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G²LM|LIC

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Datasets

The datasets of the GLM|LIC programme offer a data repository service for researchers who are interested in labour market issues in low-income countries (LICs). Files with projects or data sources listed below are associated with the GLM|LIC programme.

  • Wage Compression in Low Income Labor Markets

Datasets. Two types of data have been collected during the project: the experiment data as well as the survey data on subjects’ past wage and employment history. The data have been used in the publications: Breza, E., Kaur, S. and Shamdasani, Y., 2017. The morale effects of pay inequality. The Quarterly Journal of Economics, 133(2), pp.611-663.

  • Measuring Labor in Farm Households in Africa

Datasets. This survey experiment studies the accuracy of farm labour data in household surveys. They tested four alternative survey designs across 854 households from 18 communities in the Mara Region of Tanzania during the main 2014 agricultural season (roughly January to June).

  • Food Constraints, Yield Uncertainty and “Ganyu” Labor

Datasets. All survey data have been collected by IPA Zambia through computer assisted interviews using handheld mobile devices (Samsung Gio).

  • Promoting Migrant Remittances using Mobile Banking: Evidence from a Field Experiment

Datasets. With their project partner, Carteira Movel, administrative data have been collected on take-up and usage of mKesh services by all participants.

  • The Formal-Informal Labor Nexus and Growth: The Case of Bangladesh

Datasets. The datasets include a sample of worker histories and valuation for formal work from approximately 2,000 workers in Dhaka and Chittagong. In addition, it combines the labor force data from 2002, 2005 and 2010 LFS with information from the HIES survey rounds in 2000, 2005 and 2010, which also include modules on employment.

  • Girls Empowerment by Microfranchising: Estimating the Impacts of Microfranchising on Young Women in Nairobi

Datasets. The GEM evaluation produces four distinct data sets: the baseline survey, the enterprise census, the high frequency surveys, and the endline survey.

  • High-Risk Youth in Post-Conflict Liberia: Experimentally Testing Sustainable Strategies for Boosting Employment, Productivity and Social Stability

Datasets. The project creates a unique panel dataset on high-risk youth with valuable insights into the Liberian labor market. The data have been used in the publications: Blattman, C., Jamison, J.C. and Sheridan, M., 2017. Reducing crime and violence: Experimental evidence from cognitive behavioral therapy in Liberia. American Economic Review, 107(4), pp.1165-1206.

  • Building Management Hierarchies for Growth in LICs

Datasets. The project collects administrative data from the factories and also conducts surveys with supervisors and machine operators in the factories. The survey of selected samples of workers within the factory monitors wages, extra-hours, working conditions, relationships and communication patterns with supervisors, work attitudes, aspirations, career plans, and other individual characteristics.

  • Labour Migration and Structural Change in Rural Labour Markets

Datasets. This project collates, digitises and uses individual-level and aggregate Census data from the 1940s through 1990s to investigate whether these large migration flows and corresponding cash inflows through deferred pay schemes affected the employment patterns of men and women over the long­ term.

  • The Labour Market Impacts of Forced Migration

Datasets. LAMFOR collects additional data on this topic in Burundi in 2015 to complement data previously collected by the researchers (national dataset) in 2011.

  • The Urban Geography of Entrepreneurship and Growth in India

Datasets. The project produces a new high-resolution spatial dataset covering many aspects of the urban economy, including formal and informal labour markets, industrial structure, housing prices, zoning laws, infrastructure and poverty.

  • Globalization and the Gender Gap

Datasets. The paper associated with this dataset analyzes theoretically and empirically the impact of comparative advantage in international trade on fertility. It builds a model in which industries differ in the extent to which they use female relative to male labor and countries are characterized by Ricardian comparative advantage in either female labor or male labor-intensive goods.

  • Matched Employee-Employer Panel-Data for Labour Market Analysis in Zimbabwe

Datasets. This project addresses some of the data constraints that inhibit appropriate research and policy formulation on Zimbabwean manufacturing. The objective of the project was to build a panel of firm data in Zimbabwe that covers various years over the period 1993 to 2015 and to add a matched survey of employees covering the period 2015 to 2016. The basis of the firm panel is the Regional Programme on Enterprise Development (RPED) surveys of manufacturing firms in Zimbabwe conducted in 1993, 1994, and 1995.

  • Gender and Employment in Central Asia

Datasets. The dataset covers a wide range of topics – from household demographics, assets, income sources, expenditure, migration to individual well-being, employment, social networks, decision-making, and attitudes among many other topics.

  • The Urban Geography of Entrepreneurship and Growth in India

Datasets. The Socioeconomic High-resolution Rural-Urban Geographic Platform for India (SHRUG) data platform includes a core set of data that spans India’s 500,000 villages, 8000 towns, and 4000 legislative assemblies.

  • Trade, Labour Markets and Women’s Economic Empowerment in Ethiopia

Datasets. The datasets of the baseline, midline and endline surveys contain information on several domains of Ethiopia such as women empowerment, agricultural production, prices, labor markets, shocks, financial and non-financial assets which will have the potential to be used in a variety of different studies on labor agricultural markets and women’s empowerment beyond the scope and purpose of the original research.

  • Reducing Extreme Poverty through Skill Training for Industry Job Placement

Datasets. The datasets cover the sample for the project’s experiment in the Northern Bangladesh by employing randomized control trial (RCT) technique from a short survey to recruit eligible participants (eligibility requires that the prospective participant is interested in training if offered an opportunity) from a large population on the basis of age, education and poverty status.

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