A BUMPY RIDE TO PROSPERITY

Transcription

1 A BUMPY RIDE TO PROSPERITY Infrastructure For Shared Growth In Kenya

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3 August 2011 A BUMPY RIDE TO PROSPERITY Infrastructure For Shared Growth In Kenya Poverty Reduc on and Economic Management Unit Africa Region

4 TABLE OF CONTENTS ACKNOWLEDGEMENTS ACRONYMNS AND ABBREVIATIONS EXECUTIVE SUMMARY i ii iii 1. INTRODUCTION 1 2. INFRASTRUCTURE AND GROWTH Infrastructure and growth The state of Kenya s infrastructure Roads Electricity Water Access to infrastructure by geographic regions INFRASTRUCTURE AND HOUSEHOLDS INCOMES: WHAT MATTERS? Introduction Sources of household incomes Access to infrastructure for rural households Infrastructure and household income diversification Effects of income diversification on income and poverty CLOSING THE GAP: IS IT FEASIBLE? The Role of the National Budget in Closing the Spatial Infrastructure Deficits Constituency Development Fund Rural Electrification Program Levy Fund Local Authorities Transfer Fund Road Maintenance Levy Fund Emerging Lessons CONCLUSIONS AND RECOMMENDATIONS 33 REFERENCES 36 TECHNICAL APPENDIX 37 DATA ANNEXES 43 Annex I: Percent of households connected to electricity and piped water, by province and district 45 Annex II: Mean distance (km) to infrastructural facilities by province (pooled sample) 46 Annex III: Percent of households with electricity and water connection and mean distances (km) 46 to infrastructural facilities, by income diversification index (pooled sample) Annex IV. Share (%) of income sources in total household income across regions 47 Annex V: Effect of Infrastructure on Various Types of Diversification Index 48 Annex VI: Fixed Effects and Pooled OLS Model Results on Effect of Diversification on Income 49 Annex VII: Probit Estimation Results of Effect of Diversification on Poverty 50 Annex VIII: RMLF allocation and quality and quantity of road infrastructure stocks in Kenya t51 by districts

5 ACKNOWLEDGEMENT This report was prepared by a team led by Jane Kiringai. The core team comprised of Albert Mwenda, Catherine Gachukia, Caroline Wangusi, Fred Owegi, Laban Maiyo, Lucy Wariara, Othieno Nyanjom and Roger Sullivan. The household income analysis was led by John Olwande, Lillian Kirimi and Margaret Mathenge of Tegemeo Institute. The report was peer reviewed by Gabriel Demobynes and Cesar Calderon and also got some useful insights from Josephat Sasia, Dominic de Waal and Mits Motohashi. The team received guidance from Kathie Krumm and Wolfgang Fengler. The production of this report was funded by the Diagnostic Facility for Shared Growth. A BUMPY RIDE TO PROSPERITY i

6 ASAL CDF CDFB DI Note: Fiscal years, currency and equivalent units Fiscal year: 1 July -30 June Currency = Kenyan Shillings (Ksh) US$1.00 = Ksh 90 ACRONYMNS AND ABBREVIATIONS EIU ERC GDC GDP HHS IPP KENGEN KETRACO KM KNBS KNHA KPLC KRB KRRA KSH KURA LATF MWH NGOs OLS REA REPLF RMLF ROK Arid and Semi-Arid Land Constituencies Development Fund Constituencies Development Fund Board Diversification Index Economic Intelligence Unit Energy Regulatory Commission Geothermal Development Company Gross Domestic Product Households Independent Power Producers Kenya Electricity Generating Company Kenya Electricity Transmission Company Kilometers Kenya National Bureau of Statistics Kenya National Highways Authority Kenya Power and Lighting Company Kenya Roads Board Kenya Rural Roads Authority Kenya Shillings Kenya Urban Roads Authority Local Authorities Transfer Fund Mega Watt Hour Non Governmental Organizations Ordinary Least Squares Rural Electricity Authority Rural Electrification Programme Levy Fund Road Maintenance Levy Fund Republic of Kenya ii A BUMPY RIDE TO PROSPERITY

7 EXECUTIVE SUMMARY Physical infrastructure matters for growth in Kenya faces two challenges; a huge infrastructure deficit, and unequal access between regions and income groups. The spatial network of Kenya s infrastructure closely mimics pre independence investments, which targeted certain, high potential areas along the Northern corridor (Mombasa-Nairobi-Kisumu) tracking the railway line. After two decades of neglect, recent investments particularly for maintenance and rehabilitation have followed the same pattern as the original investments. Consequently, economic activities and opportunities are concentrated along the corridor and peters out as distance from the network increases. This report profiles the spatial pattern of infrastructure investments (roads, electricity and water), and offers some suggestions which can be used to inform future infrastructure investment decisions for more inclusive growth. Kenya has an extensive road network but less than half of it is in good condition. Kenya has an extensive road network (160,886 km), and investments during the last decade are reversing the declining trends observed during the previous two decades. Nevertheless, only 7 percent of the road network is paved (11,197 km), and less than half of the entire road network (42 percent) is in good condition (See Figure 1). Spatially, regional disparities are pronounced and road density broadly tracks population density and agricultural productivity. North Eastern, Coast and Eastern provinces have the lowest road density and the lowest population density as well, and can easily be classified as lagging areas. Access to improved water lags behind regional comparators. Figure 2 shows the strong positive relationship between access to water and income per capita. Access levels in Kenya lag behind in Sub- Sahara Africa and low income countries, and regional disparities are significant. Investments during the last two decades have not kept pace with rapid population growth, particularly in urban areas where access to piped water declined from 31 percent in 1999 to 30 percent in However, in the rural areas, access to improved water (dams, wells and boreholes) increased from 33 to 35 percent (See Figure 3). Trends in rural electrification are more promising but from a very low base. At the close of the last decade, 23 percent of households in Kenya had access to electricity, a remarkable increase from 13 percent in However, regional disparities in the country are significant; 31 percent of households have access to electricity in the best served province, five times more than the least connected province at 6 percent (See Figure 3). Unlike roads, electricity connectivity broadly tracks the share of urban population. Analysis shows that at the household level, access to infrastructure determines economic opportunities. Although crops are the main source of income in the rural areas, low income households tend to be more dependent on crops for livelihood. Households with access to infrastructure have diverse sources of income including wages and business activities. Figure 1: Kenya has an extensive road network (11 percent is in good condition). Nairobi Central Western Nyanza R. Valley Eastern Coast N. Eastern Road Density (km per sq. km) (Source : Kenya Roads Board 2010). Note: Data on Nairobi roads - by road condition - was not available. poor fair good A BUMPY RIDE TO PROSPERITY iii

8 The share of income from crops in households tend to decline as income levels increase. Low income households depend on crops and diversify into farming economic activities often as a distress push. High income households enjoy better access to infrastructure compared to low income households. Low income household dwellers travel twice the distance to access fertilizer and hybrid maize seed markets compared to high income households. Farm productivity increases as access to markets, hybrid seed and fertilizer improves. Road infrastructure increases labour mobility, thus, diversifying the sources of income. Electricity in trading centers increases economic opportunities outside farming activities. High income households have better access to water and electricity, and the gap to accessing these facilities between income groups has increased between 2000 and For growth to be broadly shared, rural households need to diversify their source of income to non-farming activities (including employment). Targeted infrastructure investments will be required, to increase agricultural productivity and opportunities outside farming. Should investment priorities focus on poor regions, or should the focus be where poor people live? How should the government prioritize investments on infrastructure? The government needs to have clear infrastructure investment criteria for both leading and lagging areas. The World Development report 2009 offers some guiding principles as follows: If lagging areas are sparsely populated as is the case in Kenya (see Figure 6), characterized by rural dispersed settlements, the priority should be to provide basic services such as primary health care, security, education, water and sanitation, rather than invest in expensive infrastructure. iv Figure 2: Access to improved water and incomes per capita. Population with access to improved water (%, 2009) On the other hand, if lagging areas are densely populated the priority should be on both investments in basic services and infrastructure, to open up markets and provide incentives for production. In a devolved government structure, the central government should target infrastructure investments to accelerate overall growth. Expensive infrastructure investments should be leveraged to open up markets where most poor people live. The constitution provides for Equalization Fund (0.5% of revenue) to provide for basic services including water, roads, health Income Total Household of Share (%) Kenya Middle & North Africa Sub Sahara Africa Figure 4: The share of crop income declines as household income increases. Sources of Household Income Lowest Highest Crops Low income countries Log of GDP per capita (Constant 2000 US$) (Source : Computations from Tegemeo data.) World Share of Income from salary Latin America & Caribbean (Source: Kenya Roads Board and Kenya national Bureau of Statistics). Share of Income from crops Quintile of Household Income Salary and remittance A BUMPY RIDE TO PROSPERITY

