KENYA'S VISION 2030: AN AUDIT FROM AN INCOME AND GENDER INEQUALITIES PERSPECTIVE SID Society for International Development
I Contents Section 1 List of Abbreviations and Acronyms x Executive Summary xiv Acknowledgements xvii Section 1- Growing Unequally: An audit of the impact of Kenya's Vision 2030 growth on equality 1 1. Introduction 2 2. Inequality and Growth 3 2.1 The state of inequality in Kenya over time 4 2.2 Drivers of inequality in Kenya 5 2.3 A structural explanation for inequality in Kenya 6 3. Vision 2030, Past Growth and Inequality 9 4. Methodology 13 4.1 Employment growth in Vision 2030 13 4.2 The possibility of 10 per cent growth 14 4.3 Estimating the impact of growth on employment 14 5. Simulations 18 5.1 Simulation of employment and income effects at the national level 18 5.2 Simulation of employment effects by sex at the national level 21 5.3 Simulation of regional employment effects 22 6. Priority Sectors: Growth, employment and inequality 24 6.1 Employment impacts 24 6.2 Inequality 25 7. Addressing Inequality: Social programmes 27 8. Policy Implications 28 8.1 Data and information recommendations 29 8.2 Labour intensive employment 29 8.3 The agrarian and rural questions 29 Land redistribution 29
Rural environmental conservation 8.4 The urban question and transforming the Jua Kali sector Urban housing, redistribution and creating green jobs Upgrading the Jua Kali sector 8.5 Dividing national income: The wage versus profit share 30 31 31 32 33 9. Conclusions 35 References Appendix Acknowledgements 36 39 40 List of Tables Table 1.1: Income Gini coefficients, 1890-1996 4 Table 1.2: Projected GDP and employment growth rates, 2008-2012 14 Table 1.3: Highest Kenyan GDP growth rates for 3-, 5- and 10-year periods 14 Table 1.4: Gross elasticities of employment, 1966 2006 16 Table 1.5: Simulation of employment and income changes with fixed unemployment rate using total employment elasticity, 2007-2016 19 Table 1.6: Simulation of employment and income changes with fixed unemployment rate using private sector employment elasticity, 2007-2016 20 Table 1.7: Cumulative growth of labour incomes compared with per capita GDP, 2007-2012 21 Table 1.8: Simulation of employment impact on women and men, 2007-2016 22 Table 1.9: Simulation of regional employment impact ('000 ) 23 Table 1.10: Simulation of rural urban employment impact ('000 ) 23 List of Figures Figure 1.1: Figure 1.2: Figure 1.3: Figure 1.4: Figure 1.5: Figure 1.6: Figure 1.7: Figure 1.Al: Ratio of rural to urban earning and formal sector job dependency, 1972-2007 6 Indexes of real earnings per capita, 1972-2007 7 GDP per capita in US$ (2001), 1964-2007 9 Ratio of Kenyan GDP per capita with that of comparable countries, 1964-2007 10 Rural income per capita in US$ (2000) by industry as proportion of GDP for South Korea, 1960-2006 - 15 Rural income per capita in US$ (2000) by industry as percentage of GDP for Malaysia, 1960-2006 15 Employment by sex, 1972-2006 21 Public and private sector employment, 1972-2007 39
I I Contents Section 2 Section 2 - Gender and Kenya Vision 2030: An audit of the economic pillar 41 1. Introduction 43 2. Background Information 45 2.1 The economic pillar of Kenya Vision 2030 45 2.2 Situation analysis of gender in Kenya 46 Education 46 Labour force participation and employment 46 Access to finance 48 Participation in women groups and cooperative societies 48 2.3 Gender mainstreaming in public policy in Kenya 49 The National Policy on Gender and Development 50 Sessional Paper No. 2 of 2006 on Gender Equality and Development 50 Plan of Action to Implement the National Policy on Gender and Development 51 Monitoring and Evaluation Framework for Gender Mainstreaming 51 3. Gender and the Macro Economy 52 3.1 Understanding the link between gender and development 52 3.2 Linking gender and macroeconomics 53 Gendered databases 54 Gender and macroeconomic policy analysis 54 4. Gender and the Economic Pillar of Vision 2030 56 4.1 Agriculture 56 Reforming institutions 57 Increasing productivity 57 Land transformation 58 Development of ASAL areas 58 Increasing market access through value chain addition 58 4.2 Manufacturing 58 Gender dimensions of the flagship projects in the manufacturing sector 59 Gender constraints 59 4.3 Tourism 59
