## 1. Labor Force and Earnings in Ethiopia

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---

### Introduction
- Investigates macroeconomic impact of existing gender gaps in Ethiopia and discusses authorities’ policies on gender equality and women’s rights, focusing on women’s economic engagement.
- Key quantitative finding: eliminating gender gaps in both educational attainment and the rate of formal employment could increase output in Ethiopia over time by over 24 percent.
- Global and regional context:
  - Worldwide labor force participation: only 50 percent of women participate in the labor force, compared to 75 percent of men.
  - By one estimate, GDP in the US was 14 percent higher due to the increase in women’s labor force participation (LFP) and hours worked since 1970.
  - Losses in per capita GDP attributed to gender gaps in the labor market estimated at around 12 percent in sub-Saharan Africa (SSA).
  - IMF (2014) estimate: a 1 percentage point increase in gender equality is associated with a 0.2 percentage point increase in growth over a five-year period.

### Situation of Women in Ethiopia
- Comparative indicators (2016):
  - Human Development Index (HDI): 0.448 (SSA: 0.523)
  - Gender Inequality Index (GII): 0.499 (SSA: 0.572)
  - GDP per capita (2011 PPP USD): $1,608
- Rankings:
  - UNDP GII rank: 116th out of 188 countries (2016).
  - HDI rank: 174th out of 188 countries.
- Comparative example:
  - Rwanda: GDP per capita $1,774; GII 0.383; HDI 0.498.

### Women in the Economy — participation, time use, informality, productivity
- Labor force participation and composition:
  - Share of women engaged in the labor force in 2017: 77 percent; men: 88 percent.
  - Labor Force Participation (LFP) ratio (Female-Male): 88%.
- Time use and unpaid work:
  - Of those engaged in domestic or personal production (2013 Time Use Survey), 93 percent were women compared to 57 percent for men.
  - Women are over three times more likely to spend time collecting firewood or water: 38 percent (women) vs 18 percent (men).
  - Time spent collecting firewood or water when doing so: around 50 mins per day (women) vs 12 mins per day (men).
  - Female farmers: around 14.4 hours per week on their farm; male farmers: 23 hours per week.
- Informal employment:
  - Rate of informal employment among women fell from 58 percent in 2000 to 36 percent in 2016; for men: 38 percent in 2000 to 20 percent in 2016.
- Wages, productivity, and business ownership:
  - Women earned, on average, about 63 percent of what men did (2016 Urban Employment Unemployment Survey).
  - Wage gap largest in agriculture and smallest in the public sector.
  - Female-managed farms found to be 24 percent less productive than male-managed farms.
  - UN Women (2018) estimates the gender gap reduced total agricultural output by $203.5 million in Ethiopia in 2010 U.S. dollars.
  - Only 16.6 percent of all businesses registered with the Ministry of Trade in 2014 were owned by women.
  - Median start-up capital of male-owned enterprises is five times higher than that of female-owned enterprises.

### Women’s Health and Education
- Health and violence:
  - Maternal mortality per 100,000 live births declined from 1,400 in 1990 to 350 in 2015 (compared to 550 across SSA in 2015).
  - Rates of FGM/C: 65 percent (large regional disparities).
  - Incidence of gender-based physical violence: 23 percent of women aged 15-49 have experienced physical violence (2016 DHS).
- Education outcomes:
  - Literacy rates among women more than doubled to 38 percent nationally between 1990 and 2014.
  - Enrollment ratio (Female-Male):
    - primary: 93%
    - secondary: 90%
    - tertiary: 46%
  - Female-to-male literacy ratio: 58% (versus SSA 80%).
  - Men are much more likely to be enrolled in tertiary education than women; twice as many men enrolled in undergraduate programs than women in 2015/16.

### Macroeconomic return to increased women’s LFP — conceptual channels
- Mechanisms for output gains:
  - Formalization of previously uncounted activities increases measured output.
  - Higher labor supply from increased female participation.
  - Efficiency gains via better allocative efficiency, improved job matching, reduced misallocation of skills, and higher human capital investment.
- Evidence suggests significant gender productivity gaps in agriculture and in education that imply aggregate LFP statistics understate full economic losses from gender gaps.

### Approaches used in the analysis
- Cross-country analysis of LFP rates, income levels and growth (1990–2016).
- Decomposition of output lost due to gender gaps in human capital and formal sector employment using a production-function framework.
- Household panel analysis using World Bank LSMS panel (three waves: 2011/12, 2013/14, 2015/16).

### Cross-country LFP and growth — key regression findings
- U-shaped relationship: female LFP rates high at low income, fall with rising income, then rise in rich countries.
- Regression coefficients reported (significance notation: * p<0.051, ** p<0.01, *** p<0.001):
  - Female LFP rate coefficient on log GDPpc: -0.669**.
  - Female LFP rate coefficient on Δ log GDPpc: 0.397**.
  - Female LFP rate coefficient on Δ log GDPpc with squared term: -0.147**; female LFP rate - squared coefficient: 0.022**.
  - Female-Male LFP ratio coefficient on Δ log GDPpc: -0.411**; Female-Male LFP ratio - squared: 0.203** and -0.029** in different columns.
  - Initial log GDP per capita coefficient: 0.999** and 0.000** in different specifications.
  - Initial Female LFP rate coefficient: 0.035**.
  - Observations: 4713, 4218, 4218 (across columns).
  - Year controls: Yes.
- Estimate: a 1 percentage point increase in the female-male LFP ratio is associated with a 0.2 percentage point increase in the rate of growth, at lower levels of female participation.

### Production-function decomposition — model structure and calibration
- Economy split: traditional agricultural sector (Qa) and modern sector (Qm).
- Key model equations used:
  1. Qa = Aa ha
  2. Qm = Am K^(1−α) (hm)^α
  3. hi = (hfi^ρi + hmi^ρi)^(1/ρi)
  4. hj i = e^(φ s) (s_j,k y_k) l_j i
  5. l_j i = μ_i(p_j,k k_j,k w)
  6. Q = Qa + Qm
- Assumptions and calibration inputs:
  - Male and female labor are imperfect substitutes.
  - Elasticity of substitution between men and women: σm = 0.4 in the modern sector and σa = 2 in the agricultural sector.
  - Agriculture share of value added: around 40 percent; modern sectors: 60 percent.
  - Investment series from IMF WEO (1980–16); depreciation rate assumed 7 percent per year.
  - Around 70 percent of women engaged in agriculture (compared to 80 percent of men).
  - 8 percent of women in the labor force engaged in formal wage employment (compared to 11 percent of men).
  - α set to 0.3.
  - Returns to schooling (Psacharopulos, 1994) assumed: basic 13.4 percent, intermediate 10.8 percent, advanced 21.9 percent.
  - TFP (Ai) backed out for each sector and kept constant.
  - Within-sector distribution of education assumed identical by gender.

### Quantified impacts of closing gender gaps (production-function results)
- Increasing women’s levels of education to those of men could increase output by around 11.3 percent.
- Moving women into wage employment in the modern sector (closing gap: agriculture share from 70 percent to 80 percent and formal wage employment from 8 percent to 11 percent) could increase output by a further 12.4 percent.
- Joint effect: eliminating gender gaps in educational attainment and formal sector employment could increase output in Ethiopia by 24.1 percent.
- Important caveat: closing the gender gap in participation rates alone would reduce output by 0.5 percent due to relatively high participation rates among women with basic education; composition matters.

### Household panel evidence (LSMS 2011–16) — employment, wages, time use
- Data coverage and sample caveat:
  - LSMS household panel three waves: 2011/12, 2013/14, 2015/16; roughly 16 percent attrition rate between each wave.
  - Full sample >46,760 individuals aged >7 years; only around 2,500 (5.5 percent) report having engaged in wage employment in the past 12 months (1,400 in 2015/16, 530 in 2013/14 and 640 in 2011/12).
- Employment and education patterns:
  - On average 7.2 percent of men report having a wage-paying job, compared to 3.4 percent of women.
  - Education distribution: men — 31.1 percent primary, 3.8 percent tertiary; women — 20.5 percent primary, 1.8 percent tertiary.
- Wage levels and trends (mean hourly wages, 2016/17 Birr):
  - Male: 13.6 (2011/12), 15.3 (2013/14), 17.5 (2015/16), All: 15.9.
  - Female: 12.8 (2011/12), 14.1 (2013/14), 13.2 (2015/16), All: 13.2.
  - Gap (Birr): 0.8, 1.2, 4.3, All: 2.7.
  - Average hourly wage for women with a wage-paying job: 13 Birr (0.60 USD); men: 16 Birr (0.72 USD).
  - Women’s wage ≈ 80 percent of men’s in raw averages.
- Regional and sectoral wage statistics (selected):
  - Wage employment (All): Male 7.2%, Female 3.4%, All 5.3%.
  - Addis Ababa: Male 38.0%, Female 22.2%, All 29.2%.
  - Oromia: Male 6.8%, Female 3.2%, All 4.9%.
  - Amhara: Male 5.7%, Female 3.2%, All 4.4%.
  - Aggregate regional mean hourly wages (All education): Male All: 33.0 Birr/hour; Female All: 19.3 Birr/hour; Gap 58.5%.
  - Sectoral mean hourly wages:
    - Agriculture & fishing: Male All 32.2; Female All 24.6; Gap 76.2%.
    - Manufacturing: Male All 19.3; Female All 17.0; Gap 88.2%.
    - Services: Male All 25.3; Female All 14.2; Gap 56.0%.
- Time use:
  - Women over three times more likely to spend time collecting firewood or water (38 percent vs 18 percent); when they do, women spend around 50 minutes per day versus 12 minutes for men.
  - Regional disparities: gaps largest in Harari and Dire Dawe, lowest in Addis Ababa.