9 Figure 3: Kenya s Infrastructure is concentration along the northern corridor within a radius of the railway line. County Pattern of Infrastructure Development - Roads, Electricity and Water Turkana Mandera Marsabit West Pokot Wajir Samburu Trans Nzoia Elgeyo Marakwet Isiolo Bungoma Baringo Uasin Gishu Busia Kakamega Laikipia Nandi Meru Vihiga Siaya Kisumu Tharaka Nithi Nyandarua Kericho Nakuru Nyeri Kirinyaga Homa Bay Nyamira Embu Bomet Kisii Muranga Migori Kiambu Narok Nairobi Machakos Kitui Tana River Garissa Kajiado Makueni Lamu Kenya roads % access to electricity Class A Class B Class C Class D Kilifi Class E Railway % access to piped and portable water Counties Boundary Taita Taveta Lakes Kwale Mombasa Mombasa Kilometers (Source: Kenya National Bureau of Statistics Census 2009). A BUMPY RIDE TO PROSPERITY v

10 facilities and electricity to marginalised areas to the extent necessary to bring the quality of those services in those areas to the level generally enjoyed by the rest of the nation, so far as possible. markets where most poor people live, and social services are concentrated in the sparsely populated lagging areas. (See Figure 8.) However, in order to apply the World Development report 2009 framework, expensive infrastructure investments should be leveraged to open up Figure 5: High income households travel shorter distances to markets. Figure 6: Road density and population density define leading and lagging areas. (Km ) ance Dist Mean Distances (Km) by Income Quintiles Fertilizer market Hybrid maize market Lowest Highest Income Quintile Road Density 2.5 County Road and Population density Kiambu 2.0 Kisumu Kirinyaga 1.5 Muranga Nyeri Nyamira Nakuru Embu U. Gichu Kakamega Nyandarua 1.1 Migori 1.0 Machakos Bungoma Makueni Busia Siaya, Nandi Marakwet 0.7 Meru Kwale, Nithi Bomet Homabay Kisii Vihiga lagging areas Population density /Km (Source KNBS 2009 Census and Kenya Roads Board). vi A BUMPY RIDE TO PROSPERITY

11 1 INTRODUCTION

12 1. INTRODUCTION In an effort to reduce major constraints to Kenya s growth, the government has stepped up investments in infrastructure over the last decade (from about 3 to 4 percent of GDP). Investments in roads and energy have seen remarkable reductions in the distance to markets, services, and infrastructure, even for the poor. Consequently, economic growth has rebounded from an average of 2.1 percent during the last decade, to an average of 3.7 percent for the decade ending 2010, even after experiencing four severe shocks during this period. Despite these improvements, Kenya still faces two challenges: a huge infrastructure deficit and unequal access between regions and income groups. National level aggregates mask important differences which determine economic opportunities within regions. Concerns linger that the growth experienced during the last decade was not broadly shared. These concerns clearly surfaced in the 2008 political crises, and demonstrated that spatial inequality attributed to uneven access to public resources. Reforms in the constitution seek to address historical regional inequality to access public services and give increased attention to equalizing economic opportunities across different geographical regions through, for example, having decentralized funding structures. In this regard, the constitution provides for an equalization fund to improve access of public resources in marginalized areas. Reforms that improve equity in access will also need to take into account the limited fiscal space and the danger of spreading resources too thinly to have a meaningful impact in changing livelihoods, or improving the pattern of growth. For instance, in regions where population density and agricultural productivities are low, the unit cost of infrastructure provision increases, and return on investments decline. This report coincides with the implementation of Kenya s new constitution which provides for an equalization fund equivalent to 0.5 percent of total government revenue (0.1% of GDP) to provide basic services including water, roads, health facilities and electricity to marginalized areas. Should the equalization fund be invested in poor regions or where most of the poor live? The World Development Report 2009 has shaped the debate on regional development and argues for clarity between poor places and where most of the poor live. The case of roads and population density in Kenya is a good example. Figure 6 shows road density and population density. The figure shows that there is a positive relationship between road density and population density, and also the level of urbanization (size of the bubble) where economic activity is concentrated. The population density shows that in Kenya, few people live in the lagging areas and the investment choices are more complex compared to cases where most of the poor live in lagging areas. This report profiles the state of Kenya s infrastructure against regional comparators and provides an overview of the state of infrastructure by geographical regions. The report is structured in five parts. In section two, we use aggregate district level data to establish the spatial differences in access to different types of infrastructure (electricity, roads and water), and estimate correlation coefficients between district level poverty (incomes) and access to infrastructure. In the third section we use a three year panel household survey data-set for 2000, 2004 and 2007², to investigate the empirical link between access to infrastructure and household income diversification, and between income diversification and overall household income; including the type of infrastructure required for shared growth. In section four we discuss the institutional framework of infrastructure provision (political economy) and the state of infrastructure, particularly with regard to spatial differences in access. In section five, the report uses the World Development Report 2009 framework on territorial development as a rough guide for investments in infrastructure for shared growth as recommendations for policy. ¹ Several studies support this finding (Suri et al 2008; Chamberlin and Jayne, 2009; KPIA, World Bank, 2009). ² The panel data set is collected by Tegemeo Ins tute. 2 A BUMPY RIDE TO PROSPERITY

13 2 INFRASTRUCTURE AND GROWTH

14 2.1 INFRASTRUCTURE AND GROWTH The relationship between infrastructure and growth (household incomes) is complex. Existing evidence shows that infrastructure development, as measured by increased stocks and quality of infrastructure services, has a positive association with long-term growth and a negative correlation with income inequality (Aschauer, 1989; Calderon and Servin, 2008; Khandker et al, 2009a, Khandker et al, 2009b). Other studies have also shown that regional disparities in the quality and stock of road infrastructure may lead to disparities in farm wages, agricultural productivity, food availability, primary school completion rates, opportunities in non-agricultural activities and nonfarm activities among women (Khandker et al. 2006; Mu and van de Walle, 2007; Escobal and Ponce, 2002; Lokshin and Yemtsov, 2005). Kenya s pattern of growth suggests that although growth averaged 3.7 percent between 2000 to 2009, it was not broadly shared in the rural economy. The country has undergone a gradual economic transformation over the last four decades, which has seen the share of agriculture in GDP decline from one third (33 percent in 1969) to about a quarter (26 percent in 2009). The contraction of agriculture reflects the stagnation of the sector whose annual growth averaged 1.7 percent during the last decade, less than half the growth rate of the economy. During the same period, rural population growth rate averaged 2.5 percent, which means that on average rural incomes per capita contracted. Even as agriculture contracted, the rural economy has remained broadly agricultural. Agriculture contributes 60 percent of rural household incomes, while salaries and remittances account for 19 percent, and business and other informal activities contribute about 17 percent (see Figure 7). It is only in the Coast province where household incomes are broadly diversified and business activities contribute to the largest share of household incomes (about 41 percent). Economic growth in Kenya has been driven by services, whose share in GDP increased from about 40 to 60 percent during the last decade. Crops are the main source of income for rural households and the share is disproportionately high for low income households. Crop income accounts for 60 percent of rural household incomes and the balance is shared between wages and informal business activities (see Figure 7). The pattern of growth suggests that growth has been concentrated in urban areas where services have been vibrant. Access to infrastructure expands the opportunities to improve livelihoods. Rural infrastructure reduces the distance to input and Figure 7: Rural household incomes remain broadly agricultural and have stagnated while the rest of the economy has become more services oriented. Share (%) of Total Household Income a. Sources of Household Incomes in the Rural Economy National Average Coast Province Crops & Livestock Salary & remittance Business & informal labour activities b. Sector Contributions to GDP 70% 60% Services 50% 40% 30% Agriculture 20% 10% Industry 0% (Source: Tegemeo and Economic surveys). 4 A BUMPY RIDE TO PROSPERITY

15 output markets. It also increases farm productivity and opportunities to diversify into non-farm economic activities, including employment. In a study of African countries, Calderon (2009) found that there is a positive correlation between an increase in the stock of infrastructure (comprising of telecommunications, electricity, and road), and economic growth. There is a strong negative correlation between rural poverty on one hand, and the access to water, and electricity connection at trading centers, as well as road density. The converse holds true; distance to portable water is positively correlated with poverty. The correlation between electricity connections at household level and poverty is weak (see Table 1), but access to electricity is still relatively low, and could be below the minimum threshold to have a meaningful impact. The data also shows a strong correlation between infrastructure variables for instance between roads and electricity because most infrastructure facilities are provided along the road network, especially piped water, electricity and wired telephony. In summary, the data confirms that infrastructure matters for growth and access to it is unequal across Kenya between and within regions. Road density has the strongest negative correlation with district level poverty. District level data shows that by comparing the four infrastructure variables road density, distance to portable water, electricity connections to trading centers, and electricity connections to households road density has the strongest negative correlation with district level poverty. (See Figure 7). Table 1 and Figure 7 also show that the distance to portable water and poverty are positively correlated³. Ubiquitous access of households to electricity, though desirable, is far less catalytic for growth than connectivity at trading centers. Figure 8 presents the correlations between infrastructure and poverty in scatter diagrams. It shows that electricity connection to trading centers has a higher negative correlation with poverty than connections to households. Therefore, in making the choice between supplying households or trading centers with electricity, the latter would be a preferable option. At the national level, rural absolute poverty increases as the distance to portable water increases and some households have to travel more than 10 kilometers to get water. Table 1: Correlations between district poverty and access to infrastructure. Rural poverty Rural Poverty 1 House hold size 0.45* Access to piped water -0.56* Access to potable water -0.31* Distance (Km) to potable water 0.28* Electricity Connections (households) 3 Electricity Connections (Trading Total road Centers) density -0.49* -0.2 Arable land (Road density) Household size Access to piped water * Access to potable water * 0.47* Distance (Km) to potable water * * Electricity Connections (HH) Electricity Connections (Trading Centers) * 0.24 Total road density * Arable land (Road density) 1 *Correlation coefficient that reflect a strong association (Source: World Bank Staff Estimates). ³ The results are based on a simple Ordinary Least Squares es ma on A BUMPY RIDE TO PROSPERITY 5

16 Figure 8: Trading centre electricity connections have more impact on poverty than household connections. There is a negative relationship between poverty and access to electricity. The relationship is stronger for access to electricity at trading centers (-0.13 Figure a.) compared to access at households (-6) b.) a. Rural Poverty and Electricty at Trading Centers b. Rural Poverty and Electricity in Households a. Road Density and Rural Poverty (2006/06) Rural Household poverty 2005/ Rural Household Poverty 2005/ No. of trading centres with electricity conenctions District y= x Fitted values R^2=0.14 Rural Household Poverty 2005/ Rural Poverty Index Percent of households with electricty connections district Fitted values Y=4.1-6X : R2 =0.1 There is a negative correlation between rural poverty and road density (-0.2 Figure a.) but a positive relationship with distance to portable water (0.1 figure b.) b. Rural Household Poverty and Distance to Portable Water Total road density (km/sq km) Average distance to nearest potable water source (km) District y= x R^2=0.2 Fitted values district y= x Fitted values R^2=6 6 A BUMPY RIDE TO PROSPERITY

17 2.2 THE STATE OF KENYA S INFRASTRUCTURE Roads Kenya has a wide road network of 160,886 kilometers, but only 11 percent is in good condition. Only 7 percent of Kenya s road network (11,197 km) is paved, while the rest of it is unpaved and spread over large parts of the country that are underserved, representing a significant but unexploited economic development potential. About 56 percent of the road network is in poor condition which reflects many years of neglect and inadequate financing and maintenance. Kenya s stock of road infrastructure, as measured by the ratio of paved roads to total roads, falls below that of regional comparators. It even falls below neighboring countries with lower levels of GDP per capita, such as Rwanda and Uganda (see Figure 10). Compared to Kenya s main competitors, South Africa has more than double, while Egypt has ten times more paved road density. Provincial averages mask important differences within each region, and three clusters have been identified with regards to road infrastructure which can be used to inform policy actions. The first cluster is the low population density poor infrastructure comprising of the Rift Valley, North Eastern and Eastern provinces. The second cluster is the high population density and high agricultural productivity but medium connectivity areas consisting of Nyanza and Western provinces. The Central province clusters is an area with high population density and a relatively better road network. (See Figure 11) Electricity Rural investments in electricity, through the Rural Electrification Programme (REP), has seen a remarkable increase in access by households from 13 to 23 percent between 1999 and The REP strategy is to connect secondary schools, health facilities, community water projects, coffee factories, tea buying centers, and businesses operating in rural trading centers, to help open up opportunities for growth. Through the strategy, individual households are expected to make connections from the nearest point at an average cost of about US$ 500. This approach is clearly in line with the observation that electricity provision at trading centers has a stronger positive impact on incomes. Despite the REP strategy on rural electricity investments, regional differences in access are still significant. For instance, North Eastern and Western provinces have the same electricity connectivity at 6 percent, yet these provinces have very different demographic and agricultural potential profiles. On the high end are Coast and Central provinces which have access levels which are five times higher than North Eastern and Western provinces (see Figure 12). However, the lagging areas are also low population density areas, where the cost of provision is high and the pastoral lifestyle in North Eastern is not amenable to electricity provision. Kenya s access level at 23 percent is still below that of countries at a similar level of development (see Figure 10). In South Africa 70 percent of households have access to electricity, 46 percent in Nigeria, but closer home, Kenya is ahead of Tanzania and Ethiopia at eleven and fifteen percent respectively. Figure 9: 7 percent of Kenya s road network is paved and only 11 percent of the entire network is in good condition. (The country lags behind regional comparators.) 60% 50% 40% 30% 20% 10% 0% Status of Kenya's road Network 30% 55% 8% 3% 3% 1% good fair poor paved unpaved (Source: a. Kenya Roads Board (KRB) and b. World Development Indicators). A BUMPY RIDE TO PROSPERITY 7

