NESC - Growth Poverty Income Inequality FINAL …s3.amazonaws.com/zanran_storage/ · combinations of growth and distribution policies. • Economic growth does not consistently affect

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Kenya Institute for Public Policy Research and Analysis

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May 2009

A project of the Kenya Institute for Public Policy Research and Analysis in conjunction with the National Economic and Social Council, United Nations Development Program and the Royal Danish Embassy

Anthony Wambugu Boaz Munga

Poverty, growth and income inequality in Kenya: Suggested policy options

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List of Abbreviations & Acronyms AfDB African Development Bank AFC Agricultural Finance Corporation AIDS Acquired Immunodeficiency Syndrome ASAL Arid and Semi Arid Lands CBN cost of basic needs CBS Central Bureau of Statistics CDF Constituency Development Fund CDP Community Development Programme CDTF Community Development Trust Fund CEF Community Environment Facility CIDA Canadian International Development agency DDC District Development Committee DFID Department for International Development DFRD District Focus for Rural Development DPEC District Poverty Eradication Committee ERSWC Economic Recovery Strategy for Wealth and Employment Creation EC European Commission EDF European Development Fund ERS Economic Recovery Strategy EU European Union FAO Food and Agriculture Organization FDSE Free Day Secondary Education FEI food-energy-intake FGT Foster-Greer-Thorbecke FPE Free Primary Education GDP Gross Domestic Product GEF Global Environment Facility GJLOS Governance, Justice, Law and Order Sector GoK Government of Kenya GTZ Deutsche Gesellschaft fur Technische Zusammenarbeit HDI Human Development Index HIV Human Immunodeficiency Virus HPI Human Poverty Index HRD Human Resource Development ICT Information Communication Technology IDRC International Development Research Center IFAD International Fund for Agricultural Development IFC International Finance Corporation IFPRI International Food Policy Research Institute IIRR International Institute of Rural Reconstruction ILO International Labour Organization IMF International Monetary Fund JBIC Japan Bank for International Cooperation


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JICA Japan International Cooperation Agency KESSP Kenya Education Sector Support Programme KIA Kenya Investment Authority KIE Kenya Industrial Estate KIHBS Kenya Integrated Household Budget Survey KIPPRA Kenya institute for Public Policy Research and Analysis KJAS Kenya Joint Assistance Strategy KMC Kenya Meat Commission KNBS Kenya National Bureau of Statistics K-REP Kenya Rural Enterprise Programme KWFT Kenya Women Finance Trust LATF Local Authority Transfer Fund LDC Less Developed Country MAPSKID Master Plan for Kenya’s Industrial Development M&E Monitoring and Evaluation MDG Millennium Development Goals MFI Micro-Finance Institution MSE Medium and Small Enterprise MTP Medium Term Plan NES National Exports Strategy NORAD Norwegian Agency for Development Cooperation OPEC Organization of the Petroleum Exporting Countries PEC Poverty Eradication Commission PGI Poverty-growth-inequality triangle PPP Purchasing Power Parity PSDS Private Sector Development Strategy REPLF Rural Electrification Programme Levy Fund RMLF Road Maintenance Levy Fund SID Society for International Development SIDA Swedish International Development Agency SNV Netherlands Development Organization SRA Strategy for Revitalizing Agriculture UK United Kingdom UN United Nations UNDP United Nations Development Programme UNECA United Nations Economic Commission for Africa UNFPA United Nations Population Fund UNIDO United Nations Industrial Development Organization US/USA United States/United States of America USAID United States Agency for International Development WB World Bank WFP World Food Programme WMS I Welfare Monitoring Survey I WMS II Welfare Monitoring Survey II WMS III Welfare Monitoring Survey III


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Table of Contents List of Abbreviations & Acronyms i Acknowledgements vi Executive Summary vii 1 Introduction 1

1.1 Objectives of the study 2 1.2 Outline of the paper 2

2 Economic Growth in Kenya 4 3 Poverty Situation in Kenya 6

3.1 Key concepts in poverty measurement 6 3.2 Poverty in Kenya 8 3.3 Poverty as capability deprivation 12

4 Income Inequality in Kenya 15

4.1 Measurement of income inequality 15 4.2 Estimates of income inequality in Kenya 18

5 Growth and Income Inequality 23

5.1 Impact of growth on income inequality 23 5.2 Impact of income inequality on growth 24

6 Growth and Poverty Reduction 29 7 Current Poverty Alleviation Initiatives 35

7.1 Government of Kenya initiatives 35 7.2 Initiatives by other stakeholders 46

8 Summary and conclusion 49

8.1 Summary 49 8.2 Addressing poverty and inequality 51


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References 54 Appendices 60


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Acknowledgements We are grateful to the National Social and Economic Council (NESC) Secretariat for commissioning the study and to its members for providing valuable comments during the presentation and discussion of the draft reports. We also wish to thank KIPPRA staff for providing very useful comments during the process of writing the paper. This paper is deeply indebted to the Danish Embassy and United Nations Development Programme (UNDP) – Kenya for their financial support. The authors alone bear the responsibility for the views expressed in this paper and any errors.


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Executive Summary The situation

• Poverty remains a major concern of development policy in Africa and other developing regions including Kenya. In 2005, it was estimated that 45.9% of Kenyans were poor (KNBS, 2007). Previously the percentage of the poor increased to about 52.9% (rural) and 49.2% (urban) in 1997 up from 46% (rural) and 29.3% (urban) in 1992. The overall poverty was estimated at 56% (51.5% urban and 59.6% rural) in 2000.

• Regional poverty estimates for Kenya reveal that poverty varies widely by region and its incidence is particularly high in semi-arid areas of the country. Overall, the Kenyan poor are disproportionately found in: rural areas; households headed by widows and less educated persons; large households; and certain types of occupations - such as subsistence farmers, unskilled public and private sector workers and unpaid family workers. Some of the reasons put forward for high poverty rates in Kenya include: lack of income earning opportunities; inadequate human capital investments; unfavorable agro-climatic conditions, HIV-AIDS pandemic and weak implementation of antipoverty interventions.

• Economic growth is important for poverty reduction; however, the concern is that it may not do so substantially. For growth to impact on poverty substantially, it has to be sustained at relatively high levels. UNECA (1999) for instance estimated that for African countries to reduce poverty by half by 2015, they need to attain and sustain a GDP growth rate of 8.0% p.a. starting from 2000. Kenya is yet to attain and sustain such high rates of growth despite the post 2003 recovery in economic growth.

• In Kenya, the 1966-2003 period was generally marked by declining economic growth. Growth averaged 7.2% in 1966-70; 4.9% in 1971-80; 4.3% in 1981-90; 2.1% in 1991-2000 and 4.2% in 2001-06.

• Income inequality measures for Kenya, as measured by the Gini coefficient, suggest that income inequality has all along been relatively high but has not been increasing. Understanding the sources or causes of inequality and its relationships with poverty is crucial in formulating appropriate policy responses.

• Kenya has numerous policy, regulatory and operational initiatives by government and other stakeholders to address growth, poverty and income inequality. Some of the government’s policy and operational initiatives include: the use of devolved funds, Youth Enterprise Development Fund, and the Women Enterprise Development Fund. Some of the broad groups of other stakeholders involved in addressing poverty include: multilateral organizations, bilateral partners, and CSOs.


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The relationships between growth poverty and inequality

• Although economic growth and poverty reduction move together, the response of poverty to growth varies across countries. The emerging view is that reduction of absolute poverty requires strong, country specific combinations of growth and distribution policies.

• Economic growth does not consistently affect inequality one way or the other. Income inequality may decline with economic growth or change little with growth. On the other hand, even though economic theory is inconclusive, empirical work points towards a negative impact of inequality on growth. High initial inequality in assets and income is likely to undermine growth and hence poverty reduction efforts.

• The implication of these relationships is that economic growth is necessary but not sufficient for poverty reduction. Poverty reduction requires economies to address inequality and economic structures - in addition to sustaining high levels of economic growth.

Conclusions and suggested policy interventions

• There is need to accelerate and sustain economic growth in Kenya. Countries that managed to reduce poverty substantially, e.g. China, had high rates of economic growth. However; poverty alleviation efforts are more successful when accompanied by not only growth policies but also distributional policies that reduce inequality.

• The government should remove factor price distortions in markets. Improvement in the functioning of markets for farm inputs can contribute to higher farm incomes to poor farmers and employment opportunities for those without land. Because the poor participate in multiple markets, better linkages between markets can improve their participation.

• Pro-poor growth should focus on the activities in which the poor participate directly. Studies in Kenya show that the poor are mainly engaged in agricultural activities and informal sector activities in rural and urban areas respectively.

• Redistribution of asset ownership/user rights. An institutional framework to lay out conditions for land ownership and land use, such as leasehold contracts or share tenancy contracts is required. There is need to implement policies to check income inequality and poverty by the use of progressive income and wealth taxation.

• Use of public transfers, goods and services. Increased investment in human capital through provision of basic social services can generate relatively


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higher returns for the poor than the non-poor, because of relative scarcity of human capital stocks.

• Empowering the poor. Since economic decisions are related to the power balance, it is essential for the poor to be fully accommodated in decision-making. This will not only enable them articulate their needs but also enhance ownership of projects and programmes meant to improve their welfare.

• Encourage development of insurance mechanisms for the poor. While risk and uncertainty are pervasive in many economic and social settings, the poor often have limited capacity to handle shocks (health, economic) and natural calamities. Consequently, poverty eradication initiatives should include mechanisms to build the capacity of the poor to handle shocks. For example, improved storage of grain on the farm can improve food security to smooth consumption.

• Conduct research to inform policy design and implementation. There is relatively little empirical evidence on growth and poverty relationship. A research agenda should be developed on this topic to bring about deeper understanding of the link between poverty, economic growth and income inequality in Kenya.

• A key question regards where to focus development policy i.e. whether a country should place more focus on economic growth, or poverty and/or inequality. In this respect, the argument by Bourguignon (2004) is compelling. He points out that: (i) the rapid elimination of absolute poverty, under all forms, is a meaningful goal for development; and (ii) to reduce absolute poverty rapidly requires strong, country-specific combinations of growth and distribution policies. To be efficient and growth-enhancing, redistribution should be concerned with wealth rather than current income of consumption expenditures. This efficient redistribution can be achieved by correcting credit markets imperfections, lowering the tax rate, or freeing other distortionary income redistribution mechanisms.


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1 Introduction Poverty remains a major concern of development policy in Africa and other developing regions. However, poverty in Africa is substantially higher, chronic and rising (UNECA, 2005). In view of the social costs associated with poverty, poverty reduction is an important goal for development policy. This is evidenced by the attention poverty is receiving in international development debate. For example, two recent World Development Reports (World Bank, 1990; 2001), focused on poverty. Further, in the year 2000, leaders from 189 countries endorsed a set of Millennium Development Goals (MDGs) to be achieved by 2015, one of which was to ‘halve’ the number of people living in absolute income povertyrlative to the 1990 levels. To achieve the goal, it is estimated that African countries must attain a GDP growth rate of at least 8 per cent per annum.

In Kenya, the government identified poverty as a major problem soon after independence (GOK, 1965) and many policies, programmes and projects have been designed and implemented with the aim of poverty alleviation. The development strategies that the country pursued aimed at poverty reduction, placed emphasis on income growth, job creation and provision of basic social services. However, poverty continues to afflict a large segment of the Kenyan population. It is estimated from the latest Household Budget Survey that 45.9 per cent of the population lives below the poverty line (KNBS, 2007), and this percentage is likely to have increased due to post-election violence. Approximately 49.1 per cent of the population in rural areas and 33.7 per cent in urban areas were poor in 2005 (KNBS, 2007). The high poverty incidence in Kenya poses a major development challenge.

