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India suffers from a crisis of credible data, not jobs, and that makes for poor policymaking and meaningless debates

The debate over jobs has become shrill and is expected to become shriller still in the ongoing election season. Democracy survives on debates. This debate, in particular, should be encouraged because nothing concerns a demographically young nation more than the creation of good quality jobs.

In the absence of credible and timely data, and devoid of 'big data', however, these debates carry little meaning. A lack of reliable reference points degenerates such debates into shouting matches or partisan political posturing. The lack of dependable data and analytical tools force the government and policymakers to operate within a fog of disinformation, and subsequently, policies run into unseen obstacles and fail in objectives. At this stage of its development curve, India cannot afford such laxity.

Representational image. Thinkstock

Representational image. Thinkstock

Disinformation over unemployment is so pervasive and rampant that many assumptions have become axiomatic truths. For example, the notion that 12 million youth are entering the Indian workforce every year and that the Narendra Modi-led government has failed to create enough employment opportunities to absorb them, leading to a debilitating job crisis. Variations of this alarmism are available in reams and reams of newspaper columns and zettabytes of digital data.

The Opposition has latched on to it, trying to create a narrative of incompetence around Modi. In seeking to sensationalise the issue and turn it into a poll plank, some often lose the focal point of the problem and make outlandish claims that carry little credibility.

For instance, during a rally in Himachal Pradesh last year, Congress president Rahul Gandhi said: "The Chinese government creates over 1 lakh jobs in a span of two days, while in India only 450 jobs are created in a day. Isn’t that shameful?"

He repeated the charge this year during a rally in Karnataka, which goes to the polls on 12 May.

Rahul Gandhi's data (he didn't provide any source) suggests that India, under Modi, generated 6,48,000 jobs in four years. Curiously, the Congress government in Karnataka had claimed last year that the state generated "13.91 lakh jobs in the last four years and is inching closer towards meeting the government's target of creating 15 lakh jobs by 2019," according to a PTI report quoting R V Deshpande, the minister for large and medium industries in November 2017.

If only 6,48,000 jobs were created under the Modi government in four years, then it is unclear how Karnataka managed to add nearly 14 lakh jobs in that same period. This anomaly has been highlighted by rebel Congress leader Shehzad Poonawalla in a tweet.

During his tour of the US last year, the Congress president lambasted Modi for inflicting "tremendous damage" on India's economy with "reckless and dangerous" policies. On that occasion, while addressing students at the University of California, Berkeley, he said: "30,000 new youngsters were joining the job market every single day and the government was only creating 500 jobs a day.."

He also identified (rightly so) creation of jobs as the country's "central challenge" and noted that roughly 12 million young people join the Indian job market every year, according to a PTI report.

Once again, the source of Rahul Gandhi's data wasn't clear but that figure is now a common refrain in political discourse. If India is adding one million employable youth every month and the government is failing to create enough opportunities for them, it stands to reason that Modi has failed in his primary task and legitimate questions should be raised about his performance. However, this criticism is valid only if it is based on credible data.

Former Niti Ayog chief Arvind Panagariya posits that the figure of "12 million youth entering the job market every year" is likely misleading, and points out that basing all debates and analyses on a piece of unverified statistic is problematic.

Panagariya, a professor of economics at Columbia University, cites economist Rahul Ahluwalia's work to claim that the "approximate number of jobs seekers… (is) a good 4.2 to 4.5 million smaller than the 12 million figure that is defining the current debate and policy formulation." In his column for The Times of India, he acknowledges that these figures are not definitive, and writes that the "LFPR (labour force participation rate) during 2016-21 may turn out to be different from those in the NSSO and MoL surveys. But even applying the LFPR in the 2004-05 NSSO survey, the highest such rate observed during the past 25 years, the number of new entrants per year rises to only 8.5 million, a far cry from 12 million."

Panagariya's key contention is simple. Not all working-age individuals who are added monthly or annually to the population are active "job seekers", which is to say that it is not necessary for policymakers to take '12 million' as the definitive target. He clarifies that "it is nobody’s case that fewer entrants to the workforce than previously thought make our jobs problem go away. The point, instead, is that our debates and policy analyses need to be conducted using as accurate numbers as may be available."