### Wage regressions and selection-corrected gaps
- Basic wage regression (time and woreda controls): Female coefficient -0.271*** (women earn around 27 percent less than men).
- Adding education and sector controls: Female coefficient -0.269***.
- Heckman selection correction:
  - Work probability (probit): concave relationship with age, positive relationship with education; women less likely to have a wage-paying job controlling for observables.
  - Wage regression with IMR included: Female coefficient -0.313***; IMR coefficient 0.512*.
  - Controlling for selection increases measured gender wage gap to over 30 percent.
- Education returns (selected coefficients):
  - Primary: up to 1.083*.
  - Secondary: up to 1.632**.
  - Tertiary: up to 2.762***.
  - Other: up to 2.393***.
- Other household income has coefficient -0.128*** in selection equation.
- Observations across regressions reported: 2538, 2092, 27714, 2092 (across columns).

### Main empirical insights
- Macro-level: smaller gender gaps in LFP rates and higher female formal employment rates are associated with faster growth; formal employment for women correlates positively with income per capita.
- Decomposition: closing gender gaps in education and formal sector employment can materially raise aggregate output — estimated 11.3 percent from education, 12.4 percent from formal employment, and 24.1 percent jointly.
- Micro-level: women are less likely to have wage employment, have lower formal education, earn less conditional on observables, and face additional unpaid household time burdens; selection-corrected estimates indicate a gender wage gap exceeding 30 percent even after controlling for education, sector, and ability proxies.

### The Ethiopian authorities — political commitment, legal framework, and remaining challenges
- Political and legal actions:
  - National Policy on Women issued in 1993; commitment renewed in the constitution in 1995.
  - Ethiopian Women, Development and Change Strategy developed in 2017/18.
  - Family Law revised in 2000; Penal Codes revised in 2005 to tackle gender-based violence.
  - Financial Administration proclamation revised in 2016 to mainstream gender issues in the budget process.
  - On October 25, 2018, Ethiopia’s parliament appointed Sahle-Work Zewde as the first woman president in Ethiopia’s history.
  - Cabinet representation of women increased to 50 percent following ministerial changes approved by parliament in late-2018.
- International commitments:
  - Ratified CEDAW in 1981; submitted 8th CEDAW report in 2016.
  - Adopted the Beijing Platform for Action (September 1995).
  - Committed to SDGs, including ending violence against women and girls by 2030 (SDG goal 5).
  - Committed to Agenda 2063 goal of full gender equality.
- National plans and constraints:
  - GTP I (2010/11–2014/15) and GTP II reaffirmed commitments; GTP I extended financial services to millions of women.
  - Key constraints: access to agricultural extension services and farming technologies for women; land right issues; increasing availability of credit.
  - 2017 Gender Statistics Report: women have not been equal beneficiaries of economic, social and political opportunities; persistent social norms and traditions remain.