In recent years, there has been intense debate about pro-poor growth, which is an attempt to examine the extent of gains to the poor from economic growth. While it is widely agreed that economic growth is critical for poverty reduction, the response of poverty to economic growth differs across countries. Three reasons are advanced for the lack of response of poverty to economic growth in Africa (UNECA, 2005). First, the rates of growth so far achieved are inadequate to make a noticeable contribution to poverty reduction. Second, the growth sectors have low labour absorption capacity and; third there is inequality in the distribution of opportunities generated by economic growth.

Poverty reduction in a particular country is a function of the changes in average income and distribution of income. However, this raises important questions for policy on what should be the correct balance between pro-growth and pro-distribution interventions in a poverty reduction strategy (Lopez, 2004). First, should a poverty reduction strategy have a growth bias or concentrate on


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empowering the poor to benefit from growth? Second, is inequality affected as a general rule by growth? Third, does lowering inequality promote or hinder economic growth? Finally, how does the level of initial inequality affect the impact of growth on poverty reduction?

In this context, drawing on a survey of previous literature on Kenya and other parts of the developing world, this paper takes up the following questions about growth, poverty and income inequality in Kenya. What is the extent of poverty and inequality in Kenya? What are the characteristics of the poor in Kenya? What has been the trend in growth, poverty and income inequality? What are the current poverty alleviation initiatives? What are the key findings in the literature on growth, poverty and income inequality? How successful have the various initiatives aimed at reducing poverty and inequality been? What steps can be taken to increase their effectiveness?

1.1 Objectives of the study

The main objective of the study is to review the poverty and income inequality situation in Kenya, and the strategies and initiatives aimed at poverty reduction, and also suggest topics that require further investigation. The specific objectives are:

a) To review the trend in economic growth in Kenya since independence.

b) To review the poverty situation in Kenya.

c) To review the income inequality situation in Kenya.

d) To review previous literature on the relationship between economic growth, poverty, and income inequality.

e) To review poverty alleviation efforts in Kenya.

f) To draw policy lessons and suggest areas for further investigation.

1.2 Outline of the paper

The rest of the paper is organized as follows. Section 2 presents the trend in economic growth in Kenya since independence. The trend in poverty in Kenya over the period 1990-2005 is presented in Section 3, while in Section 4, the trend in income inequality is discussed. Section 5 reviews literature on growth and income inequality whereas Section 6 presents a review on poverty-growth-inequality link. Section 7, provides a review of recent poverty alleviation initiatives in Kenya and Section 8 provides a summary and conclusion.


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2 Economic Growth in Kenya Achieving pro-poor economic growth is a major challenge for Africa and the developing world. Over the past few years, there has been intense debate among researchers and policy makers about the meaning of pro-poor growth and its elements (Lopez, 2004). Given the central position of growth in poverty reduction efforts, this section presents the trend of Kenya’s economic growth since independence. Although growth is a major factor in poverty reduction, there is concern that growth may be inadequate to reduce poverty substantially, hence the need to accelerate growth.

Table 2.1 provides an illustrative summary of growth rates achieved in Kenya since independence. The table shows that growth has been declining over time until the year 2000, before picking up in the first half of 2000s. It is important to note that between 1966 and 2006, Kenya achieved an economic growth rate of about 6 per cent and above in only 6 years out of the 40 years - with all the six years falling within the period of 1960s and 1970s. For the remaining 34 years, economic growth rate was below 6 per cent. And for the first time since 1978, the economy registered a growth rate of 6.1 per cent in 2006 (GOK, 2008). This table highlights two points. First, it seems that it is not easy to attain and sustain a high economic growth rate. Whenever Kenya attains a relatively high economic growth rate, it is not sustained over time.

Table 2.1: Growth rates achieved by Kenya since independence (%)

Period Average growth rate

Lowest growth rate for the period

Highest growth rate for the period

1966- 1970 7.2 3.12 12.84

1971- 1980 4.9 2.90 8.13

1981- 1990 4.3 0.35 5.97

1991- 2000 2.1 -0.33 4.82

2001- 2006 4.2 0.60 6.10

Source: Economic Survey, various issues

Second, the growth rates recorded since 2000 are below the level of growth required to ensure substantial gains in poverty reduction. UNECA (1999) estimated that for African countries to reduce poverty by half by 2015, they need to attain and sustain a GDP growth rate of 8.0 per cent per annum starting from the year 2000. The average growth rate for Kenya between


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2001-2006 is 3.8 per cent. This has been increasing and if the same effort is maintained, the country could move towards 7 per cent. However, it is important to note that attaining growth rate of 8 per cent will require greater effort if the targeted reduction in poverty by 2015 is to be achieved. Kenya’s Vision 2030 proposes to accelerate and sustain a 10 per cent growth rate for the next 22 years. With the data showing that Kenya attained a growth rate greater than 10 per cent in 1966, this means it can be done.

However, there are indications that even the periods 1960s and 1970s when Kenya achieved relatively high levels of economic growth did not translate into substantial reduction in poverty. This suggests that growth is necessary but not by itself sufficient. Therefore, there is need to address other issues such as income inequality and economic structures for growth to effectively address the problem of poverty.


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3 Poverty Situation in Kenya 3.1 Key concepts in poverty measurement

Poverty refers to whether individuals or households have adequate resources or ability to attain a predetermined minimum level of consumption at which basic needs of a society or country are assumed to be satisfied. The formulation of appropriate programmes to effectively combat poverty requires proper identification of the poor. For income poverty, this requires the estimation of a poverty line and construction of indices for the level, inequality and intensity of poverty. Individuals or households falling below the poverty line are considered poor. However, the poor are not a homogeneous group. Therefore, no single programme or policy can adequately address the various dimensions of poverty. This section presents key poverty concepts and reviews the extent of poverty situation in Kenya and the characteristics of the poor.

The poverty line is defined as the minimum level of consumption at which basic needs are assumed to be satisfied. Two methods commonly used to derive poverty lines are the cost of basic needs (CBN) and the food-energy-intake (FEI) methods (Ravallion, 1994; Lipton and Ravallion, 1995). These two methods have previously been used to derive poverty lines for Kenya (Greer and Thorbecke, 1986; Republic of Kenya, 1994; and Mwabu et al., 2000). The food poverty line is used to identify the food poor while the overall poverty line identifies the absolutely poor. Absolute poverty measures are preferred in the context of developing countries where majority of the people live below subsistence level because, in such circumstances, one should be concerned with looking into the situation of those in absolute deprivation rather than with the relative deprivation.

Absolute poverty specifies the level of absolute deprivation on the basis of norms, which identify the minimum requirements of food and non-food items considered adequate to satisfy the minimum basic needs. The minimum food requirement is based on minimum nutrition requirements (calories) for healthy growth and maintenance of human body. To derive the food poverty line, most studies (Republic of Kenya, 1998; Mwabu et al., 2000; KNBS, 2007) use the FAO minimum recommended daily average calorie intake of 2,250 calories per adult equivalent. Food poverty line is the amount of expenditure required to meet the recommended daily average calorie intake given the agreed food basket. A household whose food expenditure is below the food poverty line is considered food poor. Overall, poverty line encompasses the food and non-food items consumed by households falling in the band of a certain percentage of the food poverty line. The hardcore poor are defined as those who would not meet their minimum calorie requirement even if they concentrated all their


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spending on food. For certain policy purposes, what matters is not the precise location of the poverty line, but rather the poverty comparisons across dates, sub-groups and regions. The main point in poverty comparisons is that comparisons should be consistent so that two individuals who enjoy the same standard of living should not be at different levels of poverty (Lipton and Ravallion, 1995). The core and key measures of poverty encountered in the literature are absolute poverty measures as opposed to relative poverty measures, both of which can be expressed in money metrics.1

A poverty measure is an aggregate indicator of a poverty dimension. The FGT poverty measure developed by Foster, Greer and Thorbecke (1984) quantifies three poverty dimensions, namely; incidence, depth and severity of poverty. It facilitates presentation of information on poverty in an operationally convenient manner. The first measure of poverty according to the FGT is the headcount ratio (P�=0), which indicates the proportion of individuals (or households) below the poverty line, that is the poor expressed as a proportion of the total population. The incidence of poverty, however, does not indicate how far below the poverty line the poor are. The second measure is the poverty gap or average income shortfall (P�=1), which gives the proportional shortfall of the average poor person from the poverty line. It can give an estimate of the resources that would be required to bring the expenditure of every poor person up to the poverty line, thereby eradicating poverty. The poverty gap is, however, insensitive to the effect of income redistribution among the poor on poverty. The third measure that overcomes this problem is the severity of poverty (P�=2). This measure reflects the degree of inequality among the poor.

A poverty profile is a special case of poverty comparison, showing how poverty differs across sub-groups of society, such as region of residence or sector of employment (Ravallion, 1994). Presentation of poverty profiles follows two formats. The first format reports poverty measures (poverty incidence, inequality and intensity) for each sub-group identified by a characteristic such as area of residence. The second format gives the incidence of characteristics (education and family size) amongst sub-groups defined in terms of poverty status, such as poor and non-poor (Ravallion, 1994).

1 A broad based poverty, which includes non-monetary dimensions such as powerlessness, voicelessness, risk and vulnerability, cannot be as easily aggregated as is done with income poverty. This multidimensional poverty is also amenable to a wide range of policy instruments (World Bank, 2000a)


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3.2 Poverty in Kenya

Poverty in Kenya has attracted increased research attention since 1990 from individual academic researchers, donors and the government. Intensification of poverty analyses coincided with the World Development Report (World Bank, 1990) on poverty and enhanced household data collection efforts by the then Central Bureau of Statistics in 1992, 1994, 1997 and 2005. Various estimates from these research efforts provide an account of recent poverty trends in the country. Table 3.1 provides estimates of the incidence of poverty for Kenya between 1990 and 2006 as derived from previous studies. The number of the poor increased to about 52.9 per cent of the rural population and 49.2 per cent of the urban population in 1997 up from 46.0 per cent for rural and 29.3 per cent for urban households in 1992. Estimates for 2000 show that poverty had increased further to 56 per cent, with 51.5 per cent of the urban population and 59.6 per cent of the rural population being poor (Mwabu et al., 2002). However, poverty estimates for 2005/2006 show that there has been a general reduction in poverty since the early 2000s with overall poverty declining from 56.0 per cent to 45.9 per cent. Poverty reduction was experienced in both the urban and rural areas. However, it is likely that the poverty situation was adversely affected by post-election violence.


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Table 3.1: Summary of poverty estimates for Kenya, 1990 to 2006

Author Reference Year

Data Source Poverty Incidence

Mukui (1993) 1992 1992 WMSI Rural: 46% for 1992 Urban: 29.3 % for 1992

Republic of Kenya (1998)

1994 1994 WMS I 46.8% rural population 29% urban population 40% national estimates

Mwabu et al. (2000)

1994 1994 WMS II 39.7% rural population 28.9% urban population 38.8% national population

Republic of Kenya (2000) results for WMS III

1997 1997 WMS III 52.9% rural population 49.2% urban population 52.3% national population

Mwabu et al. (2002)

2000 Predictions based on GDP and Gini coefficients and poverty estimates for 1997 using WMS III

59.6% rural population 51.5% urban population 56.8% national population

KNBS (2007) 2005/2006 KIHBS 49.1% rural population 33.7% urban population 45.9% national population

Source: Economic Survey 1994, 1997; Mwabu et al., 2000 and Kimalu et al., 2002. Na = not available.

Republic of Kenya, 2007: and, KNBS, 2007

Table 3.2 provides national and regional absolute poverty measures in Kenya. Substantial regional differences in the incidence of poverty exist in Kenya. About half of the rural population and between 29 to 50 per cent of the urban population were poor in the 1990s and 2000s. Rural poverty is marked by its common connection to agriculture and land, whereas urban poverty is more heterogeneous in how incomes are generated. The rural poor depend very much on agriculture than the non-poor (Quibria and Srinivasan, 1991; Reardon et al., 1992). Also, the few non-farm activities in the rural areas derive their


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prosperity on forward and backward production linkages with agriculture. Poverty in the rural areas tends to be explained more by low access to physical assets (particularly land), low agricultural productivity, inadequate non-farm employment opportunities, and low access to healthcare and schooling while labour market distortions tend to explain poverty in the urban areas.

