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/data sources listed below are associated with the GLM|LIC and G2LM|LIC programme:
Developed within the G2LM|LIC programme, the The Jobs of the World Project is a publicly available resource built to enable researchers to analyse comparable labor market outcomes across countries and time using micro data. At the core of the project is the collation and harmonisation of all available Censuses (IPUMS) and Demographic and Health Surveys (DHS) for low and middle income countries. The two sources combined provides coverage of countries representing about 81 percent of the world’s population, and more than 90 percent of the population in low- and middle-income countries. A key innovation is the construction of comparable wealth measures that allow researchers to analyse labor market outcomes across wealth classes. The project has three outputs:
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- Codes that allow researchers to implement the harmonisation and produce customised data sets from publicly available IPUMS and DHS.
- The Jobs of the World Database (JWD): The database focuses on a wide range of labor market characteristics including, but not limited to, labor force participation, type of employment (e.g., waged or self-employment), sector of employment (e.g., agriculture, manufacturing, or service), skill level (e.g., managers and professionals, white collar, or blue collar).
- Web platform to build downloadable maps and charts based on JWD.
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Datasets. The data collection from jobseekers and firms is done as part of the enrollment and operations for the job search platform called “Job Talash”. The Firm survey dataset consists of all the attempts made to employers to enlist vacancies on the platform. The dataset also has the ads listing data which specifies the requirements of firms for vacancies that are listed on the platform, Job Talash. All registered firms on the platform receive a call every 3 months, asking them if they’d like to list a vacancy on the platform. If they decide to list a vacancy, the information about the requirements for the vacancy is collected so that relevant candidates can be matched to those jobs. The Jobseeker dataset is based on the job matches generated for the jobseekers periodically based on their profile that includes, work experience, gender, education level and job interest. These job matches are communicated to the jobseeker via text message and phone call. A screening instrument is used by the field team while making phone calls for giving job updates to the jobseekers and recording their interest in the available positions. Along with the application interest, also information ) is collected about whether they have been employed to earn an income in the last 14 or 30 days (randomized recall period for each jobseeker.
Datasets. In this project, rich administrative data on search and recruitment from a low-wage online job portal are used to study the labor market impacts of COVID-19 in India. The data from the job portal includes information on vacancies and job seekers across 2019 and 2020. It covers all users that either posted a vacancy or applied to a job on the portal across the two years. Aggregate and state-level data are available.
Datasets. The project investigate a sample of over 3,000 small-scale farmers in Zambia, who were given the opportunity to exchange randomly assigned household items for alternative items of similar value. Analyzing a total of 5,842 trading decisions over a range of items, including cash, this study shows that exchange asymmetries are sizable and remarkably robust across items and experimental procedures. Using cross-sectional, seasonal, and randomized variations in financial resource availability, the authors show that exchange asymmetries decrease in magnitude when subjects are more constrained. Consistent with the interpretation that variation in decision stakes drives the results, the authors also show that trading probabilities increase when the value of the items involved is exogenously increased.
Datasets. The project conducted a randomized evaluation of two labor market interventions between 2013 and 2017 targeted to 905 young women aged 18 to 19 in three of Nairobi’s poorest neighborhoods, Baba Dogo, Dandora, and Lunga Lunga. Applicants to the program were stratified by neighborhood and application date and then randomly assigned to one of three treatment arms: a franchise treatment, a cash grant treatment, and a control group. This design allows to estimate the impact of the franchise and grant treatments on those invited to the program, and to compare the impacts of the cash grant treatment — which relaxes the credit constraint but provides no other training or support — to a multifaceted program designed to address many of the obstacles to youth entrepreneurship simultaneously.
Datasets. A field experiment was carried out in which randomly selected markets received community-wide trainings to help local farmers identify government-certified seeds. The dataset makes reference to “treated” households, which are households that were sampled from market areas that were selected for treatment, and therefore reside within 1 kilometer from the market center. The researcher examined differential impacts on female-headed versus male-headed households, potential mechanisms through information-sharing networks, and implications of the results for closing the gender gap in productivity
Datasets. The study seeks to support the Philippine COVID-19 response by quantifying the role of international migrant remittances in helping households cope with the pandemic’s economic consequences. The research team conducted surveys of an existing study sample of 2,000 Filipino workers in Dubai, United Arab Emirates (UAE) and their origin‐households in the Philippines.
Datasets. This study does examine the resilience of young micro-entrepreneurs in the informal sector and their families in rural Uganda against the COVID-19 shock. More specifically, the study investigates how firms have built up considerable amounts of physical and human capital over the past decade versus those that have not. The survey focuses on economic resilience and how it relates to skilled labor and assets. It also provides information on the impact of COVID-19 on frequently discussed outcomes (e.g. health status, food security, urban-rural migration).
