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Unleashing the Potential of Ethiopian Women: Trends and Options for Economic Empowerment

Outline of the report. Trends in women's wellbeing indicators and international comparisonsDeterminants of economic disparities:Labor markets (time use, returns to human capital)?Barriers to entrepreneurship Access to landInitial estimates of economic implications of addressing gender dispariti

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Unleashing the Potential of Ethiopian Women: Trends and Options for Economic Empowerment

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    1. Unleashing the Potential of Ethiopian Women: Trends and Options for Economic Empowerment Edited version of presentations to the Ministry of Finance and Economic Development, Addis Ababa, July 2, 2008; and to the Sixth International Conference on the Ethiopian Economy of the Ethiopian Economic Association, held at the United Nations Conference Center, Addis Ababa, July 4, 2008. Caterina Ruggeri Laderchi and Hans Lofgren, World Bank

    2. Outline of the report Trends in women’s wellbeing indicators and international comparisons Determinants of economic disparities: Labor markets (time use, returns to human capital)? Barriers to entrepreneurship Access to land Initial estimates of economic implications of addressing gender disparities in economic empowerment (MAMS modeling) Policy options for addressing gender disparities

    3. Why a focus on gender disparities in economic empowerment Multidimensional and interlocking nature of gender disparities Economic empowerment – “Unleashing the potential of Ethiopian women”– is one of the priorities in PASDEP Economic empowerment complements and reinforces other measures for broader empowerment, such as removing gender bias from the legal system and granting women effective legal access Recent and ongoing work at the WB offers an opportunity to take stock of challenges women face in the economic sphere – an area which has been less explored in both policy oriented and academic literature

    4. Key messages Significant achievements in reducing gender disparities in some dimensions but serious challenges remain Heterogeneity of women’s conditions and progress over the decade 1995-2005 raises the question of whether “general development” is enough to reduce disparities International experience shows that some targeted measures can complement “general development” efforts, but an evidence based approach is needed Analysis of determinants of economic disparities shows: importance of education yet pervasive influence of cultural and customary factors, also in mediating policy effectiveness ? challenge of implementation The potential implications in terms of increased efficiency and growth of addressing gender disparity – as other disparities – are significant This calls for continued efforts in mainstreaming gender, assigning responsibilities for gender targets and careful monitoring

    5. Recent trends and international comparisons

    6. International comparisons (2004-2006)

    7. International comparisons (1991-97) Significant progress on primary education and political participation The disparity between Ethiopia and SSA in terms of ratio of female to male secondary enrolment has grown

    8. Selected trends: education

    9. Selected trends: monetary poverty Data show no signs of women being increasingly over-represented among the poor (the “feminization of poverty”)? BUT: household poverty rates are likely to underestimate the extent of poverty and vulnerability experienced by women ? need to understand better the intrahousehold allocation of resources

    10. It seems likely that more women live in poverty than captured by household based measures There is evidence of: Different spheres of control over household resources and spending decisions Systematic gender bias in consumption by adults, that discriminate against female children

    11. Women’s heterogeneity Across the rural-urban divide Across regions Across groups Income groups Female headed households

    12. Heterogeneity: the rural-urban divide

    13. Heterogeneity: Regional disparities Best and worst performing regions change by indicator Increasing disparities between best and worst performing regions in at least some indicators

    14. Heterogeneity: differences across groups Income groups differ in terms of access to primary school and information Other indicators such as those of women’s empowerment show less variations across quintiles.

    15. Heterogeneity: differences across groups Female-headed households face specific challenges: disadvantages in household composition and size … compounded by the gendered division of labor prevalent in agriculture But are in themselves a heterogeneous category: e.g. marital status matters: in urban areas, FHHs with never married heads have the lowest probability of being poor (the poverty incidence rate is only 9 percent). in rural areas FHH with currently married heads have the lowest probability of being poor widowhood increase women’s risk of being poor FHH, while not more likely to be poor than MHH, are generally more vulnerable

    16. The Determinants of Gender Economic Disparities

    17. Gender disparities in the labour markets Women have lower activity rates in GDP/market activities, lower employment rates and higher unemployment rates than men. They are disproportionately concentrated in unpaid occupations or hold insecure jobs that offer lower earnings Earnings and opportunities are limited by: Greater burden of household responsibilities Lower education Discrimination

    18. The unequal burden of household responsibilities

    19. Discrimination in returns to wage labor Data allow exploration of discrimination for a limited segment of the labor market (wage work in Ethiopia accounts for about Ľ of all employment -- 11 percent in rural areas)? Decomposition of the differences in earnings between men and women reveals that about 45 percent can be explained by worker characteristics lower investments in human capital and less experience on the job account for 25 to 39 percent of the gap. This captures women’s greater concentration in the informal sector and lower concentration in better-paying formal public and private jobs. about 40 percent can be ascribed to “pure wage discrimination effects”.