This is the nub of the debate. If the numbers are inaccurate, then there is little to choose between economics and political commentary because both are subjective and hence vulnerable to bias. If politicized interpretations are propagated in the name of objective analysis then it squeezes the space for reasoned debate.

As R Jagannathan summarises Panagariya's argument in an article published in the Swarajya magazine, "the simple number to focus on is probably this: there may be a gap of two to three million jobs at current LFPR rates, and the jobs created may also be of poor quality. The other challenge is to get female work participation rates up, as it is currently abysmally low at just 13.6 percent, according to CMIE. This is essentially India’s real jobs challenge."

The focus is on data. Payroll data released by the Employees’ Provident Fund Organisation (EPFO) and the National Pension System (NPS) record that over the six-month period to February, 3.1 million new additions have taken place, "of which those in the 18-25 age group, considered a proxy for new jobs, amount to 1.85 million… In the case of the NPS, new accounts opened in the central and government sector stood at 350,000 during this period, corresponding to new jobs and taking the total to 2.2 million," The Economic Times points out in a report.

This supplements the findings of Soumya Kanti Ghosh, chief economic adviser at the State Bank of India (SBI) and Professor Pulak Ghosh of the Indian Institute of Management, who had estimated in a paper published earlier this year that the Indian economy may create seven million employment opportunities in the 2018 financial year.

In a subsequent column for The Times of India, the authors had elaborated on their methodology and stressed on the "downward bias" of their estimates to err on the side of caution. They wrote: "Based on these (EPFO, ESIC, NPS and GPF), our total stock of payroll is around 9.2 crore (including zero contributions, it is around 10 crore) and is much lower than NSSO estimate. Based on all estimates, we believe that 7 million formal jobs are being added to payroll on a yearly basis."

The authors also contended that the "formal sector payroll number may be enlarged further" if data from ICAI, ICSI, the National Bar Council, the Medical Council of India and income tax payees are taken into consideration. The thrust of their argument was that big data analytics must be relied upon to make policymaking more effective.

Critics have pointed out that Ghosh and his postulation is faulty, because an increase in state-run social security fund accounts does not necessarily mean an increase in employment. Congress leader Jairam Ramesh and Praveen Chakravarty, head of the Congress party's Data Analytics Department, countered the paper in an article for The Hindu, where they claimed that "cherry-picking data points (EPFO data) and time periods (FY-2017 and FY-2018) are old, time-tested statistical tricks to arrive at fallacious conclusions."

Economist V Anantha Nageswaran has rebutted Chakravarty and Ramesh, positing that Ghosh and Ghosh's paper has fallen prey to "politicised interpretation" that ignored the conservative bias in their findings.

In his article for Livemint, Nageswaran cites "healthy growth in job creation by large corporations, RBI surveys of manufacturing companies, funding constraints for businesses and informal employment" to note that "Ghoshs have done is a very good starting point." Giving an example of how partial information clouds our understanding of market forces, he contends that it is too simplistic to claim that private investments are not picking up because banks are not lending to corporates. Quoting the International Monetary Fund (IMF), he writes, "corporates increased private debt placements and issued commercial paper, replacing bank funding with market sources" which is a sign of greater diversification in Indian financial system.

Once again we find our judgement being hampered due to an inability to look at the bigger picture, which won't be possible until we harness big data for policymaking. Using payroll data is a step in the right direction.

As the Mint rightly pointed out in an editorial, "the sort of credible monthly data that is available in more advanced economies is extremely difficult to deliver here. However, it is good that the first steps towards overhauling employment statistics have been taken with the release of the payroll data… Rising wages across all job categories over the past decade are strong proof that the extreme narrative about jobless growth is just not true."

In another report, Niranjan Rajadhyaksha said that the Reserve Bank of India (RBI) is finally stepping into the world of big data. The central bank reportedly plans to set up a "data sciences laboratory that would employ professionals with skills in computer science, data analytics, statistics, economics, econometrics and finance. The unit is expected to begin work in December."

The author contends that "such a unit could help monetary policymakers get a better sense of how prices are moving in real time." Basing policies on big data, as against on sample surveys, could improve accuracy, effectiveness and also raise the bar of debates.


Updated Date: May 03, 2018 14:34 PM

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