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Impacts of Vocational Education and Training on Employment and Wages in Indian Manufacturing Industries: Variation across Social Groups—Empirical Evidences from the 68th Round NSSO Data

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  • Tanima Banerjee

    () (University of Calcutta)

Abstract

Abstract Vocational education and training (VET) is critical in developing skilled manpower resources in a country. However, in India, where various administrative and institutional factors are key in the determination of employment and wages, people from all social groups may not benefit equally, from VET. This study analyses how the impact of VET on employment and wages varies across social groups in the Indian manufacturing sector. The main data source for this study is the Employment and Unemployment Survey in India (10th Schedule) of the 68th National Sample Survey quinquennial round (2011–2012). To tackle the problem of bias in sample selection, this study uses Heckman’s Sample Selection Model (1979) with the two-steps estimation technique (Heckit). It reveals that VET significantly enhances participation from all social groups in the manufacturing sector and aggregates wages, but is ineffective in certain manufacturing industries. In certain cases, VET variously impacts wages across workers from different castes and ethnicities.

Suggested Citation

  • Tanima Banerjee, 2016. "Impacts of Vocational Education and Training on Employment and Wages in Indian Manufacturing Industries: Variation across Social Groups—Empirical Evidences from the 68th Round NSSO Data," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 59(4), pages 489-509, December.
  • Handle: RePEc:spr:ijlaec:v:59:y:2016:i:4:d:10.1007_s41027-017-0074-3
    DOI: 10.1007/s41027-017-0074-3
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    References listed on IDEAS

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    1. Sujoy Chakravarty & E. Somanathan, 2008. "Discrimination in an elite labour market? Job placements at the Indian Institute of Management, Ahmedabad," Indian Statistical Institute, Planning Unit, New Delhi Discussion Papers 08-01, Indian Statistical Institute, New Delhi, India.
    2. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters,in: Schooling, Experience, and Earnings, pages 1-4 National Bureau of Economic Research, Inc.
    3. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, September.
    4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    5. Leontaridi, Marianthi Rannia, 1998. " Segmented Labour Markets: Theory and Evidence," Journal of Economic Surveys, Wiley Blackwell, vol. 12(1), pages 63-101, February.
    6. Banerjee, Abhijit & Bertrand, Marianne & Datta, Saugato & Mullainathan, Sendhil, 2009. "Labor market discrimination in Delhi: Evidence from a field experiment," Journal of Comparative Economics, Elsevier, vol. 37(1), pages 14-27, March.
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    More about this item

    Keywords

    Employment; Wage; Vocational education and training; Social groups; Manufacturing; India;

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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