How Comparable are India’s Labour Market Surveys?

Abraham, Rosa; Shrivastava, Anand

doi:10.1007/s41027-022-00381-x

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…The comparison of CPHS data with other official nationally representative data also indicates substantive differences in employment and income statistics. Abraham and Shrivastava (2019) find that CPHS substantially underestimates the women's labour force participation rate. They estimate that while the difference in the men's labour force participation rate between CPHS and PLFS is only 5 per cent, women's labour force participation is underestimated by 40 per cent in CPHS compared to PLFS.…”

Section: Shortcomings Of Cphs Datamentioning

confidence: 77%

Who was impacted and how? COVID-19 pandemic and the long uneven recovery in India

Jha¹,

Lahoti²

2022

WIDER Working Paper

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Section: Shortcomings Of Cphs Datamentioning

confidence: 77%

Who was impacted and how? COVID-19 pandemic and the long uneven recovery in India

Jha¹,

Lahoti²

2022

WIDER Working Paper

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“…The other panel data set at the household level currently available is the CPHS. However, the focus of this database is on tracking consumption (Abraham & Shrivastava, 2022) and, similar to the PLFS, it is too short to study medium or long-term impacts on wages attributable to education or experience. Singha Roy (2020) uses a smaller regional panel of 18 villages in semi-arid regions to study wage determination.…”

Section: Discussionmentioning

confidence: 99%

How Much do Education, Experience, and Social Networks Impact Earnings in India? A Panel Data Analysis Disaggregated by Class, Gender, Caste and Religion

Hussain,

Mukhopadhyay

2023

SAGE Open

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We estimate the returns (measured by hourly earnings) to education, experience, and social networking in India using individual-level panel data from the India Human Development Surveys. We combined the two latest waves of this survey using individual-level identifiers to generate a balanced panel and merged it with various household characteristics. We provide estimates of private returns for an additional year of education and experience by consumption quintiles, gender, caste, and religion in a fixed-effects Heckman model that controls for selection bias. This methodology improves upon estimates of all earlier studies on earnings in India, as most of the literature has relied on cross-section data or pseudo-panel data. We also examine the impact of social networking on earnings, which is under-explored in nationwide studies in India. We find that education significantly and positively affects earnings for all consumption quintiles, gender, caste (except schedule castes), and religious groups. Among economic groups, the highest returns are observed for the third quintile above the poverty line. Returns to females for an additional year of education are nearly double that of males but the difference in starting earnings keeps earnings of males higher for long periods. Among the castes, scheduled castes have the highest returns to education and other minorities among religious groups. Social networking positively impacts males, Hindus, and the quintile just above the poverty line. Experience positively impacts women’s earnings, general caste and scheduled caste, Hindus and Other minorities and two consumption quintiles (two and five) above the poverty line.

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“…The response rate during the lockdown was slightly over 60%, compared to over 95% before the lockdown (Vyas 2020 ). This is the only nationally representative survey that was carried out prior to the lockdown, during the lockdown (partially, as phone survey), as well as in its aftermath (Abraham & Srivastava 2022 ). The entire sample is surveyed for a period of four months, called a wave .…”

Section: Datamentioning

confidence: 99%

Labour Market Dynamics and Worker Flows in India: Impact of Covid-19

Chatterjee

Dev

2023

Ind. J. Labour Econ.

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Tracking and analyzing the labour market dynamics at regular, frequent intervals is critical. However, this was not possible for India, a large emerging economy with a significant population undergoing demographic transition, due to a paucity of data. We use the new dataset Centre for Monitoring Indian Economy (CMIE)—Consumer Pyramids Household Survey (CPHS) and use a panel to create Labour Flow Charts and Transition Matrices for India from January 2019 to December 2021. To the best of our knowledge, this is the first time these were created for India. We then use that to look at the impact of Covid-19 on the Indian labour market. We not only look at transitions between employment, unemployment and out of labour force, but also across types of employment—full-time and part-time. The rich data also allows us to consider heterogeneity in the labour market and look at the differential impact of the pandemic across different education groups and gender. From the labour flow charts and transition probabilities, we find that while all groups have been impacted, the magnitude of the impact is different across groups. The recovery is also uneven, and the extent depends on education levels. Further, we do an event study analysis to examine the likelihood of getting a full-time job across different educational and gender groups. Men, on average, enjoy a higher likelihood of getting a full-time job than women. The likelihood coefficients also go up with increasing educational qualifications. Looking at skill heterogeneity, while the likelihood of getting a full-time job either goes down for most groups during the pandemic or the change is minuscule, strikingly it goes up for those with no education, for both men and women. The likelihood coefficients remain elevated for men even after the restrictions are removed, and that for women reverts to the level seen before the pandemic. Finally, this paper provides a way to continuously monitor the dynamics of the labour market as data is released in the regular intervals in the future, which would be of great value for researchers and policymakers alike.

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How Comparable are India’s Labour Market Surveys?

Cited by 11 publications

References 5 publications

Who was impacted and how? COVID-19 pandemic and the long uneven recovery in India

Who was impacted and how? COVID-19 pandemic and the long uneven recovery in India

How Much do Education, Experience, and Social Networks Impact Earnings in India? A Panel Data Analysis Disaggregated by Class, Gender, Caste and Religion

Labour Market Dynamics and Worker Flows in India: Impact of Covid-19

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