DATA INTEGRATION TO STUDY THE ENTERPRISE GROUP STRATEGY IN UKRAINE Olga A. Vasechko Scientific and Technical Complex for Statistical Research, 3, Shota.

DATA INTEGRATION TO STUDY THE ENTERPRISE GROUP STRATEGY

IN UKRAINE

Olga A. VasechkoScientific and Technical Complex for Statistical

Research,3, Shota Rustaveli Str., Kyiv, Ukraine

E-Mail : [email protected]

Michel Grun-Réhomme, Université Paris 2, ERMES-UMR7181-CNRS,

12 Place du Panthéon, 75005 Paris, France

E-Mail : [email protected]

1. The issue

2. Suggestions

3. Basic information and the retrospective

4. The models

5. The results for total population and non-offshore

6. The findings

7. Conclusion

Plan

The issue (1)

1. Large businesses and enterprise groups (EG) have a big impact on GDP formation and the level of employment.

2. Recent theoretical and empirical researches tend to look at multinational enterprises as the main type of EG from the point of view of economically advanced countries.

3. The dynamically developed emerging economies also face similar questions of EG.

The issue (2)Basic issues of EG statistics in Ukraine are regarding to:

• Definition of observation unit • Legislative base to provide the common framework of statistics of EG• Statistical register of EG• Sources of actual information

Statistics of Enterprise Groups in Ukraine, International Conference of Globalization and Challenges for Official Statistics/ UNO-Eurostat-EFTA, Kiev, Ukraine, 3-6 July 2007.

Administrative and Statistical Registers in Business Statistics of Ukraine, Baltic-Nordic Conference on Survey, 2-7 June 2007, Kuusamo, Finland .

Quality Measurement of a Register for Structural Business Survey: Application to Ukrainian Data / European Conference on Quality and Methodology in Official Statistics. – Mainz, Germany, 2004.

• Data integration and modeling

Suggestion (1)In the case of data absent to study EG indirectly we can suggest

that: • The dominant pattern of EG is the Transnational Group, which is

multinational. • The reasons and consequences of multinationals' activities closely

connected to FDI. • FDI is defined as investment made to acquire lasting interest in

enterprises operating outside of the economy of the investor. • FDI relationship consists of a parent enterprise and a Ukraine

affiliate which together form a multinational. • To study multinational strategies we can use all types of statistics

regarding the main foreign investors that could explain the motivation and tendencies of their policy.

Suggestion (2)

• Using available data we study actual strategies of EG in Ukraine.

• We revise the question:

Why do the multinationals invest in Ukraine and what are their strategies and FDI patterns?

Basic information and the retrospective (1)

International investmentposition of Ukraine

Liabilities, 100%

FDI, 30%

Portfolio investmens, 17%

OtherInvestment liabilities, 53%

The credits, 49,7%

Assets in % to liabilities 42%

Basic information and the retrospective (2) The main vectors of impact on large business in Ukraine

World transnational

groups

Russian penetration

Asian emerging economies

European integration

Large business in Ukraine

Basic information and the retrospective

FDI percentage by the types of activities, 2006

Rest15.2%

Education, health care, public and

individual services 1.4%

Real estate 9.3%

Financial activity10.8%

Non-financial services21.7%

Construction activity3.3%

Agriculture, forestry 2.2%

Industry36.1%

32,6

14,2

7,6 7,4 7,0 6,74,6 3,9 3,8

0,5

4,44,9

9,7 8,57,0

5,4

8,2

26,5

0

5

10

15

20

25

30

35

Germany Cy prus Austria United

Kingdom

Netherlands United

States

Russia France Virgin

Islands,

Britannic

in the begin 2006 in the begin 2007

Basic information and the retrospective (4)

FDI elasticity in Ukraine

0

0,5

1

1,5

2

2,5

3

3,5

2002 2003 2004 2005 2006

with respect to import with respect to GDP per capita

with respect to FDI in financial activity with respect to credits and loans from direct investors

with respect to FDI in trade activity with respect to FDI in industry

00.5

11.5

22.5

33.5

with respect to import

with respect to GDP per capita

with respect to FDI in financial activitywith respect to FDI in trade activity

with respect to FDI in industry

2004 2005 2006

The models

Variables   A database contains 87 countries, which significantly invested to

Ukraine during the year 2006. First, to explain FDI patterns into Ukraine we dispose of 10 exogenous

variables, 7 quantitative: export, import, volume of investment from Ukraine,

distance between the examined country and Ukraine, GDP of the per capita proper country, ratio of VAT rate of country-investor to Ukraine, ratio of corporate income tax rate.