### Agriculture, social norms, institutional capacity — targeted interventions
- Agriculture and productivity:
  - Policies to increase productivity of female farmers can yield large economy-wide gains.
  - Suggested interventions:
    - Promoting the use of pesticides and other inputs on female managed farms (including male labor and machinery).
    - Better tailoring advice to female farmers on input use.
    - Providing services that reduce the time women spend on household duties.
- Social norms and programming:
  - Customary laws and cultural practices often make women secondary earners and limit household decision-making power.
  - Joint Program approaches (Amhara and Tigray): holistic interventions addressing attitudes and behaviors of community members, including men, boys, and traditional and religious leaders.
- Institutional capacity:
  - Gender units exist within many ministries but limited institutional structures and supporting organizations hinder response to rural women’s needs and slow progress on women’s empowerment.
  - Limited capacity affects implementation of gender-budgeting practices; women underrepresented in leadership positions.

### Key policy recommendations and programmatic priorities
- Narrow productivity gap between male and female farmers by:
  - Promoting input use (pesticides and other inputs) on female managed farms, including access to male labor and machinery.
  - Tailoring agricultural advice to female farmers on input use.
  - Providing services that reduce time spent on household duties.
- Increase female education opportunities, particularly in rural areas, by:
  - Reducing barriers to education beyond the primary level (distance, personal security, economic challenges).
  - Complementing education policies with measures to raise female LFP in formal sectors.
- Address time-use constraints (water/firewood collection) that disproportionately fall on women.
- Change social attitudes and norms through community-level interventions targeting men, boys, and traditional and religious leaders.
- Strengthen institutional capacity and supporting organizations (cooperatives, micro-finance institutions, government bureaus) to better respond to rural women’s needs and implement gender-budgeting practices.
- Improve women’s representation in leadership positions across institutions.

*Prepared by Thomas McGregor (AFR), with contributions from UN Women ESARO. November 13, 2018. Source: IMF staff paper "Women and the Economy in Ethiopia."*

### 1. Labor Force and Earnings in Ethiopia ________________________________________________ 6

### 1. Labor Force and Earnings in Ethiopia

### Introduction
- This paper investigates the macroeconomic impact of existing gender gaps in Ethiopia and discusses the authorities’ policies in the areas of gender equality and women’s rights, with a focus on women’s economic engagement.
- Key quantitative finding: eliminating gender gaps in both educational attainment and the rate of formal employment could increase output in Ethiopia over time by over 24 percent.
- Global and regional context:
  - Worldwide labor force participation: only 50 percent of women participate in the labor force, compared to 75 percent of men.
  - By one estimate, GDP in the US was 14 percent higher due to the increase in women’s labor force participation (LFP) and hours worked since 1970.
  - Losses in per capita GDP attributed to gender gaps in the labor market estimated at around 12 percent in sub-Saharan Africa (SSA) (Cuberes and Teigner, 2012).
  - IMF (2014) estimate: a 1 percentage point increase in gender equality is associated with a 0.2 percentage point increase in growth over a five-year period.

### Situation of Women in Ethiopia
- Ethiopia’s comparative indicators (2016 data and WDI/WEO sources):
  - Human Development Index (HDI): 0.448 (SSA: 0.523)
  - Gender Inequality Index (GII): 0.499 (SSA: 0.572)
  - GDP per capita (2011 PPP USD): $1,608
- Relative performance:
  - Ethiopia ranked 116th out of 188 countries on the UNDP’s Gender Inequality Index (GII) in 2016.
  - Ethiopia ranked 174th out of 188 on the overall Human Development Index (HDI).
  - Comparative example: Rwanda—GDP per capita $1,774; GII 0.383; HDI 0.498.

### Women in the Economy
- Labor force participation and composition:
  - Share of women engaged in the labor force in 2017: 77 percent, compared to 88 percent for men (both above the SSA average).
  - Labor Force Participation (LFP) ratio (Female-Male): 88% (Table 1 summary).
- Time use and unpaid work:
  - Of those engaged in domestic or personal production (2013 Time Use Survey), 93 percent were women compared to 57 percent for men.
  - Women are over three times more likely to spend time collecting firewood or water: 38 percent (women) vs 18 percent (men).
  - Time spent collecting firewood or water when doing so: around 50 mins per day (women) vs 12 mins per day (men).
  - Female farmers: around 14.4 hours per week on their farm; male farmers: 23 hours per week.
- Informal employment:
  - Rate of informal employment among women fell from 58 percent in 2000 to 36 percent in 2016; for men the comparable figures were 38 percent in 2000 and 20 percent in 2016.
- Wages, productivity, and business ownership:
  - Women earned, on average, about 63 percent of what men did (2016 Urban Employment Unemployment Survey).
  - Wage gap largest in agriculture and smallest in the public sector.
  - Female-managed farms found to be 24 percent less productive than male-managed farms (Aguilar et al. 2013; MoANR, UN Women and PEI Africa, 2018).
  - UN Women (2018) finds the gender gap in agricultural productivity was 24 percent and estimates the gender gap reduced total agricultural output by an amount of $203.5 million in Ethiopia in 2010 U.S. dollars.
  - Only 16.6 percent of all businesses registered with the Ministry of Trade in 2014 were owned by women.
  - Median start-up capital of male-owned enterprises is five times higher than that of female-owned enterprises (World Bank, 2009).