Datasets. The broad objective of this project was to provide information that could be used to target aid and welfare or employment support to those who are stuck in an unemployment or underemployment trap due to the COVID-19 pandemic. To meet these objectives, a large sample of respondents was targeted living in Kibera, Kenya. N = 597 respondents were successfully recruited. The sample comprised mostly of women (67.7%), in a marriage or marriage-like relationship (51.4%), with three+ kids living at home (M=2.67, SD=1.50).
Datasets. The Meet Your Future Project (MYF) is an RCT designed in partnership with BRAC Uganda to investigate the relative importance of several barriers to quality employment that students face when transitioning from the educational sector into labor markets characterized by high levels of informality. The main study is aimed at understanding whether career-services are specifically beneficial for disadvantaged populations, including: (i) economically disadvantaged students sponsored by NGOs, (ii) women and (iii) minorities, such as under-represented ethnic groups and migrants. The experimental setting is that of Vocational Training Institutes (VTIs) in Uganda.
Datasets. The data were collected during April and May 2016 on a sample of 300 Ethiopian manufacturing firms and 3.000 workers. As sampling frame the 2015 Census of Manufacturing Firms was used conducted by the Central Statistical Agency (CSA) of Ethiopia that captures all manufacturing firms that use power-driven machinery and employ at least 10 workers. The Census is officially referred to as “Large and Medium Scale Manufacturing and Electricity Survey”
Datasets. Data is based on a phone survey of 1,545 rural Indian households collected in August 2020 in 20 districts across 6 states (Rajasthan, Uttar Pradesh, Bihar, Jharkhand, Madhya Pradesh, and Maharashtra) in Northern India in August 2020. Households participated in a 20–30 min survey with two parts, a household head module and a female respondent module. In the household head module the household head surveyed about the household’s socioeconomic conditions, household head’s income, the male and female heads’ nutrition, and the number of days the respondent wished for more food for themselves or their children. The nutrition questions were taken from the National Family and Health Survey (NFHS) 2015–16, allowing to use the pre-pandemic responses to the survey from the same district to benchmark nutritional outcomes.
Datasets. The Dataset contains information on COVID-Induced Migrants in India. In total, 8,265 migrants were surveyed across four survey rounds: April to June 2020; July to August 2020; January to March 2021; and June to July 2021. In the first round, enrollment of approximately 5,000 migrants was targeted. In subsequent rounds, the researchers attempted to re-interview approximately 4,000 of these respondents, drawing randomly from each initial state sample frame. Up to four observations per respondent were collected (an average of 2.37 observations per respondent, with 23.41% of migrants participating in all waves of the panel). If it was impossible to reach respondents from a previous round, participants were replaced with other migrants of the same gender, drawn randomly from the initial state sample frames.
Datasets. The intervention was carried out in October 2017. A baseline survey was conducted prior to the intervention in 2017 and two follow-up surveys were carried out in December 2018 and end of 2019. In addition, a special follow-up survey of the workers was carried out in January 2021 following the Covid-19 pandemic outbreak to gauge their wellbeing.
The surveys undertaken in 2017-2019 also include workers’ characteristics such as workers’ age, occupation (foreman, skilled worker, or apprentice), monthly salary, daily hours, experience in the workshop, and experience in the occupation. This information is collected in all three rounds, although the data provides only a repeated cross-section of workers and does not allow to link the same worker over time.
Datasets. This dataset contains phone survey responses from the Western Terai Panel Survey. The data includes phone surveys from 2,636 rural households in 90 villages in the districts of Kailali and Kanchanpur in the western Terai region of Nepal, collected from August 2019 through October 2020.
Datasets. Two interventions designed to help young urban dwellers search for employment by removing spatial and informational obstacles to job search were evaluated experimentally in Addis Ababa. The first intervention was a transport subsidy lowering the cost of job search. The second intervention was a job application workshop, designed to improve job seekers’ ability to signal their skills to employers. Participants were offered orientation on how to make effective job applications using CVs and cover letters, and on how to approach job interviews. Further, they took a mix of standardized personnel selection tests.
Datasets. 20+ years longitudinal survey on health, educational, nutritional, demographic, social, and labor market outcomes among a sample of thousands of Kenyans who were participants in one or more randomized health, skills training, and financial capital interventions during childhood and adolescence. These surveys measured labor market activity, childcare hours, food security, migration, the home learning environment (including parent-child reading), knowledge of COVID-19 and social distancing adherence.
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.
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).
Datasets. All survey data have been collected by IPA Zambia through computer assisted interviews using handheld mobile devices (Samsung Gio).
Datasets. With their project partner, Carteira Movel, administrative data have been collected on take-up and usage of mKesh services by all participants.
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.
Datasets. The GEM evaluation produces four distinct data sets: the baseline survey, the enterprise census, the high frequency surveys, and the endline survey.
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.
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.
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.
Datasets. LAMFOR collects additional data on this topic in Burundi in 2015 to complement data previously collected by the researchers (national dataset) in 2011.
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.
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.
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.
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.
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.
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.