## 1. Summary of Major Employment Social Programs in Uganda

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---

### A. Introduction
- Key challenge: create enough employment opportunities to cope with rapid population growth while ensuring strong and inclusive growth.
- Uganda has experienced strong economic performance following stabilization in the 1990s, but with one of the youngest and fastest-growing populations in the world, promoting employment is crucial for development and inclusive growth.
- Paper structure:
  - Section B: literature review.
  - Section C: stylized facts (labor market challenges, labor market overview, employment characteristics).
  - Section D: policy recommendations.

### B. Literature Review
- Existing literature is largely based on economic reports and qualitative studies, with limited enterprise-level labor demand data.
- Selected research findings:
  - Bbale and Mpuga (2011): female education increased likelihood of women participating in the labor force and being wage employed.
  - Eijdenberg and Masurel (2013): entrepreneurial motivation includes push and pull factors; pull factors can be more important.
  - Guma (2015): barriers to urban women entrepreneurs include limited access to finance, bureaucracy/cost of licenses, lack of education/training, transportation cost.
  - Olivier, Namirembe and Richard (2015): wider gender gap in private marginal returns to education among wage-employed than self-employed; investing in education can reduce income inequality.
  - Ackah, Bofah and Asuman (2017): entrepreneurs motivated by career and survival, facing institutional weaknesses.
- Other cited sources: Kiranda, Walter and Mugisha (2017); UBOS (2015, 2018); Merotto, Weber, and Reyes (2018); GEM (2014); World Bank 2013 enterprise survey.

### C. Stylized Facts

- Labor Market Challenges
  - Since 2011, economic slowdown has deeply affected Uganda; GDP per capita growth slowed and poverty reduction stalled in the five years to 2016.
  - Labor force participation has significantly dropped, especially for the youth; participation showed some recovery starting in 2016, but youth participation remained flat.
  - Population and demographic pressures:
    - Uganda’s population reached 38.8 million in 2018.
    - Population growth rate: around 3 percent.
    - UN projections: population expected to almost triple by 2050.
  - Job creation requirement:
    - Uganda will need to create more than 600,000 jobs per year before 2030.
    - Uganda will need to create more than 1 million jobs per year by 2040.
  - Work-force population will increase for both males and females (UN World Population Prospects 2017 Revision).

- Labor Market Overview
  - Employment elasticity to growth:
    - Estimated point elasticity: 0.6 (2000-2017, log-linear regression).
    - Interpretation: a 1 percentage point increase in economic growth is associated with a 0.6 percentage change in employment.
    - Elasticity similar to SSA and LICs.
  - Employment composition:
    - Share of wage workers has increased since 2000, but vulnerable employment (own-account workers + unpaid family workers) still dominates, especially for women.
    - Within vulnerable employment, more women have become own-account workers instead of unpaid family workers in recent years.
  - Entrepreneurship and firm constraints:
    - Ugandan youth are highly entrepreneurial: GEM (2014) finds 70 percent of youth perceive good opportunities for business and believe they have capability to start and run a business.
    - Firms are very small on average; World Bank enterprise survey (2013) highlights constraints including electricity, competition with informal firms, access to finance, tax rates, labor regulation, and trade.
    - Uganda firms have made more progress on innovation compared with SSA average (higher shares introducing process innovation and new products/services).

- Characteristics of the Employed
  - Education and employment:
    - Higher education levels increase the chance of being employed and of working in non-agriculture sectors (2016 household survey data).
    - Primary education matters more for agriculture employment; secondary and higher education matter more for non-agriculture employment.
    - Paid employment increases with higher education levels, especially for those who completed secondary education or have higher education.
    - Type of employment by education:
      - About half of people with no education could only find seasonal and temporary jobs.
      - Around 75 percent of employed people with higher education have more stable all-year jobs.
  - Education outcomes:
    - Education outcomes have deteriorated; primary school completion rate has dropped in recent years, contrary to trends in comparator countries.
    - Main reasons for dropping out of training institutions (manpower survey):
      - Male students: failure to afford tuition (78 percent); high local demand for labor (5 percent).
      - Female students: failure to afford tuition (48 percent); pregnancy (40 percent).
  - Gender gaps:
    - Female employment levels are lower among working-age population compared to males.
    - Women have a larger share with no education; men have larger shares with secondary and higher education.
    - Other barriers for women: more household work burdens, less access to financing, inputs and technology, market information and marketing networks (UNDP 2015).
    - Urban context: higher share of unemployed women in urban areas than rural areas; many rural women are seasonal and temporary workers.
    - Occupational segregation: women over-represented in unskilled manual and sales; under-represented among skilled manual, professionals, executives.
    - Average earnings of women are substantially lower than those of men.
  - Youth employment and skills mismatch:
    - Young age decreases the probability of getting employed.
    - NEET (not in education, employment or training) share for youth: 34 percent of the total youth population in 2017.
      - Comparators: Tanzania 15 percent; Nigeria 21 percent; Ghana 26 percent.
    - Skill mismatch: on average 80 percent of working young people were under-educated for their occupations (UBOS 2015), particularly high for professional and skilled agricultural young workers.
    - Average wages of paid young workers are low, especially for those with lower education levels, in rural areas, and for young women—reflecting concentration in informal sector and less skilled jobs.

