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Female labor force participation rates in urban India between 1987 and 2011 are surprisingly low and have stagnated since the late 1980s. Despite rising growth, fertility decline, and rising wages and education levels, married women's labor force participation hovered around 18 percent. Analysis of five large cross-sectional micro surveys shows that a combination of supply and demand effects have contributed to this stagnation. The main supply side factors are rising household incomes and husband's education as well as the falling selectivity of highly educated women. On the demand side, the sectors that draw in female workers have expanded least, so that changes in the sectoral structure of employment alone would have actually led to declining participation rates.
Education --- Female Labor Force Participation --- Gender --- Gender & Development --- Labor Markets --- Labor Policies --- Population Policies --- Primary Education
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Female labor force participation rates in urban India between 1987 and 2011 are surprisingly low and have stagnated since the late 1980s. Despite rising growth, fertility decline, and rising wages and education levels, married women's labor force participation hovered around 18 percent. Analysis of five large cross-sectional micro surveys shows that a combination of supply and demand effects have contributed to this stagnation. The main supply side factors are rising household incomes and husband's education as well as the falling selectivity of highly educated women. On the demand side, the sectors that draw in female workers have expanded least, so that changes in the sectoral structure of employment alone would have actually led to declining participation rates.
Education --- Female Labor Force Participation --- Gender --- Gender & Development --- Labor Markets --- Labor Policies --- Population Policies --- Primary Education
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This paper investigates gender differences in the impact of Brazil' trade liberalization on labor market outcomes. To identify the causal effect of trade reforms, the paper uses difference-in-difference estimation exploiting variation across microregions in pre-liberalization industry composition. The analysis finds that trade liberalization reduced male and female labor force participation and employment rates, but the effects on men were significantly larger. Thereby, tariff reductions contributed to gender convergence in labor force participation and employment rates. Gender differences are concentrated among the low-skilled population and in the tradable sector, where male and female workers are most likely to be imperfect substitutes.
Free Trade --- Gender --- Gender & Development --- Gender Inequality --- International Economics and Trade --- Labor Force Participation --- Labor Markets --- Labor Policies --- Social Protections and Labor --- Trade Liberalization --- Trade Policy
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This work brings together the contributions of 2014 IZA Prize in Labor Economics award winner Gary Fields to address global employment and poverty problems. The central questions in his work are how economic growth affects standards of living, how labor markets work in developing countries, and how different labor market policies affect well-being.
Working poor. --- Labor market. --- Income distribution. --- Distribution of income --- Income inequality --- Inequality of income --- Distribution (Economic theory) --- Disposable income --- Employees --- Market, Labor --- Supply and demand for labor --- Markets --- Poor --- Working class --- Supply and demand --- Employment
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This study examines recall bias in farm labor by conducting a randomized survey experiment in Ghana. Hours of farm labor obtained from a recall survey conducted at the end of the season are compared with data collected weekly throughout the season. The study finds that the recall method overestimates farm labor per person per plot by about 10 percent, controlling for observable differences at baseline. Recall bias in farm labor per person per plot is accounted for by the fact that households in the recall group report fewer marginal plots and farm workers, denoted here as listing bias. This listing bias also creates a countervailing effect on hours of farm labor at higher levels of aggregation, so that the recall method underestimates farm labor per plot and per household and overestimates the labor productivity of household-operated farms. Consistent with the notion that recall bias is linked to the cognitive burden of reporting on past events, the study finds that recall bias in farm labor has a strong educational gradient.
Agricultural Productivity --- Agriculture --- Education --- Educational Sciences --- Farm Labor --- Food Security --- Gender --- Gender and Development --- Labor Markets --- Measurement Error --- Recall Bias
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The 19th International Conference of Labour Statisticians (in 2013) redefined labor statistics standards. A major change was to narrow the definition of employment to work for pay or profit. By the revised standards, farming that is only or mainly intended for own use is no longer considered employment, and such a farmer is no longer considered to be employed or in the labor force. This paper analyzes the implications of the revised standards on measures of employment in Sub-Saharan Africa obtained from multi-topic household surveys. It shows that, in some contexts, 70 to 80 percent of farmers produce only or mainly for family consumption and are therefore, based on this activity, not considered employed by the revised standards. However, there is wide variation across countries and regions. Moreover, farmers are more likely to report intending to produce for sale at the end of the growing season of the main local crop than earlier in the season. Men are more likely than women to produce for sale. The revised standards lead to significantly lower employment-to-population ratios in rural Africa and change the sectoral composition of the employed population toward non-agricultural sectors. The paper concludes with recommendations for data producers and users.
Agricultural Sector Economics --- Agriculture --- Employment --- Farm Production --- Female Labor Force Participation --- Gender --- Household Survey --- Informality --- Labor Force Participation --- Labor Market --- Labor Statistics --- Own-Use Production --- Rural Development --- Rural Labor Markets
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