Jobs puzzle: Confusion over use of flexible vs formal jobs in calculation

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Updated: February 4, 2019 7:14:50 AM

If the economy has been growing at 7% on average for five years, a 10% drop in employment would imply a 17% rise in labour productivity which would be the highest ever in the world

A lot of debate about job creation is about formal sector jobs and it is not clear whether flexible definitions of jobs are used in recent calculations or whether the formal sector definition of jobs dominates. (Representational photo/IE))

My very first published article, way back in 1962, threw doubt on NSS estimates of expenditure on food with official estimates of food-grains output. The two sides of the transaction—supply and demand—did not tally. Thus, despite its high reputation, NSS has not always got things right. The debates on measurement of consumption for poverty estimate has proved so controversial that further rounds of NSS surveys have been halted. But the contradictions in rival data estimates on the employment situation are just bizarre. The latest leak of NSSO data says unemployment was 6.4% in 2017-18, apparently the highest in 45 years! This is despite a fall in Labour force participation rate from 39.5 % in 2011-12 to 36.9 % in 2017-18. This would mean a 10% drop in employment.

If the economy has been growing at 7% on average for five years, a 10% drop in employment would imply a 17% rise in labour productivity which would be highest ever in the world. The data on jobs are just not making any sense. (The new estimate of GDP growth for 2016-17 as 8.2% is also hard to credit.)
Compare the CMIE estimates of the unemployment rate with those in the Annual Labour Force Survey. I list the CMIE first and the Labour Force survey second. The first is a point estimate. while the second is annual—September 2016 8.46%/ 2015-16 average 3.7% // December 2017 4.77% / 2016-17 3.9%. The gap between the two estimates is large, almost 2/1 and the direction of change is contradictory.

The situation is equally dire on jobs created. Surjit Bhalla and Tirthtanmoy Das have a paper on the website of the Prime Minister’s Council of Economic Advisers where they have discussed all aspects of measurement. Compare their estimates of employment with that of CMIE and you feel they live in two different countries. Here are the estimates of employment (in millions), Bhalla-Das first and CMIE next: 2016 437/417.9 // 2017 449.8/ 407.9. Thus, the difference between the two is not merely in size but also in the direction of change. Between them the difference over the two years is 61 million jobs, equal to about 7% of the labour force. This is hard to credit.

Since both sources are respectable, the discrepancy must be about definitions or measurement techniques. But, it is too wide to be comfortable. One reason may be the way jobs are defined especially in a largely informal economy. Here, the pakodawala example is apt. The pakodawala has a livelihood—a rojgar, but not a naukri. Does an Ola driver count as doing a job or not? During the No Confidence debate last July, Narendra Modi talked of the jobs created in a variety of different ways. Formal sector jobs can be measured by looking at Employee Provident Fund subscribers. But, the prime minister also gave example of jobs created as a result number of three-wheelers bought. As these vehicles are driven round the clock, each could be providing jobs for two people. He also cited the number of new cars bought. A large proportion would require drivers. Newly qualified doctors would start practise and hire assistants. Thus, he pointed out that jobs come in various shapes and sizes.

It is not clear whether such flexible definitions are used in recent calculations or whether the formal sector definition of jobs dominates. A lot of the debate on job creation is about formal sector jobs.
Young people queue up for government jobs as they are lifelong employment till retirement. The salary gets upgraded with every Pay Commission. Then, there is a pension, also upgraded. This is why government jobs are at a premium and, furthermore, there are few unreserved jobs—each is a rare gem. No wonder thousands apply for a single opening.

Obviously,there is a problem with Indian statistics in the measurement of many variables. Sudipto Mundle chaired a commission on statistics, but his recommendations do not seem to have been accepted. After the elections are over, the new government should look at this issue of unreliable statistics. An international panel should be constituted to look at this issue. If India is to be the fastest growing economy for the next decade or two, it is time it got itself credible statistical services.

-The author is Prominent economist and labour peer

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