There are large disparities in rural poverty incidence in Kenya (CBS, 2003; KNBS, 2007). Regional disparities in the incidence of rural poverty are strongly associated with rainfall and dependence on rain fed agriculture (Webb et al., 1991). Poverty incidence is high in arid and semi-arid areas of the country (Republic of Kenya, 1998; CBS, 2003; KNBS, 2007).

Previous studies (Ravallion, 1996; van de Walle, 1995; Wodon, 1995; and, Jalan and Ravallion, 1995) suggest two sets of determinants of geographic concentration of poverty. The first set is based on individualistic model in which poverty arises from low household-level endowment of privately held productive resources such as human capital. In this case, poor areas exist because people with poor endowments tend to live together. The second set of determinants is based on a geographical model in which individual poverty depends heavily on geographic capacity and mobility is limited.


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Table 3.2: Overall poverty estimates in Kenya, 1981-2005

Region Percent of the poor 1981/82 1992 1994a 1994b 1997 2000 (est.) 2005/2006

Central Coast Eastern Rift Valley North Eastern Nyanza Western Nairobi

25.7 54.6 47.7 51.1 Na

57.9 53.8 Na

35.9 43.5 42.2 51.5 Na

47.4 54.2 26.5

31.9 55.6 57.8 42.9 58.0 42.2 53.8 25.9

31.79 41.36 44.96 38.31 51.33 38.31 40.58 22.30

31.4 62.1 58.6 50.1

- 63.1 58.8 50.2

32.3* 69.9* 65.9* 73.1*

- 71.0* 56.4* 52.6*

30.4 69.7 50.9 49.0 73.9 47.6 52.2 21.3

Rural Urban National

48.8 Na

46.8

46.3 29.3 46.3

46.8 28.9 46.8

39.70 28.63 38.80

52.9 49.2 52.3

59.6 51.5 56.8

49.1 33.7 45.9

Source: Economic Survey, 1994 and 1997; Mwabu et al., 2000 and Kimalu et al., 2002. Na = not available.

* Rural poverty estimates for provinces (see Mwabu et al., 2002), Republic of Kenya (2007)

In this case the marginal returns to a level of schooling or loan amount depend on the geographical area of residence. Limited factor mobility leads to persistent geographical differences. The relevant geographic factors include local agro-climatic conditions, local physical infrastructure, access to social services and the stock of shared local knowledge about agro-climatic conditions and technologies appropriate to those conditions. If the model is right, then the policies called for entail either public investment in geographical capital or (under certain conditions) pro-active efforts to encourage migration. However, the individualist model begs the questions of why individual endowments differ persistently and why residential differentiation. The geographic model begs the questions why common endowments differ, and why mobility is restricted. Nevertheless, knowing which model dominates is very important for anti-poverty policy formulation.

A poverty indicator is an index of the level of poverty while a poverty determinant is a cause of variation of poverty (Manda, Kimenyi and Mwabu, 2001). Previous studies on poverty in Kenya emphasize different poverty determinants that include: economic growth, income inequality, inequality in access to productive resources such as land, natural shocks (e.g. droughts, floods and fire), rural-urban migration, poor implementation of development programmes, lack of effective social security policies and safety nets, and heavy disease burden (Manda, Kimenyi and Mwabu, 2001).


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In addition to knowledge about the extent of poverty, formulation of effective poverty alleviation policies and programmes also require knowledge about the characteristics of the poor (Manda, Kimenyi and Mwabu, 2001). The poor are disproportionately found in: rural Kenya, households headed by less educated persons, large households, certain occupations such as small scale farming, unskilled public and private sector workers, unpaid family workers, households headed by widows and women in polygamous households. In addition, the poor in Kenya are less likely to report health problems or to seek treatment compared to the non-poor. Long distances to health facilities and long waiting times (which has opportunity cost) limits access to health services by the poor. Furthermore, recent evidence also indicates that poverty level employment is rampant in Kenya. Using data from the Integrated Household Budget Survey – 2005/06, Pollin et al., (2007) notes that Kenyans who work for 40 hours or more per week have a high chance (nearly 50%) of being poor due to low wages and low earnings.

Apart from the above characteristics, there are also environmental characteristics correlated with poverty, which can provide strong indications about the standard of living. In areas where the incidence of poverty is high, rivers, ponds and lakes are major sources of drinking water. In addition, a large proportion of rural residents have limited or no access to safe drinking water and proper sanitation. Firewood is the main source of energy for many poor households in rural areas while kerosene is their main source of lighting. In urban areas, charcoal and Kerosene are the main energy sources for the poor.

As noted earlier, a large proportion of the poor are in agricultural production. However, data shows that, on average, the poor cultivate less land than the non-poor. Furthermore, output per acre for the non-poor is substantially higher than that of the poor. This can partly be attributed to differences in quantity and quality of inputs. For example, in 1997, the poor spent a third of the amount the non-poor spent on farm inputs.

3.3 Poverty as capability deprivation

Although income or expenditure based measures of poverty are very useful in poverty analysis, they do not capture all the differences in individual and social characteristics that determine well-being. For example, different individuals may have different capabilities to translate income into well-being depending on circumstances. A capability is a person’s potential functioning. A functioning is what a person is able to be or to do, for example, being well nourished, being able to read and write, being healthy, and being able to


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participate in community activities, labour market and so on. For example, if a woman has monetary income but is unable to buy food for her family because of gender discrimination, she lacks the capability to achieve a basic functioning for life.

Sen (1985) suggests that poverty should be viewed as capability deprivation-failure of some basic capabilities to function. Poverty in this sense means that an individual lacks the opportunity to achieve a minimum level of capability for human, physical, and intellectual functioning. Thus if an individual or group of individuals is excluded from social and economic life due to some handicap or social barriers they are considered poor. Poverty is, therefore, a multidimensional phenomenon with income being only one of the means of attaining individual capabilities. According to this approach, normative evaluations should focus on what people are able to be and to do, and not on what they can consume, or on their incomes. The latter are only the means of well-being, whereas evaluations and judgments should focus on those things that matter intrinsically, that is, on a person’s capabilities.

This approach is closely related with the human development index (HDI). The HDI provides a composite measure of three dimensions of human development: living a long and healthy life (measured by life expectancy), being educated (measured by adult literacy and enrolment at the primary, secondary and tertiary level) and having a decent standard of living (measured by purchasing power parity, PPP, and income). The index is not in any sense a comprehensive measure of human development. It does not, for example, include important indicators such as gender or income inequality and more difficult to measure indicators like respect for human rights and political freedoms. What it does provide is a broadened prism for viewing human progress and the complex relationship between income and well-being.2 In 2005, the HDI for Kenya was 0.521, which gave the country a rank of 148th out of 177 countries with data. Further, the Human Poverty Index (HPI) for developing countries focuses on the proportion of people below a threshold level in the same dimensions of human development as the HDI - living a long and healthy life, having access to education, and a decent standard of living. It is a multi-dimensional poverty measure. The HPI value of 30.8 in 2005 for Kenya ranks 60th among 108 developing countries.

2 http://hdrstats.undp.org/countries/country_fact_sheets/cty_fs_KEN.html


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4 Income Inequality in Kenya It is now widely recognized that economic growth on its own might not bring about reduction in absolute poverty. The reason is that economic growth might increase, decrease or have no effect on income inequality, which has a bearing on the degree of reduction in absolute poverty. In this section, we examine the extent of income inequality in Kenya, but first we discuss key concepts used in the measurement of income inequality.

4.1 Measurement of income inequality

The term inequality is used in a variety of ways. However, the literature on growth and poverty focuses on inequality in the distribution of income. Income inequality is a relative term, which indicates the extent to which distribution of income in an economy differs from that of equal shares among the population. It is concerned with variations in standards of living in the whole population. In contrast, as indicated earlier, poverty focuses only on those whose standards of living fall below a given threshold - the poverty line. Discussions of inequality focus mainly on the more easily observed inequalities in outcomes such as income, wealth, employment and education.

Inequality in outcomes can partially be accounted for by the normal functioning of the market economy, which determines, for example, participation in the labour market. However, a substantial component of inequality in people’s circumstances may reflect differences in opportunities, which varies with region of residence, parental circumstances, and gender. An understanding of the sources or causes of inequality is crucial in formulating appropriate policy responses.

The personal or size distribution of income is commonly used to quantify income inequality. It is concerned with the total incomes that individuals or households receive. The income gap between the rich and the poor is the most visible and widely discussed form of inequality. This gap is characterized by one segment of the population having a disproportionately large share of income than other segments of that population. This gives rise to differences in lifestyles and standards of living in a society.

Personal or household incomes (consumption expenditure) are arranged by ascending order and then the total population is divided into groups to determine the proportion of income that goes to various groups. The population may be divided into deciles (tenths) or quintiles (fifths), For example, the top quintile (decile) represents the 20 per cent (10%) of the population households’ with the highest income (consumption), and the


14

bottom quintile (decile) represents the 20 per cent (10%) of the population with the lowest income (consumption).

The common approach used to analyze the distribution of income is to compute the Gini coefficient based on the Lorenz curve. To construct the Lorenz curve, the cumulative percentages of income are plotted on the horizontal axis while the cumulative share of total income received by each percentage of the population is plotted on the vertical axis. Along the diagonal line, the percentage of income received is equal to the percentage of income recipients. This is the line of equality in the distribution of income. For example, the top (bottom) 10 per cent of the population receives 10 per cent of the income.


15

Figure 4.1: The Lorenz Curve

The shape of the Lorenz curve can be used as an indicator of the extent of income inequality. The more it curves away from the line of equality the greater the income inequality. The Gini coefficient is computed as the area between the Lorenz curve and the line of equality. Given the Lorenz curve, the Gini (G) is )( BAAG += (see figure 4.1). In a situation of complete equality in the distribution of income the Lorenz curve coincides with the 450 line, that is, the line of complete equality and 0=G . With total inequality (i.e. one household or percentile having all the income), area B disappears and 1=G . Gini values closer to one indicate greater income inequality.3

A drawback of the Gini coefficient is that it varies when the income distribution varies (due to an income transfer) regardless of whether the change occurs among the rich, the poor or between the rich and the poor. If society’s concern is about the share of income of the poor, a better indicator may be a direct measure, such as the income or consumption share of, say, the poorest 10 or 20 per cent.

3 G is mainly used to assess inequality in income and consumption although it can also be used for other dimensions, including assets, education, and malnutrition.

A

B

Percent of income

Perc

ent o

f pop

ulat

ion


16

4.2 Estimates of income inequality in Kenya

While measures of poverty summarize income or expenditure for those below a poverty line, income inequality measures are concerned with the entire income or expenditure distribution. Table 4.1 shows the percentage of total household income received by various deciles of households ranked by income levels in 1999. The income distribution is clearly skewed in favour of upper deciles. Overall, the top 10 per cent of the households controlled 43 per cent of total income while the bottom 10 per cent of the households controlled 0.76 per cent of total income. The top 10 per cent of urban households controlled 39 per cent while the top 10 per cent of rural households controlled 41 per cent.