3 binary variables: English-speaking countries, Russian-speaking countries and countries that are offshore.

Second, to explain the patterns both of production-oriented and distribution-oriented FDI

3 additional variables: consumer input export and import for sub-contract processing

and to precise new tendency 1 binary variable: FDI in financing. Finally, to precise directly the FDI strategies of developed economy

investors and to display indirectly the offshore strategy we have examined non-offshore only.

The models

Data sources   • The data on investment and import into Ukraine, export from Ukraine, offshore are collected by the State Statistics Committee of Ukraine.

• GDP per capita we calculated using Ukrainian and World Bank statistics.

• A tax ratio we took from KPMG's Corporate and Indirect Tax Rate Survey 2007.

• A distance from Ukraine was made with Internet calculator as the distance between the capitals.

The modelsTypes of models

• The generalized log linear model

• Qualitative model with logistic regression

• Bivariate ordinal probit model

)Distance(

)()1()Import1()1()(

1098)(7)(6)(5

4321

LogTaxeTVAIII

PIBLogInvLogLogExpLogIDELog

offshoreAnglaisRusse

The modelsThe generalized log linear model

Results (1):

The generalized log linear model

°significant at the level 10% , * at the level significant for 5%,** significant at the level 1%.• The transformation of VAT and tax variables in logarithm gives very

similar result.• Model is robust.• The FDI diminishes with the distance and the size of VAT, and

grows with the GDP and the investment from Ukraine.

Parameter Estimate t Value

Log(Distance) -0.852 -2.97*

Log(1+ Investment) 0.22 3.64**

Log(GDP) 0.929 4.22**

Log(VAT) -0.85 -1.79°

The models

Logistic regression

Y Volume of FDI, million USD

Number of countries

0 Less then 10 33

1 10-55 24

2 56-300 19

3 + 300 12

Results (2):

Logistic regression

Parameter Estimate Wald

Intercept 1 1.5656 9.51**(1%)

Intercept 2 3.4494 29.90***(0.1%)

Importation -0.000015 8.14**

Investment -0.00017 8.21**

Distance 0.000185 8.89**

GDP -1.3777 17.86***

Results (3):

Logistic regression

• Distance, investment and GDP: identical to the linear model.

• Import growths with FDI.

• The tax variable is not already significant.

• 83.3% of concordant pairs.

• The tests (Wald, score and coefficient of verisimilitude) are meaningful in the threshold size p <0,0001.

The models

Bivariate ordinal probit model • To define what characteristics of countries and import

are the most considerable in probability of more or less meaningful FDI.

• Bivariate model, which estimates the import and FDI simultaneously, allows checking endogeneity of import to FDI.

• It gives robust results, with respect to estimation of probabilities of FDI level.

• The FDI level can reflect the impact of unobserved characteristics too.

The modelsBivariate ordinal probit model

11* XZ

eZXY 22*

Y corresponds to the variable of FDI with 4 modalities

Z designates the variable of import

5000002

500000500001

000500

isimportif

andbetweenisimportif

iscountrytheforimportif

Z i

Results (4):

Bivariate ordinal probit model (equation of FDI)

Parameter Estimate t Value

Y. Z (import) 2.1001 10.63***

Y. Log (GDP) 0.4671 2.42*

Y. Tax -0.5530 -1.99*

Y. Russian -0.9024 -2.43*

Y. Offshore 1.4324 4.08***

Limit2.Y 0.8438 5.58***

Limit3.Y 1.6001 7.20***

Rho -0.8557 -3.59***

Results (5):

• The variable of import is endogenous.

• The unobserved factors can also explain FDI and import, for example:

- Public policy like any close ties between EG and the government.

- Family controlled EG.

- Bilateral relations, etc.

