expenditure category. The more sensitive an expenditure category is, the higher is the risk not to make that expenditure. In the period analyzed, tax expenditures registered a sensitivity value of 25906198.0=fγ which leads to the hypothesis that any modification by one percent of tax expenditures determines a taxpayer’s global risk increased by 0.25%. By size the tax expenditures are ranked in the second position, in what sensitivity is concerned after durables expenditures.

The last indicator analyzed and determined for the fiscal policies was the volatility coefficient. This measures the probability that an expenditure included in the taxpayer’s budget modifies its value in a short period of time. From the perspective of volatility, the tax expenditures were ranked on the second position after durable expenditures with a coefficient, 00196797.0=fβ .

The general conclusion is that Eastern Europe’s fiscal policies were pretty risky from the perspective of taxpayer’s budget. The sensitivity, quite high, makes the fiscal policies elaborated be really hard to implement especially if they lead to increased tax rates. At the same time, volatility shows an increase in tax expenditures on short-term caused especially by the stagnation or even reduction of taxpayer’s income.

The risk, the sensitivity and the volatility of tax expenditures in relation with the taxpayer’s budget provide complete information for local and central governments related to the fiscal policies elaborated. The successful implementation of a fiscal policy also depends on the value of these indicators. In order to avoid the risk of not collecting the tax debts and the phenomena of tax evasion the governments have to monitor the value of these indicators so that avoiding measures can be taken by the central and local governments.

If the fiscal policy is risky the analysis can be continued through the calculation of risk, sensitivity and volatility for each expenditure category which is part of the fiscal policy. To perform this type of factorial analysis, the tax expenditures were grouped in wage tax expenditures, pension contribution expenditures, health contribution expenditures and unemployment expenditures. The calculation leads to the hypothesis that the riskiest expenditure category is wage tax registering a risk 5823.182 =sσ , a sensitivity coefficient 396242.0=sγ and a volatility coefficient 108352.0=sβ . High values of risk, sensitivity and volatility can, as we mentioned, cause difficulties to the change in fiscal policies of central governments given by the transition from a taxation mechanism based on flat tax to a taxation mechanism based on progressive taxes.

Regardless of the information provided to the central and local governments, through the calculation of risk, sensitivity coefficient, volatility coefficient, there still stays as a future research direction, the study of fiscal policy boundaries and the impact of stagnating or reducted incomes on the risk of not collecting the tax debts. An important direction of research is represented by the calculation of expenditure efficiency frontier included in the taxpayer’s budget having as a starting point the calculation hypothesis for the Markowitz efficiency frontier for financial markets.

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Appendix A: Monetary Units

Table A1 The Values for Expenditure and Revenues in the Period 2008-2010, for Each Trimester

Monthly total expenditure/ person

Expenditure on consumer goods/person

Expenditure on taxes/person

Expenditure on long term use goods

Expenditure on public services

Total revenues/ household

Total revenues/ person

2008 Trimester 1 619.28 391.49062 106.597011 31.1447107 90.047658 1,647.73 612.679969 2008 Trimester 2 624.38 413.737662 107.684998 36.1634542 66.7938851 1,753.88 650.92733 2008 Trimester 3 698.21 463.725684 120.354962 41.1354959 72.9938577 1,889.2 732.521246 2008 Trimester 4 714.58 462.812093 121.130079 39.8469388 90.7908891 1,969.77 733.133801 2009 Trimester 1 686.58 452.160111 90.7902656 41.6719515 101.957672 1,895.66 728.744019 2009 Trimester 2 707.3 484.39481 95.2171555 46.8613622 80.826672 2,033.66 781.276258 2009 Trimester 3 686.97 484.125755 85.0959617 36.3065675 81.4417158 1,977.71 773.415139 2009 Trimester 4 738.25 490.88497 90.2727726 62.1956405 94.8966171 1,986.13 767.687698 2010 Trimester 1 714.39 464.577994 96.9219384 46.0314147 106.858653 2,000.34 776.968021 2010 Trimester 2 698.21 484.174605 81.8401709 44.0594211 88.1358028 2,038.37 791.481469 2010 Trimester 3 698.21 488.330541 75.8511141 43.0818505 90.9464945 1,955.03 773.356994 2010 Trimester 4 730.21 504.908211 80.1776807 44.6267907 100.497318 1,954.98 770.438742


Table A2 The Growth Rhythm From a Trimester to Another, for Each Expenditure

Growth rhythm for consumer expenditure

Growth rhythm for taxes expenditure

Growth rhythm for durables expenditure

Growth rhythm for public utility expenditure

Trimester 2/1 2008 5.68265016 1.02065437 16.1142723 -25.82385 Trimester 3/2 2008 12.0820574 11.765765 13.748802 9.2822458 Trimester 4/3 2008 -0.19701107 0.6440255 -3.1324701 24.381547 Trimester 1 2009/4 2008 -2.30157824 -25.0472992 4.58005748 12.299453 Trimester 2/1 2009 7.12904538 4.87595212 12.4530062 -20.72527 Trimester 3/2 2009 -0.05554461 -10.6295906 -22.5234485 0.7609417 Trimester 4/3 2009 1.39616921 6.0834978 71.3068595 16.520896 Trimester 1 2010/4 2009 -5.35909174 7.36563813 -25.9893228 12.605334 Trimester 2/1 2010 4.21815313 -15.5607365 -4.28401691 -17.52114 Trimester 3/2 2010 0.85835473 -7.31799153 -2.21875498 3.1890465 Trimester 4/3 2010 3.39476415 5.70402503 3.58605794 10.501585 Table A3 The Growth Rhythm From a Trimester to Another, for Each Type of Expenditure on Taxes

Growth rhythm for tax expenditure

Growth rhythm for wage tax expenditure

Growth rhythm for pension contribution expenditure

Growth rhythm for unemployment expenditure

Trimester 2/1 2008 5.68265016 1.02065437 16.1142723 -25.82385 Trimester 3/2 2008 12.0820574 11.765765 13.748802 9.2822458 Trimester 4/3 2008 -0.19701107 0.6440255 -3.1324701 24.381547 Trimester 1 2009/4 2008 -2.30157824 -25.0472992 4.58005748 12.299453 Trimester 2/1 2009 7.12904538 4.87595212 12.4530062 -20.72527 Trimester 3/2 2009 -0.05554461 -10.6295906 -22.5234485 0.7609417 Trimester 4/3 2009 1.39616921 6.0834978 71.3068595 16.520896 Trimester 1 2010/4 2009 -5.35909174 7.36563813 -25.9893228 12.605334 Trimester 2/1 2010 4.21815313 -15.5607365 -4.28401691 -17.52114 Trimester 3/2 2010 0.85835473 -7.31799153 -2.21875498 3.1890465 Trimester 4/3 2010 3.39476415 5.70402503 3.58605794 10.501585 Table A4 The Risks Calculated for Each Type of Expenditure, in the Analyzed Period The risk for the total expenditure / person

The risk for expenditure on consumer goods/person

The risk for expenditure on taxes/person

The risk for expenditure on long term use goods

The risk for expenditure on public services

22.0287846 20.87507 116.6408 597.26563 248.107557 Table A5 The Sensitivity Calculated for Each Type of Expenditure, in the Analyzed Period The sensitivity for expenditure on consumer goods/person

The sensitivity for expenditure on taxes/person

The sensitivity for expenditure on long term use goods

The sensitivity for expenditure on public services

0.105305042 0.25906198 0.53432052 0.10131246 Table A6 The Volatility Calculated for Each Type of Expenditure, in the Analyzed Period The volatility for expenditure on consumer goods/person

The volatility for expenditure on taxes / person

The volatility for expenditure on long term use goods

The volatility for expenditure on public services

0.105305042 0.25906198 0.53432052 0.10131246


Table A7 The Values for Each Type of Expenditure on Taxes in the Period 2008-2010, for Each Trimester

Expenditure on taxes /person

Expenditure on wage tax

Health insurance contribution

State social insurance contribution

Unemployment fund expenses

2008 Trimester 2 602.64 236.51 143.29 208.09 14.75 2008 Trimester 3 632.69 256.49 141.43 219.81 14.96 2008 Trimester 4 660.12 272.78 142.41 230.2 14.73 2009 Trimester 1 659.46 270.33 139.68 235.02 14.43 2009 Trimester 2 703.97 287.04 146.53 255.61 14.79 2009 Trimester 3 696.55 284.05 144.93 252.6 14.97 2009 Trimester 4 695.62 284.4 143.67 253.27 14.28 2010 Trimester 1 692.97 285.27 141.63 251.88 14.19 2010 Trimester 2 691.49 283.15 141.02 252.83 14.49 2010 Trimester 3 661.35 268.38 133.93 245.48 13.56 2010 Trimester 4 670.04 272.23 135.83 248.26 13.72 Table A8 The Risks Calculated for Each Type of Expenditure on Taxes, in the Analyzed Period The risk for expenditure on taxes / person

The risk for expenditure on wage tax

The risk for health insurance contribution

The risk for state social insurance contribution

The risk for unemployment fund expenses

11.65603 18.5823 8.781152 12.16907 10.97704 Table A9 The Sensitivity Calculated for Each Type of Expenditure on Taxes, in the Analyzed Period The sensitivity for expenditure on wage tax

The sensitivity for health insurance contribution

The sensitivity for state social insurance contribution

The sensitivity for unemployment fund expenses

0.3962421 0.2362452 0.3200744 0.0474382 Table A10 The Volatility Calculated for Each Type of Expenditure on Taxes, in the Analyzed Period The volatility for expenditure on wage tax

The volatility for health insurance contribution

The volatility for state social insurance contribution

The volatility for unemployment fund expenses

0.0108352 0.0064601 0.0087524 0.0012972


Interactions Between Knowledge Sharing and

Organizational Citizenship Behavior

Yavuz Demirel, Zeliha Seçkin, Mehmet Faruk Özçınar Aksaray University, Aksaray, Turkey

Recently, researches toward the social and psychological structure of organizations have proliferated observably.

As the quality and quantity of these studies improve, the value of such issues gets more manifest. In this context,

efforts toward making employees’ knowledge, which is an indispensable value for organizations, accessible and

efforts to make it available for work processes and social relations extend new behavioral patterns. Organizational

citizenship behavior is an example of such patterns. This paper attempts to explain and discuss interactions between

organizational citizenship behavior and knowledge sharing, which is reasoned to have a defining role over it, and to

draw attention on the issue. Organizational knowledge sharing, the factors influential on it, and the relationships

between the antecedents of organizational citizenship behavior and knowledge sharing are being dwelled upon

conceptually.