18 Figure 10: Kenya s paved roads density lags behind key competitors and EAC member states. (Within the East Africa region, Kenya lags behind Uganda, Rwanda and Tanzania.) Egypt, Arab Rep. Density Population Botswana Uganda Rwanda South Africa Nigeria Ghana Ethiopia Tanzania Kenya Paved roads % of total roads Paved roads as a % of total roads Figure 11: Regional disparities are pronounced but road density closes tracks population density. County Roads and Population Density 2009 Bubble size shows share of urban Population in County (%) Road Density (Km per Square km) Vihiga Kenya s electricity supply network comprises of approximately 3,542 km of high voltage network and another 39,952 km of medium voltage network⁴. Kenya relies heavily on hydropower, whose supply is determined by seasonal rainfall patterns and is therefore unpredictable. However, rainfall determines the hydro power supply and in a good year the contribution can increase to 60 percent and drop to 32 percent in a drought year. For instance in 2008, hydropower accounted for 56.7 percent of the national power supply while thermal and geothermal power Kisii Nyamira Bungoma Kakamega Busia Murang'a Homa Bay Bomet Trans Nzoia Siaya Migori Kirinyaga Kericho Uasin Gichu Meru Nakuru Kilifi Samburu E. Marakwet Machakos Mandera T.Nithi T.Taveta Makueni Baringo (Source: Kenya Roads Board, Kenya National Bureau of Statistics Census 2009). 81 Kiambu Kisumu accounted for 33 percent and 10.1 percent respectively (see Figure 14). Broadly, Kenya seems to have the right approach with regard to rural electricity investments. Nevertheless, there is urgent need to pay attention to regional disparities, particularly in regions with high population density and high agricultural potential. In these regions, the return on investment would justify giving them a high priority in terms of ranking future investments Water Access to improved sources of water (wells and boreholes) has improved in Kenya over the last three decades. In 1999 rivers, lakes, and streams were the main sources of water for 40 percent of households. Trends show that investments over the past decade have been concentrated in wells and boreholes, as access from these sources increased from 21 percent of households in 1999 to 35 percent in Consequently, there has been a reduction in the number of households that draw water from rivers, lakes, and streams, from 40 percent in 1999 to 23 percent in 2009 (see Figure 15). However, access to piped water has declined nationally from 31 percent in 1999 to 30 percent in 2009 (Figure 15). Piped water remains an urban phenomenon where 53 percent of households have access to piped water compared to 16 percent for rural households (both into dwelling and within reach). Among the poor households, only 1 in 5 have access to piped water, compared to 2 in 5 in non-poor households. The non-poor and urban have better access to safe drinking water percent of poor households and 59.8 percent of non-poor households in Kenya have access to safe drinking water. Only 40.6 percent of poor households in rural areas access safe drinking water (KNBS, 2008). The proportion of population with access 8 A BUMPY RIDE TO PROSPERITY

19 Figure 12: Access to electricity has increased, but with substantial regional disparities (2009). County Pattern of Infrastructure Development - Electricity Turkana Mandera Marsabit Wajir West Pokot Samburu Trans Nzoia Isiolo Elgeyo Marakwet Baringo Bungoma Uasin Gishu Busia Kakamega Vihiga Siaya Laikipia Nandi Meru Kisumu Kericho Homa Bay Nyandarua Nyeri Nakuru NyamiraBomet Kirinyaga Garissa Embu Muranga Kisii Migori Tharaka Nithi Kiambu Narok Nairobi Machakos Kitui Tana River Makueni Kajiado Lamu % access to electricity Kilifi Taita Taveta Mombasa Kwale (Source: Kenya National Bureau of Statistics, and the 2009 Kenya Population and Housing Census). A BUMPY RIDE TO PROSPERITY Kilometers 9

20 Figure 13: Access to electricity has increased, but with substantial regional disparities (2009) South Africa Nigeria Botswana Sudan Kenya Ethiopia settlements, where majority of Kenyans live is a daunting task for any country due to the extensive costs. Providing potable water is not expensive. Given that there is still a sizeable population without access to potable water, the country s focus could be on improving access to this type of water. This would be particularly useful in regions where access to water is lagging behind other regions. Tanzania to improved water sources in Kenya is below the average for Sub-Saharan Africa. There are major disparities across regions in terms of basic coverage as well as quality of water. The proportion of households with access to piped water in Nairobi province is almost 11 times higher than that in Western province (see Figure 15). Most households in Western province use unsafe drinking water. Of all the non-urban provinces, only Central and Coast provinces have access rates of 40 percent or over. Providing piped water to dispersed rural Figure 14: Hydro-power is Kenya s principal source of power. Other Geothermal Power Thermal Power Hydro -power Electrification rate (% of population connected to electricity) (Source: World Bank, 2010 World Development Indicators and KNBS, 2010, The 2009 Kenya Population and Housing Census for Kenya).z 0.2% 10.1% 33.0% 56.7% 2.3 ACCESS TO INFRASTRUCTURE BY GEOGRAPHIC REGIONS Nationally, crops contribute to be the largest share of household income, followed by formal employment, business and informal labour activities, and livestock in that order. Across provinces, crops are the largest contributors to household income except in Coast province, where business and informal labour income contribute to the largest share (see Figure 16). Crop income is the most dominant source in all the districts, except Kilifi and Kwale, where business and informal labour income is leading. Other outliers include Mwingi, where salary and remittances is the principal source, and Nakuru, where income from livestock activities is the largest (See Annex IV for more details). The national income data shows that the relative share of income from crops and informal business activities declines, as overall income increases. The converse holds true for income from salaries and remittances; their relative share in total household income increases as overall income increases. Figure 16 shows that with the exception of the coast region, rural economy depends on crops for income, a characteristic of low income households. The coast region represents a complex case beyond the analysis of this report. % 1% 2% 3% 4% 5% 6% (Source: Kenya National Bureau of Statistics, Economic Survey 2009). In the rural sector, access to infrastructure closely matches agricultural potential. A relatively higher proportion of households with 10 A BUMPY RIDE TO PROSPERITY

21 access to electricity and water are found in the high potential maize zones and central highlands located in the Eastern, Central and Rift Valley provinces (see Annex I). Eastern lowlands in the Eastern province and Coastal lowlands in the Coast province have a relatively modest to high percentage of households with access to piped water, perhaps due to targeted efforts to provide water in these semi-arid areas. There is, however, a general decline in the proportion of households with access to piped water between 2000 and 2007, particularly in the Coast, and Rift Valley provinces. This is probably because other sources of water such as boreholes are becoming more dominant compared to piped water, as demand could have risen faster than supply. This finding is consistent with the findings in section 2 of this report. Household data shows that access to infrastructure closely matches agricultural potential. Access to electricity and piped water is relatively better in Eastern, Central and Rift Valley provinces (see Annex I). Over time, however, larger declines in the proportion of households with piped water are observed in Coast and Rift Valley provinces (household data confirms observations in section 2). Distribution by district shows that there are more households connected to electricity and water in Meru, Murang a and Nakuru districts. Also, the percentage of households with piped Figure 15: Access to piped water has been declining and is concentrated in urban areas. Other Pond/dam Well/Borehole Piped Lake/Stream/River/Spring water in Kilifi district is considerable, at 28 percent. The mean distances to water and electricity are greater in the Rift Valley and Coast provinces (see Figure 18) and least in Central Province, while for roads, the average distance to tarmac roads is greatest in Coast and Eastern provinces. Kenya has made progress in improving access to all types of infrastructure during the last decade. Since piped water and electricity are provided along the road networks in Kenya, roads become the most logical, visible starting point for infrastructure provision. Four distinct regional clusters emerge when roads and poverty are mapped in Kenya by geographical regions, and these strikingly resemble four countries. North Eastern and Coast provinces form the first cluster which maps closely with Moldova (per capita income, US$ 1302). The second cluster is the Eastern and Rift Valley provinces which maps closely with Armenia (per capita income, US$ 2878). The third cluster is Western and Nyanza provinces which lie between Vietnam (per capita income, US$ 1030) and Armenia. Central province is an outlier which maps closely with Costa Rica (per capita income, US$ 6368). (See figure 19). Kenya faces two challenges in providing infrastructure for shared growth. The first challenge is that the infrastructure deficit is huge and budgetary resources are limited (see section 4). The second challenge is that regional disparities are significant and the cost of provision increases in underserved areas where population density is low, particularly in the Coast and North Eastern provinces. Using economic criteria and cost benefit analysis, these regions have low priority ranking in infrastructure provision, although some 2009 strategic investments may be necessary 1999 if they were to have important beneficial returns. The next section uses the household panel data to estimate the relationship between infrastructure and household incomes. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% A BUMPY RIDE TO PROSPERITY 11

