Mrinalini Jha and Amit Basole
Azim Premji University
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 stylized 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.
Keywords – Income data, Labour income, Income distribution, Household survey data, India.
Jha Mrinalini and Amit Basole. 2022. “Labour incomes in India: A comparison of PLFS and CMIE-CPHS data” Centre for Sustainable Employment Working Paper #46, Azim Premji University, Bangalore.