Keywords: knowledge, knowledge sharing, organizational citizenship behavior

Introduction

The key capital and locomotive power of organizations is “human”, which is a social being. Thus, the existence of workers who have adopted the organization’s values, who see the organization’s purposes as their own purposes, and who make an effort more than expected in the organization with willingness is becoming more important for the organizations, so that they can carry out their activities and achieve their goals. When the studies on organizations conducted in recent years are looked at, it will stand out that interest in psycho-social issues, which were formerly going unnoticed though they are crucial for organizations, has grown. An outstanding example of such issues is organizational citizenship behavior. Organizational citizenship behavior involves the organization members’ behaviors that include positive actions. In other words, it is the behaviors of the workers that are demonstrated voluntarily without any expectations and beneficial for the organization. Findings of studies on the subject have revealed that workers who tend to demonstrate organizational citizenship

Yavuz Demirel, Ph.D., Associate Professor, Department of Business Administration, Faculty of Economics and Administrative

Sciences, Aksaray University. Zeliha Seçkin, Ph.D., Assistant Professor, Department of Administrative and Economical Programs, Ortaköy School of

Vocational Studies, Aksaray University. Mehmet Faruk Özçınar, Ph.D., Assistant Professor, Department of Public Administration, Faculty of Economics and

Administrative Sciences, Aksaray University. Correspondence concerning this article should be addressed to Yavuz Demirel, Aksaray University, Faculty of Economics and

Administrative Sciences Department of Business Administration, 68100 Aksaray/Turkey. E-mail: [email protected].

KNOWLEDGE SHARING AND ORGANIZATIONAL CITIZENSHIP BEHAVIOR 1062

behavior are more efficient and productive, prone to teamwork, enthusiastic for full participation and knowledge-sharing, and have higher levels of loyalty and responsibility.

In order for the workers to demonstrate organizational citizenship behavior, it seems necessary to build a culture of communication, trust and knowledge sharing. Organizational citizenship behavior and knowledge sharing are not expected to meet the prospects in a working atmosphere where suspicion and uncertainty reign. The sense of organizational citizenship behavior can be positive or negative, depending on the workers’ perceptions of organizational knowledge sharing. The positive perception among the workers that knowledge sharing is supposed to generate is an important factor for determining the tendency of the workers toward organizational citizenship behavior. Consequently, this study grounds on the principle that workers cannot be forced, but they can share knowledge depending on behaviors that are not pre-defined, and it is beneficial for the social system of the organization. The conceptual relationship and interaction between organizational knowledge sharing and organizational citizenship behavior is analyzed in detail.

Organizational Knowledge Sharing: Concept and Content

Knowledge, which has become the most powerful tool for surplus value, produces more value when it is shared. This fact has caused the “Knowledge is power” (Liao, Chang, Cheng, & Kuo, 2004, p. 24) aphorism of Bacon to be moved one step further as “Knowledge sharing is power” (Gurteen, 1999, p. 3). In this respect, it can be pronounced that knowledge is doubtlessly among the most strategic and important resources for organizations (Fei & Chen, 2007, p. 2), and not simply a rhetorical expression. Knowledge sharing functions as a fundamental element that contributes to the competitive power of the organization in the global market, improves management-worker relations, and increases the performances of the employees. Consequently, as long as knowledge is shared in an organization, that organization will gain competitive advantage. Sharing requires the circulation of knowledge. The boundaries of this circulation are drawn not only by technology, but also depending on the behavioral factors of the employees (Liao et al., 2004, pp. 24-25). The view of Cheah and his colleagues (2009, p. 1423) that knowledge sharing is an activity and knowledge is transmitted by this action corresponds to the studies of Liao and his colleagues. Takeuchi (1995) also considers the production of knowledge as a process and emphasizes that production of knowledge cannot take place without the individuals by drawing attention to the importance of individuals in this process, and he points to the importance of knowledge sharing in enabling organizational effectiveness. According to Lin (2008, p. 241), whereas knowledge sharing improves the competitive power of an organization, the lack of knowledge sharing can cause serious trouble for the organization. Active knowledge sharing is related to how willing and prone to sharing knowledge the employees are (Fei & Chen, 2007, p. 3) and how enthusiastic they are (Vries & Hooff, 2006, p. 116). The development of knowledge sharing arises from the active external relations among the employees, shareholders, intermediates and customers and it is transformed to organizational strategies that will enable to organization to gain competitive power in the future. However, Batt has reached the conclusion that an organization cannot compel the employees to share tacit knowledge. Nevertheless, it is indispensable for the knowledge managers to put forward incentives and rewards that will encourage the employees to contribute to knowledge sharing and the information pool. According to Gagne (2009), knowledge sharing is a process when the employees exchange knowledge and produce new knowledge. However, the fact that organizational


knowledge sharing generates value requires the reproduction of knowledge at personal and organizational levels. Considering this fact, it is necessary for the managers to set up systems that will motivate the employees to share knowledge positively and willingly. The result of this motivation is related to how important the employees consider knowledge sharing with a personal or collective purpose (Gagne, 2009, p. 572). In other words, individuals or groups need to share knowledge with each other through cooperation and therefore gain mutual benefits. In their study, Small and Sage (2005/2006) offer three explanations for the dilemma of why employees tend to/need to share knowledge in spite of the fact that they will lose power and profit: gaining knowledge, reusing knowledge and the aspiration to produce knowledge.

Although knowledge sharing creates personal and organizational value, it may not always occur in an ideal way for every organization. It must not be ignored that there are factors of secondary importance in the resolution of the mentioned conflict. The term knowledge sharing also represents a dilemma between personal benefit and organizational benefit. In terms of organizational benefit, knowledge sharing is indispensable whereas it can be seen as a behavior that can cause negative effects for the individual. Knowledge sharing will increase the possibility of an individual or a group to provide benefits to another individual or group that will become a rival in the future. Therefore, organizations that foresee the fact that individuals will avoid knowledge sharing, introduce certain systems of incentives and rewards in order to prevent this and to ensure knowledge sharing in the organization (Liao et al., 2004, p. 25). These systems of incentives and rewards should not be considered different from technological tools in terms of overcoming the dilemma between personal and organizational benefits. Knowledge sharing is also related to the degree of trust among the shareholders. As Bratianu and Orzea (2010, p. 108) indicated, most people will avoid their knowledge and experience when they do not have a certain degree of trust for their interlocutors. When people share a certain piece of knowledge, they need to be assured that it will not be misused. In this case, we can say that knowledge sharing, and flow and transfer of knowledge will occur more frequently in organizations and working units where there is high level of sense of trust. In this respect, plenty of research that supports the relationship between trust and knowledge sharing has been carried out (Nita, 2008, p. 16; Yücel & Samancı, 2009, pp. 116-117). It must not be forgotten that when people believe that knowledge is the source of power and prestige, knowledge sharing will cause the individuals to be afraid to lose power and therefore it will negatively affect knowledge sharing. Moreover, individuals will think that a decline in their power and status will cause their perceived value in the organization to decrease and they will fear becoming expendable. Studies that have been carried out so far confirm that knowledge sharing provides benefit for everyone except the one who shares the knowledge. This, therefore, means a decrease in the personal value of the individual who contributes. Riege (2005, p. 23-25) considers the problem of knowledge sharing that is assumed to arise from various reasons as an “obstacle” and suggests three dimensions of the concept which are personal, organizational and technological. Knowledge sharing obstacles at employee and individual level are the lack of communication and social bonds among the employees, differences in national culture, too much emphasis on the position, lack of time and trust. On the other hand, obstacles at organizational level are economic capacity, lack of background and resources, lack of formal and informal meeting places, inconvenient physical environment. Technological obstacles are insufficient or no technological devices, the fact that these devices are not used for the purpose of sharing knowledge among the employees and not being able to follow technological advancements. In addition to these factors, difficulty to transform personal knowledge into organizational


knowledge represents another important obstacle in knowledge sharing. Kankanhalli, Tan and Wei (2005) suggests that transforming personal knowledge into organizational knowledge can be difficult in the following ways:

• Discouraging organizational climate and the motivational lack of the individuals; • Tensions that may occur between efficient and inefficient knowledge cycles in different organizational

levels; • Compulsion in codification; • Difficulties in the relationships.

According to Chow and his colleagues (2008), the effectiveness of knowledge sharing for the employees and the organization depends on organizational culture, performance evaluation, reward system and the use of information technologies. When we focus on the production and sharing forms of knowledge through the interaction between explicit and implicit knowledge, we come across four possible processes:

• Socialization: Sharing of tacit knowledge among individuals; • Externalization: The appreciation of tacit knowledge and its transformation into easily understandable

forms; • Internalization: Transformation of explicit knowledge into tacit knowledge; • Combination: Placing explicit knowledge into more complex explicit knowledge sets.

As tacit knowledge becomes explicit knowledge and creates surplus value, knowledge sharing becomes more important for the organization and individuals.

Organizational Citizenship Behavior Concept, Its Dimensions and Its Importance for Organizations

The highly competitive environment urges organizations to search for new ways of gaining sustainable competitive advantage. After it was found out that technological-, structural- and capital-based assets are insufficient for getting the desired result, attention was drawn to human factor. However, it is not enough for the employees to carry out the defined role requirements in order to gain sustainable competitive advantage. In this respect, organizational citizenship behavior (OCB), which is believed to increase the performance of the employees, and therefore the organization, is among the leading issues that draws the most attention in the fields of organizational psychology, organizational behavior and human resources. Although the term is attributed to Barnard (1938) and Katz (1964) (Tayyab, 2005, p. 49; Organ et al., 2006, pp. 44-51; Sezgin, 2005, p. 320; Farh, Zhong, & Organ, 2004, p. 241), it became popular in the literature through the papers of Organ and Bateman in the “42nd National Management Conference” in 1982 and their studies afterwards (Podsakoff, Mackenzie, Paine, & Bachrach, 2000, p. 513; Karaaslan, Ergün, & Kulaklıoğlu, 2009, p. 138). Barnard called attention to the willingness of the employees to contribute to the organization with their efforts, and Katz put emphasis on the importance of extra role behaviors that were neither considered compulsory by the managers nor predefined. The well accepted definition of OCB is attributed to Organ (Yener & Akyol, 2009, p. 258). According to Organ (1988), OCB is “the voluntary behaviors of the individual that are not directly and clearly defined by the formal reward system of the organization, but help the organization work effectively and efficiently as a whole”. Knowsky and Pugh (1994) define the term as the voluntary behaviors of the employees that are independent from


the formal reward system and beyond the role definitions. According to the definition of Blakely (2003), OCB is a pattern of behaviors that are different from the technical efforts required by the job and add surplus value to the activities related to the work being done in psycho-social terms. Van Dyne and his colleagues (1995) define OCB as voluntary behaviors that go beyond defined job expectations and performed with the intention to provide benefit for the organization. Briefly, OCB involves all the positive voluntary actions of the employees that are related to the behaviors of the organization members and are performed for the benefit of the organization. (Jahangir, Akbar, & Haq, 2004, p. 76).