### Women’s Health and Education
- Health outcomes and violence:
  - Maternal mortality per 100,000 live births declined from 1,400 in 1990 to 350 in 2015 (compared to 550 across SSA in 2015).
  - Rates of Female Genital Mutilation or Cutting (FGM/C): 65 percent (large regional disparities).
  - Incidence of gender-based physical violence: 23 percent of women aged 15-49 have experienced physical violence (2016 DHS).
- Education outcomes:
  - Literacy rates among women more than doubled to 38 percent nationally between 1990 and 2014.
  - Enrollment ratio (Female-Male):
    - primary: 93%
    - secondary: 90%
    - tertiary: 46%
  - Female-to-male literacy ratio reported as 58% (versus SSA 80% in Table 1 summary).
  - Men are much more likely to be enrolled in tertiary education than women; twice as many men enrolled in undergraduate programs than women in 2015/16 (Annual Abstract of MoFEC note).

### Macroeconomic Return to Increased Women’s LFP
- Conceptual channels:
  - Increasing women’s participation in the formal economy could increase output by bringing previously uncounted activities into formal measurements and by increasing labor supply.
  - Efficiency gains expected from better allocative efficiency, improved job matching, reduced misallocation of skills, and higher human capital investment.
- Quantified impact:
  - Eliminating gender gaps in both educational attainment and the rate of formal employment could increase output in Ethiopia over time by over 24 percent.
  - Evidence suggests significant gender productivity gaps in agriculture and gender gaps in education mean aggregate labor force participation statistics likely underestimate the full economic losses due to gender gaps.

*Prepared by Thomas McGregor (AFR), with contributions from UN Women ESARO. November 13, 2018. Source: IMF staff paper "Women and the Economy in Ethiopia."*

### 13.      This paper uses three approaches to assess the impact of gender gaps on economic

### 13.      This paper uses three approaches to assess the impact of gender gaps on economic

### Approaches used
- Cross-country analysis of labor force participation (LFP) rates, income levels and growth between 1990 and 2016.
- Decomposition of output lost due to gender gaps in human capital and formal sector employment using a production-function framework.
- Household panel analysis using the World Bank LSMS panel (three waves: 2011/12, 2013/14, 2015/16) to investigate micro-level drivers of gender gaps.

### Labor force participation and growth: cross-country evidence
- A U-shaped relationship exists between overall female LFP rates and per capita incomes at the cross-country level.
- Female LFP rates tend to be high at low income levels, fall as countries become richer, and rise again in rich countries.
- Regression results reported:
  - Female LFP rate coefficient on log GDPpc: -0.669**.
  - Female LFP rate coefficient on Δ log GDPpc: 0.397**.
  - Female LFP rate coefficient on Δ log GDPpc in a specification with squared term: -0.147**; female LFP rate - squared coefficient: 0.022**.
  - Female-Male LFP ratio coefficient on Δ log GDPpc: -0.411**; Female-Male LFP ratio - squared: 0.203** and -0.029** in different columns.
  - Initial log GDP per capita coefficient: 0.999** and 0.000** in different specifications.
  - Initial Female LFP rate coefficient: 0.035**.
  - Observations: 4713, 4218, 4218 (across columns).
  - Year controls: Yes.
  - Significance notation: * p<0.051, ** p<0.01, *** p<0.001.
- A moderate female-male LFP ratio is associated with higher growth.
- Estimate: a 1 percentage point increase in the female-male LFP ratio is associated with a 0.2 percentage point increase in the rate of growth, at lower levels of female participation (figure 3).
- Prior studies find similar estimates (IMF, 2015; Amin et. al., 2015).