22 Figure 16: Access to piped water has been declining and is concentrated in urban areas County Pattern of Infrastructure Development - Water Turkana Mandera Marsabit West Pokot Wajir Samburu Trans Nzoia Elgeyo Marakwet Isiolo Bungoma Baringo Uasin Gishu Busia Kakamega Laikipia Nandi Meru Vihiga Siaya Kisumu Tharaka Nithi Nyandarua Kericho Nakuru Nyeri Homa Bay Kirinyaga Nyamira Embu Bomet Kisii Muranga Migori Kiambu Narok Nairobi Machakos Kitui Tana River Garissa Kajiado Makueni Lamu % access to water Taita Taveta Kilifi Kwale Mombasa Kilometers (Source: Kenya National Bureau of Statistics (KNBS), the 2009 Kenya Population and Housing Census). 12 A BUMPY RIDE TO PROSPERITY

23 I Figure 17: Rural households largely depend on crops; a characteristic of low household incomes. Figure 19: Spatial mapping of infrastructure and poverty. (Kenya is like four countries in one). ncome Shar e (% ) of T otal H ousehold Crops Salary and remittance Business and informal labour activities Livestock National Average Coast Province Rural Poverty (%) North Eastern Eastern Coast Rift Valley Road Density and Rural Poverty Bubble size = Population Density Armenia Moldava Vietnam Western Nyanza Costa Rica Central Road Density (km of road per 100 sq. km of land area) (Source: WDI, Kenya National Bureau of Statistics and Kenya Roads Board). Figure 18: Mean distance (km) to infrastructural facilities by province (pooled sample). a. Water b. Electricity Rift Valley Coast Nyanza Western Overall sample Eastern Central Rift Valley Coast Overall sample Eastern Western Nyanza Central Distance (Kms) Distance (Kms) A BUMPY RIDE TO PROSPERITY 13

24 14 A BUMPY RIDE TO PROSPERITY

25 3 INFRASTRUCTURE AND HOUSEHOLDS INCOMES: WHAT MATTERS?

26 3. INFRASTRUCTURE AND HOUSEHOLDS INCOMES: WHAT MATTERS? This section uses econometric methodology to analyze the links between infrastructure and changes in household income. The following questions are of special interest: (i). Does access to infrastructure lead to diversification of household economic activities on and off the farm? (ii). Does diversification increase household incomes? and, (iii). Which types of infrastructures matter? 3.1 INTRODUCTION Infrastructure plays a key role in the growth and development of an economy. It is argued that since infrastructure is good for growth, which leads to poverty reduction, then infrastructural investment and development are important for poverty reduction (Estache, 2003). Access to infrastructure can catalyze growth and poverty reduction in several ways. First, access to infrastructure leads to diversification of household economic activities, which in turn leads to higher household incomes. Second, access to infrastructure facilities such as transportation, water, electricity and communication improves access to input and output markets, and creates opportunities for non-agricultural incomegenerating activities in the formal and informal sectors. Third, distance to markets influences effective prices, and fourth, it improves access to basic services like health and education, which are essential for human development. Infrastructure can increase the farmers incomes directly by increasing agricultural productivity, which in turn reduces rural poverty (Fan et al 2004). This is mainly due to its supportive role to facilitate access to output and input markets, mobility of production factors, and also enhance the efficiency and productivity of production factors. There are also indirect impacts as a result of higher agricultural wages and improved non-farm employment opportunities arising from growth in agricultural productivity. In addition, increased agricultural outputs often lead to lower food prices, which helps the poor indirectly, because they are often net buyers of food. Infrastructure development directly promotes rural wages and non-farm employment, thus reducing rural poverty (Fan et al 2004). It helps poor individuals and underdeveloped areas to get connected to core economic activities, thus allowing them to access additional productive opportunities (Estache, 2003). Apart from contributing to growth, employment, and wages in the rural areas, infrastructure also helps the development of the national economy by providing labor, human and physical capital, cheaper food, and markets for urban industrial and service development (Fan et al 2004). This growth in the national economy leads to poverty reduction in both rural and urban areas. Several studies indicate that in Kenya, distances to various infrastructure facilities and services have generally reduced over the last decade, but regional disparities remain, (Suri et al 2008; Chamberlin and Jayne, 2009). What is less clear is how improved access to different types of infrastructure has impacted household incomes, and what types of infrastructure have the greatest potential to catalyze growth, and this will be addressed in this section. 3.2 SOURCES OF HOUSEHOLD INCOMES This section uses a three year household panel data collected in 2000, 2004, and The panel data was obtained through rural household surveys covering 24 administrative districts, 39 divisions, and 120 villages, using structured questionnaires. Standard proportional sampling using census data for rural divisions of the country formed the basis of extraction of the sample households. Due to the variation in agroecological patterns within the administrative units, the analysis stratifies households into eight agroregional zones based on relative homogeneity of agricultural activities within a zone and population density. The sample consists of 1,275 households which were consistently interviewed in the three 16 A BUMPY RIDE TO PROSPERITY

27 surveys. The number of the households in the eight agro-regional zones and the districts covered are provided in the Data Annexes, Table 1. The data collected over the years is quite broad, covering several aspects of household livelihoods. Detailed information on crop production, livestock and livestock products, and off-farm activities was collected, thus enabling the computation of household incomes. Information on crops grown, livestock types, and off-farm activities also provides measures of diversification both on and off the farm. The survey also contained detailed information on distances to various infrastructural facilities, such as distances to the closest stock points for fertilizer and hybrid maize seeds, as well as and the availability of extension and veterinary services, motorable roads, tarmac roads, piped water sources, electricity supply, and public telephones. Demographic information on the households was also collected. Descriptive analyses is used to show trends in diversification between 2000 and 2007, as well as how these trends have varied across different agro-regional zones over this period. In addition, partial correlation analyses are conducted to show the relationship between diversification and access to various infrastructural facilities. In addressing the question of whether infrastructure affects household incomes and levels of poverty, econometric analysis is conducted in two stages. The first stage seeks to determine the effect of infrastructure access on a household s diversification of its economic activities, using the fixed effects model (see the Technical Appendix for the methodology). Crops are the main source of income in the rural areas contributing to 46 percent of household incomes. We can identify four sources of income for rural households; crops, livestock, salaries and remittances, and informal business activities. Comparing the income streams, rural households depend disproportionately on crops, followed by salaries and remittances at 19 percent, business and informal labour activities (18.6 percent) and livestock (16 percent) take third and fourth positions respectively, (See Table 2 and Figure 20). The share of crop income declines as household income increases. High income households have balanced income portfolios compared to low income households. The diversification pattern across quintiles of income shows that crops account for the largest share in household income but this share declines as income increases. On average, crop income contributes to 54 percent share in low income households, compared to 43 percent in high income households (see Figure 20). Table 2: Share (%) of income sources in total household income by quintiles of income. Quintile of Household Income Crops Livestock Salary and Remittance Business and Informal Labour Activities Lowest Highest Total (Source: Tegemeo Institute). A BUMPY RIDE TO PROSPERITY 17