17

Table 4.1: Household income shares by deciles, 1999

Total population Rural population Urban population Decile Share % Cumulative Share (%) Cumulative Share (%) Cumulative

1 0.76 0.76 0.84 0.84 1.39 1.392 1.75 2.51 1.89 2.73 2.84 4.233 2.72 5.23 2.84 5.57 3.64 7.874 3.83 9.06 4.12 9.69 4.65 12.525 5.05 14.11 5.16 14.85 5.6 18.126 6.58 20.70 6.94 21.79 7.22 25.347 8.52 29.22 8.73 30.52 8.72 34.068 11.61 40.83 11.72 42.24 11.11 45.179 16.46 57.28 16.70 58.94 15.81 60.98

10 42.72 100 41.06 100 39.04 100Source: SID, 2004 – cited as computed from the Integrated Labour Force Survey, 1998/99 data.

However, household income can be a “noisy” measure of welfare. For this reason, household consumption expenditure is often used in analysis of poverty and inequality. According to the KNBS (2008: 83), based on the 2005/2006 household survey, the lowest 10 per cent of households in rural areas controlled 1.63 per cent of total expenditure while the top 10 per cent controlled approximately 36 per cent. It is also noted that expenditure shares tend to be higher in poor regions compared to richer regions. Moreover, poor regions tend to have larger proportions of their populations in the lower expenditure deciles.

As discussed earlier, the Gini coefficient (or index) is commonly used to measure income inequality in a country and for comparisons across countries or regions. Table 4.2 provides estimates of the Gini coefficient for Kenya from various studies and time periods. The estimates suggest that income inequality in Kenya was high in the 1960s, 1970s and 1980s while estimates based on recent household surveys (1992, 1994, 1997 and 2005) suggest relatively lower but still substantial income inequality. This is summarized in Table 4.2 and illustrated in Figure 4.2.

Table 4.2: Trends in income inequality estimates for Kenya, 1964-2006 Author Reference

year Data source Gini coefficient

Bigsten, 1986 1964 - 0.63 Jain, 1975 Lecaillon et al.

1969 1969

ILO, 1972 -

0.481 0.604

Bigsten, 1986 1974 - 0.690 ILO, 1984 1976 Based on National Accounts 0.599 Van Ginneken and Park, 1984 1977 Social Accounting Matrix 0.570


18

(synthetic data) Milanovic, 1994 1981-83 Chen, Datt and Ravallion,

1993 0.573

Lecaillon et al. 1984 - 0.604 Deininger & Squire, World Bank, 2004

1992 Welfare Monitoring Survey I 0.599

World Bank Poverty Monitoring Database, 2002

1992 Social Dimensions of Adjustment Survey

0.569

World Bank Poverty Monitoring Database, 2002

1994 Welfare Monitoring Survey II 0.443

World Bank, World Development Indicators, 2004

1997 Welfare Monitoring Survey III 0.419

Society for International Development, 2004

1999 Integrated Labour Force Survey

0.556 (No adjustment) 0.625 (per capita)

World Bank estimates 2005/2006 Kenya Integrated Household Budget Survey

0.452

Source: World Income Inequality Database V2.0c, May 2008 http://www.wider.unu.edu/research/Database/en_GB/wiid/

Figure 4.2: Income Inequality Estimates for Kenya 1964-2006

63.0

%

48.1

%

60.4

%

59.9

%

57.0

%

57.3

%

60.4

%

59.9

%

56.9

%

44.3

%

41.9

%

55.6

% 62.5

%

45.2

%

69.0

%

0%

10%

20%

30%

40%

50%

60%

70%

80%

1964

1969

1969

1974

1976

1977

1981-8

3198

4199

2199

2199

4199

7199

9199

9

2005/0

6

Year(s)

Gin

i Coe

ffici

ent (

%)


19

Table 4.3 provides cross-country comparison of poverty and income inequality among several countries. Since the Gini coefficient is a unit-free measure of income inequality it can be compared across countries and regions. The Kenya Integrated Household Budget Survey (KIHBS) of 2005/2006 shows that the Gini coefficient was 0.447 in urban areas and 0.380 in rural areas (KIHBS, 2008). Countries such as China and Malaysia have had Gini coefficients close to 0.5 but low poverty incidence. These countries have also recorded high rates of economic growth. This suggests that the poverty reducing effect of growth dominated the poverty, increasing effect of income inequality. In Africa, Uganda had a Gini coefficient close to Kenya’s but managed to reduce poverty. Again, Uganda’s growth record in recent years has been impressive. The figures for Kenya seem to differ depending on the authors. However, poverty has declined recently even with income inequality at around 0.45. This suggests that the positive impact of recent economic growth on poverty has been stronger than the negative impact of income inequality.


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Table 4.3: Income inequality and poverty in selected countries

Country Survey year Gini Population below national poverty line (%)

China* 2004 0.469 4.6 Malaysia* 1997 0.492 15.5 Thailand* 2002 0.420 13.6 Ghana* 1998/99 0.408 39.5 Ethiopia** 1999/2000 0.300 23.0 Malawi** 2004/2005 0.390 20.8 Rwanda** 2000 0.468 60.3 Tanzania* 2000/01 0.346 35.7 Uganda* 2002 0.457 37.7 Kenya* 1997 0.452 52.0 Kenya*** 2005/2006 Rural: 0.380

Urban: 0.447 49.1 33.7

Sources: **World Development Indicators (World Bank, 2008); *UNDP (2007); and, *** KNBS (2008)


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5 Growth and Income Inequality The question of how inequality behaves in the development process and whether inequality is detrimental to growth has been a topic of concern for a long time. However, new impetus to the topic emerged in the 1990s as researchers and policy makers sort to identify factors that influence economic growth. The purpose of this section is to review briefly the theoretical arguments and the empirical evidence.

5.1 Impact of growth on income inequality

The study of the relationship between economic growth and income inequality dates back to the research by Kuznets (1955 and 1963). He examined the determinants of levels and trends in income inequality and the link between growth and income inequality. The key finding of this work came to be known as the inverted U-shaped pattern of income inequality - inequality first rising during the initial stage of development and then declining. The Kuznet hypothesis assumes that the economy consists of two sectors - a low average income and low income inequality rural agricultural sector and a high average income high income inequality urban sector. The hypothesized pattern of income inequality is accompanied by structural change - the agricultural sector becomes small as the higher productivity urban industrial sector expands.

However, empirical studies show that growth does not consistently affect income inequality one way or the other (Deininger and Squire, 1998; Ravallion and Chen, 1997). Many studies in the 1970s (Adelman and Morris, 1971; Ahluwalia, 1974, 1976) produced evidence that the Kuznets hypothesis explained the pattern of income inequality in industrialized countries. However, beginning in the 1980s, the hypothesis came under renewed scrutiny. For example, Anand and Kanbur (1984) argued that the earlier studies that supported Kuznet’s hypothesis were based on low quality data and weak methodology. In the 1990s, renewed interest in income inequality emerged when Deininger and Squire (1998) conducted a detailed study using high quality data for 108 countries. The key result from this study is that neither cross-country data nor individual country data provides support for Kuznets hypothesis.

While the original version of the Kuznets hypothesis related income inequality to income level, another version postulates a positive relationship between the rate of economic growth and changes in inequality. Thus, in fast growing economies, the rich would receive proportionally higher gains from growth than the poor. However, studies by Fields (1989) and Deininger and Squire (1998), find empirical evidence to support this version of Kuznets hypothesis.


22

Ravallion and Chen (1997) find evidence to suggest that income inequality declines with economic growth, but the finding is not robust to exclusion of countries in Eastern Europe and Central Asia. Ravallion (2001) found little or no correlation between growth in average household income and change in measured income inequality.

Although debate over methodology continues, the evidence suggests that the sequence in income inequality as an economy grows predicted by Kuznets’ hypothesis is not inevitable. Moreover, a number of East Asian countries (Korea, Taiwan, Hong Kong) have enjoyed high growth rates with low income inequality.

5.2 Impact of income inequality on growth

The economics literature suggests three channels through which income inequality can affect growth. These are encapsulated in three approaches: (i) classical approach (ii) modern approach; and (iii) the unified approach (Iradian, 2005). Figure 5.1 summarizes these channels.

In the classical view, inequality can have positive impact on growth, that is, countries with more unequal distribution of income would grow faster than those with equal distribution of income. This view is based on the idea that average propensity to save increases with income level so that if income is redistributed in favour of the rich, the economy wide average propensity to save and hence the fraction of GDP devoted to capital formation would rise, promoting economic growth. This view is also associated with the work of Kaldor (1957) and Bourguignon (1981).

Under the modern approaches, several arguments suggesting that income inequality is detrimental to growth have also been put forward. The first view, associated with the work of Alesina & Perotti (1996) and Benhabib and Rustichini (1996), emphasizes the difficulties in collective action as reflected in: (i) a propensity for populist redistributive policies; (ii) a greater volatility in policies; and (iii) socio-political unrest and instability. High income inequality tends to generate increased crime, social unrest and political instability. This social unrest discourages investment as it generates uncertainty and disrupts the normal functioning of markets. As a consequence, economic growth declines.

A second view is that high inequality can increase the fertility rate and retard growth. This could occur if there is a poverty threshold below which there exists high fertility rate. Below this threshold, quantity of children is preferred to quality of children. Therefore, by increasing the number of people living


23

below the threshold, inequality would increase the economy-wide fertility rate and thereby reduce economic growth (Perotti, 1996).

The third view is that high income inequality may be detrimental to growth in the face of credit market imperfections such that the poor are unable to invest in growth-promoting physical and human capital (Galor & Zeira, 1993; Aghion et al., 1999). This can lead poor households to forgo human capital investment, even if the investments offer very high rates of return. The greater the inequality of wealth and income, the greater the number of people for whom the constraints could be binding and, therefore, the lower the stock of human capital in the economy. This explanation presumes that economic growth is enhanced through human capital accumulation as suggested by new growth theory (Romer, 1994).

The fourth argument is linked to endogenous fiscal policy or political economy (Alesina and Rodrik, 1994). The idea is that high level of inequality leads to redistributive fiscal policy in the form of higher government expenditure and distortionary taxation, which could retard growth. It is argued that in a situation of higher inequality, a majority of voters tend to favour taxation and government spending in form of either direct transfers or as public expenditure programmes. Higher taxes and transfers distort economic decisions, including private saving and investment, thereby causing economic growth to decline.

The unified approach is attributed to Galor (2000), and it attempts to reconcile the classical approach and the modern approaches given their conflicting predictions. He argues that the classical approach is valid at early stage of economic development when incomes are low but not at later stages of development. This is because the early stage of development is characterized by scarce physical capital. In such circumstances, inequality could result in higher savings and investments and hence the promotion of growth. However, at the later stages of economic development, as the return to human capital increases - owing to capital-skill complementarity - human capital becomes the main thrust of growth. Credit constraints become less binding as wages increase, and the adverse effect of income inequality on the growth process becomes insignificant.

The theoretical explanations reveal the existence of contradictory predictions. The earlier view held that the effect of inequality on growth could be positive whereas the more recent view predicts a negative effect of inequality on growth. The arguments for a positive impact of income inequality on growth have not found support in recent empirical work. Instead, the evidence points towards a negative impact of inequality on growth (Aghion et al., 1999). The initial evidence that income inequality is detrimental to growth was generated


24

by Persson and Tabellini (1994) and Alesina and Rodrik (1994) based on the fourth argument discussed above. Barro (2000) also finds a negative impact of income inequality on growth for countries with average income less than US$ 2100 (1985=100). In addition, high income inequality raised fertility rates, which reduces economic growth and exacerbates income inequality.

Figure 5.1: Channels linking effects of inequality on growth (adapted from Iradian (2005)

High initial income inequality

High physical capital

The unified approach: Galor (2000)

Early stage of development Credit market largely binding.