It is possible to evaluate the work attitudes of the employees in terms of OCB in two dimensions. The cognitive dimension that is towards the features of the attitude object and affective dimension that is towards the attitude object. Both dimensions are known to affect OCB in a positive way. When it is considered that OCB depends on the desires, voluntary efforts and sincere actions, it will be better understood how important individuals act “voluntarily” affectively and cognitively. In other words, individuals do not act in this way due to professional duties (Sezgin, 2005, p. 320). Therefore, in the case of a performance evaluation of the employees, a two-dimensional process will need to be taken into consideration: In-role and extra-role performance. In-role performance involves behaviors that employees are expected to perform by the organization, that exist in their formal job descriptions and that are directly or indirectly related to the mission of the organization. Extra-role behavior, on the other hand, involves behaviors that support the organization but do not exist in the job description of the employees, and behaviors that are voluntary, and different from the job role. Examples of these behaviors are cooperation among the employees, voluntarily undertaking extra responsibility, orientation of the new employees, willingness to help others succeed in their work, and doing more work than they are required by the job (Bergeron, 2007, p. 1078; Chen & Chıu, 2009, p. 476; Zellars, Teper, & Duffy, 2002, p. 1068). These behaviors include positive and voluntary behaviors as they are independent from the formal reward system and their repudiation is not subject to a penal enforcement (Çetin, 2004, p. 128; Acar, 2006, p. 3; Finkelstein, 2006, p. 604). The definition of organizational citizenship behavior by Organ (1988) involves a structure consisting of the components below (Schlecter & Engelbrecht, 2006, p. 3; Karaaslan et al., 2009, pp. 138-139).

• These behaviors go beyond the job requirements and formal job descriptions of the employees. They are out of the formal roles of the employees;

• These behaviors are voluntary by nature and employees decide to demonstrate these behaviors willingly. Thus, employees cannot be forced to perform these actions by the organization;

• These behaviors depend on the voluntary preferences of the employees as they are not defined by the formal reward system or the structure of the organization. Employees do not expect to get a reward in return for their extra efforts. Besides, they are not to be penalized because of the roles and behaviors that they do not perform in terms of OCB;

• OCB is the whole set of behaviors that contribute to the employees and the organization. In many studies on organizational citizenship behavior, there are differences among the numbers and

classifications of the dimensions related to this behavior. Smith and his colleagues (1983) mention two dimensions related to OCB that they call altruism and generalized compliance (conscientiousness). Graham (1991), on the other hand, divides these dimensions into three, which are obedience, loyalty, and participation. While Williams and Anderson (1991) considered OCB in individual and organizational levels, Podsakoff and his


colleagues (2000) and Karaaslan and his colleagues (2009) considered OCB in seven dimensions. On the other hand, Organ (1988) mentions five dimensions. Although there are various dimensions in the literature suggested by the researchers, Organ’s five-dimensional classification is the fundamental one. These five dimensions are altruism, conscientiousness, courtesy, civic virtue and sportsmanship (Kays, 2001, p. 104; Tayyab, 2005, p. 51, Boiral, 2009, p. 224; Çetin, 2004, p. 19; Bolat & Bolat, 2008, p. 79).

Altruism It involves attitudes and behaviors that are related to helping other workers overcome the problems they

encounter and contribute voluntarily to their performances and activities in this way. When an employee voluntarily helps another employee complete his/her work and succeed in an activity he/she cannot overcome, that is altruism. These behaviors that are intended to increase the performance of the colleagues also contribute to group efficiency and to the fulfillment of organizational goals thanks to the cooperative effect. Although altruism represents the individual efforts of the employees, it provides benefit for the organization on the whole.

Conscientiousness It expresses the fact that the employees in an organization go beyond the requirements of their formal duties

and roles and willingly contribute to the functioning of the organization as a whole. Behaviors such as the attendance of the employees to work, using time of work efficiently and effectively, performing work-oriented and target-oriented actions that require effort, abiding by the formal rules, protecting the resources of the organization, making suggestions that solve problems, etc., can be listed as examples of conscientiousness.

Courtesy Courtesy involves the conscious behaviors of the employees that are preventive against the problems that

may arise in the organization. In this respect, courtesy points to the fact that employees must act thoughtfully and carefully before performing actions that will affect the work they are doing and they must determine the problematic points beforehand and make the necessary efforts for resolution. It emphasizes the fact the employees need to act responsibly before performing actions that will affect their work. Courtesy-based informing and voluntary participation in efforts of knowledge sharing can be considered as an example in this respect. The dimension of courtesy, which contributes to the development of cooperation awareness among the employees, also has an effect on establishing the positive communication necessary for cooperation. Conscientiousness involves behaviors that are intended to prevent organizational problems.

Civic Virtue It is the behaviors that are intended to protect the benefit of the organization at utmost level. It refers to the

highest level of active participation in the organizational life. It involves the behaviors in terms of voluntary participation in organizational activities. Civic virtue also reflects a situation where commitment and interest in the organization is at the highest level. Behaviors such as actively contributing to the resolution of the problems by voluntarily participating in management, expressing ideas about the strategy that the organization should follow, voluntarily supporting the action of converting the threats for the organization into opportunities, performing actions and practices that will benefit the company can be considered relevant to civic virtue. Voluntary behaviors such as taking part in the social activities in the organization can be shown as an example of the civic virtue dimension of OCB. Being sensitive to the change occurring in the atmosphere of the organization


and developing positive reactions, accessing knowledge and being willing to share this knowledge with colleagues also are involved in civic virtue dimension.

Sportsmanship Sportsmanship involves behaviors such as being sensitive to the inconveniences, constraints and extra

efforts caused by job requirements and process, not complaining about the job and other employees, protecting the positive attitude against negative occurrences, tolerating those who have different ideas, willingness to participating in group work, etc.. They are behaviors that require the skill of internalizing the understanding of not minding problems too much. Trying to avoid possible tensions in the organization can be considered an example of behaviors involved in sportsmanship.

Considering the dimensions representing OCB, it is understood that these behaviors depend on “willingness”, which emphasizes the preferences of employees concerning OCB. Studies dealing with the effect of the state of mind and personality traits of the individuals on their preferences have been carried out. According to what Messer and White (2006, p. 67) cite from George, Carlson and their friends Isen and Daubman, it was found out that there was a positive correlation between the positive state of mind of the employees and altruism, and the employees were more willing to fulfill the formal and extra role requirements. Koys (2001) draws attention the fact that there are strong correlations between each dimension of organizational citizenship behavior and customer satisfaction. Besides, when the employees have strong organizational citizenship behaviors, the manager will be able to allow time for more important issues (Koys, 2001, p. 104; Bateman & Organ, 1983, p. 588).

The Relationship Between Knowledge Sharing and Organizational Citizenship Behavior

These two terms have been the subject of the scores of diverse studies in the literature. The interest in the issue is growing particularly because of the fact that both terms occur as a result of interactions among the employees and they increase the performance. Whether organizations can achieve sustainable competitive advantage depends on the precondition that they must attain their defined performance/success aims. When the organizations achieve this, the need for the behaviors as part of OCB arises. In this respect, it is obvious that knowledge sharing will have a positive effect on the organizational performance directly or indirectly due to its definition. As Hendriks (1999, pp. 91-100) states, knowledge sharing is a very significant channel for transforming personal knowledge to a strategic source for the organization. Many studies are carried out without the need to explain the necessity and importance of knowledge sharing for an organization. However, it must be accepted that knowledge sharing is not a behavior that can easily be accomplished. Therefore, the ways of ensuring that the employees share knowledge have been studied. Ipe (2003) indicates that many researchers have handled the motivation for knowledge sharing as a function of reciprocity. Li and his colleagues (2010), who have made a recent study on this issue, have approached the issue on a cultural level and have focused on whether the organizational climate is suitable for knowledge sharing or not. This study focuses on OCB, which is a variable that must be considered to be relevant to the organizational climate and atmosphere. Naturally, neither knowledge sharing nor OCB is a phenomenon that is equally available in every organization. Thus, whether the level of OCB varies depending on the pervasiveness of knowledge sharing is a meaningful research subject. When the relationship between organizational citizenship behavior and trust within the organization (Wech, 2002,


p. 354) is considered, naturally it will be assumed that there is a relationship between OCB and knowledge sharing. Connelly and Kelloway have found out that social interaction reinforces the perception of knowledge sharing culture but technology does not have such an effect, in their study where they evaluated various factors that possibly impinge on the perceptions of knowledge sharing culture in an organization (Connelly & Kelloway, 2003, p. 298).

This finding show that not material factors but social and psychological factors and human relations are decisive in accomplishing knowledge sharing. OCB is a significant topic to be evaluated in this respect. There are studies, though in limited numbers, that measures the relationship between the two terms. Mogotsi (2009, p. 136) has reached the conclusion that there is a positive correlation between knowledge sharing and OCB and has reached the inference that knowledge sharing is a type of OCB. Connelly and Keloway (2003, p. 294) even concluded that knowledge sharing and OCB are similar behaviors. Lin (2008, pp. 242-243) has put forward the positive correlation between knowledge sharing and the dimensions of OCB in his research. Lin states that knowledge sharing is affected by altruism, conscientiousness, courtesy, civic virtue and sportsmanship, which are the dimensions of OCB, and discusses the relationship between these dimensions and knowledge sharing. Nevertheless, in such a case where knowledge sharing is the defined policy of the organization and it is included in the reward system (Sezgin, 2005, p. 320), there can be a difference in terms of the voluntary OCB actions of the employer. Much as the view that OCB must be supported by the reward system is emphasized, this situation bears the possibility of a conflict about OCB. Including actions of OCB in the reward system will not be in accordance with the understanding of “not being included in the reward system” which forms the essence of this behavior. In that case, whether employees perform actions of OCB for reward or for the sake of OCB spirit will need to be discussed. Furthermore, including OCB in the reward system will make the separation between these two terms more ambiguous.

