Toward Labor Market Policy 2.0
Economists and other social scientists are increasingly using big data analytics to address longstanding economic questions and complement existing information sources. Big data produced by online platforms can yield a wealth of diverse, highly granular, multidimensional information with a variety of potential applications. This paper examines how online job-portal data can be used as a basis for policy-relevant research in the fields of labor economics and workforce skills development, through an empirical analysis of information generated by Babajob, an online Indian job portal. The analysis highlights five key areas where online job-portal data can contribute to the development of labor market policies and analytical knowledge: (i) labor market monitoring and analysis; (ii) assessing demand for workforce skills; (iii) observing job-search behavior and improving skills matching; (iv) predictive analysis of skills demand; and (v) experimental studies. The unique nature of the data produced by online job-search portals allows for the application of diverse analytical methodologies, including descriptive data analysis, time-series analysis, text analysis, predictive analysis, and transactional data analysis. This paper is intended to contribute to the academic literature and the development of public policies. It contributes to the literature on labor economics through application of big data analytics to real-world data. The analysis also provides a unique case study on labor market data analytics in a developing-country context in South Asia. Finally, the report examines the potential for using big data to improve the design and implementation of labor market policies and promote demand-driven skills development.
| Main Authors: | , , , |
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| Format: | Working Paper biblioteca |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2017-02
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| Subjects: | labor market, labor skills, job-search behavior, labor demand, labor market analytics, big data, wage, gender, skills demand, forecasting, behavioral, |
| Online Access: | http://documents.worldbank.org/curated/en/370301486667802852/Toward-labor-market-policy-2-0-the-potential-for-using-online-job-portal-big-data-to-inform-labor-market-policies-in-India https://hdl.handle.net/10986/26133 |
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| Summary: | Economists and other social scientists
are increasingly using big data analytics to address
longstanding economic questions and complement existing
information sources. Big data produced by online platforms
can yield a wealth of diverse, highly granular,
multidimensional information with a variety of potential
applications. This paper examines how online job-portal data
can be used as a basis for policy-relevant research in the
fields of labor economics and workforce skills development,
through an empirical analysis of information generated by
Babajob, an online Indian job portal. The analysis
highlights five key areas where online job-portal data can
contribute to the development of labor market policies and
analytical knowledge: (i) labor market monitoring and
analysis; (ii) assessing demand for workforce skills; (iii)
observing job-search behavior and improving skills matching;
(iv) predictive analysis of skills demand; and (v)
experimental studies. The unique nature of the data produced
by online job-search portals allows for the application of
diverse analytical methodologies, including descriptive data
analysis, time-series analysis, text analysis, predictive
analysis, and transactional data analysis. This paper is
intended to contribute to the academic literature and the
development of public policies. It contributes to the
literature on labor economics through application of big
data analytics to real-world data. The analysis also
provides a unique case study on labor market data analytics
in a developing-country context in South Asia. Finally, the
report examines the potential for using big data to improve
the design and implementation of labor market policies and
promote demand-driven skills development. |
|---|