New Delhi: he suppression of the National Sample Survey Office’s (NSSO’s) jobs report has been at the receiving end of much criticism, but one fallout of the non-disclosure has gained little attention: the lack of reliable jobs data could bring a decade-long effort to improve estimates of informal sector activity (which feeds into gross domestic product, or GDP, calculation) to a creaking halt.
The origins of the Periodic Labour Force Survey (PLFS) 2016-17 lie in the recommendations of a committee set up by the National Statistical Commission (NSC) in 2009 and headed by one of its members, Amitabh Kundu. He believes “the government should release the (jobs) report and the raw data".
The Kundu committee’s task was to establish a framework for collecting high-frequency (monthly or quarterly) labour market data for the urban areas of the country. And the interest in labour market data was, in part, fuelled by the need to make sense of India’s nebulous and difficult-to-measure informal sector.
The lack of a high-frequency labour market indicator meant that so far India has not fully met the Special Data Dissemination Standard of the International Monetary Fund, established in 1996 to guide member countries “in providing their economic and financial data to the public".
Based on the pilots suggested by the Kundu committee and feedback from other committees that looked into the issue, the NSC recommended a survey questionnaire that was similar to the quinquennial (every five years) employment-unemployment surveys (last conducted in 2011-12), and which would provide quarterly estimates for urban areas, and annual estimates for both urban and rural areas, setting the stage for the launch of the PLFS survey in 2016.
When the report was finalized, it dawned upon the government that this showed a steep spike in unemployment rates compared to the past quinquennial rounds and the report was held back, prompting the resignations of two NSC members. Government officials such as NITI Aayog chief executive Amitabh Kant expressed scepticism about the findings of the report and raised questions about the methodology.
According to independent experts, some of the limitations that were highlighted (such as the under-representation of urban areas) are well-identified problems that the NSSO is in the process of fixing. But they do not affect comparability of the findings since previous surveys also faced these issues. However, some changes in the survey could have affected comparability of results.
“Unlike the earlier surveys, in the PLFS survey, the enumerator revisits a sampled (urban) respondent, and this can change the nature of responses the enumerator gets," said Kundu, who first laid the groundwork for the PLFS. “Even a change in ordering of questions and the technology of canvassing the questionnaire (whether filled using paper or tablets) can change responses."
However, the results should be broadly comparable, Kundu said.
“I don’t think the results would have shown a decline in unemployment had it been conducted in any other way," said Kundu. “The magnitude might have been different but that is an academic debate that should be settled by academics. The raw data must be released."
Kant in an emailed response said he objected to the report because the methodology was finalized by one person and without his knowledge even though he is an NSC member. However, the facts do not bear him out. The NSC annual reports of the past two years, which bear Kant’s signature, show that there were extensive discussions on the sampling frame, stratification strategy, and type of questions that should be used for the survey. Kant did not respond to follow-up questions regarding his degree of involvement.
The release of the report is important because several committees have recommended the use of the PLFS results in estimating annual growth in parts of the informal economy, for which CSO uses (potentially inflated) formal sector indicators. The use of the PLFS in national accounts could provide more realistic estimates of informal sector growth and perhaps improve the reliability of the GDP numbers as well.