    20. Gender disparities in entrepreneurial activities

    21. Barriers to female entrepreneurship in large and small scale activities In the formal urban sector women business owners face a more hostile environment than their male counterparts are more educated and successful in running their businesses than male business owners, but are more vulnerable to crime and corruption are more likely to run businesses in partnerships In rural areas their likelihood to be involved in non-agricultural rural activities is driven by “push factors” rather than “pull forces” from farm activities directed towards activities with low barriers to entry resulting in lower profitability than either female-owned enterprises in small urban areas or male-owned enterprises in rural areas

    22. Gender disparities in land access Informal institutions and customary mediate land access and effectiveness of specific programs– also related to heterogeneity by region or by ethnic group These limitations compounded by other traditional gender roles/customs

    23. The Economic Implications of Addressing Disparities in Women Economic Empowerment

    24. General question What are the long-run effects of stronger efforts to foster the economic empowerment of women? To answer this question, we “engendered” MAMS, a CGE model for development-strategy analysis, including MDG and education strategies. Simulations focus on two kinds of interventions: promoting women’s access to and returns from productive assets reducing costs to women of their household roles

    25. 25 Why use a CGE model? The effects of efforts to promote the empowerment of women depend on and influence the evolution of the economy as a whole. For example, if education is expanded, other things that matter and can be considered in a CGE model include: How is the expansion in education financed? To what extent is the labor market gender blind? To what extent is it possible to reduce time spent on “home services”? How rapid is GDP growth?

    26. Engendering MAMS As opposed to standard MAMS, the engendered version of MAMS: covers full time use (not only GDP labor time); adds leisure and “home services” (cooking, cleaning, child care, fetching fuel, shopping, …) to the production activities (i.e. these are no longer limited to GDP activities); disaggregates population in working age and their time use by gender (not only by education) – their time use is a “production input.”

    27. 27 Labor nesting in GDP production

    28. 28 Database Development of database matching model characteristics: disaggregating payments and accounts related to labor and leisure in the SAM; creating separate time accounts that match SAM payments; and disaggregating education-related data by gender (accounting for the situation in the base-year and gender-specific responses to changes in the determinants of educational outcomes)?

    29. 29 Disaggregation (1)? Sectors (activities and commodities): Government: education (four cycles); health, water-sanitation; other infrastructure; other Non-government GDP: agriculture, industry, private health services, other private services Non-government non-GDP: home services, leisure (by gender and education)?

    30. 30 Disaggregation (2)? Factors Labor (by gender and education)? Government capital (by government sector)? Private capital Agricultural land Institutions Household NGO Government Rest of World

    31. 31 Wage discrimination against women Across all GDP activities, for females: wage paid < marginal value product (MVP); surplus (the gap) paid to male labor. Treatment justified by need to consider: the fact that economic benefits of increasing female employment > financial benefits reaped by female workers; impact of reduced discrimination (direct on earnings; indirect on broader indicators, considering differences in male and female spending patterns).

    32. 32 Treatment of leisure and home services For both leisure and home services: commodities disaggregated by gender and education; only demanded by the household; each commodity produced with the related labor type as input. For each leisure type, a “subsistence” quantity demanded defined on the basis of the total size of the related labor type; its total quantity demanded depends on price and income effects. For each home-service type, subsistence quantities scaled to keep fixed total per-capita home service time; when productivity improves, these subsistence quantities are scaled down for all labor types. This non-neoclassical treatment is justified by the special nature of leisure and home services: norms important in time allocation by gender and education; leisure produced and consumed by the same person. [Students exiting from the school system or becoming of labor-force age while not in school enter the labor force at the relevant educational level.] [Students exiting from the school system or becoming of labor-force age while not in school enter the labor force at the relevant educational level.]

    33. Time use by gender (%), 2005 Sources: the 2005 LFS; more detailed time-use information from surveys in other countries in SSA Sources: the 2005 LFS; more detailed time-use information from surveys in other countries in SSA

    34. Employment shares by labor type, 2005 (%)?

    35. Determinants of GDP growth Growth in factor employment in GDP activities; for labor (including female labor), the higher its level of education, the higher the MP; Growth in the TFP of production activities, with two components: endogenous: depending on economic openness and growth in government infrastructure stocks exogenous part captures what is not explained in model (institutions, new technologies, ….)? I will not state all assumptions; only highlight some of them when analyzing the results.I will not state all assumptions; only highlight some of them when analyzing the results.

    36. Simulations: period and description Period: 2005-2030. Description on the following table … I will not state all assumptions; only highlight some of them when analyzing the results.I will not state all assumptions; only highlight some of them when analyzing the results.