### D. Policy Discussions
- Existing social programs:
  - Uganda has implemented social programs aimed at creating employment specifically for youth and women; programs focus on enabling private sector job creation and building skills to improve employability.
  - Coverage of these programs remains limited; funding constraints identified as one of the main challenges.
- Implicit policy directions based on findings:
  - Improve education outcomes and completion rates (especially primary completion).
  - Address financing constraints for training and education to reduce dropout due to tuition costs.
  - Target gender disparities through policies improving female education and reducing non-market burdens on women.
  - Strengthen labor demand by addressing business environment constraints: electricity, access to finance, competition with informal firms, tax and regulatory burdens.
  - Focus on youth skills and reduce skill mismatch through vocational and technical training aligned with labor market needs.
  - Expand coverage and financing of employment social programs targeting youth and women to meet large annual job-creation needs (more than 600,000 jobs per year before 2030; more than 1 million jobs per year by 2040).

### Box 1 — Major youth and women employment programs
- Youth Entrepreneurial Scheme (YES)
  - Introduced in 1995.
  - Designed as a loan scheme for youth who wished to venture into business.
  - The scheme did not perform as anticipated with low recovery rate.
- Youth Venture Capital Fund (YVCF)
  - Introduced in 2011.
  - Offered fixed subsided interest loans and depends on both public funds as well as funds offered by commercial banks.
  - Program results were mixed.
- Young Livelihood Programme (YLP)
  - Introduced in 2013, targeting the unemployed and poor youth.
  - Provides revolving funds to groups of 10 to 15 persons with access of up to US$7000 to be repaid after 3 years.
  - There are currently 18,063 projects of youth projects financed.
  - The recovery rate of funds has increased over the year, with a 70 percent estimated projected repayment rate for FY18/19.
  - Reported positive impacts from the program (2018 impact evaluation):
    - Employment creation of more than 200,000 direct jobs and 500,000 indirect jobs.
    - Increased financial inclusion.
    - Positive impacts on economy.
  - Challenges:
    - Inadequate funds.
    - Low technical capacity in some local governments.
    - Improper usage of the funds.
    - Some project failures due to disease outbreaks and other project issues.
- Uganda Women Entrepreneurship Programme (UWEP)
  - Initiated in 2015, targeting unemployed women with similar structure as the YLP.
  - Most projects of women groups are in agriculture (34 percent), wholesale and retail trade (43 percent) and services (11 percent).
  - The repayment of the revolving fund represents 68 percent of the total amount due to date by the end of December 2018.
  - Benefits:
    - Women empowerment and women engagement in the economy.
  - Measures to improve recovery:
    - Enhance local government capacity.
    - More active involvement and participation of women councils.
  - Other challenges:
    - Inadequate funds which are much lower than the demand.
    - Access to financing.
    - Some project failures.

### Policy directions to create quality jobs (Box 1)
- Raise growth
  - Maintain macroeconomic stability (low inflation and output volatility).
  - Promote headline growth through:
    - Developing and maintaining strategic infrastructure (related to electricity, water, transportation).
    - Improving the general business environment, good governance and service delivery.
- Invest in education
  - Improve education outcomes through better quality and alignment with the needs of the growth sectors of the education curriculum.
  - Study highlights benefits of education for employment and earnings and that required education level differs across sectors and job categories.
- Reduce gender gap
  - Aim to reduce the education gap for women and promote women labor force participation.
  - Include policies on education on child care.
- Facilitate youth labor market entrance
  - Active labor market policy (ALMP) could help, including vocational trainings and search and matching assistance through employment services.
- Support firms to expand
  - Improve access to financing for entrepreneurs by:
    - Reducing the high cost of financial services.
    - Improving credit information.
    - Increasing public confidence in formal financial institutions.
  - More enabling government policies to support expansion and job creation.

