SYLLABUS: GS MAINS PAPER III
Recently, The Labour Bureau released the results of the All-India Quarterly Establishment- Based Employment Survey (QES) for the first quarter of 2021 (April-June).
1. It has been taken up by the Labour Bureau to provide quarterly updates about the employment and related variables of establishments, in both organised and unorganised segments of nine selected sectors.
2. The survey covers establishments employing 10 or more workers in the organised segment of nine sectors (construction, trade, manufacturing, transport, health, education, accommodation and restaurants, ITI/BPO, and financial service activities.
3. These sectors account for 85% of the total employment in establishment employing 10 or more workers as per the sixth Economic Census (EC), which serves as the basis of QES survey.
4. The data for QES were collected either telephonically or through visits.
5. The report cautions that “verification of records has not been resorted to for collection of data”. This could have significant implications for the statistics generated from the survey.
The objective of the QES is to enable to the government to frame a “sound national policy on empowerment’.
REQUIREMENT OF QES
●India ratified the International Labour Organisation’s Employment Policy Convention, 1964.
It requires the ratifying countries to implement “an active policy designed to promote full, productive and freely chosen employment”.
●India does not have one till now.
KEY FINDINGS OF QES
1. The remarkable simple growth rate reported compares a normal period to a pandemic-ravaged period.
2. The overall growth rate is incongruent with macro-economic factors and other labour market portrayals.
3. The Centre for Monitoring Indian Economy (CMIE) data revealed a rather discouraging picture in April, 2021 as the salaried class shed an estimated 3.4. Million jobs from the level in March, 2021 and the urban unemployment rate was as high as 9.78%.
4. Normal economic indicators like income growth rates, business confidence, capacity utilisation, aggregate demand measured by the Purchasing Managers’ Index and the Reserve Bank of India’s growth rates of high frequency indicators during the pandemic did not show any encouraging trends even though they were fluctuating.
5. The provisional estimates of annual national income for 2020-2021 showed contraction in manufacturing (-7.2. %), construction (-8.6%) and trade (-18.2. %), which are covered in QES.
6. The real national income growth rates, though controversial for upward revisions, declined 2017-2018 onwards- the annual average growth rate in 2013-2014 to 2020-2021 was 4.95%.
7. The report throws up another perplexing statistic on contract workers, accounted for 0.7% (IT/BPOs), 10.4% (manufacturing), and 17.6% (construction) and overall inadequate 7.8%.
8. According to the Annual survey of Industries for 2017-2018, 36.37% of the total workers are employed in the organised factory sector.
9. On the flip side, the report concedes a decline in the share of female workers from 31% in the sixth EC to 29% in FQ2021.
1. The Periodic Labour Force Survey (PLFS) have not presented an encouraging picture of the labour market.
2. The CMIE has been projecting a distressed labour market scenario, especially during the pandemic.
3. The CMIE database has dominated the analyses and understanding of the labour market. This could be quite annoying to any ruling party.
Thus, the government needed an ‘official data-base that projects a good picture of the economy and labour market.
4. QES is primarily a telephonic survey which shows lack of verification of responses of establishments.
● There is need to wait for unit level data to generate data at the disaggregated levels and create cross-tabulations to understand the labour market dynamics much better than ratios released in this report.
●Like the sixth Economic Census, it could have collected data on social aspects like caste and religion as the pandemic would have had differential impacts on social status of workers.
The initiative to produce quarterly employment data for selected industries in the organised sector is desirable. Simultaneously, in a rush to generate high-frequency estimates we cannot comprise on data quality and its reliability.