28 Figure 20: High income households have more diversified sources of income compared to low income households. Income Income 6 5 Household Total Household Total Share (%) of 5.0 Lowest Highest Quintile of Household Income Share (%) of 1 Lowest Highest Quintile of Household Income Livestock Business and informal labour activities Crops Salary and remittance (Source: Tegemeo Institute). The share of income from wages and salaries is higher for high income households. A reverse pattern can be observed with regard to incomes from salaries and wages: high income households enjoy the highest income contribution from salaries and wages at 24 percent compared to 13 percent for low income households. Statistical test showed significant differences in the mean shares of all income sources between the lowest and highest income quintiles (see Figure 21). Low income households depend on crops and informal business activities. Figure 21 shows that for the low income household, crops and informal business activities are the most significant sources of income. On the other hand, the relative share of income from livestock and salaries, and remittances increases as overall income increases. Intuitively, livestock represents household asset ownership while salaried employment represents human capital endowments, which are limited to low income households. High income households have higher income diversification index. There is a positive relationship between income diversification and levels of household income, low income households are less diversified but are catching up. The percentage change in household income diversification index is highest for the lowest income quintile, and lowest for the highest income quintile, see Figure ACCESS TO INFRASTRUCTURE FOR RURAL HOUSEHOLDS Access to infrastructure improved for all households between 2000 and Over the last decade the mean distances travelled by households have remarkably declined for electricity, motorable road and input (fertilizer and hybrid maize seed) markets. Although the mean distance to piped water has generally declined, the trend during the seven-year period does not show a consistent pattern. Mean distance to tarmac road, on the other hand, has marginally declined. In general, these results suggests that households have improved access to infrastructure over the 2000 to 2007 period, see Table 3. High income households have better access to water and electricity, compared to low income households. The mean distance to water and electricity is significantly lower for the highest income quintile than the lowest income quintile, and the difference is significant. The gap in access between low and high income households 18 A BUMPY RIDE TO PROSPERITY

29 Figure 21: Rural Low income households depend mainly on crops and informal business activitieshouseholds largely depend on crops; a characteristic of low household incomes. Household Income Total of Share (%) c. Sources of Income by Quintile Crops Livestock Lowest Highest Income Quintile Figure 22: During the last decade even low income households have also become diversified. Index Income Diversification (Source: Tegemeo Institute) Year Lowest Highest quintiles and the difference is significant, see Figure 23. The mean distance to fertilizer and hybrid maize seed market is shorter for highest quintile than for the lowest quintile. However, the average distance to the nearest road and shopping centre is the same for all income groups. Perhaps the regional profiles could provide some useful insights since Table 3 shows a negative correlation between distance to motorable roads and household income. 3.4 INFRASTRUCTURE AND HOUSEHOLD INCOME DIVERSIFICATION Access to motorable roads permits catalyzes income diversification. An increase of one kilometer in distance to motorable road results to 1 percent drop in crop as well as off-farm income diversification index. Only motorable roads matter for income diversification, see Table 4. This implies that better access to a motorable road does result in enhanced diversification for crop and off-farm activities. This result is consistent with a prior expectations that households closer to a motorable road may have better access to markets and other services, and hence, more likely to diversify both their crop and off-farm income portfolios. A similar result is observed for tarmac road, whereby the shorter the distance to a tarmac road, the higher the diversification especially for crops. also increased between 2000 and 2007 (See Figure 23). Electricity and water connections to high income households increased, but declined for low income households. For electricity and water (piped), the initial investments are high and maybe out of reach for a majority of low income households. High income households travel shorter distances to fertilizer and input markets. The average distance to fertilizer vendors and hybrid maize seed markets declines across income Improved access to electricity and water is associated with more household income diversification. Access to infrastructural facilities also varies by household income diversification (see Figure 25a). This finding also holds true in terms of the distance to a tarmac road and input markets (see Figure 25b). Households that have broadly diversified sources of income travel shorter distances to fertilizer and other input and output markets, and are also located closer to tarmac and motorable roads (see Figure 25b and Annex III for more details). A BUMPY RIDE TO PROSPERITY 19

30 Table 3: Trends in household access to infrastructure. Infrastructure % of households with electricity connection % of households with piped water connection Mean distance (km) to electricity Mean distance (km) to piped water Mean distance (km) to motorable road Mean distance (km) to tarmac road Mean distance (km) to fertilizer market Mean distance (km) to hybrid maize seed market Mean distance (km) to shopping center Access to water and electricity has a limited impact on diversification of crop and non-farm economic activities. Although not statistically significant, regression results suggest that improved access to water and electricity does not positively impact on the level of households diversification in respect to crop farming, offfarm activities, and overall income generating activities. This implies that households with better access to these facilities do not diversify their income portfolios as much. Although a bit of a surprising result, it is possible that most of the income activities in rural areas are manual and few require electricity. Besides, access to electricity in the rural areas is too low to have any meaningful impact. Table 4: Mean distance (km) to infrastructural facilities by income quintile (pooled sample). Motorable Tarmac Fertilizer Hybrid Shopping Income quintile Water Electricity road road market maize centre market Lowest Highest Overall sample A BUMPY RIDE TO PROSPERITY

31 Figure 23: Non poor households have better connectivity to electricity and water, and the gap widened between 2000 and Households Connected to Electricity 35.0 Households Connected to Piped Water Percent Percent Year Year Income poor Income non -poor Income poor Income non -poor (Source: Tegemeo Institute) Distance to input suppliers (fertilizer and hybrid maize seed markets) do not significantly impact on any of the diversification indices. This is not surprising since networks of agricultural input suppliers have expanded over time. Access to inputs is increasingly becoming a function of the ability to purchase and not necessarily proximity. As expected, better access to extension services does significantly increase diversification of crop activities. In terms of demographics, households with younger heads do diversify into more off-farm activities compared to those with older heads. This however, only happens up to a certain age after which off-farm diversification increases with Figure 24: High income households travel shorter distances to fertilizer and hybrid maize markets, but the distance to the shopping centre and tarmac roads is the same. Distance to Input Markets Distance to Tarmac Road and Shopping Center Distance (Km) Fertilizer market Hybrid maize marke Lowest Highest Distance (Km) Tarmac road Shopping centre Lowest Highest Income Quintile Income Quintile (Source: Tegemeo Institute) A BUMPY RIDE TO PROSPERITY 21

32 Figure 24: Access to infrastructure increases income diversification. Comparing cumulative public spending on REP and percent of households with electricity connection by districts. Percent a. Percent of Households with Connection to Electricity and Water Distance (Km) b. Average Distance to Roads (Km) (Lowest) 2 3 (Highest) Coast Eastern Rift Valley Nyanza Western Central Tercile of Diversification Index Province Electricity Water Motorable road Tarmac road age, a result that could imply that a reduction in off-farm activities is determined by the age of the household head; up to the point where his/her off springs take over some of the activities, which also explains the u-shaped curve (see Annex ). 3.5 EFFECTS OF INCOME DIVERSIFICATION ON INCOME AND POVERTY High crop diversification is associated with low crop income, and low income households diversify income sources as a survival strategy. The fixed effect regression model results indicate that increased overall diversification is associated with low total household income per adult equivalent, suggesting that households with low income diversify more as a survival strategy (see Table 5, Column i and iv). Crops account for almost half (46.3 percent) of household incomes, but crop diversification is associated with low crop income. This could explain the negative correlation between income diversification and total household income. Although crop income is positively and significantly correlated with productivity, evidence suggests that the link to productivity gain is not through crop diversification (see Table 5, Column iii and vi). These results are consistent with findings of a study by Kimenju and Tschirley (2009) that higher income households are more specialized in both cropping and broader livelihood activities. Crops diversification is associated with a higher probability of being poor (see Table 5). This is consistent with the previous finding that crops diversification has a negative impact on crop income, and further emphasizes that crops diversification among the households is a distress push, and the poor are more inclined to diversify more. Overall income and off-farm diversifications have a negative effect on the probability of being poor. However, their effect is not significant. The other variables that have a negative and significant effect on the probability of a household being poor includes crop productivity, a male household head, membership in farmer groups, rainfall and the education level of household head. Numbers of male and female adults in a household have negative and significant effect on total income, a result which is counter-intuitive and deserves further examination. In addition, variations in agricultural potential have significant bearing on poverty among the rural households in Kenya. See Annex VII for more details. The analysis suggests that: 22 A BUMPY RIDE TO PROSPERITY

33 Greater diversification in off-farm activities is associated with higher off-farm income, suggesting that households make a deliberate choice of engaging in off-farm activities which have relatively higher returns (see Table 5, Column ii and v). Roads and electricity at trading centers open up opportunities for non-farm income generating activities. The link between infrastructure and farm incomes is through access to hybrid seed and fertilizer markets, which increase crop productivity. Diversification of crops is not beneficial and actually reduces productivity. The overall access to motorable roads is important for income diversification, which leads to an increase in overall household incomes. Geographically there are remarkable differences in access to road infrastructure, which determines the opportunities for farm and nonfarm activities. A strategy for inclusive growth would pay urgent attention to motorable roads for all geographic regions. Figure 26: Access to Motorable roads varies by geographic regions b. Average Distance to Roads (Km) Distance (Km) Coast Eastern Rift Valley Nyanza Western Central Province Motorable road Tarmac road (Source: Tegemeo Institute) A BUMPY RIDE TO PROSPERITY 23

34 24 A BUMPY RIDE TO PROSPERITY

35 4 CLOSING THE GAP: IS IT FEASIBLE?