### Empirical approach and summarized findings (Box 1)
- Empirical approach
  - Used Probit model to estimate determinants of the probability of being employed.
  - Dependent variable: dummy of employment status (working=1, not working=0).
  - Tests included: probability of employment in agriculture; employment in non-agriculture sectors; full-time jobs; and paid jobs.
  - Individual-level data: 2016 Uganda Demographic and Health Survey (2016 UDHS) conducted by UBOS.
- Key regression findings
  - Probability of employment is significantly influenced by age, marriage status, head of household dummy, and education levels.
  - Higher education levels (primary, secondary, higher) are associated with higher probability of being employed.
  - Wealth index: the richer the individual is, the less likelihood of being employed (possible lack of incentives to work).
  - Probability of employment is significantly lower for women, especially for a woman with children under 5 years old or more than one child.
  - Probability of employment increases with age (youth have lower chance of getting employed).
  - Young women identified as the most vulnerable group (affected by both age and gender).
  - Different education levels affect employment categories differently:
    - Full-time job probability increases with all levels of education.
    - Employment in agriculture positively associated with primary education.
    - Employment in non-agriculture sector positively associated with secondary education and higher education.
    - Secondary and higher education are more important for getting a paid job.
- Robustness checks
  - Logit model produced similar results to Probit.
  - Separate estimations for female and male employment confirm main results; urban dummy significant with negative coefficient in female regressions (higher chance of employment in rural areas).
  - Youth employment regressions confirm general findings.

*Source: IMF staff report "Addressing Employment Challenges in Uganda", April 16, 2019.*

### 1. Summary of Major Employment Social Programs in Uganda  _______________________ 10

### 1. Summary of Major Employment Social Programs in Uganda

### A. Introduction
- Key challenge: create enough employment opportunities to cope with rapid population growth while ensuring strong and inclusive growth.
- Uganda has experienced strong economic performance following stabilization in the 1990s, but with one of the youngest and fastest-growing populations in the world, promoting employment is crucial for development and inclusive growth.
- Paper structure:
  - Section B: literature review.
  - Section C: stylized facts (labor market challenges, labor market overview, employment characteristics).
  - Section D: policy recommendations.

### B. Literature Review
- Existing literature is largely based on economic reports and qualitative studies, with limited enterprise-level labor demand data.
- Notable reports cited:
  - Kiranda, Walter and Mugisha (2017); UBOS (2015) on labor market transitions of young people.
  - UBOS (2018) manpower survey and Merotto, Weber, and Reyes (2018) (World Bank jobs diagnostics).
  - GEM (2014) and World Bank 2013 enterprise survey highlight labor demand constraints (business environment, private sector).
- Selected research findings:
  - Bbale and Mpuga (2011): female education increased likelihood of women participating in the labor force and being wage employed.
  - Eijdenberg and Masurel (2013): entrepreneurial motivation in Uganda includes both push and pull factors; pull factors can be more important.
  - Guma (2015): barriers to urban women entrepreneurs include limited access to finance, bureaucracy/cost of licenses, lack of education/training, transportation cost.
  - Olivier, Namirembe and Richard (2015): wider gender gap in private marginal returns to education among wage-employed than self-employed; investing in education can reduce income inequality.
  - Ackah, Bofah and Asuman (2017): entrepreneurs motivated by career and survival, facing institutional weaknesses.

### C. Stylized Facts

- Labor Market Challenges
  - Since 2011, economic slowdown has deeply affected Uganda; GDP per capita growth slowed and poverty reduction stalled in the five years to 2016.
  - Labor force participation has significantly dropped, especially for the youth; decline follows the slowdown in trend growth since 2011. Participation showed some recovery starting in 2016, but youth participation remained flat.
  - Population and demographic pressures:
    - Uganda’s population reached 38.8 million in 2018.
    - Population growth rate: around 3 percent.
    - UN projections: population expected to almost triple by 2050.
  - Job creation requirement:
    - Uganda will need to create more than 600,000 jobs per year before 2030.
    - Uganda will need to create more than 1 million jobs per year by 2040.
  - Work-force population will increase for both males and females (UN World Population Prospects 2017 Revision).