Complementary results (1)

• We input 3 new variables:

- export of semifinished goods for sub-contracts processing,

- import of semifinished goods for sub-contracts processing,

- investment in financial activity (in % of FDI for each country).

• The similar results are likely for the 10 variables (for each type of model). The tax variable is not significant in explaining FDI.

• The variables of export of semifinished goods for processing and investment financial are significant in explaining FDI.

Comparison of results, 2006

10 variables 13 variables

-4

-2

0

2

4GDP per capita

Distance

Vat ratio

Tax ratio

Russian speakingEnglish speaking

Offshore

Import

Investment from Ukraine

Import FDI

-4

-2

0

2

4GDP per capita

Distance

Vat ratio

Tax ratio

Russian speaking

English speaking

Offshore

Import

Investment from Ukraine

Import of customer input

Export of customer input

Finance activity

Import FDI

Subpopulations: offshore (23) and non-offshore (64)countries-investors

For offshore countries, there are not any explicative variables from the 10 and 13 variables. Only a variable of

finance is explicative with the positive meaning in the threshold of 10%.

0 5 10 15

limp

0

2

4

6

8

ln

y

Comparison of results, non-offshore, 2006

10 variables 13 variables

-1

0

1

2

3GDP per capita

Distance

VAT ratio

Tax ratio

Russian speaking

English speaking

Import

Investment from Ukraine

Import FDI

0

1

2

3GDP per capita

Distance

VAT ratio

Tax ratio

Russian speaking

English speaking Import

Investment from Ukraine

Import of customer input

Export of customer input

Finance activity

Import FDI

Findings (1)• The literature's benchmark distinction between horizontal and vertical FDI

does not capture the growing diversity of strategies the multinationals use, particular, in emerging economy.

• There is evidence of two subpopulations of the countries-investors: offshore and non-offshore. These two subpopulations behavior differently.

• The variable of GDP per capita looks not so much significant for FDI coming in the Ukraine.

• The variable of distance is significant at all for FDI. But it arises with negative sign for import.

• The VAT ratio explains weak FDI of non-offshore only. But it can explain the EG’ strategy to invest through the import.

• Production-oriented FDI consists of two patterns. One of them locates production in Ukraine because of low material and manual-labor cost (light industry). Another one makes outsourcing in Ukraine because of skilled-labor cost are low here (IT industry).

Findings (2)

• Offshore factor plays essential role as well as CIS countries’ EG prefer to realize IT outsourcing through the offshore companies.

• The variables of Russian and English speaking explain weakly EG strategy in Ukraine.

• There is evidence for relation between FDI, import and explicative variable of the investment from Ukraine. This variable does not explain FDI directly, but through the import. Obviously, it explains, fist of all, the FDI activity not foreign but domestic EGs, who invest in other countries to import then in Ukraine.

• The study did not confirm our suggestion about the production-oriented EGs importing a semi-finished input to future process. Instead of to import, EGs prefer to invest in order to export a semi-finished input to future process in the parent country.

• Beside evidence of vertical FDI, there is a new pattern mostly arising through mixes of vertical and horizontal FDI (diversification) in Russian and Ukraine EGs, what we refer to as diagonal FDI.

• A diagonal FDI pattern suggests an agglomeration of quite different activities with input of different types of production factors.

Horizontal and vertical integration in EG

NACE –

PRODCOM

NACE –

Technology

cycle

DN

Manufacturing of furniture

chairs and seats - 36.11

office and shop furniture – 36.12

kitchen furniture – 36.13

other furniture – 36.14

A 02 Logging and tree felling

DD 20 Manufacturing of wood and wood products

DN 36 Manufacturing of furniture

G 51, 52 Wholesale and retail trade

Diagonal integration in EG

NACE CB 13

Mining of metals ores

DF 23

Coke oven products

DJ 27 Basic metals and metal products

DK

Machinery and equipment

DA 15.96 Manufacture of beer

G 51.51

Wholesale of solid, liquid and gaseous fuels

H

Hotels and restaurants

J 65, 66

Financial intermediation

CB 13

Mining of metals ores

DF 23

Coke oven products

DJ 27 Basic metals and metal products

DK

Machinery and equipment

DA 15.96 Manufacture of beer

G 51.51

Wholesale of solid, liquid and gaseous fuels

H

Hotels and restaurants

J 65, 66

Financial intermediation

System Capital Management Group Structure (SCM), the head of group is situated in Donetsk. SCM has a controlling interest over 90 enterprises, for which 160 000 employers work.

