Gender Inequality in Africa's Labor Market (Africa Development Forum Series)

Gender inequality in the labor market remains a pressing problem of contemporary Africa. Notwithstanding the existence of large variations across countries with regard to male and female labor market outcomes, available evidence shows that in several countries of the region women are less likely to be in paid work, they are disproportionately concentrated in informal and precarious employment, and they are paid substantially less. Assessing and comparing the extent and the nature of women disadvantages in Africa's labor markets remains a challenge, however. In-depth comparative analyses are lacking, largely because reliable and comparable comprehensive data have been for a long time hardly available. The objective of this study, a collaboration between the World Bank and the Agence fran?§aise de d?©veloppement (AFD), is to contribute to fill-in an important knowledge gap regarding the extent and the nature of gender disparities in Africa’s labor markets. The study is novel in providing a comparative analysis based on standardized nationally representative survey-data for several Sub-Saharan Africa countries and one North Africa country: The countries are: Benin, Burkina Faso, Burundi, Cameroon, C??te d’Ivoire, Ethiopia, The Gambia, Ghana, Guinea, Kenya, Madagascar, Malawi, Mauritania, Mauritius, Morocco, Mozambique, Nigeria, Republic of Congo, Sao Tome and Principe, Senegal, Sierra Leone, Tanzania, Uganda, and Zambia. It also offers a more in-depth gender analysis by using a comprehensive set of labor market indicators disaggregated by location, age groups and consumption quintiles, and several sophisticated micro and macro techniques. Contents......Page 9 Foreword......Page 21 About the Editors and Authors......Page 23 Acknowledgments......Page 27 Abbreviations......Page 29 Why Study Gender Disparities in Africa’s Labor Markets?......Page 31 Objective of This Book......Page 32 O.1 Countries Covered in This Volume......Page 33 Book Organization and Topics......Page 35 The Main Findings on Gender Disparities in Africa......Page 38 Policy Recommendations and the Way Forward......Page 46 PART 1 STYLIZED FACTS......Page 51 1 Gender Disparities in Africa’s Labor Markets: A Cross-Country Comparison Using Standardized Survey Data......Page 53 Data and Concepts......Page 54 Gender Differences in Labor Market Outcomes......Page 57 Gender Disparities at Work......Page 66 1.7 Employment Status of the Active Population by Gender and Education Level, Regional Average, around 2000......Page 72 Conclusions......Page 79 1A.1 Frequencies for Missing Data by Country—Individuals, ages 15–64......Page 81 PART 2 DISPARITIES IN EMPLOYMENT, PAY, EDUCATION, AND OTHER DIMENSIONS: A MICRO-ANALYSIS......Page 85 2 Exploring the Gender Pay Gap Through Different Age Cohorts: The Case of Ethiopia......Page 87 Data and Concepts......Page 88 2.3 Unadjusted Gender Monthly Wage Gap by Age and Wage Level, 2005......Page 92 Results......Page 95 Conclusions......Page 100 2A.1 Selectivity Corrected (Heckman Two-Step Method) Log Monthly Earnings Equations in Wage Employment by Gender, 2005......Page 102 3 Gender Disparities in the Malagasy Labor Market......Page 117 3.1 Selected Labor Market Indicators in Madagascar......Page 121 Data, Definitions, and Methods......Page 122 Results......Page 124 Summary and Concluding Remarks......Page 139 Annex 3A Concepts and Methods......Page 143 3B.1 Summary Statistics of the Variables Used in the Labor Allocation Models......Page 150 3C.1 Nature and Terms of Employment in Total Employment in Madagascar......Page 152 3D.1 Log Hourly Earnings Equations for Wage Employment......Page 164 3E.1 Neumark’s Decomposition of the Gender Log Hourly Earnings Gap (OLS estimates)......Page 174 4 Gender Differences in Pay in African Manufacturing Firms......Page 185 Data and Descriptive Statistics......Page 188 4.2 Descriptive Statistics of the Gender Wage Gap......Page 193 Conclusions......Page 201 4A.1 Descriptive Statistics on the Workforce......Page 205 Annex 4B Methodology......Page 215 5 Addressing Gender Inequality in Ethiopia: Trends, Impacts, and the Way Forward......Page 223 National Data on Gender Disparities over the Last Decade......Page 225 The Macroeconomic Benefits of Addressing Gender Inequalities......Page 231 Insights from the MAMS Modeling......Page 241 Conclusions and Policy Implications......Page 244 5A.2 Selected Gender Indicators: Ethiopia vs. Sub-Saharan Africa vs. Low-Income Countries, 1991–97......Page 246 Annex 5B A Brief Description of the Engendered Ethiopia MAMS Application......Page 252 PART 3 DISPARITIES IN LABOR INCOME: MACRO–MICRO SIMULATIONS......Page 259 Introduction......Page 261 Gender, Labor Income, and Time Use from Household Survey Analysis......Page 263 Macroeconomic Analysis of Sectoral Growth and Labor Income Shares......Page 275 Sectoral Demand Shocks and Impact on Labor Income Shares by Gender......Page 282 6.6 Difference in Sectoral Impact on Urban Unskilled and Urban Skilled Labor Income (Shock of 1% of Aggregate Exports)......Page 291 6A.1 Definition of Aggregate Household Income......Page 295 Annex 6B Block Decomposition of the SAM Multiplier Matrix......Page 296 Introduction......Page 303 Main Features of the 2001 Tanzania SAM......Page 306 Sectoral Growth and Impact on Labor Income Shares by Gender......Page 310 Structural Path Analysis......Page 315 Conclusions......Page 321 7A.1 Sketch Map for Calculation of Total Influence......Page 322 PART 4 DISPARITIES IN TIME USE......Page 327 8 Gender Disparities in Time Allocation, Time Poverty, and Labor Allocation Across Employment Sectors in Ethiopia......Page 329 Data, Concepts, and Methodology......Page 331 Results......Page 336 Conclusions......Page 352 8A.1-1 Determinants of Hours Per Week Worked in the Labor Market by Gender and Place of Residence in Ethiopia, 2005 (Tobit models)......Page 354 8A.2-1 Marginal Impacts of Covariates on Male Segment Employment Choices after Multinomial Logit Estimation......Page 357 Introduction......Page 363 Basic Statistics......Page 365 Regression Analysis......Page 382 Conclusions......Page 384 PART 5 DISPARITIES IN BARGAINING POWER......Page 387 Introduction......Page 389 Income Sources in the Republic of Congo......Page 391 Impact of Gender Labor Income Shares on Consumption......Page 400 10.6 Correlates of Household Consumption Shares for Two Aggregated Categories, Republic of Congo, 2005......Page 407 Introduction......Page 411 Data and Basic Statistics......Page 413 Econometric Analysis......Page 423 Conclusions......Page 427 11A.1 Bivariate Probit Regressions for Women in Nigeria......Page 428 Index......Page 437 1.1 Labor Force Participation Rate by Gender, around 2000......Page 58 1.2 Relationships Between Male and Female Employment Ratios, around 2000......Page 60 1.3 Women’s Share in Total Employment, around 2000......Page 61 1.4 Male-to-Female Employment Ratio by Country, around 2000......Page 63 1.5 Average Incidence of Underemployment (Less Than 30 hours of Work per Week)......Page 65 1.6 Incidence of Low-Paid Work in Total Wage Employment and Self-Employment, around 2000......Page 67 1.7 Weekly Female-to-Male Pay Ratios, around 2000......Page 68 1.8 Share of Employed Men and Women in Different Employment Status, around 2000......Page 69 1.9 Gender Differences in Sectors of Employment......Page 71 1.10 Gender Differences in Literacy and Education, around 2000......Page 76 1.12 Gender Differences in Enrollment Ratios Among Children Ages 7–12 by Consumption