- Labor Market Overview
  - Employment elasticity to growth:
    - Estimated point elasticity: 0.6 (2000-2017, log-linear regression).
    - Interpretation: a 1 percentage point increase in economic growth is associated with a 0.6 percentage change in employment.
    - Elasticity similar to SSA and LICs.
  - Employment composition:
    - Share of wage workers has increased since 2000, but vulnerable employment (own-account workers + unpaid family workers) still dominates, especially for women.
    - Within vulnerable employment, more women have become own-account workers instead of unpaid family workers in recent years.
  - Entrepreneurship and firm constraints:
    - Ugandan youth are highly entrepreneurial: GEM (2014) finds 70 percent of youth perceive good opportunities for business and believe they have capability to start and run a business.
    - Firms are very small on average; World Bank enterprise survey (2013) highlights constraints including electricity, competition with informal firms, access to finance, tax rates, labor regulation, and trade.
    - Uganda firms have made more progress on innovation compared with SSA average (higher shares introducing process innovation and new products/services).

- Characteristics of the Employed
  - Education and employment:
    - Higher education levels increase the chance of being employed and of working in non-agriculture sectors (2016 household survey data).
    - Primary education matters more for agriculture employment; secondary and higher education matter more for non-agriculture employment.
    - Paid employment increases with higher education levels, especially for those who completed secondary education or have higher education.
    - Type of employment by education:
      - About half of people with no education could only find seasonal and temporary jobs.
      - Around 75 percent of employed people with higher education have more stable all-year jobs.
  - Education outcomes:
    - Education outcomes have deteriorated; primary school completion rate has dropped in recent years, contrary to trends in comparator countries.
    - Main reasons for dropping out of training institutions (manpower survey):
      - Male students: failure to afford tuition (78 percent); high local demand for labor (5 percent).
      - Female students: failure to afford tuition (48 percent); pregnancy (40 percent).
  - Gender gaps:
    - Female employment levels are lower among working-age population compared to males.
    - Women have a larger share with no education; men have larger shares with secondary and higher education.
    - Other barriers for women: more household work burdens, less access to financing, inputs and technology, market information and marketing networks (UNDP 2015).
    - Urban context: higher share of unemployed women in urban areas than rural areas; many rural women are seasonal and temporary workers.
    - Occupational segregation: women over-represented in unskilled manual and sales; under-represented among skilled manual, professionals, executives.
    - Average earnings of women are substantially lower than those of men.
  - Youth employment and skills mismatch:
    - Young age decreases the probability of getting employed.
    - NEET (not in education, employment or training) share for youth: 34 percent of the total youth population in 2017.
      - Comparators: Tanzania 15 percent; Nigeria 21 percent; Ghana 26 percent.
    - Skill mismatch: on average 80 percent of working young people were under-educated for their occupations (UBOS 2015), particularly high for professional and skilled agricultural young workers.
    - Average wages of paid young workers are low, especially for those with lower education levels, in rural areas, and for young women—reflecting concentration in informal sector and less skilled jobs.

### D. Policy Discussions
- Existing social programs:
  - Uganda has implemented social programs aimed at creating employment specifically for youth and women; programs focus on enabling private sector job creation and building skills to improve employability.
  - Coverage of these programs remains limited; funding constraints identified as one of the main challenges.
- Implicit policy directions based on findings:
  - Improve education outcomes and completion rates (especially primary completion).
  - Address financing constraints for training and education to reduce dropout due to tuition costs.
  - Target gender disparities through policies improving female education and reducing non-market burdens on women.
  - Strengthen labor demand by addressing business environment constraints: electricity, access to finance, competition with informal firms, tax and regulatory burdens.
  - Focus on youth skills and reduce skill mismatch through vocational and technical training aligned with labor market needs.
  - Expand coverage and financing of employment social programs targeting youth and women to meet large annual job-creation needs (more than 600,000 jobs per year before 2030; more than 1 million jobs per year by 2040).