The key business of SCM includes the following areas:

• Mining and metallurgical activity• Power energy activity • Financial activity • Additional activities

The largest companies of SCM:

• Metallurgical Company Azovstal • Еnakievо Metallurgical Works • Joint Enterprise LLC Metalen • Ferriera Valsider S.P.A. (Italy) • Khartsyzskiy Pipe Plant• OJSC Avdeevskiy Coke-Processing Works • Krasnodonugol• Northern Mining and Ore-Processing Plant • Central Mining and Ore-Processing Plant• Pavlogradugol • “Komsomolets Donbassa” Mine• Vostokenergo • Tekhrempostavka• Druzhkovskiy Machine Building Plant• Kaolin Production (3 enterprises)

• Dongorbank • First Ukrainian International Bank• Ukrainian Joint Stock Insurance

Company ASKA • Ukrainian Joint Stock Insurance

Company ASKA – LIFE

• Mobile Operator Life: LLC Astelit • Optima Telecom• Fixed-Communications operator PJSC Farlep-

Invest

• Druzhkovka Ore Management - refractory and fire-clays

• Vesco - refractory and fire-clays• Gefest – chain of gas stations

• Brewing Group “Sarmat”

• “Donbass Palace” Hotel

• Publishing Group “Segodnya” • TV and Radio Company “Ukraine”

• Football Club “Shakhter” (Donetsk)

Findings (3)

• In order to serve the financial flows there is always the banking structure in the centre of such group.

• The last explicative variable of finance activity is very significant for FDI of all population and for two subpopulations

• Ukraine is very attractive for financial activity as financial sector was not developed before.

• Financial and banking enterprises arise due either horizontal FDI from developed economies or diagonal FDI (diversification) of Ukrainian and especially Russian groups.

• Thanks to them, FDI is the source of different credits for businesses and consumers. The consumer credit system is quickly developing in trade and real estate.

The control of the kaolin production in the group System Capital Management, 2007

JSC SCM

SCM Limited

UMG Limited

JSC Ogneupornerud, 100%

JSC Druzhkovsk, 90.6%

JSC Vesko,93.9%

Sub - group 1,100%

Sub - group 2, 100%

The head of the group

Ukraine

Offshore

Conclusion• Indirect sources can be useful auxiliary information to study EG as a complex

phenomenon. It needs to define the unit of observation.

• The empirical findings acknowledge that despite Ukraine is very weak in business and investment freedom it becomes more and more attractive for FDI.

• Obtained results suggest a marked difference in the FDI patterns and their evolution. Multinationals act in Ukraine as production-oriented and distribution-oriented FDI with growing variety.

• These differences may be a source of both positive and adverse impacts on the Ukraine economy.

• Lastly, we found evidence of diversified business of domestic EG and coming from emerging countries with a financial intermediary in the group's core.

• We found statistically significant coefficients for some variables for their impact power on FDI strategies.

• FDI patterns in Ukraine depend on both endogenous and exogenous factors.

References (1)Altshuler, R., H. Grubert, and T.S. Newlon. (2001). Has U.S. Investment Abroad Become More Sensitive to Tax Rates? In J.R. Hines, ed., International Taxation and Multinational Activity, University of Chicago Press, forthcoming.Altshuler, R. and R.G. Hubbard. (2000). The Effects of the Tax Reform Act of 1986 on the Location of Assets in Financial Services Firms. NBER Working Paper No. 7903.Blonigen, B.A., Davies, R.B., Naughton, H.T., and Waddell, G.R. (2006).Spacey parents: Spatial

Autoregressive Patterns in Inbound IDE. Department of Economics, University of Oregon, Eugene, OR 97403-1285, USA.