Physical capital accumulation is prime engine of

Later stage of development Credit constraints less binding. Human capital accumulation is

High saving rates

High economic growth

Positive effect of inequality on saving is offset or dominated by the negative effect on investment

in human capital accumulation

High initial income inequality

Higher taxation

Low

er e

cono

mic

gro

wth

High initial

income inequality

Difficulties in collective

action

Through credit market

imperfections

Through endogenous fiscal policy

(political

High rent seeking

Poor unlikely to invest in human and

physical capital

Demand for redistribution

Reduction in security of property rights

• Increased uncertainty • Demand for

redistribution

• Lower investment

• Higher

Classical approach Contributors include: Keynes (1920), Kaldor (1956), and Bourguignon (1981)

High initial income

inequality

Higher aggregate savings - since richer households save more

than the poor

High capital

accumulation

High economic growth

Modern approaches Contributors include: Alesina and Perotti (1993); and Alesina and Rodrik (1994)


25

Birdsall, et al., (1995) conducted a cross-country study for East Asia, and rejected the idea that high levels of income inequality are associated with rapid growth. Instead, they argued that low inequality has a positive causal effect on economic growth. They pointed out that policies that reduced poverty and income inequality, such as the emphasis of high quality basic education, also stimulated growth. They hypothesize that low inequality and well designed inequality reducing policies stimulate growth. The policies they refer to include those that increase the productivity of the poor and eliminate consumption subsidies for the rich; they do not include income transfers.

An attempt to discriminate among the alternative channels through which inequality might be detrimental to economic growth was made by Perotti (1996) based on a sample of developed and developing countries. He found that income inequality is negatively correlated with growth in the full sample and the evidence supported the sociopolitical instability view of why income inequality negatively affects economic growth. However, when the income inequality growth relationship was estimated for the sub-sample of countries with less than US$ 1500 (1985=100), the inequality variable was not significantly related to growth. But this could be explained by data problems (measurement, comparability and reliability).

Another question that the literature has addressed is whether initial inequality in assets or income is detrimental to subsequent growth. Galor and Zeira (1993); Alesina and Rodrik (1994); Perotti, (1996); Ravallion (1997); and, Aghion et al. (1999) conclude that the higher the initial inequality, the lower the subsequent growth. In contrast, Barro (2000) finds no evidence that initial inequality in consumption reduces subsequent growth.

The impact of other forms of inequality on growth has also come under scrutiny. Lundberg and Squire (1999) and Deininger and Olinto (2000) conclude that high assets inequality (e.g. land), retards economic growth to a greater extent than income inequality. Birdsall et al. (1995) conclude that inequality in educational access generates inequalities in human capital within and across countries.

In Africa, available evidence suggests that income inequality is not good for growth. A study by Nel (2003) explored the effect of income inequality on growth using a sample of SSA countries based on household expenditure data for 1986-97. The results suggested that high levels of income inequality impacted growth negatively over the medium term. However, the statistical association was not strong and the negative association lacked robustness. The study also found that high levels of income inequality negatively affected the risk perceptions of potential investors, and may have contributed to lower growth prospects.


26

Odedokun and Round (2001) used quasi-panel data for 35 African countries over different periods during the 1960s to 1990s. The main finding is that high inequality hindered economic growth in the countries during the sample period. Their findings can be summarized as follows:

• High inequality is negatively associated with political stability – in support of the socio-political instability argument.

• High inequality increased the fertility rate, thus lending support to the endogenous fertility argument.

• High inequality reduced both secondary and tertiary school enrolment ratios, hence supporting the credit market-imperfection induced human capital channel.

• Therefore, there is no evidence that inequality reduces private saving and investment and hence growth. Thus, there is no evidence to support the endogenous fiscal policy argument in the classical view.


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6 Growth and Poverty Reduction The extent to which the poor gain from economic growth is a major topic in development policy analysis and discussions. In the 1960s and 1970s, the widely held view was that gains from rapid economic growth automatically trickle down to the poor. Consequently, the main task for development policy was to increase growth by promoting savings and investment. Recent empirical studies show that economic growth and poverty reduction move together, but the response of poverty to growth varies across countries. Consequently, the question of how sensitive poverty is to economic growth has become the subject of extensive research.

Ali and Thorbecke (2000) studied the sensitivity of rural and urban poverty to growth in Sub-Saharan Africa in the 1990s, including Kenya. The elasticities derived show that the impact of economic growth on poverty is less than one-to-one, implying that the economic growth rates required may exceed what can be reasonably expected in terms of poverty reduction. A study of India by Ravallion and Datt (1995) used consumption-based poverty measures for India spanning forty years to test the claim that the sectoral composition of growth is important for poverty reduction. While consumption growth in rural areas reduced poverty in both rural and urban areas, consumption growth in urban areas benefited the urban poor, but had no impact on rural poverty. In addition, output growth in the primary and tertiary sectors contributed to poverty reduction in both urban and rural areas but the secondary sector output growth did not reduce poverty in either.

Ravallion and Chen (1997), suggest that rapid economic growth could reduce poverty incidence rapidly. A one (1) per cent increase in per capita income was associated with a 3.1 per cent reduction in head count poverty index. The estimated growth elasticity of poverty was higher for lower poverty lines. This implies that the response of extreme poverty to growth exceeds the response of moderate poverty to growth. Dollar and Kraay (2002), investigated the determinants of growth in incomes of the poorest quintile in a large panel of countries and concluded that the income of the poor rises roughly one-for-one with overall growth. The growth elasticity of average income of individuals in the lowest quintile was between 0.96 and 1.06. The implication is that there is no need for pro-poor growth policies. However, as empirical studies reviewed below suggest, the reduction in poverty is unlikely to be one-for-one with overall income growth.

The specification of poverty, inequality and growth relationship has important implications. Bourguignon (2003) and Lopez and Serven (2004) conclude that the log normal distribution is an appropriate representation of the distribution


28

of income. This is important as it allows computation of the poverty elasticity of growth and income inequality. There is also evidence that while average income reduces poverty, income inequality increases it. Person and Tabellini (1989) and Ali and Thorbecke (2000) find a strong negative relationship between income inequality and growth and poverty for both developing and developed countries. Ravallion (1997) compared the extent of poverty reduction between high and low inequality developing countries, using data for 23 developing countries constructed from two household surveys over time. The study finds that if inequality is high enough, countries that would have very good growth prospects at low levels of inequality may see little or no overall growth and little or no progress in reducing poverty. It is suggested that inequality can be high enough to result in rising poverty despite good underlying growth prospects. This suggests that reducing inequality would directly abate poverty, increase the poverty impact of growth, and could even increase growth itself.

The relative impact of growth and changes in inequality on poverty and welfare changes among socio-economic groups in Nigeria has been investigated in Nigeria (Aighbokan, 2000) using 1982/85 to 2003/2004 data. The estimates of growth elasticity of poverty, estimated using a system of Generalized Method of Moments, suggest that inequality rises with growth and poverty declines with growth. But the growth elasticity of poverty reduction is low in Nigeria because of high initial inequality rise. In the Philippines, Basilaca and Pernia (2002) report that there are substantial differences in the evolution of poverty across provinces. The estimated growth elasticity of poverty is slightly above -0.5, indicating that income growth alone does not translate one for one to changes in poverty. Other than growth, the paper highlights the importance of other explanatory factors such as education, infrastructure, terms of trade, agrarian reform and governance for poverty reduction. In terms of infrastructure, for instance, the authors pinpoint that high transport costs lead to geographic poverty traps as the poor are impeded from taking advantage of economic opportunities elsewhere.

The rate at which poverty declines in response to economic growth also depends on initial income inequality. Ravallion (1997) investigated the issue for 23 developing countries and found that the growth elasticity of poverty was 3.3 at a Gini coefficienct of 0.25 and 1.8 at a Gini coefficienct of 0.60. UNECA (2004) examined the impact of initial inequality on growth required to attain the MDGs for SSA countries. The results showed that countries with high initial income inequality would need a higher acceleration in per capita GDP to meet the MDGs. Thus, high initial income inequality reduces the efficiency of economic growth in reducing poverty and vice versa.


29

Initial levels of inequality and poverty can also undermine the impact of growth on poverty reduction. In a study of 12 Latin American countries for 1970 to 1994, Janvry and Sadoulet (1999) show that income growth is only effective in reducing poverty and inequality if the initial levels of inequality and poverty are not too high and if educational levels are sufficiently high. In the absence of these conditions, the beneficial effects of growth for poverty and inequality reduction are not fully realized. Moreover, due to an asymmetry in the effect of income change on poverty and inequality, the beneficial effects of income growth are erased one-for-one by a decline in income, reflecting the high social costs of economic shocks. Further, income growth in the aftermath of structural reforms was more effective in reducing poverty than income growth under import substitution industrialization policies.

Over recent decades, economies in East and South East Asia have achieved large reductions in poverty. However, the Asian experience of poverty reduction is not uniform. The economies of East and South East Asia have achieved substantial reduction in the incidence of absolute poverty but those in South Asia have recorded relatively lower reduction in poverty incidence (Warr, 2000). Warr analyzed the determinants of changes in poverty incidence based on data from Indonesia, Malaysia, Philippines, Thailand, and Taipei China. Table 6.1 provides average rates of growth of real GDP per capita and the annual rate of change of poverty incidence in East and South Asia. The evidence suggests that in these countries, the overall economic growth rate is more important for poverty reduction than the sectoral composition of the growth.


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Table 6.1: Growth and poverty reduction in east and south Asia

Country Period Average rates of growth of real GDP per person (%)

Annual rate of change of poverty incidence (%)

India

1957-1992

1.9

Aggregate: -0.7 Rural: -0.3 Urban: -0.4

Taipei-China

1964-1995

6.9 Aggregate: -1.6 Rural: -1.1 Urban: -0.4

Thailand

1969-1999


Indonesia

1976-1999


Malaysia

1976-1995


Philippines

1965-1997


Source: Warr P., 2000

Pro-poor Growth

The term ‘pro-poor growth’ has become common in development policy discussions. As the foregoing review demonstrates, poverty reduction is a function of changes in average incomes and income inequality. Initial inequality in income and assets also influences poverty reduction. It has been observed that there can be large differences in poverty reduction even when the differences in growth rates, are not large. If the income of the poor rose one-for-one with overall growth, it would imply that the poor and the non-poor have similar proportional gains from growth. The nature of growth would not matter. However, many empirical studies do not find such a one-to-one correspondence. Consequently, there is debate about what elements constitute a pro-poor growth strategy. If the impact of growth on poverty is very large compared to the impact of income inequality on poverty, growth promotion policies may be enough to generate rapid reduction in poverty. In contrast, if the impact of income inequality on poverty dominates, then there is room for pro-poor policies to reduce inequality.


31

Two different definitions of pro-poor growth have been proposed. According to Kakwani (2000), growth is pro-poor if the change in income inequality resulting from growth leads to poverty reduction. Variants of this definition have been proposed by White and Anderson (2000). Growth is pro-poor if the income of the poor grows at a rate that exceeds the average growth rate. Alternatively, growth is pro-poor if the share of the poor in the growth reflects their share in the population. But Ravallion and Chen (2003) propose that growth should be defined as pro-poor if the poverty measure being considered falls. Under this definition, growth that reduces poverty regardless of the impact on inequality is considered pro-poor.

Kakwani (2000) considers the income inequality-growth tradeoff in Thailand, Korea, Lao PDR and the Philippines to determine how much growth is needed to offset the detrimental impact of an increase in income inequality on economic growth. South Korea and Thailand are among the Asian Tigers with high growth rates and rapid reduction in poverty. However, while South Korea maintained low income inequality, Thailand’s income inequality increased. The Philippines has been characterized by lower growth, higher level of income inequality and higher incidence of poverty. Lao PDR is the poorest in this set of countries. The results suggest that pro-poor policies would have greater impact on poverty reduction in Thailand while growth-maximizing policies would be better for South Korea and Lao PDR. The Philippines would be better of with a mix of pro-poor policies and growth-maximizing policies. Another finding from the paper is that countries with low initial inequality enjoy a higher poverty reduction from growth than countries with high initial inequality.