Quintiles, around 2000......Page 78 3.1 Distribution of Individuals Aged 15 and Older Across All Sectors of Employment in Madagascar......Page 125 3.2 Distribution of Individuals Aged 15 and Older Across All Sectors of Employment in Urban and Rural Areas......Page 127 4.1 Gender Composition of the Employee Samples......Page 189 4.3 Quantile Decompositions of the Gender Wage Gap, by Country......Page 198 4.4 Decomposition of Gender Earnings Differentials Accounting for Gender Segregation Across Firms......Page 200 5.1 Selected Gender Indicators......Page 226 5.2 Profile of Educational Attainment by Age Cohort, Gender, and Rural and Urban Location......Page 227 5.4 Simulation Results: Gross Enrollment Rate, Secondary......Page 242 5.5 Simulation Results: Wage Growth for Labor with Secondary Education......Page 243 6.1 Average Household Income and Consumption by Consumption Quintile in Guinea......Page 264 6.3 Sectoral Impact on Female Labor and Female Labor Elasticity (Shock of 1% of Aggregate Exports)......Page 288 6.4 Difference in Sectoral Impact on Female and Male Labor Income and Impact on Aggregate GDP (Shock of 1% of Aggregate Exports)......Page 289 6.5 Difference in Sectoral Impact on Rural and Urban Labor Income (Shock of 1% of Aggregate Exports)......Page 290 7.1 Difference Between Sectoral Impact on Female and Male Labor Income, and Impact on Aggregate GDP (Shock of T Sh 100 million)......Page 314 7.2 Difference Between Sectoral Impact on Workers with No Formal Education and Unfinished Secondary (Shock of T Sh 100 million)......Page 316 7.4 Example of Paths to a Category of Labor......Page 319 7.5 Speed of Selected Transmission Channels of Shocks from Growth to Labor Income......Page 320 8.1 Generalized Lorenz Curves for Total Work Time by Gender in Urban Areas in Ethiopia, 2005......Page 341 8.2 Generalized Lorenz Curves for Total Work Time by Gender in Rural Areas in Ethiopia, 2005......Page 342 10.1 Impact of Gender Variables on Consumption Patterns in the Republic of Congo, 2005......Page 406 11.2 Decision Making on Health by Age and Gender in Nigeria......Page 419 11.4 Decision Making on Clothing by Age and Gender in Nigeria......Page 420 11.6 Decision Making on Sale of Farm Crop by Age and Gender in Nigeria......Page 421 11.8 Main Contributor of Income in the Household by Age and Gender in Nigeria......Page 422 1.1 List of Surveys by Country and Date......Page 55 1.2 Employment Ratio by Gender, around 2000......Page 59 1.3 Employment Ratio by Gender and Age Class, around 2000......Page 62 1.4 Gender Differences in Unemployment Rates by Age and Location, around 2000......Page 64 1.6 Share of Employed Men and Women in Selected Employment Status, around 2000......Page 70 1.8 Share of Employed Individuals in Selected Employment Status by Gender and Education, Regional Average, around 2000......Page 73 1.9 Earnings Gap Ratio by Education Level and Gender......Page 74 2.2 Nature and Terms of Wage Employment in Total Wage Employment, 2005......Page 91 2.4 Levels of Education Among the Wage-Employed by Gender, 2005......Page 93 2.5 Lower and Upper Estimates of Private Returns to Education, 2005......Page 97 2A.2-1 Selectivity Corrected (Heckman Two-Step Method) Log Monthly Earnings Equations in Wage Employment by Gender, 2005 (age group 15–24)......Page 104 2A.2-2 Selectivity Corrected (Heckman Two-Step Method) Log Monthly Earnings Equations in Wage Employment by Gender, 2005 (age group 25–34)......Page 106 2A.2-3 Selectivity Corrected (Heckman Two-Step Method) Log Monthly Earnings Equations in Wage Employment by Gender, 2005 (age group 35+)......Page 108 2A.3 The Cotton-Neumark Decomposition of the Gender Mean Log Monthly Earnings Differentials in Wage Employment......Page 110 2A.4 The Cotton-Neumark Decomposition of the