Rebuilding India’s Employment Statistics System

The Covid-19 pandemic caused not only unprecedented disruption of normal life, but the lockdowns, waves of mass reverse migration, shortages in medical care, impact on earnings and employment, etc., have exposed the deficiencies in our data systems for an objective understanding of its impact. One such area of concern is the lack of real-time data on changes in employment and unemployment. How good is our understanding of the current employment scenario and how helpful are the available data from government and non-governmental sources to address the job crisis?

A simple framework to look at the source of employment data is that of households supplying labour to the businesses, making it possible to measure employment either from households or from business establishments. However, these two sides do not provide the same numbers as often the boundaries of business establishments and households are blurred and the relation is not always one-to-one. The household surveys are the preferred option for measuring employment as it is more representative of the population and can be disaggregated for deeper analysis.

To identify employed people in a household it is important to understand the concept of work. ‘Working’ means producing goods for own use or use of others and providing services to others. Given the substantial presence of informal work arrangements within and outside the households, identifying workers has always been a bit tricky in India. Conceptually the efforts have been to link work with the production of goods and services in the economy. The refinements in measuring the macroeconomic indicators have led to the adoption of a ‘system of national accounts’ providing a consistent set of numbers to describe the economy, the most important of which is the gross domestic product. The definition of work is accordingly set as the activities whose output goes into the GDP or activities falling within the production boundary of the national economy.

Given the nature of economic activities in a predominantly agrarian population, the issue of measuring employment and unemployment has been debated for long.

Employment is also highly seasonal and intermittent. This is unlike in western economies where the employed are those with paid jobs and the unemployed are people who are jobless and looking for a job.

A cursory look at the available data shows how complex the employment pattern remains in India.

• In rural India, as much as 58% of the employed are in agriculture and allied sectors (National Statistics Office, 2018-19), mostly operated by households without hiring any workers.

• Among the total workers, 52% are reported as self-employed and only 24% as regular wage-paid workers among whom only 70% had any form of written job contracts.

• Overall, about 68% find employment in unincorporated enterprises.

• In rural areas, around 38% of women workers are actually just unpaid helpers in household enterprises.

The unemployment indicators for the general population had remained very low for most of the past decades, though for certain categories of the population like the educated youth the unemployment rates were always much higher. Coupled with a stable employment structure for much of the time, there was only limited demand for employment statistics with high frequency. The National Sample Surveys of the government did employment surveys only every five years. However, the recent surveys of NSO as well as of other agencies have started showing a decline in employment and a much higher unemployment rate leading to heightened public interest on the subject. The pandemic impact has further worsened the scenario.

The other alternative of establishment surveys to count the number of employed from the monthly payroll has also its downsides as a vast majority of the enterprises are in the unorganised sector with few formal employment arrangements. No reliable lists of enterprises are available even for the organised sector as these get registered under a variety of institutional arrangements. Besides, the payrolls sometimes mask actual employment with contracting out of jobs.

The Periodic Labour Force Survey of NSO was planned to provide internationally comparable data on employment-unemployment on an annual basis for rural areas and on a quarterly basis for urban areas. Unfortunately, the publication of the results has been slow, sporadic, and mired in controversies. The last reports we have are for 2018-19, and the October-December quarter of 2019 for the urban sector. The Ministry of Statistics has been releasing data on the monthly subscriptions of social security schemes like the Employee Provident Fund, National Pension Scheme, and Employee State Insurance and rather misleadingly calling it payroll reporting. The perspective provided through this subscription-based monthly data has not been of much use to understand the current employment-unemployment crisis.

It is in this context that employment indicators coming out of the Consumer Pyramid Household Survey or CPHS (a large panel survey of households repeatedly surveyed) of the Centre for Monitoring Indian Economy have come to be widely received.

CMIE has been publishing key numbers and rates relating to employment and unemployment on a real-time basis, which no government agency could do so far. There are research institutions, like the Centre for Sustainable Employment of Azim Premji University that brings out the annual State of the Working India Reports using data from a variety of surveys, that are critically examining employment issues with academic rigour.

The present economic crisis is the right time to begin compiling employment statistics in a holistic manner for the country. The assumption that changes in rural employment do not call for monthly or quarterly data is questionable in the context of employment disruptions and reverse migration. Also, workers commuting to urban areas get missed while covering only the urban households as at present for the quarterly surveys. It is thus important that the PLFS produce quarterly employment-unemployment estimates covering both rural and urban areas.

Considering the frequency and timelines, one would expect only limited information in the quarterly statistics. The annual report will however carry detailed tabulation as at present and possibly also include aspects of work-related migrations. Organised sector employment is more often derived as a residual of total employment except for the manufacturing sector where we have the annual survey of industries.

The current efforts of the Statistics Ministry to provide an employment perspective from monthly social security subscriptions are inadequate. Instead, a system of data collection through surveys covering the registered non-agricultural establishment needs to be instituted. Data for most of the key indicators like Index of Industrial Production, Wholesale Price Index, and Consumer Price Index, etc. are collected from a fixed panel of factories/shops. In a similar manner, NSO should gather quarterly employment data from a panel of establishments as is the case in most countries. Such a panel can be drawn from the lists already available with government agencies and later extended to cover unorganised establishments using information available from the current Economic Census. Establishment surveys can provide information on payroll employment, employment location, broad occupational types, contractual employment, indirect employment through outsourcing, etc. giving a better industry perspective to labour statistics.

NSO has been planning to have annual surveys of non-manufacturing establishments for quite some time. The suggested quarterly establishment surveys on labour can be suitably wedged into this scheme to save resources and reduce the response burden.

A well-thought-out system of household and establishment surveys by NSO can minimise the need for ad-hoc efforts like the recent proposals of the Ministry of Labour to conduct five large-scale surveys on labour-related issues.

PC Mohanan is former acting chairman of the National Statistical Commission.

The views expressed here are those of the author, and do not necessarily represent the views of BloombergQuint or its editorial team.