Kraay (2004) adopts the definition of pro-poor growth by Ravallion and Chen (2003) and decomposes changes in poverty to identify the potential sources of pro-poor growth. The paper arrived at three main results. First, almost 70 per cent of the short-term variation in poverty can be attributed to growth in average income. The medium and long-term growth contributes about 97 per cent of the changes in headcount index. Moreover, the headcount ratio is more responsive to growth than the poverty gap index. The explanation is that the bottom poverty measures place less weight on growth in average incomes.

Should the main focus of development policy be placed on economic growth, or poverty, and/or inequality? According to Bourguignon (2004), this question raises a false dilemma. He argues that: (i) the rapid elimination of absolute poverty, under all forms, is a meaningful goal for development; and (ii) to reduce absolute poverty rapidly requires strong, country-specific combinations of growth and distribution policies. Recent studies have shifted focus to distribution policies and a key message is that redistribution may be necessary


32

for growth. Bourguignon (2004) suggests that redistribution of wealth from rich to less rich people may have a positive impact on growth. He adds that to be efficient and growth-enhancing, redistribution should be concerned with wealth rather than current income of consumption expenditures. This may occur by correcting credit markets imperfections, lowering the tax rate, or freeing other distortionary income redistribution mechanisms.


33

7 Current Poverty Alleviation Initiatives There are many policies, regulatory and operational initiatives aimed at alleviating poverty in Kenya. This section reviews the initiatives put in place by the Government of Kenya before summarizing the efforts of other stakeholders.

7.1 Government of Kenya initiatives

7.1.1 Policy initiatives

Accelerating and sustaining economic growth

Rapid economic growth is viewed as the key to alleviating poverty. This might explain why all core public policy documents emphasize rapid economic growth as a way of alleviating poverty. The current 9th National Development Plan (2002-2008) and the National Poverty Eradication Plan (1999-2015) focus on poverty eradication mainly through high and sustained economic growth. Recent policy documents, especially the Economic Recovery Strategy for Wealth and Employment Creation (ERSWEC) 2002-2007, emphasized economic growth and job creation. The objective of the ERS included the reduction of poverty levels by about 5 per cent; achieving high real GDP growth rate of 7 per cent by 2006, and creating 500,000 jobs annually. The ERSWEC was succeeded by Vision 2030: First Medium Term Plan (MTP), 2008-2012, which aims at increasing real GDP growth from the estimated 7 per cent in 2007 to 10 per cent by 2012. The Vision 2030: MTP recognizes that inequality and poverty remain key development challenges that the government continues to confront. The ERSWEC received some level of success. Economic growth steadily rose from 2.9 per cent in 2003 to 7.0 per cent in 2007 (Government of Kenya, 2008). However, following the dampening effects of the post-election shocks, growth prospects for 2008 are projected to be lower than 7 per cent.

A major challenge concerns the focus of policy given that the review presented in the previous sections implies that growth promotion should not be the only focus of development. Empirical evidence suggests that growth policies may yield better outcomes in terms of poverty reduction if they take into account the distributional impact of economic growth. There is, therefore, need to focus development policy not only on growth but also on poverty, and/or inequality. The incidence of poverty decreased from 56.8 per cent in 2000 to 45.9 per cent in 2005. From the various estimates of income inequality (Table 4.2), income inequality was lower in 2005/2006 than in 1999 with Gini coefficients of 0.447 and 0.556, respectively.


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A recent report (World Bank, 2008) identifies some of the key problems holding back economic growth as corruption, poor transport and communication services, weak institutions to handle political risk, and inadequate integration into the global economy. The report recommends a growth strategy that emphasizes reduction of business costs and risks that emanate from insecurity and corruption, reducing costs of transport and telecommunication services, improving reliability of energy supply, and improving access to finance for small and rural enterprises.

Devolved Funds

The decentralized funds include the Constituency Development Fund (CDF), Local Authority Transfer Fund (LATF), HIV/AIDS Fund, Rural Electrification Programme Levy Fund (REPLF), Secondary School Education Bursary Fund, Road Maintenance Levy Fund (RMLF), and the Free Primary Education (FPE).4 Among other objectives, the funds are aimed at reducing regional disparities and taking care of emerging developmental challenges such as HIV/AIDS, youth unemployment and the negative impact of the failure of past government programmes.

The recent Democratic Governance Survey Programme (DGSP)5 study by KIPPRA reveals that households perceive some of the funds to have had a positive impact on development. This includes the FPE, for which over 90 per cent of respondents concurred that it had a positive impact on education. However, the overall perception by households is that the funds have had little impact on quality of life despite the large increase in allocations for the last few years.

Some of the challenges facing the decentralized funds identified by the DGSP study - and other studies include:

• A low level of awareness about the decentralized funds by local communities and hence low levels of participation in the funds management (for example, only less than 30 per cent were aware about the LATF). Low awareness by fund managers and community members of their roles and responsibilities in the governance of funds has contributed to implementation difficulties.

4 Other funds usually discussed in this category include: the Community Development Trust Fund, Poverty Reduction Fund, Youth Enterprise Development Fund, and the Women’s Enterprise Development Fund. These funds are discussed in this paper under the government’s operational initiatives.

5 Accessed from http://www.kippra.org on 30th September, 2008. Democratic Governance Survey Programme was carried out in all provinces in Kenya. The bulk of the respondents were households.


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• Some of the funds’ management structures such as the CDF give immense power to the political leaders, paving way for anomalies such as inequitable distribution among administrative units. Corruption cases have been witnessed in the use of some of the funds. In addition, there is a general lack of transparency and accountability, probably due to the blending of supervisory and implementing roles. The lack of transparency in procurement systems has affected the cost-effectiveness of projects.

• Weak monitoring and evaluation has led to poor project quality. This is partly due to inadequacy of data and general information about the funds and also lack of professional and technical supervision.

• There has been increased dependency on these funds, especially in education. The decentralized funds may/can, therefore, stifle local fiscal effort through voluntary contributions for community development (Kimenyi, 2005).

• The allocations from the various funds are usually adjudged to be inadequate.

• Decentralized funds in Kenya also face a challenge of poor coordination and overlaps due to the large number of decentralized funds.

Various proposals have been put forward on how the identified challenges can be resolved. One key proposal is the need to intensify education given to the communities on the role of the various funds. There is also need to provide and/or deepen information to the fund managers and communities on the procedures for application and use of the allocated funds. This can stimulate effective public participation particularly for funds such as the Local Authority Transfer Fund. Development of a better legal and institutional framework is necessary for improved administration and better utilization of the decentralized funds. In addition, there is a need to mitigate barriers to effective implementation of projects, such as the interruptions that may occur with changes in government or the ‘privatization’ of funds by certain fund managers. Perhaps better developmental outcomes can be achieved by streamlining and/or merging various funds.

Sectoral Policies and Initiatives

Antipoverty policies and initiatives are also found in specific sectors. This section reviews some of the sectoral policy initiatives in agriculture, manufacturing, tourism and education. Other sectors (though not discussed here) are health, finance, energy, transport and communication, building and construction, and trade.


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Agriculture - In agriculture, the government rolled out the Strategy for the Revitalization of Agriculture (SRA) 2003-2007 which focused on liberalization and policy reform. The SRA recognized that expansion of agriculture is crucial for poverty reduction in Kenya. One element of the changes was the reinvigoration of government intervention in the agricultural sector, including the rehabilitation of several firms that had ceased operations (for example, the Kenya Meat Commission). The period 2003-2007 was marked by improved agricultural performance, with respect to output compared to the 1997-2002 era (GOK, 2008). Nevertheless, the agricultural sector is still constrained by a number of factors, including high cost of inputs, limited adoption of technology, weak farmer institutions, over dependence on rain-fed agriculture, and inadequate credit facilities. The Vision 2030 MTP 2008-2012, which succeeds the SRA, has ambitious flagship projects lined up to tackle the challenges facing the sector. These include the development of a land use master plan and development of ASAL areas.

Manufacturing - There were several policy initiatives targeting the manufacturing sector between 2003 and 2007. These included: the enactment of the Investment Promotion Act of 2004 which also established the Kenya Investment Authority as a one-stop-shop for the licensing and registration of businesses; and formulation of the National Exports Strategy (NES) for enhancing competitiveness. Other notable initiatives included the formulation of the Private Sector Development Strategy (PSDS), development of the master plan for Kenya’s industrial development (MAPSKID) and the Sessional Paper No. 2 of 2005 on Development of MSEs. Between 2003 and 2007, the manufacturing sector grew by an annual average of 5.5 per cent and employment in the formal manufacturing sector grew by an annual average of 2.6 per cent (Government of Kenya, 2008). Despite the recovery attributed to the above policy initiatives, the manufacturing sector is still encumbered by stifling challenges. One area that poses a serious challenge is poor infrastructure evidenced partly by dilapidated transport network, and unstable and relatively costly energy supply. Other challenges include weak regulatory and institutional frameworks and influx of counterfeit goods. Apart from stemming these challenges, there will be urgent need to institute further regulatory and institutional reforms.

Tourism - Tourism is the leading foreign exchange earner and accounts for about a tenth of Kenya’s GDP. A recent policy initiative was the Tourism Recovery Programme, which began in 2003 to revitalize the sector. Between 2003 and 2007, the number of domestic and international tourists grew rapidly and employment generation within the sector grew by an average of over 3 per cent annually. Despite the recent gains, the sector still faces


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numerous challenges. Some of the emerging challenges include: insecurity, inadequate infrastructure, narrow product variety and environmental issues (Government of Kenya, 2008; Vision 2030: 1st MTP). Creating a suitable investment climate, aggressive marketing and re-branding can ameliorate some of the aforementioned challenges.

Education – As indicated earlier, education and poverty in Kenya are intimately related. The incidence of poverty among the better educated households is lower than among less educated households. Recent policy initiatives in the education and training sector include: the introduction of free primary education (FPE) in 2003; development of the Sessional Paper no. 1 of 2005 on Policy Framework for Education, Training and Research; the development of the Kenya Education Sector Support Programme (KESSP); and the Free Day Secondary Education (FDSE). Others are the school feeding programme, development and implementation of education sector HIV/AIDS policy, special support in Arid and Semi Arid Lands’ (ASAL) primary and secondary education, and support to special needs education. The outcome was positive at least as far as access to education (at all levels) is concerned. However, some of the problems the country will grapple with include: issues of quality and relevance, gender disparity and equity across regions. Other challenges are inadequate physical facilities and human resource constraints (Vision 2030: 1st MTP). Generally, the flagship projects contained in the Vision 2030: MTP can ameliorate these challenges. A few of the lined up initiatives include: construction of new schools especially at secondary level, increase of teacher recruitment, and enhancement of ICT education.

Other sectors - The government has also instituted policy initiatives in all the other sectors such as health, finance, energy, transport and communication, building and construction, trade and business process outsourcing. Some of the policy initiatives include the development of the national ICT policy, the Anti Counterfeit Goods Bill and the implementation of the Private Sector Development Strategy. These policy initiatives have had gains, including the growth of exports by 11.4 per cent between 2003 and 2007. On the other hand, challenges still abound. The cost of finance and the cost of doing business is still relatively high in Kenya. Other emerging challenges include the post-election violence, constraints to market access, low utilization of ICT, weak or inadequate institutional, legal and regulatory framework, capacity constraints, environmental degradation, and high population growth rate.

Land Settlement Programmes/Schemes and Land Reforms

The government has conducted programmes of land distribution mainly through settlement schemes in which thousands of landless people were provided with small scale landholdings mainly in the former White Highlands.


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The initial schemes – including the “million-acre-scheme” - allowed households that were displaced by the colonialists to be resettled. Land resettlement programmes enabled the government to resettle many initially landless people who now engage in agricultural production and contribute to food security and employment. The schemes are credited for the rapid output expansion in the 1960s and 1970s. Since then, successive governments have resettled people but in smaller scale.