Conclusion

For a better comprehension of the relationship between OCB and knowledge sharing, it needs to be probed in terms of the dimensions of OCB, because all behaviors performed as a part of OCB require putting knowledge sharing into practice. Voluntary behaviors representing examples of “altruism” such as contributing to overcoming hard work or taking part in group work cannot be performed without knowledge sharing. Behaviors in terms of “conscientiousness” such as making constructive suggestions in order to solve problems will not be yielded without knowledge sharing. For behaviors representing “courtesy” such as informing the relevant people, cooperating with other employees to take place, knowledge sharing is essential. “Civic virtue”, which involves behaviors intended for protecting the benefits of the organization at the highest level, also requires highest participation in organizational life. Boosting knowledge sharing is the way to ensure them at the top level. Developing knowledge sharing among employees in order to ensure active participation for the benefit of the organization is one of the fundamental requirements. “Sportsmanship”, on the other hand, involves the behaviors intended for being sensitive to the inconveniences, constraints and extra efforts that may result from the professional processes, and avoiding organizational conflicts that may arise. In order to produce resolutions to these problems, employees need to make knowledge sharing common and functional.

Organizational knowledge sharing is a considerably important element in terms of ensuring cooperation


among employees, developing awareness for taking responsibility, and enhancing the commitment toward the values of the organization. As knowledge sharing becomes common in an organization, manifestation of organizational citizenship behaviors by employees can be expected to increase. In fact, considering the two terms as interlocked to each other will be a better approach. In other words, in organizations where OCB is common, actions as part of knowledge sharing will most probably be common, too.

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organizational citizenship behavior. The Journal of Social Psychology, 149(4), 474-494. Chow, C. W., Ho, J. L., & Vera-Muñoz, S. C. (2008). Exploring the extent and determinants of knowledge sharing in audit

engagement. Asia-Pacific Journal of Accounting & Economics, 15, 141-160. Connelly, C. E., & Kelloway, E. K. (2003). Predictors of employees’ perceptions of knowledge sharing cultures. Leadership and

Organizational Development Journal, 24(5), 294-301. Farh, J. L., Zhong, C. B., & Organ, D. W. (2004). Organizational citizenship behavior in the people’s republic of china,

Organization Science, 15(2), 241-253. Gagné, M. (2009). A model of knowledge-sharing motivation. Human Resource Management, 48(4), 571-589. Hendriks, P. (1999). Why share knowledge? The influence of ICT on the motivation for knowledge sharing. Knowledge Process

Management, 6(2), 91-100. Ipe, M. (2003). Knowledge sharing in organizations: A conceptual framework. HRM Development Review, 2(4), 337-359. Jahangir, N., Akbar, M. M., & Haq, M. (2004). Organizational citizenship behavior: Its nature and antecedents. BRAC University

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Journal of Applied Psychology, 87(6), 1068-1076.


Enhancing Organization’s Performance Through

Effective Vision and Mission

Ben E. Akpoyomare Oghojafor, Olufemi O. Olayemi, Patrick S. Okonji University of Lagos, Akoka Yaba-Lagos, Nigeria

James U. Okolie Lagos State University, Ojoo-lagos, Nigeria

Organizations, no matter their kinds, are established to serve specific societal needs. The success of an organization

depends on its ability to direct the energies of its members in effectively serving these needs. The primary motive

for the existence of any organization is often expressed in its mission. It is heartwarming that most Nigerian

organizations (profit and non-profit alike) have mission statements conspicuously displayed in their front offices.

However, the efficacies of these mission statements in securing the needed employees support and commitment

have not being fully investigated within the Nigerian context. The authors used structured questionnaires to elicit

required responses from respondents’ employees of various Nigerian organizations. It was affirmed that the

statements of properly formulated and communicated missions are potent tools in the hands of management in

unleashing employees’ commitment and improving organizational performance. It was recommended that Nigeria

organizations should move beyond the use of mission statements as mere “slogans” and open up employees’ “eyes”

to see how their daily tasks and roles as enshrined in the vision and mission can move the organization towards the

attainment of its objectives.

Keywords: vision, mission, commitment, performance, objectives

Introduction

For over a decade now, corporate Nigeria suddenly woke up to the fact that the formulation of vision and mission usually compressed in statements is a sure building block for effective management of organizations. Expectedly, corporate front offices were and still filled with various sorts of statements purporting to be mission and vision statements. Lately, the non-profit organizations especially the churches have followed suit. While this realization is a welcomed development. There is a debate as to whether, and if these statements have actually improved organizational performance within Nigeria. This study was carried out to ascertain the extent to which effective vision and mission statements could help improve managerial performance and organization prosperity. Ben E. Akpoyomare Oghojafor, Ph.D., Professor and Dean, Faculty of Business Administration, University of Lagos. Olufemi O. Olayemi, Ph.D. candidate, Lecturer, Department of Business Administration, University of Lagos. Patrick S. Okonji, Ph.D. candidate, Lecturer, Department of Business Administration, University of Lagos. James U. Okolie, Lecturer, Department of Accounting and Finance, Faculty of Management Sciences, Lagos State University. Correspondence concerning this article should be addressed to Olufemi O. Olayemi, Department of Business Administration,

University of Lagos, Akoka Yaba-Lagos, Nigeria. E-mail: [email protected].

ENHANCING ORGANIZATION’S PERFORMANCE 1072

Specifically, the study focused on: (1) Determining the extent of corporate awareness of vision and mission relevance in the effective

management of organization; (2) Ascertaining the efficacy of visions and mission so formulated by Nigerian managers in improving

organizational performance.

Literature Review and Theoretical Framework

A vision is a realistic, credible and attractive future for an organization (Nanus, 1997). For Thornberry (1997), vision is a picture or view of the future, something not yet real but imaging. What the organization could and should look like, partly analytical and partly emotional. According to Dess, Lumpkin and Eisner (2007), statements of vision tend to be quite broad and can be described as a goal that represents an inspiring, over arching and emotionally driven situation. Vision statements tend to be quite enduring and seldom changes.

Hay and Williamson (1999) posit that an effective vision must possess both the external and internal dimensions. The external dimension is a shared view within the organization of what are the market, customers, competitors, industry and likely macroeconomic impacts on the market. While the internal dimension is the shared organizational beliefs and values. It is through this that meaning is created throughout the organization about what it is that the organization does—and from here other strategic actions are taken such as the development of the mission, plans, objectives and budgets.

For Nutt and Backoff (1997) visions can be crafted in three different ways: (1) Leader—Dominated approach—In this approach, the founder or chief executive officer formulates the

vision for the organization; (2) Pump—Priming approach—This is an improved method under which the leader or CEO provides

visionary ideas on which selected employee, will work on to fashion out a vision statement; (3) Facilitation approach—This is a participatory approach under which a wide range of people are engaged

in a process of developing and articulating a vision. The leader/CEO merely acts as a facilitator that guides the vision formulation process.

According to Mishe (2000), the most effective visions share six essential qualities. The visions are: (1) Vission communicates a sense of direction. All organizations need a sense of direction, a goal and

guide to a future state of existence; (2) Vision establishes a context for operating the enterprise. Contexts help to define and classify the

environment in which the leader and the organization operate; (3) Vision describes a future condition. Effective visions provide a future—state and condition that

represents a “better” state than the ones of the past and that exists in the present; (4) Vision motivates people. Leaders understand that effective and meaningful visions provide a high

value proposition to others. Those visions that appeal to the instincts, needs and intelligence of people and touch their “soul” serve as a basis for systematic acceptance and motivation;

(5) Inspires people to work toward a common state and a set of goals; (6) Serves as a centering point for organizational behaviour and performance. Visions provide a central

point for focusing the resources of the organization, developing strategy and measuring progress towards the


vision. Nutt and Backoff (1997), posit that for a vision to enhance organizational performance it must possess the

following generic features: (1) Possibility—It should entail innovative possibilities for dramatic organizational performance; (2) Desirability—It should draw upon shared organizational norms and values about the way things should

be done; (3) Actionability—A vision should provide a motivation for people to take actions that are relevant to them; (4) Articulation—The vision should possess an image that is powerful enough to communicate clearly a

picture of where the organization is headed. For Jick (2001), vision should be clear and concise, memorable, exciting and inspiring, challenging,

centered on excellence, both stable and flexible and achievable and tangible. According to Daft (2008), the mission describes the organization’s values, aspirations and reason for being. Formal mission statements are a broadly shared definition of purpose . A mission statement answers the following questions, what is our business, i.e., who are our customers and which of their needs are we seeking to serve? Given the dynamic nature of the external environment, a market-focused mission and strategy may not provide the stability and consistency of direction needed as a foundation for long term strategy (Grant, 2000).

For Bateman and Snell (2007) the mission statement is a clear and concise expression of basic purpose of the organization. It describes what the organization does, who it does it for, its basic product or service and its values. Oghojafor (2006) defined mission statement as that which reveals the long-term vision of an organization in terms of what it wants to be and whom it wants to serve. It describes the organizational purpose, customers, products or services, markets, philosophy and basic technology.

David and David (2003) posit that a well-defined mission statement can enhance employee’s motivation and organizational performance. The purpose of the mission statement is to inspire, its credibility lies in the significance and scope of the problems and needs it has identified (Ragan, 2004).

According to King and Cleland (1978), the objectives of a company mission are: • To ensure unanimity of purpose within the organization; • To provide a basis for motivating the use of organizational resources; • To establish a general tune or organizational climate to suggest a business like operations; • To develop a basis or standard for allocating organizational resources; • To serve as a focal point for those who can identify with organization’s purpose and direction and to deter

those who can not do so from participating further in it is activities; • To facilitate the translation of objectives and goals into work structures involving the assignment of tasks to

responsible elements with in the organization; • To specify organizational purpose and the translation of these purposes into goals in such a way that cost,

time, and performance parameters can be assessed and controlled. All told, an organization without a clear mission statement tends to have its short-term actions

counter-productive to its long-run purpose. It should be carefully prepared and should always be subject to revision so that it can meet major environmental changes to enable it stand the test of time (Oghojafor, 2006).