### Decomposing lost output due to gender gaps in Ethiopia (production-function approach)
- Economy split into a traditional (subsistence) agricultural sector (Qa) and a modern (agriculture, services, industry) sector (Qm).
- Traditional agricultural production uses only labor; modern sector uses physical capital and labor.
- Labor disaggregated by gender and augmented by educational attainment.
- Model equations (as presented):
  1. Qa = Aa ha
  2. Qm = Am K^(1−α) (hm)^α
  3. hi = (hfi^ρi + hmi^ρi)^(1/ρi)
  4. hj i = e^(φ s) (s_j,k y_k) l_j i
  5. l_j i = μ_i(p_j,k k_j,k w)
  6. Q = Qa + Qm
- Definitions and assumptions:
  - Superscript j ∈ M,F denotes gender; i ∈ a,m denotes sector; Ai is sector-specific TFP; K is aggregate capital stock.
  - hji is “quality adjusted” workforce via CES composite with σi = 1/(1−ρi).
  - Returns to schooling use piecewise linear returns for levels none/basic/intermediate/advanced.
- Complementarity assumptions:
  - Male and female labor are imperfect substitutes.
  - Elasticity of substitution (ES) between men and women set at σm = 0.4 in the modern sector and σa = 2 in the agricultural sector.
- Calibration/data inputs:
  - Agriculture accounted for around 40 percent of total value added; modern sectors 60 percent.
  - Investment series from IMF WEO (1980–16), depreciation rate assumed 7 percent per year to construct capital stock.
  - Aggregate LFP from ILO; education levels from WDI/ILO; labor shares and education distributions from World Bank data.
  - Around 70 percent of women engaged in agriculture (compared to 80 percent of men).
  - 8 percent of women in the labor force engaged in formal wage employment (compared to 11 percent of men).
  - Within-sector distribution of education (none, basic, intermediate, advanced) assumed identical by gender.
  - α set to 0.3.
  - Returns to schooling (Psacharopulos, 1994) assumed: basic 13.4 percent, intermediate 10.8 percent, advanced 21.9 percent.
  - TFP (Ai) backed out for each sector and kept constant.

### Quantified impacts of closing gender gaps in Ethiopia
- Increasing women’s levels of education to those of men could increase output by around 11.3 percent.
- Moving women into wage employment in the modern sector (closing gap: agriculture share from 70 percent to 80 percent and formal wage employment from 8 percent to 11 percent) could increase output by a further 12.4 percent.
- Together, eliminating gender gaps in educational attainment and formal sector employment could increase output in Ethiopia by 24.1 percent.
- Note: closing the gender gap in participation rates alone would reduce output by 0.5 percent due to relatively high participation rates among women with basic education; hence composition matters.

### Gender gaps in education and earnings: household panel evidence (LSMS 2011–16)
- Data: LSMS household panel covering three waves 2011/12, 2013/14, 2015/16; roughly 16 percent attrition rate between each wave.
- Employment and education patterns:
  - On average 7.2 percent of men report having a wage-paying job in Ethiopia, compared to 3.4 percent of women (table 3).
  - Education: 31.1 percent of men had a primary education, falling to 3.8 percent with tertiary education; for women 20.5 percent primary and 1.8 percent tertiary.
- Wages and time use:
  - Average hourly wage for women with a wage-paying job: 13 Birr (0.60 USD); men: 16 Birr (0.72 USD). Women’s wage ≈ 80 percent of men’s.
  - Wage inflation: mean hourly wages (2016/17 Birr):
    - Male: 13.6 (2011/12), 15.3 (2013/14), 17.5 (2015/16), All: 15.9.
    - Female: 12.8 (2011/12), 14.1 (2013/14), 13.2 (2015/16), All: 13.2.
    - Gap: 0.8, 1.2, 4.3, All: 2.7 (Birr).
  - Time use: women are over three times more likely to spend time collecting firewood or water (38 percent compared to 18 percent); when they do, women spend around 50 minutes per day versus 12 minutes for men.
  - Regional disparities: gaps largest in Harari and Dire Dawe, lowest in Addis Ababa.
- Sample coverage caveat:
  - Full sample >46,760 individuals aged >7 years; only around 2,500 (5.5 percent) report having engaged in wage employment in the past 12 months (1,400 in 2015/16, 530 in 2013/14 and 640 in 2011/12), making the wage sample unrepresentative of the population as a whole.
- Wage regressions (equation: y_i,t = α + β X_i,t + f_i + w_t + ε_i,t with y = log hourly wage):
  - Basic wage regression (time and woreda controls): women earn around 27 percent less than men (Female coefficient -0.271***).
  - Adding education and sector controls: Female coefficient -0.269***.
  - Selection into employment addressed via Heckman:
    - Work probability (probit) shows concave relationship with age and positive relationship with education; women less likely to have a wage-paying job controlling for observables.
    - Wage regression with IMR included: Female coefficient -0.313***; IMR coefficient 0.512*.
  - Controlling for selection increases the measured gender wage gap to over 30 percent.
  - Education effects on log wage (selected coefficients, table 6):
    - Primary: up to 1.083* in some specifications.
    - Secondary: up to 1.632**.
    - Tertiary: up to 2.762***.
    - Other: up to 2.393***.
  - Other HH income has coefficient -0.128*** in selection equation.
  - Observations reported: 2538, 2092, 27714, 2092 (across columns).

