Unemployment: Claims and Puzzles

The issue of employment creation has been a challenging task for all the governments at the Centre. Recently some researchers and newspapers have highlighted very high unemployment rate (UR) in 2017-18 in the country, based on an unpublished periodic labour force survey (PLFS) report. In India, the main sources of data on employment are NSSO, Economic Census, Registrar General of India and Labour Bureau. NSSO is considered as the main source of employment and unemployment situation as it provides quinquennial household surveys. For the first time, NSSO has conducted a PLFS for 2017-18 on a quarterly and annual basis. Apart from these sources, CMIE has also started conducting household surveys on EUS since January 2016. Because of the first high-frequency data on EUS, it has also been reported in newspapers very frequently. The recent CMIE figure shows that UR in India increased to 7.2 per cent in February 2019, highest since September 2016. Mahesh Vyas, chief of CMIE in his interview to Livemint on 8 March said: "7.2 per cent unemployment rate is a disturbing figure and it shows a situation of discouraged unemployment in the economy". However, on analysing this data, one will come to know that the latest figure reported in the newspaper and claims made by Mahesh Vyas are partly incorrect and they require closer observation of such data set.

In this context, it would be appropriate to first understand the difference in the definition of unemployment used in CMIE data and NSSO. CMIE collects following information to capture unemployment- i) a person is willing to work but may not have a job; ii) a person is available for a job but not actively seeking a job; iii) a person is not willing for work and also not looking for a job. However, the UR given in CMIE unemployment reports presents the first criteria to capture the unemployment rates. In contrast, NSSO uses two major approaches to capture unemployment figures: Usual status approach (US) and the current weekly approach (CWS). The US approach includes both, those who are unemployed and actively looking for a job and those who are unemployed and not actively looking for a job. The CWS approach includes only those who are unemployed and actively looking for a job. From the above differences in the definition of the two data sources, it is evident that UR reported in CMIE report is not directly comparable to NSSO's UR figures.

Regarding unemployment data at all India level, it shows that between January and September 2016, the overall UR was more than 8 per cent but thereafter, it declined consistently and reached the lowest point of 3.9 per cent in July 2017. It slowly started rising in subsequent months and crossed the 6 per cent figure in August 2018. This trend continued and UR reached to a level of 7.2 per cent in February 2019. However, it is evident that despite a consistent increment in the UR, it is still lower than the UR in the first 6-7 months in 2016. As compared to rural areas, the unemployment rates were always higher in urban areas. In 2016, the gap between the UR of rural and urban areas was high which has narrowed down after July 2017.

The quarterly URs show a similar trend of high unemployment rates in the initial months of 2016 and then continuous decline up to May-August, 2017. It started increasing in the subsequent quarters but still seen to be low as compared to the first two quarters of 2016. Here, significant changes have been noticed in female unemployment rates. It was very high in the first two quarters of 2016 and then declined sharply in the subsequent quarters up to May-August, 2017. Thereafter, female unemployment rates increased in each subsequent period. In the entire period, the male unemployment rate was not more than 6 per cent.

Unemployment rates across the educational groups: Unemployment rates are relatively very high in the last two categories of 10th to 12th passed person and for those who have educational attainment above undergraduate level. The first category shows the labour forces that have no education at all. In this category, UR was comparatively very high in the first quarter of 2016. In the third quarter of 2016, UR was 1.90, which increased to 2.33 per cent in the subsequent quarter but declined in the next quarter. In fact, comparison of September-December 2016 and September-December 2017 indicates that UR in these periods increased marginally by 0.40 per cent. Overall, there has been very small fluctuation in UR figures after the second quarter of 2016 in this category. In the next education category also unemployment rates fluctuate between 2.6 per cent and 1.2 per cent and UR declined from 2.1 per cent in September-December 2016 to 1.6 per cent in January-April 2017 and 1.0 per cent in September-December 2017.

Overall, UR, according to CMIE data shows a general trend of decline in UR in post-October 2016 up to July 2017. The rise in UR started after this or from the 3rd or 4th quarter of 2017, which is still continuing, but not at the rate as it was in the initial months of 2016. Usually, it is expected that UR declines when labour force participation increases, which is not happening according to CMIE data set. If both LFPR and UR are declining, then it is assumed that the further decline in UR will come only slowly and the expectation is that with the improvement in labour market, many participants who have left the market will return and contribute to the pool of unemployed. Again this situation does not exist because LFPR, according to CMIE is continuously declining in both post demonetisation and GST regime.

An ILO (2016) study outlines four key drivers of the decline in FLFPR: First, increase in enrolment in secondary schooling; second, rising household income that pulled women out of the low paid informal jobs; lack on employment opportunities for women and fourth, mismeasurement of women's participation in the labour force. In my view on the basis of above monthly and quarterly unemployment data of CMIE, it cannot be argued that what factors exactly lead to a decline in UR in post-October 2016 and what led to an increase in UR after 2017. Recently NIPFP has published a report on PMAY (U) and it has shown that this program has made a significant impact on employment generation. The report shows that between June 2015 and January 2019, a total of 18.92 lakh direct and 45.57 indirect lakh indirect jobs have been created in the country.

The CII projection based on its survey has shown that every year in India around 13 to 14 million jobs have been added by the MSME sector in India in the last four years. Therefore, a strong argument of discouraged employment situation is incorrect and seems to be motivated one. Providing sufficient and gainful employment is, of course, an issue but the current government cannot be solely held responsible for this situation.

(The author is an Assistant professor at the Institute for Studies in Industrial Development, New Delhi. The views expressed are strictly personal)