Methodology

One hundred and twenty questionnaires were administered to respondents out of which 83 were completely filled and returned. Thus, the sample of the study consists of 83 respondents. These were made up of employees of three companies (two in manufacturing and one in the service sector) and part time students of the Masters degree program in the department of Business Administration, University of Lagos (who were employees of different companies with in Lagos and its environments). These were selected through the use of systematic random sampling procedures.

Measures and Analysis

Structured questionnaires consisted of 15 items describing the benefits of vision and mission to an organization and its employees was employed. This was measured along a five-point Likert scale of “Strongly agree”, “Agree”, “Undecided”, “Disagree” and “Strongly disagree”. A content analysis revealed that four main benefits of vision and mission were recurring. Thereafter, the respondents were asked to rank these four benefits in order of importance. The result of the ranking is shown in Table 1.

Table 1 The Result of the Ranking Opinions Rank 1(%) Rank 2(%) Rank 3(%) Rank 4(%) Total Organizational focus 55 (67) 12 (14) 10 (12) 6 (7) 83 (100) Employee motivation 42 (51) 20 (24) 13 (16) 8 (9) 83 (100) Public image 25 (30) 34 (41) 15 (18) 9 (11) 83 (100) Co-ordination 28 (35) 30 (36) 10 (12) 12 (15) 83 (100)

Note. Source: Author’s Survey Instrument (2010).

Findings, Conclusion and Recommendations

Respondents were unanimous in their agreement that effective vision and mission have great potential in improving organizational performance. This is because vision and mission statements provide a sense of direction for the organization and channel employee’s behaviour towards this direction. Employee’s motivation is greatly improved since “the knowledge of where one is heading seems to make the journey easier”. Besides, vision and mission statements tend to improve the public image of an organization as well as aid coordination of organizational activities.

However, it is regrettable that vision and mission statements in most Nigerian organizations are mere “slogans” which are used as public relation tools to deceive stakeholders into believing that the management is competent. These statements do not guide managerial decisions and actions since management does not match “actions with words”. Besides, most organization’s vision and mision statements are vague and management sometimes failled to sufficiently explain the meaning and import of them to lower level employees. The result is that most employees do not understand how their daily activities contribute to the attainment of the vision and mission for the organization. Most organization’s vision and mission statements were manifestations of the “bandwagon effects”. They were simply formulated to meet the vague and not reflecting on the environments of the organizations concerned.


Given that vision and mission statements are sine quo non for better management and improved organization performance, it is recommended that top management should formulate them based on environmental realities and where possible in consultation with the rank and file in the organization. It is suggested that all employees should be properly educated on the primary role of these statements and how each member’s activities contribute towards the realization of the vision and mission of the organization.

Management’s commitment to the vision and mission should be unwavering. This should be manifested in matching actions with the vision and mission statements. Above all, vision and mission statements are starting points in the strategic management process thus its effectiveness will depend on how well the other stages in the strategic management have been mplemented or carried out.

References Bateman, T. S., & Snell, S. D. (2007). Management: Leading and collaborating in a competitive world (7th ed.). Biston: Mc

Graw-Hall: Irwin. Daft, R. C. (2008). Management 3rd Australia: Thomson. David, F. R. (2003). It is time to re-draft your mission statement. Journal of Business Strategy, 1-2, 11-14. Dess, G. G., Lumpkin, G. T., & Eisner, A. B. (2007). Strategic management: Text and cases. Boston: McGraw-Hill/Irwin. Grant, R. M. (2000). Concepts, techniques, applications (3rd ed.). Massachusetts: Blackwell Publishers. Jick, J. P. (2001). Vision is 10%, implementation is the rest. Harvard Business Review, 11(4), 36-38. Jick, T. D., & Peciperl, M. A. (2003). Managing change: Case and concepts. New York: McGraw-Hill Higher Education. King, W. R., & Cleland, D. (1978). Strategic planning and policy. New York: Van Reinhold. Mishe, M. A. (2000). Strategic renewal: Becoming a high-performance organization. New Jersey: Prentice Hall. Nanus, B. (1992). Visionary leadership: Creating a compelling sense of direction for your organization. San Francisco, C.A.:

Jossy-Boss Publishers. Nutt, P. C., & Backoff, R. W. (1997). Crafting vision. Journal of Management Inquiry, 6(4), 308-328. Oghojafor, B. E. A. (2006). Essentials of business policy. Lagos: Ababa Press. Rangan, V. K. (2004, March). Lofty mission, down-to-earth plans. Harvard Business Review, 112-119. Thornbarry, N. (1997). A view about vision. European Management Journal, 15(1), 23-34. Trichy, N., & Devannna, M. (1986). The transformational leader. New York: John Wiley.


Determinants of Female Employment

Rate in the European Union

Irena Spasenoska, Merale Fetahu-Vehapi State University of Tetovo, Tetovo, FYR of Macedonia

The aim of this paper is to provide a clear insight about the determinants of female employment rate in the

European Union where we have used panel data analyses of 27 countries members of the European Union from

1995 till 2009. Applying dynamic modeling, i.e, generalized method of moments (GMM) econometrics findings

have driven us to system estimated model where the following institutional variables have been tested: maternity

leave, child care facilities, college education, fertility rate, GDP growth, female unemployment rate and part-time

employment. We expect these variables to have a positive impact on the female employment rate except for the

female unemployment rate and maternity leave.

Keywords: female employment rate, European Union, dynamic panel data analysis

Overall Lisbon Strategy

Confronted with globalization and the challenges of a new knowledge-driven economy, the European Council held on March 23-24, 2000 in Lisbon came to an agreement for a new strategic goal for the European Union to become the most competitive and dynamic knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and greater social cohesion. Achieving this goal required an overall strategy aimed at:

Preparing the transition to a knowledge-based economy and society by better policies for the information society and R&D, as well as by stepping up the process of structural reform for competitiveness and innovation and by completing the internal market;

Modernizing the European social model, investing in people and combating social exclusion; Sustaining the healthy economic outlook and favorable growth prospects by applying an appropriate

macro-economic policy mix. Among the goals for modernizing the European Social Model by investing in people and building unactive

welfare system was creation of more and better jobs for Europe as well as substantial reduction of unemployment (Retrieved from http://www.europa.eu, summary of legislations). Hence, the European Council considered that the overall aim was to raise the employment rate from an average of 61% in 2000 to as close as possible to 70%

Irena Spasenoska, Msc., teaching assistant at Faculty of Economics, State University of Tetovo. Merale Fetahu-Vehapi, Msc., teaching assistant at Faculty of Economics, State University of Tetovo. Correspondence concerning this article should be addressed to Irena Spasenoska, Braka Miladinovi br.312 3/12 1200 Tetovo, R.

Macedonia. E-mail: [email protected].

DETERMINANTS OF FEMALE EMPLOYMENT RATE IN THE EUROPEAN UNION

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by 2010 and to increase the percentage of women in employment from an average of 51% in 2000 to more than 60% by 2010. The new goal required member states to consider setting national targets for an increased employment rate, which it was argued by enlarging the labor force would reinforce the sustainability of social protection systems. In addition to the 2010 Lisbon targets, the Stockholm Europen Council of 2001 set intermediate targets for employment rates in the EU in 2005 of 67% overall and 57% for women. It also set a new target for raising the average EU employment rate for older men and women (aged 55-64) to 50% by 2010 (Retrieved from http://www.europa.eu, summary of legislations).

Progress of Total and Female Employment Rate After the Lisbon Strategy The progress towards the Lisbon employment targets of overall employment (70%), female employment

(60%) and employment of older man and women (50%) can be seen in Table 1.

Table 1 Progress of Total and Female Employment Rate From 2000 to 2009 in Percentages

EU Benchmark

Employment rate % overall

Employment rate 55-64 years old % overall

Female employment rate 15-64 years old

GDP growth percentage change in previous year

70% (2010 target, Lisbon summit)

50% (2010 target, Stockholm summit)

60% (2010, Lisbon summit)

Base line scenario of 3% per annum, Lisbon summit

1997 60.7 36.4 50.8 2.5 2000 63.4 37.5 54.1 3.9 2001 64.1 38.4 55.0 1.9 2002 64.2 39.8 55.6 1.2 2003 64.5 41.5 56.2 1.2 2004 64.8 42.3 57.0 2.3 2005 65.4 44.2 57.8 1.8 2006 66.2 45.3 58.8 2.9 2007 67.0 46.5 59.7 2.7 2008 67.3 47.4 60.4 0.6 2009 64.6 46.0 58.6 2.5 Notes. The employment rate is calculated by dividing the number of persons aged 15 to 64 in employment by the total population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. Employed population consists of those persons who during the reference week did any work for pay or profit for at least one hour, or were not working but had jobs from which they were temporarily absent. Source: EUROSTAT—European Commission Statistics.

First three years of the decade after the launch of the Lisbon strategy were characterized with only a moderate growth in employment. The slowdown which began in the first half of 2001 and saw growth reached a standstill by the last quarter of 2002, followed by only a very moderate recovery over the course of 2003. With nearly zero growth in 2003 the progress towards the Lisbon 2010 target of 70% overall employment had came to a standstill. By 2003, it became clear that the EU was going to miss the intermediate employment rate target for 2005 although the employment rate target for women still remained in reach. In 2006, 13 member states have meet the 2010 employment target for women including for the first time Cyprus, Germany, Latvia and Lithuania. Since 2000, large increases have been achieved in Cyprus, Estonia, Greece, Latvia and Italy where rates have risen by around 5 percentage points and Spain with 12 percentage points. Greece and Italy were still far from the


1078

target. Total employment continued to expand in the EU in 2008. However, the rise was not uniform with respect to gender, age and type of employment The EU employment rate, i.e., the share of the population aged 15-64 years (the working-age population) in employment, amounted to 65.9% in 2008, up 0.5 percentage points compared with 2007. The growth rate for female employment was almost three times that for male employment. In 2008, the employment rate of women aged 15-64 amounted to 59% , while for man it was almost 73%. In 2009, the employment rate for persons aged 15-64 was above 70% while in all member states the male employment rate was higher than the female employment in 2009 except for Lithuania where the female rate was 1 percentage point higher for men. Estonia and Finland have recorded the smallest difference between male and female employment rates while Malta, Greece and Italy recorded the greatest.