### Key regional and sectoral statistics (selected)
- Wage employment by gender (All): Male 7.2%, Female 3.4%, All 5.3%; Male education primary 11.4%, female primary 7.2% (table 3 totals).
- Regional wage employment (selected rows from table 3):
  - Addis Ababa: Male 38.0%, Female 22.2%, All 29.2%.
  - Oromia: Male 6.8%, Female 3.2%, All 4.9%.
  - Amhara: Male 5.7%, Female 3.2%, All 4.4%.
- Aggregate regional mean hourly wages (All education, table 5 totals):
  - Male All: 33.0 Birr/hour; Female All: 19.3 Birr/hour; Gap 58.5%.
- Sectoral mean hourly wages (table 5 totals):
  - Agriculture & fishing: Male All 32.2; Female All 24.6; Gap 76.2%.
  - Manufacturing: Male All 19.3; Female All 17.0; Gap 88.2%.
  - Services: Male All 25.3; Female All 14.2; Gap 56.0%.

### Main empirical insights
- Macro-level: smaller gender gaps in LFP rates and higher female formal employment rates are associated with faster growth; formal employment for women correlates positively with income per capita.
- Decomposition: closing gender gaps in education and formal sector employment can materially raise aggregate output—estimated 11.3 percent from education, 12.4 percent from formal employment, and 24.1 percent jointly.
- Micro-level: women are less likely to have wage employment, have lower formal education, earn less conditional on observables, and face additional unpaid household time burdens; selection-corrected estimates indicate a gender wage gap exceeding 30 percent even after controlling for education, sector, and ability proxies.

### Policy implications (section heading present in source)
- The analysis motivates policies that:
  - Increase female educational attainment to male levels.
  - Reduce barriers to women’s entry into formal wage employment in the modern sector.
  - Address time-use constraints (water/firewood collection) that disproportionately fall on women.
  - Consider regional heterogeneity (e.g., Harari, Dire Dawe vs. Addis Ababa) when designing interventions to close gender gaps.

*Source: IMF staff analysis based on World Bank WDI, ILO, IMF WEO, and World Bank LSMS 2011–16 as presented in the provided chapter.*

### 26.      The Ethiopian authorities have shown a firm political commitment to the advancement

### The Ethiopian authorities have shown a firm political commitment to the advancement of gender equality, women’s rights and women’s economic empowerment

### Political commitment and legal framework
- National Policy on Women issued in 1993 guaranteeing equal rights of women; commitment renewed in the constitution in 1995.
- Ethiopian Women, Development and Change Strategy developed in 2017/18 aims to increase women’s economic empowerment by addressing high rates of unemployment and informality and ensuring urban job creation and food security for women.
- Family Law revised in 2000 and Penal Codes revised in 2005 to tackle gender-based violence, including child marriage and harmful traditional practices.
- Financial Administration proclamation revised in 2016 to mainstream gender issues in the budget preparation process.
- Recent appointment of a gender-balanced cabinet and the first woman president in Ethiopian history:
  - On October 25, 2018, Ethiopia’s parliament appointed Sahle-Work Zewde as the first woman president in Ethiopia’s history.
- Cabinet representation of women increased to 50 percent following ministerial changes approved by parliament in late-2018.