Gender Mean Log Monthly Earnings Differentials in Wage Employment by Age Cohorts (15–24, 25–34, 35+)......Page 111 3.3 Gender Earnings Gaps in Madagascar......Page 130 3.4 Full Decomposition of the Gender Wage Gap (OLS estimates)......Page 137 3B.2 Summary Statistics of the Variables Used in the Earnings Equations......Page 151 3C.2 Nature and Terms of Employment in Total Employment in Urban Areas......Page 154 3C.3 Nature and Terms of Employment in Total Employment in Rural Areas......Page 156 3C.4 Determinants of Labor Allocation Across Paid Employment and Agricultural Self-Employment (Multinomial Logit Models)......Page 158 3C.5 Determinants of Labor Allocation Across Sectors for Males (Multinomial Logit Models)......Page 160 3C.6 Determinants of Labor Allocation Across Sectors for Females (Multinomial Logit Models)......Page 162 3D.2 Log Hourly Earnings Equations for Public Wage Employment......Page 166 3D.3 Log Hourly Earnings Equations for Formal Wage Employment......Page 168 3D.4 Log Hourly Earnings Equations for Informal Wage Employment......Page 170 3D.5 Log Hourly Earnings Equations for Non-Farm Self-Employment......Page 172 3E.2 Neumark’s Decomposition of the Gender Log Hourly Earnings Gap by Wage Employment Sector (OLS estimates)......Page 175 3E.3 Neumark’s Decomposition of the Gender Mean Log Hourly Earnings Gap in the Non-Farm Self-Employment Sector (OLS estimates)......Page 177 4A.2 Descriptive Statistics on the Firms......Page 207 4A.3 Linear Regression of the Log Hourly Wages......Page 209 4A.4 Decomposition Using Fields of the Log Hourly Wages......Page 211 4A.5 Gender Estimates from Quantile Regressions of the Log Hourly Wages......Page 212 4A.6 Decomposition of the Gender Earnings Differentials Accounting for Gender Segregation Across Firms......Page 214 5.1 Description of Simulations......Page 233 5.2 Simulation Results: Macro Indicators......Page 235 5.3 Simulation Results: Enrollment and Gross Enrollment Rate (GER) by Cycle and Gender......Page 236 5.4 Simulation Results: Wages, Employment, and Wage Income by Education and Gender......Page 237 5A.3 Ethiopia: Selected Aggregate and Disaggregated Indicators of Gender Disparities, 1995......Page 247 5A.4 Ethiopia: Selected Aggregate and Disaggregated Indicators of Gender Disparities, 1995......Page 248 5A.5 Simulation Results: Time Use by Education and Gender—Selected Scenarios......Page 249 6.1 Analysis of the Correlates or Determinants of Individual (Log) Wage Incomes in Guinea, 2002–03......Page 266 6.2 Work Time (hours/week) of Individuals Over Age 15 in Guinea, 2002–03......Page 268 6.3 Time (hours/week) Devoted to Different Work Activities by Sex, Age, and Region, 2002–03......Page 270 6.4 Rate of Time Poverty of Individuals Over Age 15 in Guinea, 2002–03......Page 271 6.5 Effects of Work Time Increases by Individuals Over Age 15 on Household Income or Consumption in Guinea, 2002–03......Page 273 6.6 Effect of Increase and Reallocation of Work Time on Monetary Poverty and Inequality in Guinea, 2002–03......Page 274 6.7 Schematic Social Accounting Matrix......Page 278 6.8 Sectoral Analysis for the Guinea SAM, 2005 (in GNF billions)......Page 280 6.9 Summary Data on Labor Income Shares in the Guinea SAM......Page 281 6.10 Effect on Labor of an Exogenous Demand Shock of 1 Percent of Aggregate Exports, 2005......Page 283 6.11 Percentage of Total Multiplier Effect Resulting from Indirect Effects in Guinea, 2005......Page 286 7.1 Sectoral Analysis for Tanzania SAM, 2001 (T Sh million)......Page 307 7.2 Summary Data on Labor Income Shares in Tanzania SAM......Page 309 7.3 Effect on Labor of Exogenous Demand Shock of T Sh 100 million......Page 311 7.4 Example of Structural Path Results......Page 317 7A.1 Structural Path Analysis for Tanzania, 2001......Page 324 8.1 