The aim of the empirical testing in this study is to capture the common institutional determinants of female employment rate by employing the generalized method of moments (GMM) proposed by Arellano-Bond (1991) and Arellano-Bover (1995)/Blundell-Bond (1998). We have considered dynamic model estimation as a more appropriate approach because of the possibility to capture the costly sluggish adjustment of employment as well as the effect of persistence captured by adding a lagged dependent variable. Moreover, we were also interested whether there will be a change in the sings in front of the coefficients especially for fertility rate and maternity leave which traditionally have been taken as factors that negatively influence female employment rate. The contribution of this analysis can be seen in a manner that highlights the relationship and significance of the institutional variable towards improvement of the social and welfare system across countries members of the European Union as the backbone for supporting female in perusing carriers and higher employment.

The study is organized as follows. In the next section, we provide a brief yet detail insight to literature review for each variable included in the research. Empirical specification diagnostics and results are given in the third section followed by the fourth where we discuss our findings and conclusion.

Literature Review and Variable Description

In general there are two main approaches employed across studies of female employment across countries. The first approach examines the level of female employment itself, focusing on the labour force participation rate and the number of hours worked such as part-time to full-time category. The second approach explores the determinants of female employment. While the determinants selected for analysis vary from study to study, they may include one or more of the following three types of variables: (1) individual level (micro variables, such as number of children in household); (2) institutional level (macro) variables, such as the size of the welfare state; and (3) a combination of individual and institutional level variables (Warnecke, 2008). While single-country level studies use micro-level variables, macro-level variables focus on family policies as diverse social, political, institutional and cultural constraints of the average female participation rate. In the following we have provided a brief literature review by analyzing the institutional level (macro) variables used in this study.

Maternity Leave Parental leave policies support new parents usually in two complementary ways: by guaranteeing

job-protected leave and by offering financial support during that leave. The aim of benefits is to subsidize the child care provided by the mother while job protection aims to ensure continuity of women’s careers in the labor market. Most of the literature has found that more generous parental leave mandates tends to delay women’s


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return to work. However, evidence of the relationship between duration of leave and women’s labor market outcomes is mixed.

Job protected leave mandates are expected to increase women’s employment and earnings by encouraging job continuity after birth. Yet, prolonged periods of absence from the workplace might lead to loss of specific and general human capital and weaker labor market prospects after returning to work (Voicu & Hielke, 2003). Hence previous employers, while obliged to re-employ mothers when they return to work after the baby break, may either remunerate them relatively worser than their colleagues or may dismiss or layoff re-entered women with a higher probability as soon as the job protection period upon re-entry has run out (Lalive, Schlosser, & Zweimuller, 2009). Ruhm (1998) compares employment rates and wages of men and women using panel data from European countries, and finds that longer leave mandates are associated with higher female employment but lower relative wages. Ejrnaes and Kunze (2006) investigate the role of parental leave on the family wage gap using administrative data for Germany and exploiting exogenous variation in the length of parental leave generated by policy changes in the German system. The authors found that longer parental leave duration leads to detrimental effects on employment and wages. In contrast, Schonberg and Ludsteck (2008) study the same reforms and found only minor effects on employment rates and a mixed effect on wages. In our analysis maternity leave is defined as the number of paid weeks a woman is entitled in case of normal birth (International Social Comparison Database).

Child Care Facilities Theories about child care (e.g., Andersson, Duvander, & Hank, 2004; Rindfuss & Brewster, 1996) include

four dimensions of child care: availability, quality, cost, and acceptability. In our case, we are testing the impact of the availability upon female employment rate. Availability is the degree to which a family has ready access to the needed child care—This might include not only convenient geographical location but also the availability of slots for the right age range and the right time of day (Rachel, 2001). Our measure of availability is the participation rate of 4 years old children in pre-school education. This indicator presents the percentage of the 4 years old who are enrolled in education-oriented pre-primary institutions which provide education-oriented care for young children. They can either be schools or non-school settings, which generally come under authorities or ministries other than those responsible for education. As such it is a measure of utilization rather than capacity.

When estimating the child care effect on female employment rate, we have considered possible simultaneity that gives rise to endogeneity in women’s decision to work and in the decision to use institutional child care. According to Coneus, Goeggel and Muehler (2009) the decision to use child care outside the home is strongly connected to mothers’ decision to work after child birth and vice versa. They provide evidence on the determinants of institutional child care use addressing the endogeneity of mothers’ labour supply by applying an instrumental variable approach. Based on the German Socioeconomic Panel from 1989 to 2006 they have shown the children have a higher probability to attend institutional care if their mothers increase their actual weekly working time. On the other hand, limited availability in the form of limited slots and hours a facility can remain open limits compatibility with the mother’s working hours. Kreynfeld and Hank (2000) have found that due to the very limited opening hours mothers using child care may not even be able to work part time and must seek additional forms of child care, which are rarely available. Greater availability of child care it is associated


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positively with female’s employment (Van Dijk & Siegers, 1996). Therefore, a positive sign is expected in front of the coefficient (Eurostat Database).

Fertility Rate The fertility rate is defined as the mean number of live children born to a women during her lifetime.

Traditionally, a high fertility rate has a negative impact upon female employment. However, recent studies have shown that the current relationship between female employment rate and fertility rate is somewhat ambiguous and has been undergoing constant change in recent years. Due to institutional changes in form of subsidies, child care programs, possibility of part-time working and unemployment rates might have changed the sign in past decades (DelBoca & Saures, 2007). The correlation between fertility and female employment across developed countries was negative, significant and quite stable during the 1970s and up to the early 1980s. However, by the late 1980s, the correlation had become positive and equally significant (Ahn & Mira, 2002). The reversal of the sign occurred simultaneously with the emergence of a high and persistent unemployment rate, increasing dispersion in the availability of part-time jobs, child care availability and job protection provided by paid maternity leave. Where the unemployment rate is high, women are less likely to leave the labor market, knowing that it may be more difficult to reenter later due to the scarcity of jobs (Del Boca, 2003). Additionally, when there is greater insecurity in the labor market, parents may be more reluctant to have children because of the fear of not having enough income to support their potential children (Del Bono, 2002). The greater availability of part-time job opportunities within a country reduces the opportunity cost of having children, as mothers will be less likely to give up their jobs to raise their children. In a carefully conducted empirical study based on provincial-level Italian panel data, Del Boca (2002) documents that availability of child care and part-time work increases both the probability of working and having a child. Many researchers have suggested the increasing availability of market child care as a possible explanation for the recent fertility upswing in some developed countries. Moreover, countries with longer maternity leave programs have significantly higher fertility rates than countries with shorter maternity leave policies. Based on a cross-sectional time-series data for the European Union, DiCioccio and Wunnava (2008) found that neither female education nor increased employment were significant in determining fertility and vice versa.

When estimating the fertility effect on female employment, it is important to recognize the mutual dependence between the labour supply of married women and fertility, i.e., the endogeneity in either life cycle models or static models of female labour supply. Even though children can be exogenous to the hours of work decision for married women, according to Xie (1997), children are endogenous to the female participation decision where children under six have dramatic negative impact on female employment. However, based on the findings that government regulations and job protection has mitigated the effect of fertility upon employment rate, we might expect downsizing of the negative effect upon employment or even an insignificancy of the coefficient (World Bank Database).

College Education In order to estimate the effect of education upon female employment, the percentage of graduated females

with tertiary education is used, irrespective of fields of education such as mathematics, science, computing, engineering, manufacturing and construction. Greater levels of educational attainment theoretically afford


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females a greater range of employment possibilities and a greater choice of superior (more “desirable”) employment, e.g., higher paying jobs, thereby creating an incentive to enter the labour force. Therefore we can expect a positive relationship between the percentage of female population with college education and female employment (Gerner & Zick, 1983; Rextorat, 1990; Miller & Xiao, 1999; World Bank Database).

Female Unemployment Rate The female unemployed rate is female unemployed persons as a percentage of the female labour force based

on International Labour Office definition. Unemployed persons comprise persons aged 15 to 74 who are without work and have been actively seeking work. This variable captures the labour market conditions and the expectation of obtaining gainful employment. Unfavorable market conditions, i.e., a high female unemployment rate negatively influences the female employment rate, therefore we can expect a negative sign in front of the coefficient (Eurostat Database).

Female Part-Time Employment Female part-time employment is defined as the percentage of total female employment. The rise in female

participation has occurred hand-in-hand with an increase in the part-time rate in many countries. While the causality is not clear between the decision to participate into the labour market and the choice of working part-time, the rising proportion of women willing to join the labour markets, mostly explained by rising levels of education, contributed to the development of part-time employment. Sociological and cultural reasons, such as the separation of tasks within the household and the family model, combined with institutional reasons (e.g., the lack of childcare facilities) explain in part why women are more inclined to work part-time than men. For instance, a “male breadwinner” model of family encourages women to work part-time rather than full-time (Fagan & O’Reilly, 1998). According to Budelmeyer, Mourre and Ward (2008), part-time work creates an opportunity for women to combine taking care of their children with market work. Therefore a positive sign is expected (Eurostat Database).

Growth of GDP per Capita This is defined as the annual percentage growth per capita. According to the Neoclassical Endogenous

Growth theory, the rate of growth is endogenous in a sense that is driven by the rate of growth of the labour force i.e., employment and the technological change (Setterfield, 2009). At the same time, a higher employment rate implies an unambiguous increase in GDP per capita with no negative implications for long-run productivity growth in the existing workforce (Carone, Denis, Morrow, Mourre, & Roger, 2006). The growth rate in labour productivity is the most important determinant of the growth of GDP per capita as it accounts for at least half of GDP per capita growth in most OECD countries. Greater labour utilization is the factor that can make an important contribution to GDP growth by providing a significant boost to the annual growth. It is expected a positive sign in front of the coefficient (World Bank Database) describes the relative judgment of oneself in comparison with others. Overprecision is “excessive certainty regarding the accuracy of one’s beliefs” (Moore & Healy, 2008, p. 4). Overconfidence has been observed in social judgments, self-predictions, and professional predictions, in retrospective as well as prospective judgments (Allwood & Granhag, 1999; Dunning, Griffin, Milojkovic, & Ross, 1990; Lichtenstein & Fischhoff, 1977; Paese & Feuer, 1991; Vallone, Griffin, Lin, & Ross, 1990; Von Winterfeldt & Edwards, 1986). With regard to confidence judgments about achieving future goals,


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this calibration deficit implies that decision makers systematically overestimate their capacity to reach stated goals.