Carr, D.L., J.R. Markusen, and K.E. Maskus. (2001). Estimating the Knowledge-Capital Model of the Multinational Enterprise. American Economic Review, 91 (3), June: 693-708.Castejon, C. F., Woerz, J. (2006). Good or bad? – The influence of IDE on productivity growth. An

industry-level analysis: University of Zaragoza, The Vienna Institute for International economic Studies, and Tinbergen Institute, Erasmus University Rotterdam

Défis posés à la statistique structurelle d’entreprises par l’existence et l’importance économique des groupes d’entreprises - version 1. 2005. INSEE.

Feenstra, R.C. and G.H. Hanson. (1996). Foreign Investment, Outsourcing and Relative Wages. InRobert C. Feenstra, Gene M. Grossman, and Douglas A. Irwin, eds., Political Economy of Trade Policy: Essays in Honor of Jagdish Bhagwati, Cambridge: MIT Press, pp. 89-127.Feenstra, R.C. and G.H. Hanson. (2001). Global Production and Rising Inequality: A Survey of Trade and Wages. Mimeo, UC Davis and University of Michigan.Feldstein, M., J. Hines, and R.G. Hubbard. (1995). The Effects of Taxation on Multinational Corporations. Chicago: University of Chicago Press.Hanson, G.H., Mataloni, R.J., Slaughter, M. J. (2001).Expansion strategies of U.S. Multinational firms.

Working Paper 8433. http: www.nber.org/papers/w8433Hanson, G.H. (2001). Should Countries Promote Foreign Direct Investment? G-24 Discussion Paper Series No. 9.Index of Economic Freedom. Ukraine. 2008. Heritage Foundation

http://www.heritage.org/research/features/index/country.cfm?id=UkraineKumar, A. (2007). Does Foreign Direct investment Help Emerging Economies? Economic Letter. Insights

from the Federal Reserve Bank of Dallas. Vol. 2, No.1.

References (2)Lafourcade, M., Paluzie, E. (2005). European Integration, IDE and the Internal Geography of Trade Evidence from Western-

European Border Regions: Universite d'Evry, Universitat de Baarcelona.Lipsey, R.E. (1999). The Role of IDE in International Capital Flows. In Martin Feldstein, ed., International Capital Flows, Chicago: University of Chicago Press, pp. 307-362.Lipsey, R.E. (2001). Foreign Direct Investment and the Operations of Multinational Firms. Mimeo, Queens University.Markusen, J.R. (2001). Multinational Firms and the Theory of International Trade. Cambridge, MA: MIT Press, forthcoming.Markusen, J.R. and K. Maskus. (2001). Multinational Firms: Reconciling Theory and Evidence. InMagnus Blomstrom and Linda S. Goldberg, Eds., Topics in Empirical Economics: A Festschrift in Honor of Robert E. Lipsey, Chicago and London: University of Chicago Press, 71-98.Markusen, J. and A. Venables. (1998). Multinational Firms and the New Trade Theory. Journal of International Economics 46: 183-203.Markusen, J. and A. Venables. (2000). The Theory of Endowment, Intra-Industry and Multinational Trade. Journal of International Economics 52: 209-234.Markusen, J.R., A.J. Venables, D.B. Konan, and K. Zhang. (1996). “A Unified Treatment of Horizontal Direct Investment, Vertical Direct Investment, and the Pattern of Trade in Goods and Services.” NBER Working Paper No. 5696.Moran, T.H. (2001). Parental Supervision: The New Paradigm for Foreign Direct Investment and Development. Washington, D.C.: Institute for International Economics, forthcoming.Slaughter, M.J. (2001). International Trade and Labor-Demand Elasticities. Journal of International Economics, 54: 27-56.Shatz, H. and Venables, A. J. (2000). The Geography of International Investment. In Gordon L.Statistiques Structurelles fondées sur les groupes d’entreprises. (2006). CNIS.The OECD Guidelines for Multinational Enterprises. Revision (2000). http://www.oecd.org/document/28/0.2340.en UNCTAD, World Investment Report (2007) . www.unctad.org/wir or www.unctad.org/IDEstatistics .Vasechko, O.O. (2007). Developing Statistics of Enterprise Groups in Ukraine: Methodological aspects. Statistics of Ukraine

No 4. Yeaple, S.R. (1999). The Determinants of U.S. Outward Foreign Direct Investment: Market Access versus Comparative Advantage. Mimeo, University of Wisconsin.

Thank you