Gender dimensions in the tourism sector 60 Gender constraints 60 4.4 Wholesale and Retail Trade 60 Creation of organized small operator retail markets 61 Expanding formal market outreach 61 4.5 Financial Services 61 Expanding access to financial services 61 Increasing efficiency of the financial system 62 Enhancing stability of the financial system 62 4.6 Business process out-sourcing (BPO) 62 BPO challenges 63 Gender dimensions in the BPO sector 63 5. Conclusions and Policy Recommendations 64 5.1 Conclusions 64 5.2 Recommendations 65 References 67 List of Tables Table 2.1: Registered women's groups by membership, contribution and Government of Kenya grants, 2004-2007 49 Table 2.2: Women's participation in cooperative societies in 2007 49 List of Figures Figure 2.1: Wage employment in Kenya by industry and sex, 2008 47 Figure 2.2: Percentage distribution of wage employment in Kenya by sex and monthly income groups, 2007 47 Figure 2.3: Access to finance by sex, 2009 48
5. A Gender Analysis of the Social Pillar of Kenya's Vision 2030 - Environment, water and sanitation, housing and population 5.1 Situation analysis: Environment subsector Sustainable management of natural resources Demand for farmland and forest products 113 Wild animals in their natural habitat 113 Medication/hazardous waste 113 Climate change and desertification 114 Harnessing strategic natural resources 114 Summary 115 5.2 Situation analysis: Water and sanitation subsector 115 A gender analysis of the environment, water and sanitation sectors using the Harvard analytical framework 117 An analysis of the environment, water and sanitation subsector strategies and goals using the Moser framework 5.3 Housing and urbanization Situation analysis A gender analysis of the housing and urbanization subsector using the Harvard analytical framework An analysis of the urbanization and housing subsector strategies and goals using the Moser framework 125 6. A Gender Analysis of the Social Pillar of Kenya's Vision 2030 - Gender subsector 127 6.1 Gender, youth and vulnerable groups 127 Situation analysis 127 An analysis of the gender subsector strategies and goals using the Moser framework 128 6.2 Challenges to gender mainstreaming 128 7. Conclusions and Recommendations 130 7.1 Conclusions 130 7.2 Recommendations 131 Make a gender analysis of issues a prerequisite to any situation analysis 131 Collect sex-disaggregated and gender-sensitive data 131 Engender performance monitoring and evaluation frameworks 132 Institute gender responsive budgeting 133 Build awareness, capacity and ownership 133 Strategically locate the Ministry of Gender and gender focal points 133 References 134 List of Tables Table 3.1: Gender mainstreaming: Elements and features 76 Table 3.2: Moser framework: Typology of interventions 84 Table 3.3: Employment in the Ministry of Higher Education by job group and sex, 2009 88 Table 3.4: Number of primary school teachers by sex, 2000-2008 89 Table 3.5: Number of secondary school teachers by sex, 2000-2008 89
Table 3.6: Primary net enrolment rates (NER) (%) by province and sex, 2002-2008 90 Table 3.7: Secondary gross enrolment rates (GER) (%) by province and sex, 2002-2008 91 Table 3.8: Secondary to tertiary/university transition rates, 2002/03-2007/08 92 Table 3.9: Student enrolment in TIVET institutions by sex, 2003-2008 92 Table 3.10: Student enrolment in universities by sex, 2003/04-2008/09 93 Table 3.11: KCPE raw mean score by sex and subject, 2003-2007 95 Table 3.12: Key focus areas in the health sector 101 Table 3.13: Number of undergraduate and post graduate medical students by course and sex, 2003/04-2007/08 103 Table 3.14: Life expectancy at birth by sex, 2002-2007 104 Table 3.15: Total numbers and distribution by percentage of medical staff, by facility type, 2009 105 Table 3.16: Population catchments of dispensaries, health centres and district hospitals, by province, 2009 105 Table 3.17: Prevalence of HIV, HSV-2 and syphilis among women and men aged 15-64 years, 2003, 2007 106 Table 3.18: Percentage of households with access to safe drinking water, 2005/06 116 Table 3.19: Modified activity profile matrix environment, water and sanitation sectors 117 Table 3.20: Employment statistics in the ministries of Energy, Lands, Environment and Mineral Resources, and Water and Irrigation, by job group and sex, 2009 118 Table 3.21: Activity profile matrix - Urbanization and housing sector 124 Table 3.22: Employment in the Ministry of Housing disaggregated by sex and job group (2009) 125 List of Figures Figure 3.1: Primary NER (%) by province and sex, 2002-2008 90 Figure 3.2: Secondary GER (%) by province and sex, 2002-2008 91 Figure 3.3: Student enrolment in TIVET institutions by sex, 2003-2008 93 Figure 3.4: Student enrolment in universities by sex, 2003 / 04-2008 / 09 93 Figure 3.5: Proportion of Ministry of Health staff by gender in the lowest and highest job groups, 2008 102 Figure 3.6: Female Ministry of Health employees (%), 2008 102