However, resettlement programmes have faced problems of: poor project implementation, lack of commitment, and corruption (where non-deserving persons get allocated land). Other identified challenges include resettlement in marginal land that may not add much to output in the absence of complementary investments such as in water supply. In addition, the relatively high population growth makes the initiative have a limited scope in alleviating poverty (Manda et al., 2001). Most of the land settlement schemes problems could be resolved by improvements in governance and continuous adoption of improved technology in agricultural production.

Specially Targeted Projects

The methods used to specially target the poor include sectoral and geographical targeting of the poor. A number of targeted projects have been initiated including: Urban Slum Development of Nairobi, Street Children’s Fund, Constituency Education Bursary Programme, and the Micro and Small Enterprises Programme, among others. Special targeting of the poor can now benefit from the poverty mapping initiatives that resulted in the production of the Geographic dimensions of well-being in Kenya. The main issue with targeted social programmes is to ensure leakage to ineligible groups is minimized. There are often complaints that bursary funds are sometimes allocated to students from families that are able to pay, while denying deserving cases.

7.1.2 Regulatory initiatives6

Kenya is in the process of reforming its regulatory framework. Like other developing nations, the country is perceived to have complex rules and regulations that govern the various sectors of the economy. These rules and regulations cover agriculture, business registration, labour markets, commercial banking, non-bank financial institutions, capital markets among others. Complex rules and regulations can be a hindrance to the competitiveness and growth of the private sector. One way in which complex rules and regulations can act as an impediment is that they can unnecessarily

6 More information can be obtained from www.gjlos.go.ke


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increase the transaction costs and act as a barrier to entry and expansion of businesses. This state of affairs may reduce the ability of the country to fight poverty effectively.

Regulatory reforms have actually taken place in each sector, and are likely to continue as the country develops. Table 7.1 lists some of the regulatory initiatives affecting various key sectors of the Kenyan economy. Besides these sectoral initiatives, there are also broad regulatory initiatives that cut across several or all sectors. A recent broad regulatory reform programme/initiative was the Deregulatory Programme that was concerned with the business environment and business climate. The ongoing Governance, Justice, Law and Order Sector (GJLOS) reform programme is another example of a broad (mainly regulatory) initiative.

The Deregulation Project, funded mainly by the Department for International Development (DFID), has been ongoing in phases. The third phase of the Deregulation Project, also known as the Umbrella Project, begun in 2001. The project’s aim was to eliminate the constraints that increase the cost of doing business. The project was implemented through research, private sector advocacy and capacity building of the public sector. The research component involved research output on legal and regulatory constraints to the operations of the private sector. The Umbrella Project is credited for lessening complexities within the regulatory framework and improving the business environment and/or business climate.

In 2003, the government launched the Governance, Justice, Law and Order Sector (GJLOS) reform programme that takes a sector-wide approach to justice, human rights and good governance. The overarching development goal of the GJLOS programme is to contribute to the quality of life of Kenyans, particularly the poor and the vulnerable. The GJLOS programme’s purpose is to improve the delivery of justice, safety, security and the rule of law. This purpose is developed into seven result areas around which all activities are organized and implemented. They include Ethics, Integrity and Anti-corruption; Democracy, Human Rights and the Rule of Law, Justice, Law and Order, Public Safety and Security, Constitutional Development, Quality Legal Services, and Leadership and Change Management.


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Table 7.1: Examples of recent regulatory initiatives by sector

Sector Recent Regulatory initiative(s) Agriculture • National Agricultural Extension Policy (NAEP), 2001

• Implementation of the Strategy for Revitalizing Agriculture (SRA), 2003

• Food Security and Nutrition Policy (FSNP) Tourism • Finalization of Wildlife and Tourism Acts (ongoing) Wholesale retail and international trade and manufacturing

• Investment Promotion Act enacted in 2005. The Act established the Kenya Investment Authority (KIA) a one-stop-shop for both local and international investors

• Formulation of the Private Sector Development Strategy (PSDS) in 2006

• Formation of the business regulatory unit in 2007 • Drafting of the Anti-Counterfeit Goods Bill • Preparation of the National Industrial Policy

Business process outsourcing and ICT

• Launch of national ICT policy in 2006 • Enactment of the Kenya Communications Amendment Bill,

2007 • Establishment of the Media Bill, 2007

Financial services • Establishment of the Central Depository System (CDS) in 2004

Other sectors Education and training • Development of Sessional Paper No. 1 of 2005 on Policy

Framework for Education, Training and Research • Development of the Kenya Education Sector Support

Programme (KESSP) • Development of National ICT Policy in 2006 • Review of Ministry of Education legal framework (ongoing)

Health • Development and adoption of the Joint Programme of Work and funding in 2006

Energy • Enactment of the Electric Power Act, 1997 • Enactment of the Energy Act, 2006, which consolidated all

laws relating to energy Environment, water and sanitation

• Enactment of the Environmental Management and Coordination Act (EMCA) of 1999

• Enactment of the Water Act in 2002 • Development of the Nile Basin Cooperative Framework • Forest Act 2005 – whose one objective is to ensure that the

Forestry sector makes a contribution to poverty reduction Transport • Formation of a draft National Integrated Transport Policy

(ongoing). • Enactment of the Kenya Roads Act, 2007


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Cross-cutting reforms • Initiation of the Sector Wide Approach to Planning • Anti-Corruption and Economic Crimes Act, 2003 • Enactment of Public Officer Ethics Act, 2003 • Public Procurement and Disposal Act, 2005 • Occupational Safety and Health Act, 2007

Source: GOK, 2008; and, Vision 2030: MTP

7.1.3 Operational initiatives

Youth Enterprise Development Fund and the Women Enterprise Development Fund7

Youth Enterprise Development Fund (YEDF): The YEDF is a recent initiative by the Kenya government. It is now a State Corporation whose purpose is to reduce youth unemployment. The fund targets youth aged between 18 and 35. It focuses on enterprise development as a strategy to increase employment opportunities and participation by youth in productive activities. The objectives of the fund are to:

• Provide loans to MFIs for on-lending to youth enterprises.

• Attract and facilitate investment in MSEs oriented infrastructure such as business and industrial parks and business incubators.

• Support MSEs of youth to develop linkages with large firms.

• Facilitate marketing of products and services of youth firms in Kenya and abroad.

• Facilitate employment of youth in the international labour market.

• Provide business development services to young entrepreneurs.

Women’s Enterprise Development Fund: This was conceived in 2006 and launched in 2007 by the government as a strategic move towards poverty alleviation through socio-economic empowerment of women. The fund’s core purpose is to improve women’s access to finance, especially for the MSEs. The funds are mainly channeled through financial institutions. In the financial year 2007/2008, the government set aside Ksh 1 billion for the Women’s Fund.

Both the Youth Fund and Women’s Fund are relatively new. However, the funds are being accessed by the youth and women entrepreneurs as indicated by the soaring number of beneficiaries. As at 30th September 2008, Ksh 1.335 billion to finance 47,722 youth enterprises had been disbursed through financial intermediaries. The fund had also disbursed Ksh 322 million to 7,840 youth groups across the Kenyan provinces (Daily Nation, 8 December 2008).

7 Information accessed from www.youthaffairs.go.ke in 30th September, 2008.


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One of the hurdles the funds may face is evidence of poorly developed entrepreneurial culture in Kenya. Table 7.2 summarizes data on job search activities by the unemployed from the integrated labour force survey 1998/99. The data indicates that a majority of job seekers (94%) were looking for paid employment. Only 3 per cent sought to be business operators with or without employees. If this is still the case, then there is need to intensify and sustain the ongoing entrepreneurship training initiatives for better outcomes of the funding programmes. One recurring theme concerns the ideal channel of disbursing the funds. It would be beneficial to study the best strategies for disbursement of the funds to maximize their effectiveness.

Table 7.2: Distribution of unemployed aged 15-64 sex and type of job sought (1998/99)

Type of work sought Male (%) Female (%) Total (%) Paid employment 93 95 94 Business operator – with employed persons 0 0 0 Business operator – without employed persons 1 4 3 Farming & pastoralist activities 2 0 1 Other 3 1 2 Not stated 0 - 0 Total 374,201 694,735 1,068,936

Source: CBS, 2003

Poverty Eradication Commission8

The Poverty Eradication Commission (PEC) was formed in 1999. It has since spearheaded several programmes in fulfilling its mandate mainly in health, education and water sectors. The PEC has had various pilot projects, including the establishment of the District Poverty Eradication Committee (DPEC). The Commission supports specially targeted community-based poverty reduction projects in all the districts in Kenya.

There have been some gains especially in smallholder commercial farming where the PEC has introduced several commercial varieties of crops in a number of districts. These include the Grain Amaranth, which also doubles up as a food security cereal. One of PEC’s programmes, the Revolving Loan Fund Scheme, is meant to assist low income earners who are unable to access credit facilities from banks and other micro-finance institutions. One challenge has been the mode of disbursement of funds. The preferred mode of disbursement of funds is directly to individual enterprises attached to groups after the initial

8 Information accessed from www.pec.go.ke on 30 September, 2008.


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method of disbursing funds to enterprises through groups proved unsustainable. It is suffice to say that the initiative faces similar challenges to the ones faced by public sector initiatives. This suggests that the effectiveness of the Commission’s work can benefit immensely from a general improvement in governance at all levels of government.

Community Development Trust Fund (CDTF)9

The Community Development Trust Fund (CDTF) established in 1996, is a joint initiative of the European Union (EU) and the Government of Kenya (GoK). CDTF supports poverty reduction in Kenya by funding community-based development projects. CDTF’s mandate is to oversee transfer of EU funds, provided from the European Development Fund (EDF), for community development in Kenya. CDTF also receives funds from other donors.

The CDTF runs two programmes: the Community Development Programme (CDP) and the Community Environment Facility (CEF). The CDP provides direct capital investment funds and technical assistance to support poverty alleviation efforts in Kenya. The CEF aims to reduce poverty through improved environmental management. The CDTF phase 3 (which runs from January 2007 to December 2009) has about Ksh 350 million committed to it and is targeting to fund 150 projects countrywide.

Project-based evidence indicates that the various projects have alleviated poverty levels. Some of these projects have/will have a direct bearing on reduction of poverty and unemployment.

7.2 Initiatives by other stakeholders

Apart from the Government of Kenya, there are many other players involved in poverty alleviation initiatives. These include multilateral organizations, bilateral donors, foundations, research institutes and non-governmental organizations. Table 7.3 below attempts to list all the major partners involved in poverty alleviation initiatives in Kenya, including the UN.

The listed organizations and institutions are involved - mainly as funders - in numerous poverty alleviation initiatives. These organizations fund projects and programmes in sectors that have a bearing on poverty alleviation, such as agriculture and rural development, education, environment, gender, land, health and HIV/AIDS, private sector development, roads and transport, water and sanitation, social protection and public sector reform. Appendix tables I and II summarize the indicative sector presence of the Kenya Joint Assistance

9 Information accessed from www.cdtfkenya.org on 28 September, 2008.


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Strategy (KJAS) partners and the non-KJAS partners, respectively. Despite all the above initiatives, poverty is still rampant and affects a very large proportion of the rural and urban population.