    37. 37 Description of simulations New assumptions by simulation (also applying to subsequent simulations)? edtx: 2006-2015, gradual 50% increase in real services per student ed+el: gradual increase from 1.3 to 4.0 of the elasticity of substitution between males and females in all activities and at all educational levels ed+el+hp: adding 2 %-age points to productivity growth in home services ed+el+hp+pp: adding 1, 0.5, and 0.1 %-age points to productivity growth in agriculture, industry and private services, respectively New assumptions by simulation (also applying to subsequent simulations)? edtx: 2006-2015, gradual 50% increase in real services per student ed+el: gradual increase from 1.3 to 4.0 of the elasticity of substitution between males and females in all activities and at all educational levels ed+el+hp: adding 2 %-age points to productivity growth in home services ed+el+hp+pp: adding 1, 0.5, and 0.1 %-age points to productivity growth in agriculture, industry and private services, respectively

    38. 38 Results: BASE Macro: aggregates grow at rates in the range of 5-7%; increased share of domestic taxes in GDP. Education: enrollment grows more rapidly the higher the cycle and for females; female/male GERs increase; Labor: employment: female (in GDP) grows more rapidly than male; the higher the level of education, the more rapid growth. wages: female grow less rapidly than male at all education levels Time use: for all groups, time share for GDP activities increase at the expense of home services; the reduction is larger, the higher the level of education, and much larger for females than males

    39. 39 Results: EDTX (tax-financed education expansion)? Macro: dramatic increase in GDP share of domestic taxes (from 11% to 20%); real GDP growth increases by 0.2 %-age points per year. increased growth for government demand (1.4-1.8 %-age points), decreased growth for private (by 0.2-0.4 %-age points)? Education: for secondary and tertiary, strong increases in enrollment growth and GERs (by 8-11 %-age points)? Labor: employment: slight growth decline at the lowest education; more rapid growth at higher levels (esp. tertiary level and esp. for females) wages: inverse relation between changes in employment and wage growth

    40. 40 Results: ED (aid-financed education expansion)? Macro – compared to BASE: no change in GDP share of domestic taxes; foreign aid GDP share increases by 7.5 %-age points. real GDP growth increases by 0.6 %-age points per year. increased growth for government demand (1.7-2.1 %-age points), increased growth for private (by 0.4-0.8 %-age points)? Education – compared to EDTX: outcomes similar to but slightly stronger; Labor – compared to EDTX: employment: only small changes in growth wages: stronger growth across the board

    41. 41 Results: ED+EL (less gender bias)? Compared to ED, minimal changes except for relative male/female wages – see figure below.

    42. 42 Results: ED+EL (less gender bias)?

    43. 43 Results: ED+EL+HP (increased home service productivity)? Macro – compared to ED+EL: growth increases for GDP and all parts of domestic final demand (by 0.3-0.7 %-age points); Labor – compared to ED+EL: Employment: increased supply of market labor, especially for females with the least education Wages: wages for most labor types grow more rapidly as a result of the acceleration of over-all growth; downward pressure on wages for females with the least education; Time use – compared to ED+EL: home service shares decline (by 4-15 %-age points) in proportion to original shares of each labor type; most of the saved time moves into GDP production;

    44. 44 Results: ED+EL+HP+PP (increased private GDP productivity)? Macro – compared to ED+EL+HP: real GDP growth reaches 7.9% (+0.7 %-age points growth gains for domestic final demand 0.2-0.6 %-age points Labor – compared to ED+EL+HP: strong wage gains (0.5-0.6 %-age points for all labor types)?

    45. GDP at factor cost and private consumption (% growth per year)? For base: Why lower growth in private consumption than for GDP at factor cost? It is assumed that inflows from RoW (transfers to households and government) grow a bit slower than GDP. Given this, exports have to increase a bit more rapidly than imports (to keep external balance; REXR depreciates) and domestic final demands (incl. private consumption) grow a bit more slowly than GDP.For base: Why lower growth in private consumption than for GDP at factor cost? It is assumed that inflows from RoW (transfers to households and government) grow a bit slower than GDP. Given this, exports have to increase a bit more rapidly than imports (to keep external balance; REXR depreciates) and domestic final demands (incl. private consumption) grow a bit more slowly than GDP.

    46. Gross Enrollment Rate, secondary (%)? base: improvement for both males and females; females catch up; edtx: increased quality attracts additional students to secondary ed + ed+el+hp+pp: further improvements when GDP and private consumption grow more rapidlybase: improvement for both males and females; females catch up; edtx: increased quality attracts additional students to secondary ed + ed+el+hp+pp: further improvements when GDP and private consumption grow more rapidly

    47. 47 Employment growth by labor type (%)?