36 4. CLOSING THE GAP: IS IT FEASIBLE? Kenya inherited a small stock of superior class roads, concentrated along the north corridor but successive governments failed to improve the length and quality of the road network. Because of the historical nature of Kenya s initial infrastructure investments which targeted certain high potential areas, and the subsequent neglect of these investments, a great deal of Kenya s infrastructure resources in recent years, especially for maintenance and rehabilitation, has followed the same pattern as the original investments. These investments tend to be along the main national transport corridors or in urban areas with good resources and diversified economies, and have been a source of growth, though not always on an equitable basis. Despite successful early efforts to increase access for all regions, especially to potable water, access to water in the present day is characterized by service quality deterioration and glaring disparities as water access ranges between 51 to 72 percent, while sanitation access ranges between 15 to 56 percent. With regards to electricity, having enhanced its selfreliance in domestic generation, Kenya has only marginally diversified away from drought-prone hydro-electric power (HEP) which accounts for nearly 60 percent of electricity supply. Yet even existing power supplies have barely reached rural Kenya, where the majority of the country s population resides. Establishment of the Rural Electrification Authority (REA) in 2007 to broaden the national electricity outreach has not achieved intended results, as Kenya s domestic electricity uptake trails that of its comparators (for example Ghana and South Africa), and the average for Sub-Saharan Africa. The government initiated reforms during the last decade to restructure the institutional framework for infrastructure provision and to eliminate capture by political elite. The reforms also aimed to mainstream the management and administrative frameworks through reforms in public procurement processes and financial management. The other reform objective was to establish financing frameworks to facilitate a more equitable distribution of resources. The reforms necessitated the creation of new institutions (see Box 1). In the roads sector, reforms saw the establishment of the Kenya Roads Board (KRB), the Roads Maintenance Levy Fund, the Kenya Urban Roads Authority (KURA), the Kenya Rural Roads Authority (KRRA), and the Kenya National Highways Authority (KNHA). In the energy sector, the Energy Act of 2006 introduced a new institutional framework that clearly delineates the functions of generation, distribution, regulation and policy formulation for the electric power sector. In the water sector, the Water Act 2002 sought to reduce excessive executive control in the management of water resource by removing the function of service provision away from the Government to the seven Water Services Boards. These reforms also sought to improve efficiency in service delivery and reduce regional disparities in access to water. The reforms have had mixed results as demonstrated in previous sections of this report, but the new constitution offers hope for genuine reforms. Kenya s old constitution vested the Executive (the Presidency in particular) with disproportionate authority to influence the country s planning, budgeting, auditing, and implementation of public investment programs, including infrastructure investments. The new constitution, if expeditiously rolled out, could improve the scope for greater scrutiny in the management of public resources, thus promoting more equitable distribution of physical infrastructure investments across the country. Pertinent areas of the constitution that could help achieve this include the Bill of Rights, the structure of devolution, and sections on public finance. 26 A BUMPY RIDE TO PROSPERITY

37 Box 1: Key Reforms in the Infrastructure Sector The Water Act of 2002 introduced Water Services Boards which are empowered by the Act to appoint water companies, NGOs, institutions and community owned schemes to improve governance. The Water Services Boards and their appointed service providers are regulated by the Water Services Regulatory Board. A Water Resources Management Authority is to manage, regulate, apportion and conserve water resources. The Act further provides for the establishment of consumer based associations Water and River Users Association to provide avenues through which consumers interests can be articulated. The Kenya Roads Act, 2007 introduced institutional reforms in the roads sector, which led to the establishment of three independent agencies to oversee the management of various categories of roads. These agencies include: i) the Kenya National Highways Authority (KNHA) which is in charge of class A, B and C roads; ii) the Kenya Urban Roads Authority (KURA) which oversees the development and maintenance of urban roads, and the Kenya Rural Roads Authority (KRRA) which is in charge of rural roads. The law requires the Kenya Roads Board to distribute, through KRRA, 5.5 percent of the Roads Maintenance Levy Fund equally to all districts. The Energy Act of 2006 introduced a new institutional framework which comprises the Kenya Electricity Generating Company (KENGEN) which is in charge of power generation; the Kenya Power and Lighting Company (KPLC) which oversees electricity transmission and distribution; the Energy Regulatory Commission (ERC) which regulates wholesale and retail tariffs, issues licenses, formulates and enforces environmental, health, safety, and quality standards and the Rural Electrification Authority (REA), established in 2007, which is in charge of planning rural electrification development (see more below). Currently, there are also a few Independent Power Producers (IPPs). In 2007, the Rural Electrification Authority (REA) was established to broaden the national electricity outreach, targeting its investments on rural public facilities, i.e. dispensaries, schools, etc. The expectation was that once these facilities are connected, households would be able to make the needed investment to connect their homes. In 2009 Kenya Electricity Transmission Company (KETRACO) was established with the mandate to plan, build, and operate new transmission assets. In 2009 the Geothermal Development Company (GDC), was created with the primary responsibility for determining the viability of geothermal resources through exploratory drilling and technical studies. A BUMPY RIDE TO PROSPERITY 27

38 4.1 THE ROLE OF THE NATIONAL BUDGET IN CLOSING THE SPATIAL INFRASTRUCTURE DEFICITS In Kenya, the financing of infrastructure projects is derived from various sources. These include: (i). Taxation; (ii). User charges; (iii). Debt (domestic and external); and, (iv). The private sector (through public private partnerships). Central government funding for physical infrastructure projects can be channeled through central government institutions or through grants to sub-national units of the government. Indeed the government in the last two decades has introduced governmental transfers (decentralized funds) that seek to narrow the regional disparities in volume and the quality stocks of infrastructure. Decentralized funds that are dedicated to financing physical infrastructure projects include the Road Maintenance Fuel Levy and the Rural Electrification Programme Levy Fund. There are other funds that are not dedicated to infrastructure projects but nevertheless finance some physical infrastructure programs. These include the Constituency Development Fund (CDF), and the Local Authority Transfer Fund (LATF). Local Authorities also finance infrastructure projects from own-source revenues. Investment in infrastructure, outside of telecommunication infrastructure, is largely driven by the public sector. Until the 2004/05 financial year, public investment in infrastructure development and maintenance had been insufficient, leading to the deterioration of the quality and the volume of stocks of infrastructure. During this period there was less emphasis on maintenance and repair of existing roads. Public spending on the maintenance and repair of roads did not exceed Ksh. 10 billion per annum. As a result, the quality of the road network deteriorated due to neglect. Moreover, non-adherence to technical standards and corruption also resulted in low quality roads. There has however, been an improvement recently with the annual budget for maintenance and repair of roads more than doubling to over Ksh. 20 billion in the 2010/11 financial year. In addition, there has been an increase in the allocation of funds for new roads, as well as the reconstruction and rehabilitation of existing ones. Today, the third largest allocation of public funds goes to physical infrastructure, after non-discretionary and education sector expenditure. Of the total public sector expenditure on physical infrastructure, roads take up the highest proportion (over 60 percent), followed by the energy sub-sector, which takes up between 20 and 30 percent (see Table 6). A significant proportion of funds for roads and energy sub-sectors are derived from the earmarked funds under the Road Table 5: Roads take up the highest share of total public budget for physical infrastructure. Share of Total Public Spending on Physical Infrastructure Sector (Percentage - %) 2004/ / / / /09* 2009/2010* Ministry of Roads Of which RMLF CDF Roads N/A N/A Transport Energy Of which REPLF Local Authorities N/A N/A Nairobi Metropolitan Total (Ksh Millions) 25,239 36,713 45,905 65, , ,377 % of GDP *Estimates (Source: Ministry of Roads; Rural Electrification Authority; LATF Annual Reports). 28 A BUMPY RIDE TO PROSPERITY

