Person:
Nomura, Shinsaku
Author Name Variants
Fields of Specialization
Economics of education
Degrees
Departments
Education Global Practice
Externally Hosted Work
Contact Information
Last updated
January 31, 2023
Biography
Shinsaku Nomura is a Senior Economist at the Education Global Practice in the World Bank. He has worked in countries in Middle East and North Africa, Sub-Saharan Africa, and South Asia regions. In South Asia, he has managed projects of basic and secondary education, early childhood education, and skills development in Pakistan, Bangladesh and India. He has also led analytical projects such as big data labor market analytics, learning assessments, impact evaluations, and economic and financial analyses. He received a PhD in Economics from the Graduate School of International Cooperation Studies, Kobe University, Japan.
Publication Search Results
1 - 3 of 3
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Publication
Reflections of Employers' Gender Preferences in Job Ads in India: An Analysis of Online Job Portal Data
(World Bank, Washington, DC, 2018-03)Using online job portal data and probabilistic regression estimations, the paper investigates the explicit gender bias and salary gap in the Indian job market, reflected in more than 800,000 job recruitment advertisements. Exploring formal and informal sector occupations, the study finds high existence of employers' gender bias in hiring. Explicit gender preferences are highly job specific, and it is common to mention the preferred gender in job ads, which, in general, favor men over women. Although ads for professional occupations exhibit less explicit gender bias, they are not gender neutral. In all types of professional jobs, irrespective of the share of ads with preference for men or women, on average, ads targeting men specify/offer much higher salary. Employers in elementary sectors as well as blue-collar jobs express more segregated gender preference. The findings support the existing research that argues women are more preferred in low-quality, low-status, typically low-paid informal jobs. Targeting women for low-quality jobs explains half of the mean offered salary gap specified in ads; the rest is direct gender bias. The paper also suggests that, with the rise of new technology and sectors, gender bias in hiring in those new types of jobs is expected to decline. -
Publication
Asymmetric Information on Noncognitive Skills in the Indian Labor Market: An Experiment in Online Job Portal
(World Bank, Washington, DC, 2018-03)This paper examines the impact of noncognitive (socio-emotional) skills on job market outcomes, using a randomized control trial implemented in an online job portal in India. Job seekers who registered in the portal were asked to take a Big-Five type personality test and, for a random subsample of the test takers, the results were displayed to potential employers. The outcomes are measured by whether a potential employer shortlisted a job seeker by opening (unlocking) his/her application and background information. The results show that the treatment group for whom test results were shown generally enjoyed a higher probability of unlock. That is, employers are more interested in those for whom they can see personality test results. Such a relationship was not seen in the pre-test period, which confirms that the results are unlikely to be spurious. The study also finds a significant impact among organized, calm, imaginative, and/or quiet applicants (no effect is detected among easy-going, sensitive, realistic, and/or outgoing applicants), which seems to display employers' preference. -
Publication
Toward Labor Market Policy 2.0: The Potential for Using Online Job-Portal Big Data to Inform Labor Market Policies in India
(World Bank, Washington, DC, 2017-02)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.