Decomposition of Average Total Work Hours Per Week by Gender in Ethiopia, 2005......Page 337 8.2 Decomposition of Average Total Work Hours Per Week by Place of Residence and Gender in Ethiopia, 2005......Page 339 8.3 Time Poverty Rates and Gaps by Place of Residence and Gender in Ethiopia, 2005......Page 343 8.4 Labor Force Participation and Unemployment in Ethiopia, 2005......Page 346 8.5 Measures of Labor Supply in Ethiopia, 2005......Page 348 8.6 Distribution of Workers by Employment Sectors in Ethiopia, 2005......Page 349 8.7 Distribution of Workers by Sector of Activity, Occupation, and Terms of Employment in Ethiopia, 2005......Page 350 8A.1-2 Determinants of Hours Per Week Worked in the Household by Gender and Place of Residence in Ethiopia, 2005 (Tobit models)......Page 355 8A.2-2 Marginal Impacts of Covariates on Female Segment Employment Choices after Multinomial Logit Estimation......Page 359 9.1 Domestic Work According to Gender and Age Group in Sierra Leone, 2003–04......Page 366 9.2 Domestic Work According to Access to Water and Electricity in Sierra Leone, 2003–04......Page 368 9.3 Domestic Work According to Per Capita Consumption Status in Sierra Leone, 2003–04......Page 370 9.4 Domestic Work According to Employment Status in Sierra Leone, 2003–04......Page 372 9.5 Domestic Work According to Migration Status in Sierra Leone, 2003–04......Page 374 9.6 Domestic Work According to Household Composition in Sierra Leone, 2003–04......Page 376 9.7 Determinants of the Number of Hours Spent on Domestic Work per Week in Sierra Leone, 2003–04......Page 377 10.1 Household Income and Consumption by Quintile of Consumption in the Republic of Congo, 2005......Page 392 10.2 Household Income in the Republic of Congo According to Sources, 2005......Page 393 10.3 Determinants and Basic Statistics Concerning Individuals’ Wages in the Republic of Congo, 2005......Page 399 10.4 Basic Statistics on Expenditure Shares (%) in the Republic of Congo, 2005......Page 402 10.5 Correlates of Household Consumption Shares for Various Items in the Republic of Congo, 2005......Page 403 11.1 Basic Statistics on Employment and Education by Gender in Nigeria......Page 414 11.2 Contribution to Household Expenses and Decision Making by Gender and Poverty Status in Nigeria......Page 417 11.3 Impact of Income Contribution on Decision Making by Gender in Nigeria......Page 425 11.4 Impact of Income Contribution on Decision Making by Gender and Poverty Status in Nigeria......Page 426 11A.2 Bivariate Probit Regressions for Men in Nigeria......Page 432 Women's earnings are a fraction of male's earnings in several African countries. It is tempting to conclude that this wage gap is a sign of discrimination against women in the labor market. Yet this book uses new datasets to show that the gap is not simply the result of discrimination in the labor markets, but rather the result of multiple factors, including access to education and credit, cultural values and household duties, and, above all, labor market conditions. It shows that gender disparities grow when economies are not functioning well and labor markets are tiny. More than the effect of discrimination, it seems that job rationing causes those with better human capital and those with more power in the household--usually the men--to take the few jobs that are available. It is hardly surprising, then, that in a region where only a fraction of the labor force finds jobs in the formal sector, gender disparities in earnings are so high. The book further documents that firm-level and sector characteristics are additional powerful factors in explaining the gender disparities in the labor market. As the causes are not simple, neither are the solutions; multifaceted strategies are needed. By providing environments that