ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846

Articles by Arup MitraSubscribe to Arup Mitra

Understanding Migration Behaviour in India from PLFS Data

Based on the Periodic Labour Force Survey (2020–21), this study focuses on the migration data and tries to delineate certain broad characteristics of the migrant population. Negating some of the commonly held views that less advantaged individuals migrate more frequently than their counterparts, significant departures are noted after the pandemic. Not just the casual labourers, even the regular wage earners suffered seriously during the pandemic and the lockdown. The sudden crisis and the severity of job loss, particularly in the urban areas, which forced many to shift to their native residences are the main reasons of their unwillingness to move out in the future from their current locations.

Livelihood Volatility in the Urban Labour Market

This paper aims at capturing the labour market volatility, which is conceptualised in terms of the lack of sustainable sources of livelihood across different quarters in a year. Though we were unable to identify the number of times workers change their jobs, the change in the job status, which cannot occur unless the job changes, unravels important findings as retrieved from the repeated survey of the same households over different quarters. The results bring out the vulnerabilities of the lower castes, illiterates, and those belonging to large households. The urban informal economy is indeed faced with income volatility, which is connected to employment instability.

Reliability of PLFS 2019–20 Data

The April–June (2020) quarterly data for the urban sector showed a massive decline in the workforce participation rate and a huge increase in the unemployment rate. Still, the annual average work participation rate rose sharply in 2019–20 compared to the earlier two rounds of the Periodic Labour Force Survey estimates, and the average unemployment rate declined somewhat. Given these patterns, the Centre for Monitoring Indian Economy data set, despite its own problems, seems to be casting a more realistic picture.


How Unstable Are the Sources of Livelihood?

This paper, based on the data from the annual Periodic Labour Force Survey, reflects on the lack of sustainable sources of livelihood and the phenomenon of multiple activities pursued simultaneously. A thorough analysis of the quarterly data suggests that in the rural areas, workers largely dependent on agriculture are compelled to shift to other activities in the off season. The nature of employment also varies, particularly in the urban areas. The occupational choice model estimated based on the quarterly data is indicative of changes in the marginal effect for workers of a given caste or an individual with a certain educational attainment. Certain social categories and workers with less educational attainments are more susceptible to changing probability of joining a particular activity and adopting multiple activities.


The COVID-19 Pandemic and Livelihood Loss

Significant variations in the rise in the unemployment rate across regions after the nationwide lockdown was enforced without any discrimination are noted. The reasons for such disparities are explored and migration is noted as an important factor. States with higher rates of migration and urbanisation, greater dependency on casual wage employment and non-agricultural employment witnessed hunger and an adverse impact on livelihood.


Rising Unemployment in India

The rise in the unemployment rate in the recent years along with its convergence across states could be an indicator of a positive change in the economy. Its association with educational attainments and urbanisation is testimony to the brighter side of the development story of India. Further, this rise, against the backdrop of the falling share of the informal sector employment, may suggest that the labour market participants can now afford to remain unemployed instead of getting residually absorbed in petty activities. However, this must not undermine the larger issue of employment creation, which has been a matter of great concern since long.

Counting Jobs in India

A detailed review of various sources of labour statistics in India highlights the lack of long-time series data on total employment. The Labour Bureau’s attempt since the last couple of years in this respect has been helpful. To gauge the accuracy of these estimates, it is desirable to have data from at least two sources. Dependence on one specific source can be risky.

Why Wage Differences Exist across Sectors?

Inter-industry differences in wages are substantial, and over time, they do not seem to be disappearing. Productivity is a determinant of wage differences across industries, though the association between them is not very strong at the aggregate level or for intermediate goods, capital goods, and consumer non-durables. Trade liberalisation enhances productivity and wages at the aggregate level, and also in the case of basic goods and capital goods. However, in an attempt to raise productivity, firms may extract more work from those who are already engaged, and tend to pay them less than their due share in certain industry groups. Contractualisation and feminisation show similar effects for all the industry groups except the intermediate goods industries, and has a worsening effect on wages and also productivity.

Insightful but Incomplete

The Outsiders: Economic Reform and Informal Labour in a Developing Economy by Sugata Marjit and Saibal Kar (New Delhi: Oxford University Press), 2011; pp 218, Rs 695.

Social and Economic Inequalities: Contemporary Significance of Caste in India

Social and Economic Inequalities: Contemporary Significance of Caste in India Rajnish Kumar, Satendra Kumar, Arup Mitra In an attempt to revisit the caste issue in the Indian context this paper analyses a sample of households from the slums of four cities. Vulnerability conceptualised in terms of several socio-economic and demographic indicators exists among most of the social categories though the relative size of deprivation varies across social groups. In a binomial logit framework, based on the pooled sample, the extent of decline in the probability of experiencing well-being beyond a threshold limit is sharper for the socially backward classes than the others. However, in individual cities such a pattern is not so conspicuous implying that all the social categories are equally vulnerable. These findings have important policy implications, indicating that policy initiatives for deprived areas irrespective of caste factor are more important than the caste-based support measures.

Relative Size of Informal Sector

in the rural areas of Bihar, Karnataka and Orissa and in the urban areas of Gujarat, Size of Informal Sector the number of workers in informal enter prises obtained from enterprise approach ARUP MITRA both the schedules differ substantially from exceeded the number of workers obtained Teach other in terms of the number of from the household survey (Table 1). his is in response to the paper by workers. By and large the household On an average at the all-India level, as S Sakthivel and Pinaki Joddar (EPW, schedule enumerated a larger number of seen from Table 1, around 55 and 47 per May 27, 2006). The authors provide es-workers than the enterprises schedule. Only cent of the non-farm workers are located timates of the informal (unorganised) sector Table 1: Relative Size of Informal Sector in Non-Farm Activities across States Table 1: Relative Size of Informal Sector in Non-Farm Activities across StatesTable 1: Relative Size of Informal Sector in Non-Farm Activities across StatesTable 1: Relative Size of Informal Sector in Non-Farm Activities across StatesTable 1: Relative Size of Informal Sector in Non-Farm Activities across StatesTable 1: Relative Size of Informal Sector in Non-Farm Activities across States workers in non-farm activities based on (1999-2000) the 55th round of NSS (Table 7), which


Back to Top