39 Maintenance Fuel Levy (RMLF) and the Rural Electrification Programme Levy Fund (REPLF). The Constituency Development Funds (CDF) and the Local Authorities contribution to infrastructure financing are not significant. CDF contributes approximately 2 percent of the total funding for infrastructure, while Local Authorities contribute on average 1 percent every financial year. 4.2 CONSTITUENCY DEVELOPMENT FUND The water and roads sectors take up the second (12.5 percent in 2007/08) and third (8.5 percent in 2007/08) largest share of the annual CDF budget estimated at 14 billion in the 2010/11 financial year. There has been little or no CDF monies spent on electricity infrastructure. Annual CDF budget allocations are less than 3 percent of the total annual central government budget, and are therefore unlikely to have a major impact in bridging the country s infrastructure gap. The CDF was established through the CDF Act of 2003 to provide development project funds at the local constituency level, and to redress imbalances in regional development. The CDF annual allocation is based on a formula where 75 percent of the money allocated is divided evenly among the constituencies, and the other 25 percent is allocated to constituencies based on their poverty ranking, using a formula which ensures that the poorer constituencies receive more money. The CDF is typically used to finance many small projects at the local level. Projects that have been financed by CDF include construction of classrooms, water supply systems, dispensaries and roads. The CDF is too small to finance expensive infrastructure. Despite getting higher per capita CDF allocations annually, the poorer constituencies in the arid regions of Kenya (ASAL constituencies) on average spend less on road infrastructure relative to urban districts and other high potential rural districts. As Figure 26 shows, the vast ASAL constituencies spent lower proportions of CDF allocations on roads compared to the non-asal constituencies. As a result, stocks of infrastructure in the ASAL regions are smaller and of lower quality compared to infrastructure in urban areas and other high potential constituencies. This further widens regional disparities in the quality and quantity of road infrastructure stocks. 4.3 RURAL ELECTRIFICATION PROGRAM LEVY FUND The size of a district s population appeared to be the governing factor in allocations from the Rural Electrification Programme Levy Fund (REPLF), regardless of the district s poverty profile or the proportion of households connected to electricity. The REPLF was established in 1998 Figure 27: Average share of LAs expenditure on roads, 2003/ /08. Km ) Land Area (Sq. 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10, ,000-20, R² = 85 Proportion of CDF spent on Roads (%) A BUMPY RIDE TO PROSPERITY 29

40 following the enactment of the Electric Power Act of 1997, with the objective of financing electrification of rural and other underserved areas. As noted in Figure 27, there is a positive correlation between district households with electricity connection and the per capita REPLF allocation. As with the CDF allocation, the vast ASAL districts received lower allocations from the REPLF. Districts in high potential rural areas, such as Embu and Muranga, though covering a relatively smaller land area, received higher REPLF allocation than ASAL districts in Coast and North Eastern provinces (e.g. Tana River and Marsabit) which cover a wider geographic area. 4.4 LOCAL AUTHORITIES TRANSFER FUND The Local authorities contribution towards total public finance for infrastructure is extremely low, averaging 1 percent of total public spending on physical infrastructure. Local authorities derive revenues primarily from two broad sources: (i). own source revenue, through fees, rates and taxes, and (ii). grant transfers from the Local Authorities Transfer Fund (LATF) and the RMLF. Administration expenses take up a significant proportion of the local authorities revenue and make up over 30 percent of the local authorities expenses. Roads expenditure account for approximately 11 percent (2008/09), which is the third highest after administration and water expenses. Of the total amount spent on roads by local authorities, a significant proportion is spent in urban centres. For example, in 2007/08 almost half (47.2 percent) was spent in one local authority Nairobi City indicating that financing of the development of infrastructure stocks is highly skewed in favour of the large urban centres (see Figure 28). As a result, there is growing concentration of economic activities in these urban centres. Expenditure on roads by local authorities depicts a pattern similar to that in CDF and REPLF. The smaller the geographical size of a local authority, the higher the proportion of the local authority budget spent on roads. As a result, the volumes and quality of road infrastructure is better in urban areas than in rural areas. In short, the amounts local authorities set aside for infrastructure projects in the rural areas is not sufficient to generate any impact on economic growth and development. Figure 26: Average share of LAs expenditure on roads, 2003/ /08. Cumulative public spending on Rural Electrification Program (KSh M illions) R² = % of HHs with Electricity Connection (Source: Authors Construction based on Rural Electricity Authority; KNBS, 2007b). 30 A BUMPY RIDE TO PROSPERITY

41 4.5 ROAD MAINTENANCE LEVY FUND Approximately 40 percent of the RMLF annual allocation goes to international and national trunk and primary roads, while 32 percent goes to rural roads and 15 percent to urban roads. The balance is allocated to operations of the Kenya Roads Board (2 percent), Kenya Wildlife Services (1 percent), and 10 percent for emergencies and support of the Road Sector Investment Programme. The RMLF was established in 1993 through the Road Maintenance Levy Fund Act. The RMLF finances both classified and unclassified roads under the supervision of the central government or local authorities. The fund is derived from a fuel levy on petroleum products, and is administered by the Kenya Roads Board, established in In the past RMLF was used exclusively for maintenance of existing roads. The Kenya Roads Act 2007, however, allows for allocation of up to 10 percent of the fund for roads development. 4.6 EMERGING LESSONS Decentralised funds are spread too thinly across districts, and the amounts spent on infrastructure are too low to bridge the infrastructure disparities or to have meaningful impact on growth. Investment across all infrastructure ministries appears to address an array of priorities: maintain and advance the main trunk roads, rehabilitate existing roads that have been neglected over the years, and provide investment to rural areas to spur growth. Due to budget constraints, most districts/constituencies allocate resources to low priority, but less expensive projects, at the expense of higher priority-more expensive projects. To avoid this inefficient allocation of public funds, future infrastructure investment decisions should be based on sound economic rationale and secondarily on regional equalisation criteria. It would also help if the government s fiscal decentralisation strategy had mechanisms that help to channel investment to regions where growth is constrained by the low quality and volume of its infrastructure. The level of public investment in infrastructure as well as its impact on income and poverty varies across regions and infrastructure facilities. The government has created a range of agencies and decentralized funds through which the aggregate of infrastructure investment funds are channeled. The analysis in this report is that the decentralized funds namely, the CDF and the LATF provide the potential to address equity issues, as they allocate funds based on poverty criteria and at the constituency level, but that they are too insignificant to be a source of growth. Figure 28: Average share of LAs expenditure on roads, 2003/ / Nairobi Average Regional Share of LATF Spent on Roads (%) Rift Valley Coast Eastern Nyanza Central Western North Eastern (Source: RoK, LATF Annual Reports). A BUMPY RIDE TO PROSPERITY 31

42 32 A BUMPY RIDE TO PROSPERITY

43 5 CONCLUSIONS AND RECOMMENDATIONS