By tracking indicators over time, JoIn allows users to compare their country with successful episodes of jobs-related economic growth in other similar countries.įor the Jobs and Economic Transformation theme, Hackathon participants had a choice between solving three challenging jobs-related tasks: 1) developing a web-based data visualization tool or app to depict the Jobs indicators 2) creating a jobs and economic transformation taxonomy or 3) mapping worker characteristics to certain occupations and activities drawn from a sample of population census data in client countries. The disaggregated data can help economists and country analysts understand the types of jobs created with economic transformation in countries, and who gets them. JoIn includes 73 standardized labor supply indicators with disaggregation by age, sex, location and education level). It covers 112 countries and is drawn from more than 800 surveys developed from household surveys. One of the Hackathon’s big draws was the newly launched Global Jobs Indicators Database (JoIn), the result of a collaboration between the Development Data Group and the Jobs Group. Armed with datasets from the Development Data Hub and plenty of caffeine, eleven teams got to work. Their mission? Design innovative, data-driven solutions to international development challenges, ranging from matching workers with jobs to smarter lending for the world’s poorest. In October 2019, members of Data Science DC (a meetup within Data Community DC) teamed up with World Bank staff for a Data Dive Hackathon at the World Bank.
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