### International and regional commitments
- Ethiopia ratified the Convention on Elimination of All Forms of Discrimination against Women (CEDAW) in 1981 and submitted the 8th CEDAW report to the UN General Assembly in 2016.
- Ethiopia adopted the Beijing Platform for Action from the Fourth World Conference on Women (September 1995).
- The government has signed up to the Sustainable Development Goals (SDGs), including ending violence against women and girls by 2030 (SDG goal 5).
- Ethiopia committed to the Africa Renaissance Agenda 2063 with a specific goal on full gender equality in all spheres of life.

### National development plans and remaining challenges
- Growth and Transformation Plan I (GTP I, 2010/11-2014/15) committed to equity in distribution of economic and social gains to women and youth; succeeded in extending financial services to millions of women.
- Growth and Transformation Plan II (GTP II) reaffirmed the commitment and noted significant remaining challenges requiring a redoubling of efforts.
- Key constraints identified:
  - Access to agricultural extension services and farming technologies for women.
  - Land right issues.
  - Increasing availability of credit.
- 2017 Gender Statistics Report conclusion: Ethiopian women have not been equal beneficiaries of economic, social and political opportunities due to historical legacy of gender inequality and discrimination, strengthened by persistent social norms and traditions.

### Agriculture and productivity
- Policies aimed at increasing the productivity of female farmers hold enormous potential for the overall economy.
- Suggested policy interventions to narrow the productivity gap between male and female farmers:
  - Promoting the use of pesticides and other inputs on female managed farms (including male labor and machinery).
  - Better tailoring advice to female farmers on input use.
  - Providing services that reduce the time women spend on household duties.

### Education and female labor force participation (LFP)
- Literacy rates among women have more than doubled since the mid-1990s, due largely to expansion of primary and adult education, but women remain much more likely to be illiterate than men, particularly in rural areas.
- 2011 literacy comparison:
  - 30 percent of women in rural areas were literate, compared to 70 percent in urban areas.
  - For men: 50 percent in rural areas and 87 percent in urban areas.
- Barriers to secondary and tertiary education for women:
  - School distance.
  - Personal security risks.
  - Economic challenges.
- As girls grow older, academic participation becomes increasingly difficult.
- Policy directions:
  - Reduce barriers to continuing education beyond the primary level for girls and women, particularly in rural areas.
  - Supplement education policies with measures to increase female LFP, particularly in formal sectors.
  - International experience suggests changing cultural attitudes, improving childcare policies, and adopting technologies that favor sectors with gender balanced employment can increase female LFP (Ostry et al., 2018).

### Social norms, institutional capacity, and programming
- Social attitudes and traditional beliefs continue to constrain women’s equal participation; many household and community decisions regarding women are made by men (father or husband).
- Rural women face individual, community and institutional barriers compounded by limited household decision-making power and low levels of formal education.
- JP RWEE findings:
  - Customary laws and cultural practices result in a division of labor in farming that typically makes women the secondary earners of the household.
  - Women’s decision-making power related to household income is limited, increasing dependence on husbands.
- Joint Program approaches:
  - A Joint Program in the Amhara and Tigray regions that takes a holistic approach recognizes interventions that change attitudes and behavior of community members, including men, boys and traditional and religious leaders, are needed.
- Institutional capacity issues:
  - Gender units embedded within many ministries, but limited institutional structures and supporting organizations (cooperatives, micro-finance institutions, government bureaus) result in limited response to rural women’s needs and slow progress on women’s empowerment.
  - Limited capacity hinders full implementation of gender-budgeting practices.
  - Women underrepresented in leadership positions in these institutions.

### Key policy recommendations and programmatic priorities
- Narrow the productivity gap between male and female farmers through:
  - Promoting input use (pesticides and other inputs) on female managed farms, including access to male labor and machinery.
  - Tailoring agricultural advice to female farmers on input use.
  - Providing services that reduce time spent on household duties.
- Increase female education opportunities, particularly in rural areas, by:
  - Reducing barriers to education beyond the primary level (distance, personal security, economic challenges).
  - Complementing education policies with measures to raise female LFP in formal sectors.
- Change social attitudes and norms through community-level interventions targeting men, boys, and traditional and religious leaders.
- Strengthen institutional capacity and supporting organizations (cooperatives, micro-finance institutions, government bureaus) to better respond to the needs of rural women and implement gender-budgeting practices.
- Improve women’s representation in leadership positions across institutions.

*THE FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA — INTERNATIONAL MONETARY FUND*

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_Source: https://www.imf.org/-/media/files/publications/cr/2018/cr18355.pdf_