India’s female work participation rate is better than we think

Photo: Mint
Photo: Mint


Surveys that account for misclassified, mis-stated and unpaid work would yield a different picture

The debate over the inclusion of unpaid work in the calculation of gross domestic product is a long-standing one. Given practical difficulties, this was not pursued further. In recent years, this has become a hot- button issue, since India’s female labour force participation rate (LFPR) is claimed to have declined considerably since 2005. It is a conclusion that fails both experiential and rigorous scrutiny.

Let’s start with the Periodic Labour Force Survey (PLFS), India’s official labour force survey. It has been conducted annually since 2017-18, a laudable improvement over the once in four-five years Employment Unemployment Survey (EUS) conducted by the National Sample Survey (NSS) earlier. The female LFPR declined between 1999 and 2011-12 from 40% to 30% and has risen from 2017-18 to 2020-21. The 2011-12 (NSS-EUS) and 2017-18 (PLFS) numbers are not comparable owing to methodological differences. This point is often ignored and journalists draw a downward-sloping line as if this survey was done continuously for over two decades under the same methodology.

According to the PLFS, LFPR is the percentage of our working-age population engaged in work or making tangible efforts to seek ‘work’ or being available for ‘work’ if it is available. ‘Work’ includes self-employment (subsistence agriculture and collection of firewood, poultry farming, etc, for self consumption), regular wage/salaried employment, and casual labour.

The way we measure employment through the survey design and content can make a significant difference to final LFPR estimates, and this matters more for measuring female LFPR than male LFPR. We highlight three main measurement issues: overly broad categories, reliance on a single question to categorize labour force status, and the narrow approach of limiting productive work to labour force participation.

Firstly, the use of overly broad categories that club productive work (collection of firewood, poultry farming, etc) with domestic duties can in one sweep shift a significant proportion of women in the labour force into the out-of- labour-force category. For example, unless the production of primary goods is identified as the main activity by the respondent, the PLFS questionnaire would categorize women who do both domestic activities and primary goods production/collection as out-of-the- labour-force. Adding the proportion of such women (who might have been wrongly identified as out-of-the-labour-force) to the official LFPR yields an “augmented Female LFPR" of 46.2% for 2020-21, much higher than the 32.5% estimated by the conventional definition. Steven Kapsos and others made a similar attempt in an International Labour Organization (ILO) research paper in 2014, arriving at a female LFPR of 56.4% in India for 2012, against the far lower official estimate of 31.2% for 2012.

Secondly, the survey design relies excessively on a single question for measuring the labour force status of an individual, which eliminates the scope to rectify any error in self-reporting, considering the large rural population and literacy levels. Contrary to ILO recommendations, there are no additional questions (‘recovery questions’) in the PLFS questionnaire to double-check individuals’ labour force status, relying too much on how the individual self-identifies in the first instance.

Thirdly, there is a need to broaden the horizon of measuring work, which constitutes the whole universe of productive activities alongside employment. According to the latest ILO standards, limiting productive work to labour force participation is narrow and only measures work as a market product. It ignores the value of women’s unpaid domestic work, which can be seen as expenditure-saving work such as collecting firewood, cooking, tutoring children, etc, and contributes significantly to the household’s standard of living. Overvaluation of paid work and undervaluation of unpaid work is neither gender-neutral nor culturally neutral.

For example, in the context of rapidly ageing populations in the West, as Diane Coyle wrote in 2016 (, decisions on the optimal approach to caring for elders need to be informed by data. The desirability of public or private provision of services, paid or unpaid, cannot be based on ignorance or biases.

Finally, the use of international agencies’ estimates of India’s female LFPR is troublesome too. India’s female LFPR is widely quoted as too low, citing the ILO’s estimate of 19% for 2020. However, this is ILO’s modelled estimate (not the actual estimate of India’s official survey PLFS). It is essentially a black box in terms of how and why it varies from our official estimates. Their official caveat, “imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings", is conveniently ignored by commentators.

To improve the overall LFPR of women, gender-based disadvantages need to be eliminated to enable free choice for women. But India’s female LFPR is not as low as commonly assumed. We need more psychological and statistical recognition of this, along with a rectification of the methodological issues highlighted above.

These are the authors’ personal views.

V. Anantha Nageswaran, Harish Kumar Kallega & Deeksha Supyaal Bisht are, respectively, the chief economic advisor to the Government of India, and Indian Economic Service officers.

Catch all the Business News, Market News, Breaking News Events and Latest News Updates on Live Mint. Download The Mint News App to get Daily Market Updates.


Switch to the Mint app for fast and personalized news - Get App