Empirical Specification

Descriptive Statistics and Model Specification In this chapter, we test the significance of selected institutional variables on a county’s female employment

rate by conducting a first-order dynamic panel estimation. Dynamic panel estimation has been used since static modeling of an employment equation may lead to problems. According to Lachenmaier and Rottmann (2007), the high cost of hiring and firing are a well-known argument for costly employment adjustment, especially in European economies. If a firm faces these high costs, the actual employment will deviate from the equilibrium level in the short run. The short-run dynamics compound the influences from adjustment costs, expectation formation and decision processes. Therefore, a dynamic panel data model is considered in order to model the sluggish adjustment.

Dynamic panel models estimate the effects on some observed outcome of other variables of interest, which may be exogenous or potentially endogenous, conditional on both unobserved individual heterogeneity and one or more lags of the dependent variable1. In our case apart from the dependent variable, female employment rate, three individual variables were taken as endogenous variable: fertility rate, GDP per capita and childcare facilities. To get consistent estimates in the presence of lags of the dependent variable we employ the generalized method of moments (GMM)2 proposed by Arellano-Bond (1991) and Arellano-Bover (1995)/Blundell-Bond (1998) introduced also by Roodman (2006). Applying GMM we account for the potential endogeneity arising from the lagged dependent variable as well as three above mentioned variables. Using the appropriate instruments for the endogenous variables one can overcome the endogeneity problem although using lags two and deeper for the endogenous variable in the GMM-style and all regressors included in the RE increases the number of instruments and too many instruments “can overfit endogenous variables” (Roodman, 2006, p. 13).

According to Roodman (2006) dynamic panel estimation is a proper approach for situations with few time periods, say ≤ 15, and many cross-section units where the number of units is far greater than the number of time periods. However, in our case we are going to use a panel data with relatively long time period and considerably small number of cross-sections, i.e., 25 out of 27 EU countries for 13 years starting from 1995. In panels where T is large, the dynamic panel bias becomes small and a more straightforward fixed effect estimator works. However, large bias has been found even for T = 30 and our data has a considerably smaller time dimension than this. At the same time, the number of instruments in difference and system GMM tends to explode with T. If N is small, the cluster-robust standard errors and the Arellano-Bond autocorrelation test may become variables (Geoff Pugh,

1 The basic characteristics of the linear dynamic panel model are displayed in the following equation: Yit = βYi,t-1 + (αi + it). It is a first-order dynamic panel model, because the explanatory variables on the right-hand side include the first lag of the dependent variable (Yi,t-1) where the group-specific random effect (αi) control for all unobserved effects on the dependent variable that are unique to the country and do not vary over time, i.e., captures specific ignorance about country i and an error that varies all over countries and time ( it) capturing the general ignorance of the determinants of Yit. 2 GMM is a general method of estimating population parameters from a data sample. GMM assumes population conditions expressed in terms of expectations, i.e., E( t, xt) = 0 which is a restriction on the covariance between the error term and the independent variable known as conditions. GMM dynamic panel estimation allows use of set of instruments per variable within the data which give a great possibility for resolving endogeneity problems within the model.


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2009). Despite the expected problems, we continue to investigate dynamic model out of economic reasons explained at the beginning of the chapter. Hence this chapter should be seen in terms of illustrating an approach that may be more appropriate for data set with a larger cross-section dimension.

Female employment ratei,t = f(em_ratei,t-1, matleavei,t, chcarei,t, fertratei,t, educ i,t unemrate i,t part_emi,t, GDPi,t, time dummy, error term)

The chosen variables in the model given above have been considered in the literature as possible determinants of the female employment rate. The dependent variable is the female employment rate which is females in employment as a percentage of the total female population over 15 years age and up to 64 years age (Eurostat Database).

In order to obtain more valid result we have included time dummy variables in the model which will capture and place the effect of universal shocks (business cycle effects, demand shock, etc.) from the idiosyncratic error term in to the systematic part of the model. According to Roodman (2006), contemporaneous correlation, as a result of universal time-related shocks, can cause cross-individual correlation in the error term which may give biased estimates and the addition of such time dummies may lessen or remove such correlation.

The abbreviation used in the regressions as well as brief summary statistics are given in Table 2.

Table 2 Descriptive Statistics Variables Abbreviation Standard deviation Mean value Min. Max. Maternity leave matleave 8.50 19.41 13 52 Child care facilities chcare 19.63 78.07 29.7 100 Fertility rate fertrate 0.24 1.48 1.09 2.13 College education educ 10.56 25.89 2.8 54.2 Female unemployment rate unemrate 4.75 9.23 2.2 30.8 Part-time employment rate part-em 16.14 23.43 2.7 75.2 Female employment rate em_rate 9.40 55.86 31.6 74.3 Growth in GDP per capita GDP 2.37 3.47 -4.58 12.23

Empirical Results In order to estimate the significance of female employment rate determinates, we have considered dynamic

model estimation as a more appropriate approach since dynamic estimation gives us the possibility to model the costly sluggish adjustments of employment.

According to Peseran, Smith and Im (1996), pervasive slope heterogeneity is often evidence in panel-time series for groups such as countries, regions, industries and firms. In such panels inclusion of lagged dependent variable in conventional FE and RE model could lead to biased and inconsistent estimates (Peseran & Smith, 1995). Secondly, in RE estimation, the lagged dependent variable is correlated with the compound error term. Because the compound error term has a time invariant component, it influences the dependent variable in each period and hence, must be correlated with lagged values of the dependent variable which conflicts with the basic assumption of linear regression (Creen, 2003). In our case, the error component regression model controls for unobservable characteristics such as tradition, employer preferences, i.e., stereotyping, prejudice, work-life balance policies and so on. According to the literature, there is a high possibility for these to be correlated with


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some of the independent variables in the employment rate, e.g., in highly traditional counties, where the bread-winner model is dominant there is higher possibility of a higher fertility rate and less possibility of supporting the female partner to enter the working market and to enroll tertiary education.

There are two partial solutions for situations where we have slope heterogeneity and an error component correlation. One is a group—mean regression which involves reducing panel to a cross section and the second is estimating purely static panel, both eliminating dynamics. However, omitting dynamics and estimating a static model in presence of a dynamic relationship entail serious misspecification as well as bias and inconsistent estimates (Bond, 2002a). The importance of modeling dynamics has been strongly emphasized by Green (2008), according to whom, inclusion of lagged variable brings entire history in the right-hand-side of the equation, so that any measured influence is conditional on this history where any impact of the independent variables represents effect of new information. Therefore, in order to get consistent estimates in presence of lags of the dependent variable we employ the generalized method of moments (GMM) proposed by Arellano-Bond (1991) and Arellano-Bover (1995)/Blundell-Bond (1998), and developed in Roodman (2006).

In the GMM approach, apart from the dependent variable three other variables were classified as endogenous: childcare, fertility rate and GDP per capita. However, we have to be aware that classifying these variables as endogenous makes the use of this estimation procedure problematic given our data set since applying more endogenous variables create more instruments, thereby causing bias and inefficient estimates.

When analyzing cross-sectional data with slightly longer time series, difference estimation is considered as a more suitable approach. However, according to the obtained results when comparing both difference and system estimation, in our case the system approach appears as more appropriate. Examining the diagnostic statistics (m1 + m2 statistics as well Sargan test), in the system estimated model there is 1st-order serial correlation and there is No 2nd order serial correlation while Sargan test p = 0.2050. On the other hand, diagnostic testing of the Arellano and Bond Difference estimation, indicated weak instruments since Sarnan test p = 1.000 while m1 + m2 statistics suggested presence of 1st order serial correlation well as 2nd order serial correlation. On the bases of diagnostic testing, the system estimated model is going to be used as it is preferred over the difference model. The obtained results are given in Table 3. When we look at statistics of significance in the difference estimated model, all of the coefficients are statistically, individually insignificant at the conventional 5% critical level. Compared to the difference estimated model, the system estimated model has the same statistics as significant, with the exception for three variables: em_rate(lagged), GDP and unemrate.

Before the interpretation of the system GMM estimation, two tests for instrumental validity have been used: (1) test for first and second order serial correlation among the residuals (m1 and m2 statistics); and (2) the Sargan test of over-identifying restrictions. Arrelano and Bond’s (1991) GMM estimation require E[Δ it, Δ i,t-2] = 0, i.e., no second-order serial correlation in the error term of the first differenced equation, where m2 statistics test the maintained hypothesis (Ho) in the equation above. The m1 statistics has a subsidiary role by providing information on the robustness of m2 statistics. The m2 statistics is unreliable, i.e., it may fail to reject, if the error term in levels follows a random walk. Thus, if there is first order serial correlation in the first differenced error term where 0 < p < 1, the random walk in the first order errors is excluded. Therefore, the m1 and m2 statistics require first order serial correlation and No. second order serial correlation.

According to the first way of testing instrumental validity, i.e., test for first and second order of serial


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correlation among the residuals, in all cases the t-statistics for m2 we accept the null of No. 2nd order autocorrelation in the differenced error terms. At the same time we do reject the null of m1 statistics for 1st order autocorrelation in the differenced error terms.

Table 3 Comparison Between System and Difference Estimated Models

Models Variables Dependent variable: Em_rate Independent variables:

System dynamic panel-data estimation

Difference dynamic panel-data estimation

Constant Standard Errors; t-statistics

11.51 (2.595); (4.43)

45.95 (30.72); (1.50)

Em_rate(lagged) Standard Errors; t-statistics

0.84 (0.031); (27.28)

0.57 (0.177); (3.22)

chcare Standard Errors; t-statistics

-0.003 (0.01); (-0.32)

0.05 (0.039); (0.17)

fertrate Standard Errors; t-statistics

-0.05 (0.883); (-0.06)

2.43 (1.811); (1.34)

matleave Standard Errors; t-statistics

-0.05 (0.027); (-1.72)

-1.41 (1.36); (-1.04)

educ Standard Errors; t-statistics

0.006 (0.025); (0.39)

0.03 (0.036); (0.87)

unemrate Standard Errors; t-statistics

-0.20 (0.039); (-5.16)

-0.11 (0.14); (-0.81)

Part_em Standard Errors; t-statistics

0.02 (0.015); (1.63)

-0.07 (0.17); (-0.39)

GDP Standard Errors; t-statistics

0.20 (0.0054); (3.72)

0.15 (0.23); (0.64)

m1 pr > z

-2.28 (0.20)

-0.54 (0.59)

m2 pr > z

1.15 (0.25)

0.19 (0.85)

Sargan/Hansen test Prob > chi2

130.41 (0.2050)

7.888 (1.000)

Wald test Prob > chi2 If TS > CV → Reject Ho: the independent variables are jointly zero.