    48. Wage growth, secondary (%)? similar picture for tertiary; a matter of supply and demand in a gender-segmented the labor market graph shows wage per hour or year (w); not wage income (w*qf)? base: more rapid growth for males than females since male educated factor supplies grow more rapidly edtx: expanded education depresses wages in the absence of strong growth increase ed: more positive wage outcome since growth is more rapid ed+el: more gender-blind hiring reduces gaps in wage growth ed+el+hp: men and, especially, women released from home work ed+el+hp+pp: growth is good ed+el+hp+pp+rd: removal of wage discrimination is good for women similar picture for tertiary; a matter of supply and demand in a gender-segmented the labor market graph shows wage per hour or year (w); not wage income (w*qf)? base: more rapid growth for males than females since male educated factor supplies grow more rapidly edtx: expanded education depresses wages in the absence of strong growth increase ed: more positive wage outcome since growth is more rapid ed+el: more gender-blind hiring reduces gaps in wage growth ed+el+hp: men and, especially, women released from home work ed+el+hp+pp: growth is good ed+el+hp+pp+rd: removal of wage discrimination is good for women

    49. Wage income growth, secondary (%)? Simple point: Across all simulations, wage incomes grow more rapidly for females than for males; large growth in female skilled employmentSimple point: Across all simulations, wage incomes grow more rapidly for females than for males; large growth in female skilled employment

    50. 50 Conclusions (1)? Main results: Expanded higher education (with strong gains in female education) accelerates GDP growth and raises private consumption (if financed by aid); Female wage growth is positively related to: growth in educated labor demand (which depends on GDP growth); and reduced discrimination against women in wage and employment decisions.

    51. 51 Conclusions (2)? Future work (drawing on emerging micro evidence): improved database; incorporate links between incomes under female control and the allocation of spending across different types of consumption and savings; add female education indicators to the determinants of health and education outcomes. Such extensions make it possible to consider additional channels through which female empowerment contributes to human development.

    52. References Bourguignon, Francois, Carolina Diaz-Bonilla, and Hans Lofgren. 2008. “Aid, service delivery and the Millennium Development Goals in an Economywide Framework,” pp. 283-315 in François Bourguignon, Maurizio Bussolo, and Luiz A. Pereira da Silva, eds. The Impact of Macroeconomic Policies on Poverty and Income Distribution: Macro-Micro Evaluation Techniques and Tools. Washington, D.C.: World Bank. World Bank Report. Unleashing The Potential Of Ethiopian Women: Trends And Options For Economic Empowerment. June 2008 Draft. Poverty Reduction and Economic Management 2. Africa Region.

    53. Policy Options for Addressing Gender Disparities in Economic Empowerment

    54. Policy options Menu of options based on international experience to help translating PASDEP’s vision into concrete policy options Broad based and targeted policies Scope for improving wellbeing indicators of both women and men, particularly in rural areas Yet heterogeneity of women’s situations means that certain groups are particularly vulnerable or face specific challenges which call for targeted measures Further targeted measures can help addressing strong cultural barriers. Evidence-based approach Different national and international experiences can be scaled up after piloting and evaluation

    55. Policy options [2] Focus on a limited set of interventions: three main areas Promoting gender equality in access to productive resources – focus on human capital and its utilization Reducing the costs to women of their household roles Strengthening women’s voice and representation NB separate work will look specifically into land issues

    56. 1. Access to productive resources Access to human capital Untargeted measures: continuing ongoing efforts in improvement in school facilities and expansion of village schools Targeted measures for girls’ enrolment and attendance: secondary school scholarships for girls; stipends for female students linked to school distance; conditional cash transfers targeting poor households; school-feeding and take-home rations reserved for girls. Promoting safety in schools and gender awareness eg Girls' Education Advisory Committees Earning capacity and opportunities training and employment creation programs

    57. 1. Access to productive resources [2] Access to financial services: micro-credit with complementary services: business literacy training, management capacity building, product and processing training additional services such as saving options. Monitoring of gender outcomes and accountability: actions for improving awareness of women’s rights especially among agents delivering services; legal aid, incentives and support for access to formal courts; clear responsibility for gender outcomes

    58. 2. Reducing the costs to women of their household roles Time-saving technologies and services especially in rural areas: improved stoves and modern cooking fuels, water and transportation services, opportunities offered by decentralized energy generation Provision of child care: investment in child care facilities low cost solution such as wawa-wasi program in Peru Considering women’s time use in program design and implementation

    59. 3. Strengthening women’s voice and representation Examples already in major Government programs E.g. statutory gender quotas in Local Committees for land registration; women representation in PSNP structures But challenges in translating plans into practice: Quotas for Local Committees were respected by only 20 percent of them. Women account for a small number of representatives also in PSNP structures. More training and sensitization: Qualitative evidences point out women’s low awareness of their rights or fear of speaking in public Strengthening monitoring of key aspects of women’s participation

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