support economic growth and, more importantly, job creation, as well as by promoting equal access for women to education and rethinking the attitudes that limit what women may achieve, governments in the region will substantially improve the well-being of all their peoples. Gender Disparities in Africa's Labor Market helps to fill the knowledge gap and identify the links between gender disparities and poverty reduction. The work was implemented in collaboration with a range of poverty and labor market studies to maximize its usefulness for policy dialogue in specific countries. This book will be of interest to policy makers, students, academics, gender experts, and all those interested in gender issues and development A Copublication Of The Agence Française De Développement And The World Bank. Why Study Gender Disparities In Africa's Labor Markets? / Jorge Saba Arbache, Ewa Filipiak, And Alexandre Kolev -- Gender Disparities In Africa's Labor Markets : A Cross-country Comparison Using Standardized Survey Data / Alexandre Kolev And Nicolas Sirven -- Exploring The Gender Pay Gap Through Different Age Cohorts : The Case Of Ethiopia / Alexandre Kolev And Pablo Suárez Robles -- Gender Disparities In The Malagasy Labor Market / Christophe J. Nordman, Faly Rakotomanana, And Annie-sophie Robiliard -- Gender Differences In Pay In African Manufacturing Firms / Christophe J. Nordman And François-charles Wolff -- Addressing Gender Inequality In Ethiopia : Trends, Impacts, And The Way Forward / Caterina Ruggeri Laderchi, Hans Lofgren, And Rahimaisa Abdula -- Gender, Time Use, And Labor Income In Guinea : Micro And Macro Analyses / Juan Carlos Parra Osorio And Quentin Wodon -- How Does Growth Affect Labor Income By Gender? : A Structural Path Analysis For Tanzania / Juan Carlos Parra Osorio And Quentin Wodon -- Gender Disparities In Time Allocation, Time Poverty, And Labor Allocation Across Employment Sectors In Ethiopia / Pablo Suárez Robles -- Domestic Work Time In Sierra Leone / Quentin Wodon And Yvonne Ying -- Gender Labor Income Shares And Human Capital Investment In The Republic Of Congo / Prospere Backiny-yetna And Quentin Wodon -- Income Generation And Intra-household Decision Making : A Gender Analysis For Nigeria / Diego Angel-urdinola And Quentin Wodon. Jorge Saba Arbache, Alexandre Kolev, And Ewa Filipiak, Editors. Includes Bibliographical References And Index.

The main aim of this book is to help fill the gap in current knowledge about the nature, the extent, and some of the root causes of gender disparities in Africa, showing what can be revealed about the application of standard and less standard tools and methods to existing survey and national account data. The analysis herein is novel in providing in-depth assessments of some of the sources of gender disparities in different labor market outcomes. A part of the book provides results on the basis that data are as comparable as possible for 18 countries. These results were extracted from multi-topic, integrated household surveys conducted in Africa around 2000 and thus may not represent the latest trends, but they have the merit to be comparable. The cross-national perspective provides a benchmark against which other results for individual countries and more recent data presented here may be compared. Additional goals are to demonstrate the possibilities, as well as the challenges, of analysis of gender inequality in labor market outcomes with existing survey data, to support the improvement of data collection, and to stimulate further research on gender disparities in Africa. The book touches on policy issues at various points, although it is not principally a book about using policy to reduce gender inequality. Rather, it aims to provide analysis that is relevant to policy design.