Table 7.3: List of stakeholders involved in poverty alleviation initiatives in Kenya

Multilaterals The African Development Bank (AfDB) – infrastructure and others European Commission – several, including infrastructure and agriculture Food and Agriculture Organization – agriculture Global Environment Facility – environmental management Global Fund – health International Finance Corporation (IFC) – enterprise development International Fund for Agricultural Development (IFAD) – agricultural research Japan International Cooperation Agency (JICA) – various including infrastructure and health The International Monetary Fund (IMF) – macroeconomic stability The OPEC Fund for International Development – infrastructure United Nations Development Programme (UNDP) – several including education and health United Nations Population Fund (UNFPA) – health United Nations Industrial Development Organization (UNIDO) – industrial development World Bank (WB) – several including education, health and environment World Food Programme (WFP) – agriculture Bilaterals Belgian Technical Corporation Canadian International Development agency (CIDA) Deutsche Gesellschaft fur Technische Zusammenarbeit (GTZ) Department for International Development (DFID) Finland France International Development Research Center (IDRC) Japan Bank for International Cooperation (JBIC) Netherlands Development Organization (SNV) Norwegian Agency for Development Cooperation (NORAD) Swedish International Development Agency (SIDA) United States Agency for International Development (USAID) Foundations and Research Institutes Clinton Foundation – mainly HIV/AIDS and Malaria (poverty, climate change and education) International Institute of Rural Reconstruction (IIRR) - Kenya Microfund Project


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International Food Policy Research Institute (IFPRI) - research programmes Development Finance Institutions Kenya Rural Enterprise Programme (K-REP) – micro enterprise loans Kenya Women Finance Trust (KWFT) Limited – micro enterprise loans Kenya Industrial Estate (KIE) – industrial development capital Agricultural Finance Corporation (AFC) – financing rural agricultural activities Non Governmental Organizations CARE International Kenya – agriculture and health Oxfam International – poverty and injustice Agricultural Cooperative Development International and Volunteers in Overseas Cooperative Assistance (ACDI/VOCA) – agriculture (e.g. Kenya maize development programme)


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8 Summary and conclusion 8.1 Summary

In this paper, we have reviewed literature on poverty, economic growth and income inequality. The poverty-growth-inequality triangle (PGI), as it is sometimes called, is a complex interrelationship, which poses a challenge to development policy analysts and policy makers. The complexity emanates from the nature of relationships among the variables and their causality which can run in different directions (Ag’enor, 2005).

A number of observations emerge from the literature review and the situational analysis of economic growth, poverty and income inequality in Kenya.

• Kenya’s economic growth rates recovered from 2003. However, the rates were below 7 per cent, the estimated rate needed to meet the first MDG of halving the number of people in absolute income poverty by 2015.

• The incidence of poverty in Kenya declined between 1997 and 2005/2006. However, at 46 per cent it is still high. There is also wide variation in the incidence of poverty across regions and socio-economic groups.

• Many reasons have been put forward to explain why poverty in Kenya is high, including lack of income earning opportunities, inadequate human capital investments, unfavourable agro-climatic conditions, HIV-AIDS pandemic and weak implementation of antipoverty interventions.

• Countries that have recorded high and sustained economic growth have managed to reduce poverty substantially. However, evidence suggests that economic growth does not translate one-to-one in poverty reduction. Changes in poverty depend not only on economic growth but also on changes in income inequality. Recent data for Kenya shows that the Gini coefficient was 0.447 in urban areas and 0.380 in rural areas. It is also interesting to note that these estimates are lower than those for 1997, and that during this time, poverty declined. This suggests that the poverty reducing impact of growth was relatively strong.

• Some evidence suggests that the pattern of economic growth is also important. That is, the sectoral composition of growth has bearing on poverty-reducing capacity of growth.

• High initial inequality in assets and income is likely to undermine growth and hence poverty reduction efforts. Although changes in poverty depend on economic growth and changes in income inequality, the responsiveness of poverty to these variables depends on the degree


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of initial inequality. According to Bourguignon (2004), given these relationships, the optimal economic growth-income distribution policy mix would have to vary across countries. Changing income distribution is more important for reducing poverty in better off and highly unequal economies, while economic growth is relatively more important for poverty reduction in countries with low average incomes and low inequality.

• There are many policies and programmes aimed at poverty reduction in Kenya. These initiatives emanate from the government and other stakeholders and are in various sectors.


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8.2 Addressing poverty and inequality

Accelerate and sustain economic growth in Kenya

It is clear from the literature that countries that managed to reduce poverty substantially had high rates of economic growth. Therefore, it is essential for Kenya to promote growth. However, while economic growth is necessary for poverty reduction, it is not by itself sufficient. Poverty alleviation efforts are more successful when accompanied by not only growth policies but also distributional policies that reduce inequality. To this end, it is noteworthy that the Vision 2030: MTP flagship programmes and projects are mainly targeted towards the poor. The plan identifies social programmes, welfare programmes, and targeted poverty programmes and projects as some of its priority intervention areas. The World Bank (2008) has proposed a strategy to accelerate and sustain high growth rates based on reducing business risk and improving infrastructure.

Removal of factor price distortions in markets

Formulate and implement policies to improve functioning of input markets (e.g. markets for farm inputs, labour and capital) and product markets. In particular, reforms should remove constraints (such as high transport costs) that prevent the poor from taking advantage of markets to improve their welfare. Improvement in the functioning of markets for farm inputs can contribute to higher farm incomes to poor farmers and employment opportunities for those without land. This will enable the poor participate fully in rural markets for agricultural products and for labour. Improving incomes in rural areas will narrow the urban-rural income gap and help stem rural-urban migration, which gives rise to increased urban unemployment and poverty.

Promote better linkages between markets

Because the poor participate in multiple markets, better linkages between markets can improve their participation. For example, better linkages between farm and off-farm activities and rural and urban markets would permit beneficial spillover effects from one market to another. Assuming the economy grows as envisaged in Vision 2030, the benefits of growth must reach the poor if growth is to contribute in reducing poverty. In this context, isolated markets would be a hindrance to poverty reduction. Better infrastructure and dissemination of market information can facilitate linkages.

Target activities where majority of the poor participate

Studies in Kenya show that the poor are mainly in rural areas and are engaged in agricultural activities. In urban areas, the working poor are found in informal sector activities. Pro-poor growth should focus on the activities in which the


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poor participate directly. For example, programmes, projects for enhancing productivity in agriculture and livestock sector could have large payoffs in terms of poverty reduction since they would cover large segments of the poor.

Redistribution of asset ownership/user rights

Two types of pro-poor land reform may be distinguished (Mwabu and Thorbecke, 2004). The first type is one that redistributes land from land owners with large parcels of land to small scale farmers operating either under private or communal land tenure system. However, a large fraction of the poor might not benefit. The second type of land reform involves changing the land tenure system or land use rights to give poor people the right to own or use land. An institutional framework to lay out conditions for land ownership and land use, such as leasehold contracts or share tenancy contracts is required. In addition, land reform must be accompanied by complementary measures to ensure farmers get farm inputs and market their produce.

Implement policies to check inequality

Rural-based growth is usually accompanied by improved distribution of assets and income (Mwabu and Thorbecke). Since literature suggests that income inequality is not good for poverty alleviation, rural-based growth can contribute to poverty reduction. In addition, use of progressive income and wealth taxation can also contribute towards reducing income inequality and poverty.

Apart from income inequality, other forms of inequality may also hinder poverty reduction. Within Sen’s capability approach, there is need to improve the capabilities of the poor to function through investments in human capital. These would improve their capabilities to be healthy, literate and to work.

Use of public transfers, goods and services

Increased investment in human capital through provision of basic social services can generate relatively higher returns for the poor than the non-poor, because of relative scarcity of human capital stocks. Moreover, investments in human capital will enhance the productivity of the resource that the poor have in abundance-their labour. Better health and increased proportion of the literate population can contribute to productivity improvements in farm and non-farm income generating activities. Poverty is concentrated in areas with certain agro-climatic conditions, such as arid and semi-arid areas. Provision of water for domestic use and other investments in livestock sector can enhance productive capacity.

Empowering the poor


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Since economic decisions are related to the power balance, it is essential for the poor to be fully accommodated in decision-making. This will not only enable them articulate their needs but also enhance ownership of projects and programmes meant to improve their welfare. Within Sen’s capability approach, the poor’s capability to be politically active and to participate in decision making fora should be enhanced. For example, the use of devolved funds can benefit from the input of those they are meant to assist.

Encourage development of insurance mechanisms for the poor

While risk and uncertainty are pervasive in many economic and social settings, the poor often have limited capacity to handle shocks (health, economic) and natural calamities. Consequently, poverty eradication initiatives should include mechanisms to build the capacity of the poor to handle shocks. For example, improved storage of grain on the farm can improve food security to smooth consumption. The strengthening and support of local community groups and organizations can also help.

Conduct research to inform policy design and implementation

There is relatively little empirical evidence on growth and poverty relationship. A research agenda should be developed on this topic to bring about deeper understanding of the link between poverty, economic growth and income inequality in Kenya. In particular, there is need to ensure that all antipoverty alleviation projects and programmes include evaluation in their design and implementation.

A key question regards where to focus development policy i.e. whether a country should place more focus on economic growth, or poverty and/or inequality. In this respect, the argument by Bourguignon (2004) is compelling. He points out that: (i) the rapid elimination of absolute poverty, under all forms, is a meaningful goal for development; and (ii) to reduce absolute poverty rapidly requires strong, country-specific combinations of growth and distribution policies. To be efficient and growth-enhancing, redistribution should be concerned with wealth rather than current income of consumption expenditures. This efficient redistribution can be achieved by correcting credit markets imperfections, lowering the tax rate, or freeing other distortionary income redistribution mechanisms.


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Appendices

Appendix Table I: Indicative sector presence of KJAS partners (on poverty alleviation related programmes, projects, and initiatives) 10 10 The abbreviations used in the appendix tables are: African Development Bank (AfDB); Acquired Immunodeficiency Syndrome (AIDS); European Commission (EC); Global Environment Facility (GEF); Human Immunodeficiency Virus (HIV); Human Resource

Current List of Sector Groups

AfD

B

CAN

ADA

DEN

MAR

K

EC

FRAN

CE

FIN

LAN

D

GER

MAN

Y

ITAL

Y

JAPA

N

NET

HER

LAN

DS

NO

RWAY

SPAI

N

SWED

EN

UK

UN S

YSTE

M

US

WO

RLD

BAN

K

Agriculture and Rural Development � � � � � � � � � � � � � Democratic Governance � � � � � � � � � � � � � Education � � � � � � � � � � � � � Energy � � � � � � � � � Environment � � � � � � � � � � � � Gender � � � � � � � Health and HIV/AIDS � � � � � � � � � � � � � � Land � � � � � � � Private Sector Development � � � � � � � � Roads and Transportation � Urban, Local Government Decentralization � � � � � � Water and Sanitation � � � � � � � � � � � � � Statistics and M&E � � � � � Social Protection � � � � � � � Public Service Reform � � � � � � � � Public Financial Management � � � � � � � � � � �


58

Source: Kenya Country Strategy Paper/National Indicative Programme, 2008-2013

Development (HRD); International Fund for Agricultural Development (IFAD); International Food Policy Research Institute (IFPRI); International Institute of Rural Reconstruction (IIRR); Japan International Cooperation Agency (JICA); Kenya Joint Assistance Strategy (KJAS); Monitoring and Evaluation (M&E); Organization of the Petroleum Exporting Countries (OPEC); United Kingdom (UK) and the United States (US).


59

Appendix Table II: Indicative sector presence of non-KJAS partners (on poverty alleviation related programmes, projects, and initiatives)

Current List of Sector Groups

CARE

KEN

YA

CLIN

TON

FO

UND

ATIO

N

GEF

GLO

BAL

FUN

D

IFAD

IFPR

I

IIRR

JICA

OPE

C FU

ND

FO

R IN

TERN

ATIO

NAL

D

EVEL

OPM

ENT


60

Source: Kenya Country Strategy Paper/National Indicative Programme, 2008-2013 and URLs of the various organizations

Agriculture and Rural Development � � � � � Democratic Governance Education or HRD � � Energy Environment � � � � Gender Health and HIV/AIDS � � � � Land Private Sector Development Roads and Transportation � � Urban, Local Government Decentralization Water and Sanitation � Statistics and M&E Social Protection Public Service Reform Public Financial Management Emergency and Relief Operations �

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