2,345.45

(0.000)

5,062.50

(0.000)

Table 4 Interpretation of Diagnostic Tests for Arrelano and Bover System GMM

Models Diagnostic tests

1. Arellano-Bover dynamic panel-data estimation



4. Arellano-Bover dynamic panel-Data estimation

1st lag in levels 2nd lag in level and 1st lag difference

3th lag in level and 2nd lag differences (1 more instrument)

4th lag in level and 3th lag differences (2 more instruments)

Number of instruments 183(Max) 86(Min) 111 135 m1 Pr > z

2.3167 (0.0205)

-1.9278 (0.0539)

2.271 (1.1937)

-2.2837 (0.0224)

m2 Pr > z

0.1061 (0.2687)

1.6056 (0.1084)

0.2326 (0.0231)

1.1487 (0.2507)

Sargan/Hansen test Prob > chi2

181.61 (0.1928)

7.88 (1.000)

116.7 (0.0563)

130.41 (0.2050)


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Concerning the Sargan/Hansen test, as second test for instrument validity, too low and two high p-values can be indicative of weak instruments (Roodman, 2007). Also there is the problem of “to many” instruments where the Sargan test grows weaker the more instruments were tested and we unable to reject the null of instrument validity. In this case, p values obtained in most of the cases were above the apparently very high rule of thumb a threshold of p = 0.25. According to the statistics presented in the table only the forth case of estimation provided p value near to the rule of thumb suggested by Rodman, p = 0.2050. Even we do accept the null of valid instruments we still had to deal with the problem of two many instruments given that there are only 23 groups in our data set. As discussed too many instruments can overfit endogenous variables and fail to expunge their endogenous components. In our case the number of instruments is massively over the number of cross-section. There are two options in trying to deal with this problem: limiting the lags used in the GMM-style instruments or using command for collapsing instruments available in xtabond2. In this analysis the second approach has been conducted. The number of instruments are reported in Table 4, first row.

There is no clear guidance from the literature on how many instruments are “too many” (Roodman, 2009), although > xtabond2 < does give a warning when the number of instruments is larger than the number of cross-sectional units. One of the ways to limit the instrument count is by collapsing them, i.e., creating instruments for each variable only. Namely, when we “collapse” an instrument set, we create not a whole matrix of instruments but a single column vector of instruments, which means that there is only one instrument for all time periods (Pugh, 2004). At the same time there has been a growing evidence that that panel data is likely to exhibit cross-sectional dependence which may arise due to spatial dependencies, economic distances, common shocks thereby causing errors to be “correlated across the entire cross section” (Sarfidis et al., 2006). The evidence of 2nd—no order serial correlation might imply possibility of no heterogeneous error cross sectional dependence.

Table 5 The Difference in Hansen Test (≡ C-statistics) C-statistics Chi2 P-values Ho: instrument validity Hansen test of over-identified restriction Chi2 = 4.52 Prob > chi2 = 1.000 Not rejected Difference in Hansen test of exogeneity of instruments Chi2 = 5.17 Prob > chi2 = 0.819 Not rejected Comparison of both tests Chi2 = 0.65 Prob > chi2 = 1.000 Not rejected Note. The p-values given above were compared to the conservative threshold suggested by Roodman (2007 and 2009) which is p = 0.25.

According to the statistics presented in Table 5, in our preferred model the system GMM instruments for levels are valid, in which case we can accept the “steady-state” assumption required for system estimation and there is no undue problem with cross-sectional dependence. However, the number of instruments still remained high and above the number of cross-sectional groups, i.e., 48.

Despite the fact that we did not have 1st order correlation and have 2nd order correlation, at the same time valid instruments (Sargan/Hansen) we cannot say that this is a sensible model. The number of instruments remained high which overfit the number of instruments and bias the results. At the conventional 5% critical value, almost all of the coefficients were statistically individually insignificant. Apart from the coefficient of the lagged dependent variable and two other variables, i.e., tertiary education and GDP growth are significant at 10% level.


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All of the signs in front of the coefficients are as expected, i.e., there is high level of persistency between lagged dependent variable and dependent variable in level as well as a negative relationship between female employment rate and increase in female unemployment, long maternity leave and high fertility rate.

Table 6 Interpretation of the System Model Regressors Coefficient with robust SE Economic interpretation Employment rate (lagged)

0.96*

On average, the female employment rate in current period is estimated to be 0.96% of the employment rate in the last period (t-1), ceteris paribus (high level of persistency).

Child care facilities

0.07

On average, 1% point increase of 4 years old in pre-school education in current period, gives 0.07% point increase in the percentage of female employment ceteris paribus.

Fertility rate

-7.55

On average, increase average of birth rates in current period, will decrease the employment rate by 7.55%, ceteris paribus.

Maternity leave

-0.0013

On average, 1 week increase in maternity leave in the current period will give 0.0013% point decrease in the percentage of employment rate, ceteris paribus.

Education

0.11**

On average, 1% point increase in the female tertiary graduates will give 0.11% point increase in the female employment rate, ceteris paribus.

Female unemployment rate

-0.04

On average, 1% point increase in the female unemployment rate will give 0.04% point decrease in the female employment rate, ceteris paribus.

Part-time employment

0.05

On average, 1% point increase in the female part-time employment will give 0.05% point increase in the female employment rate, ceteris paribus.

GDP

0.23*

On average, 1% point increase in the GDP growth will give 0.23% point increase in the female employment rate, ceteris paribus.

Constant term 3.71 The constant term has no theoretical meaning.

Notes. * Significant at 10% level; ** Significant at 5% level; Coefficients without asterisk are statistically insignificant.

Conclusion

In this paper, we have investigated the question what determines female employment rates in the European Union where a sample of 27 countries has been analyzed over a time period of 14 years from 1995. Because of the costly sluggish adjustments of employment we have specified a dynamic model where system GMM model appeared as more suitable compared to the difference model. At the same, we have to be aware that our data set has a considerable lack of cross-sections. Moreover, the number of instruments were increasing enormously over the number of observation even though we tried to reduce them. Nevertheless, results from our study have been supported by vast number of empirical research in the literature. At the same time, the choice of variables incorporated in the model was based on theory and empirical investigations where the chosen variables were suggested as possible determinants of female employment rate. The main findings can be summarized as follows:

The coefficient estimators for tertiary education and GDP growth per capita were found to be significant at 10 percent level while lagged female employment rate had coefficient estimator significant at the 5 percent level. The significance as well as the positive sign in front of these coefficients are as expected. According to our results, the current employment rate is highly influenced by the previous year employment rate. Past research on female employment has repeatedly shown that persistence is an important aspect of the female employment,


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while first-order dependence the most important factor in explaining persistence in female labor supply behavior (Heckman & Willis, 1977; Nakamura & Nakamura, 1985; Eckstein & Wolpin, 1989). Persistence in employment may be due to state dependence which arises from human capital accumulation or the costs of searching for job which in turn may be influenced by social policies such as employment regulations and the availability of child care. Tertiary education raises the utility of working full-time and lowers the utilities associate with part-time work and no work. Our results have indicated that 1% point increase in the female tertiary graduates will give 0.11% point increase in the female employment rate, other things being constant, while a 1% point increase in the GDP growth will give 0.23% point increase in the female employment rate, ceteris paribus.

Contrary to our expectations, the rest of coefficients are statistically individually insignificant at both 5% and 10% level in our estimates. Maternity leave that guarantees a (post-leave) right to return to work is an important component of family policies. However, even though many analyses have revealed that job-protected leave can increase the time mothers spend at home with their infants and also the likelihood they return to their pre birth employer, women’s employment opportunities decline with the time away from work. Our analysis results suggest that the length of maternity leave has negative impact on female employment where for every one week increase in the length on maternity leave, female employment rate is expect to decrease by 0.013%. On the other hand, high part-time employment rate has a positive impact on employment. For every percentage point increase in the percent of working women who work part-time, female employment rate is expected to increase by 0.05. High level of education, sociological and cultural reasons as well as increase in the fertility rate and number of children per family, have increased the need for working part-time instead of working full-time so as to reconcile professional and family life. Limited availability of part-time employment and the limited availability of affordable child care services increase the costs of working for mothers, making it difficult to participate in the labour market.

Other social factors do seem to negatively contribute to countries’ employment rates. The influence of current labour market conditions and the responsiveness of women to those conditions are relatively strong. Women’s responses to labour market conditions are normally found to be sensitive to changes in the unemployment rate. Namely, high unemployment within a country has a negative effect upon female employment rates. Our results suggest that a percentage point increase in a country’s unemployment rate will decrease its employment rate by 0.04. Moreover, women in their mid-20s facing a tight labor market and worsening economic conditions (i.e., high unemployment) tend to restrict their fertility below their ideal level, even though this phenomenon seems to be much weaker if they were employed in a stable public sector job, (Adsera, 2006). Concerning fertility rate effect on female employment our analysis has revealed a negative relationship, as expected. Namely, a percentage increase in the average births, will decrease the employment rate by 7.55%, other things being equal. However, many researchers have indicated that the female employment rate and fertility decisions are both affected by similar forces. The decisions to work and have a child are positively influenced by the available supply of public child care as well as the availability of part time jobs. Many researchers have indicated that by increasing the flexibility of employment relationships, more women would find it attractive to enter into the market. As suggested by feminist observers (e.g., Folbre, 1997, 2001), countries that facilitated combining the worker and mother roles have higher fertility and higher female employment rates


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where a major institutional influence is the availability and acceptability of child care centers. According to our research, on average, 1% point increase of 4 years old in pre-school education in current period, gives 0.07% point increase in the percentage of female employment.

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