In India, as in many countries around the world, most government jobs are allocated through a system of merit-based exams. Over the past few decades, these exams have become incredibly competitive, at times receiving over 1,000 applications for each vacancy.

Against a backdrop of rising educational attainment, high aspirations, disappointment with private sector opportunities, and a deep unmet need for income security, it is understandable why the demand for public sector employment opportunities is so high.

Yet despite the large footprint that public sector recruitments have in our social, economic and political life, many basic questions about them remain shrouded in mystery. Who applies? Why do they apply? Are these intense levels of competition socially productive, or do they make people worse off? Why are people willing to invest so much in exam preparation? Why are people willing to gamble on such low odds of getting selected?

Our lack of understanding limits our ability to formulate sound labour market policy. As we will see, a large share of college graduates participate in public sector recruitment exams, and candidates for these exams make up a disproportionate share of the overall unemployed population. How can we improve employment outcomes if we do not understand who the unemployed are and how they invest their time?

The main reason for the holes in our understanding is a lack of data. To date, neither private nor public household surveys include questions on whether individuals are preparing for competitive exams; and recruitment agencies have historically been cloistered institutions, understandably concerned about protecting the integrity of the recruitment process. As a result, the crores of candidates preparing for competitive ex- ams around the country remain largely invisible in data, and by extension in policy.

This report attempts to shine a light on this dark corner of the labour market. To do so, the researcher uses several new sources of data. First, he draws on administrative data from a recruitment agency. This data allows us to observe the whole recruitment process for the entire universe of applicants — the first time such data has been made available in the Indian context. 

Second, the researcher uses data from a large-scale survey of over 3,000 candidates, which provides information about their investments in exam preparation, their access to resources, their constraints, and their beliefs. 

Third, the research collaborators and the researcher conducted interviews and focus groups with candidates to better understand them in their own words. These rich data sources provide new insights into the economic and social life of candidates preparing for competitive exams.

The goal of this report is to demonstrate how both labour market and recruitment policy can be informed by a better understanding of candidate application behaviour. This un- derstanding can, in turn, help us tackle some of the key challenges in the modern Indian labour market — high levels of educated unemployment, a lack of skill development, low levels of female labour force participation, and more.

This paper looks at a case of rural-to-rural movement of agrarian capital in southern India and the ways in which capital-labour relations are reworked to maintain oppressive forms of exploitation. Faced with an agrarian crisis, capitalist farmers from affluent communities of Wayanad, Kerala, take large tracts of land for lease in the neighbouring state of Karnataka and grow ginger based on price speculation. Landless Adivasis from Wayanad have served as labourers on these ginger farmlands for the past three decades. Recently, farmers have shifted to employing labourers from a Scheduled Caste (SC) from Karnataka. The change happened not just because of the lower wages the SC labourers were willing to work for, but also because of the farmers’ inclination to move away from Adivasis who have been resisting the poor working conditions on the farm. The story resonates with broader dynamics of agrarian-labour relations amidst capitalist expansion and highlights the centrality of socio-political factors at play.

Drawing on results from a panel of 2778 workers interviewed during and after the 68-day hard lockdown imposed in India, the following study examines the livelihood impact of the pandemic and the extent of subsequent recovery or lack thereof. Focussing specifically on workers located in the informal economy, the study is a useful addition to the burgeoning body of work on the economic impacts of Covid-19 by providing an insight into the employment and earnings recovery of those located at the margins. These findings are spliced across socio-economic groups to showcase the differential impact of the pandemic on different demographics within the informal sector.

The COVID-19 pandemic has created a need for high-frequency employment and income data to gauge the nature and extent of shock and recovery from month to month. Lack of such high frequency household-level data from official sources has forced researchers to rely almost entirely on the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). Recently, the CPHS has been criticised for missing poor and vulnerable households in its sample. In this context, it becomes important to develop a detailed understanding of how comparable CPHS estimates are to other more familiar sources. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018−19) for CPHS and the Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/​urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent to 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences.
While CPHS estimates are always higher, it should also be emphasized that the two surveys agree on some stylised facts regarding the Indian workforce. An individual earning INR 50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage.