Abstract
The literature on unemployment in India has not given adequate attention to the analysis of unemployment spells. This paper attempts to fill this gap by focusing on the trends in the incidence and distribution of unemployment spells from 1993 to 2012. It was found that shorter unemployment spells of up to two months are more prevalent in rural areas, primarily for casual labour who experience a break in their employment due to lack of work. On the other hand, longer spells of more than 6 months are predominant in urban areas, experienced predominantly by young, well-educated population, who do not come from the poorest households, and do not have any previous job market experience. Further, the incidence as well as the contribution to longer durations of unemployment is higher in the eastern region and females are more likely than males to experience them. The author discusses the findings, their policy implications, and suggests ways to improve upon the available data so that it can help in developing a better understanding of the factors contributing to unemployment.
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Notes
The 68th round conducted in 2011–2012, is an exception, as it was conducted only two years after the previous quinquennial round in 2009–2010 (66th round). This was because 2009–2010, was considered a ‘non-normal year’ (NSC 2011) (i.e. a drought year).
For instance, the sample size for the survey conducted in 2011–2012, was 456,999 persons (280,763 in rural areas and 176,236 in urban areas).
The methodology for these surveys, including sample design, sample size, estimation procedure, schedule used etc., is obtained from the respective NSS reports: 50th round: Chapter 3 of NSSO (1996); 61st round: Appendices B & C of NSSO (2006); 66th round: Appendices B & D of NSSO (2011); 68th round: Appendices B and D of NSSO (2014).
Throughout the analysis, the labour force is defined as per the Current Weekly Status (CWS) of the NSS and is composed of those who were either working or did not work but were seeking or were available for work, for at least half-a-day in the reference week.
In the interests of space, we provide the distribution for only these years. The patterns for the intervening years of 2004–2005 and 2009–2010, are broadly similar and are available on request.
In the NSS, households are classified into various types broadly based on the economic activities which constitute the major source of their incomes over the 365 days preceding the survey.
For those unemployed for up to two months in rural (urban) areas, the corresponding proportions are 62 per cent (36 per cent) in 2011–2012, and 75 per cent (28 per cent) in 1993–1994.
Based on 3-digit NCO classification.
Since we restrict the sample to those who are unemployed for the entire reference week, we understand that there are sample selection issues at work here. Given this, we do not interpret the estimates in Tables 7 and 8 as the causal effect of a variable on the likelihood of longer-duration unemployment. Instead, we only intend to capture correlations of longer-duration unemployment in a multivariate framework.
Since the 61st round in 2004–2005, the NSS has been collecting the total duration of unemployment over the past 365 days for every individual (this was earlier restricted to those unemployed by the UPS criterion). However, as noted earlier, this is an aggregation of unemployment duration over all the spells and hence the duration of a spell is not captured. See Ahmed (2015) for an analysis of factors contributing to unemployment duration.
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Acknowledgements
I would like to thank the editor and an anonymous referee for valuable comments that have considerably improved the paper. I am grateful to Sripad Motiram, S. Chandrasekhar, Sudha Narayanan, Stephan Klasen, and Mousumi Das for their valuable comments. An earlier version of this paper was presented at the 55th Annual Conference of ‘The Indian Society of Labour Economics’ and at the Summer Conference in Economics at the Indian Institute of Technology, Delhi and I would like to thank the participants for their feedback. I am alone responsible for any remaining errors.
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Naraparaju, K. Unemployment Spells in India: Patterns, Trends, and Covariates. Ind. J. Labour Econ. 60, 625–646 (2017). https://doi.org/10.1007/s41027-018-0119-2
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DOI: https://doi.org/10.1007/s41027-018-0119-2