*Source: IMF staff report "Addressing Employment Challenges in Uganda", April 16, 2019.*

### Box 1. Summary of Major Employment Social Programs in Uganda

### Box 1. Summary of Major Employment Social Programs in Uganda

### Major youth and women employment programs
- Youth Entrepreneurial Scheme (YES)
  - Introduced in 1995.
  - Designed as a loan scheme for youth who wished to venture into business.
  - The scheme did not perform as anticipated with low recovery rate.
- Youth Venture Capital Fund (YVCF)
  - Introduced in 2011.
  - Offered fixed subsided interest loans and depends on both public funds as well as funds offered by commercial banks.
  - Program results were mixed.
- Young Livelihood Programme (YLP)
  - Introduced in 2013, targeting the unemployed and poor youth.
  - Provides revolving funds to groups of 10 to 15 persons with access of up to US$7000 to be repaid after 3 years.
  - There are currently 18,063 projects of youth projects financed.
  - The recovery rate of funds has increased over the year, with a 70 percent estimated projected repayment rate for FY18/19.
  - Reported positive impacts from the program (2018 impact evaluation):
    - Employment creation of more than 200,000 direct jobs and 500,000 indirect jobs.
    - Increased financial inclusion.
    - Positive impacts on economy.
  - Challenges:
    - Inadequate funds.
    - Low technical capacity in some local governments.
    - Improper usage of the funds.
    - Some project failures due to disease outbreaks and other project issues.
- Uganda Women Entrepreneurship Programme (UWEP)
  - Initiated in 2015, targeting unemployed women with similar structure as the YLP.
  - Most projects of women groups are in agriculture (34 percent), wholesale and retail trade (43 percent) and services (11 percent).
  - The repayment of the revolving fund represents 68 percent of the total amount due to date by the end of December 2018.
  - Benefits:
    - Women empowerment and women engagement in the economy.
  - Measures to improve recovery:
    - Enhance local government capacity.
    - More active involvement and participation of women councils.
  - Other challenges:
    - Inadequate funds which are much lower than the demand.
    - Access to financing.
    - Some project failures.

### Policy directions to create quality jobs
- Raise growth
  - Maintain macroeconomic stability (low inflation and output volatility).
  - Promote headline growth through:
    - Developing and maintaining strategic infrastructure (related to electricity, water, transportation).
    - Improving the general business environment, good governance and service delivery.
- Invest in education
  - Improve education outcomes through better quality and alignment with the needs of the growth sectors of the education curriculum.
  - Study highlights benefits of education for employment and earnings and that required education level differs across sectors and job categories.
- Reduce gender gap
  - Aim to reduce the education gap for women and promote women labor force participation.
  - Include policies on education on child care.
- Facilitate youth labor market entrance
  - Active labor market policy (ALMP) could help, including vocational trainings and search and matching assistance through employment services.
- Support firms to expand
  - Improve access to financing for entrepreneurs by:
    - Reducing the high cost of financial services.
    - Improving credit information.
    - Increasing public confidence in formal financial institutions.
  - More enabling government policies to support expansion and job creation.

### Empirical approach and summarized findings
- Empirical approach
  - Used Probit model to estimate determinants of the probability of being employed.
  - Dependent variable: dummy of employment status (working=1, not working=0).
  - Tests included: probability of employment in agriculture; employment in non-agriculture sectors; full-time jobs; and paid jobs.
  - Individual-level data: 2016 Uganda Demographic and Health Survey (2016 UDHS) conducted by UBOS.
- Key regression findings
  - Probability of employment is significantly influenced by age, marriage status, head of household dummy, and education levels.
  - Higher education levels (primary, secondary, higher) are associated with higher probability of being employed.
  - Wealth index: the richer the individual is, the less likelihood of being employed (possible lack of incentives to work).
  - Probability of employment is significantly lower for women, especially for a woman with children under 5 years old or more than one child.
  - Probability of employment increases with age (youth have lower chance of getting employed).
  - Young women identified as the most vulnerable group (affected by both age and gender).
  - Different education levels affect employment categories differently:
    - Full-time job probability increases with all levels of education.
    - Employment in agriculture positively associated with primary education.
    - Employment in non-agriculture sector positively associated with secondary education and higher education.
    - Secondary and higher education are more important for getting a paid job.
- Robustness checks
  - Logit model produced similar results to Probit.
  - Separate estimations for female and male employment confirm main results; urban dummy significant with negative coefficient in female regressions (higher chance of employment in rural areas).
  - Youth employment regressions confirm general findings.

*Source: Box 1. Summary of Major Employment Social Programs in Uganda, IMF staff report content provided.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2019/1ugaea2019002.pdf_