The Republic of Statistical Scramble

Straightening out data inconsistencies should be a government priority

Many a caustic word has been exchanged in the acrimonious debate over the Indian economy’s employment data. One set of numbers claims the current phase of economic growth as jobless. Alternative data sets have accompanied vigorous assertions of rising employment. And then there are many in the middle, trying to make sense of the scant (and outdated) data and wondering how anybody reached any conclusion at all.

Welcome to the republic of statistical scramble in the age of Big Data. The Bharatiya Janata Party’s (BJP’s) 2014 election victory was predicated partly on the promise of enhanced economic well-being; straightening out data inconsistencies should be a priority on the path to fulfilling that promise.

Take a look at labour data. Currently, employment data is collated from different surveys, each one measuring different things using varied methodologies. NITI Aayog’s task force on improving employment data recently released the first draft of its report, which lists how several arms of the government get involved in collecting and mashing up data. The report is unequivocal about the current state of data collection: “The available estimates are either out-dated or based on surveys with design flaws that render them unsuitable for inferring nationwide employment level.”

On the demand side, the National Sample Survey Organization (NSSO), in the ministry of statistics and programme implementation (Mospi), conducts a comprehensive household survey once every five years, with the last one occurring in 2011-12. The labour bureau in the ministry of labour and employment also conducts two household surveys—a quarterly quick employment survey and another on an annual basis. These are in addition to the decadal population census surveys, which measure two variables: a headcount of all types of workers at 10-year intervals and all non-agricultural enterprises, regardless of size.

On the jobs supply side, Mospi conducts a statutory annual industries survey for units registered under the Factories Act, 1948. NSSO also conducts an unorganized units survey; this is in addition to the micro, small and medium enterprises (MSME) census conducted by the MSME ministry. Finally, various government administrative bodies, such as the Employees Provident Fund Organization (EPFO) or Employees’ State Insurance Corporation (ESIC), provide some indication of organized sector employment trends (though this is being increasingly undermined by growing preference for contract labour). In addition, there are some private sector surveys also—for example, by the Centre for Monitoring Indian Economy.

All these measures suffer from some infirmity, whether it’s methodological, unviable sample size, inability to distinguish between different types of employment, long gaps or irregular frequencies. But one thing is common: the findings only provide a partial picture and are therefore useless as a tool for policy design. Part two of the Economic Survey says: “The lack of reliable estimates on employment in recent years has impeded its measurement and thereby the Government faces challenges in adopting appropriate policy interventions.”

The NSSO has, in the meantime, begun a fresh, ambitious annual exercise to map all nature of employment data; a quarterly survey will generate similar estimates for urban areas. In its report, NITI Aayog has recommended, among other things, vast improvements to existing surveys, institutional and legislative changes, overhauling physical and digital infrastructure and more aggressive use of technology to crunch the time-gap. 

But the study might need to extend beyond employment data because statistical distortions also exist in other areas. NITI Aayog provides an example about the state of statistical confusion: each enterprise, while filing returns or statutory information, is assigned a different identification number under Good and Services Tax Network, EPFO, ESIC, Factories Act and Shops and Establishment Act.

This problem is not restricted to enterprise data and exists in other government departments as well. Take the example of estimating the cotton crop. Two separate ministries release two separate estimates every year.

The agriculture ministry’s cotton crop estimate for 2015-16 was 30.15 million bales of 170kg each, while the textile ministry’s estimate for the same year was 33.8 million bales—that’s a difference of 620 million kg! In the previous year, 2014-15, the estimates put out by the two ministries were 34.8 million bales and 38 million bales, respectively. This divergence seems bewildering, especially when acreage estimates from both the ministries broadly tally.

Forget discrepancies between ministries: this paper had reported (goo.gl/vsYGzc) how cotton yield figures differ widely within the agriculture ministry. There have also been reports (goo.gl/fd9adW) about vastly varying data on the number of taxpayers added since demonetization emerging from different parts of the government. Mismatch between data sets from within the government also breeds scepticism regarding the statistical robustness of national accounting, especially when anecdotal evidence seems contra to buoyant gross domestic product data.

India’s magnificent statistical heritage distinguishes the nation from its neighbours, whose growth record is often viewed with scepticism globally. This infrastructure needs an urgent overhaul to maintain credibility, perceive economic trends and deliver appropriate policy prescriptions.

The article originally appeared in Mint newspaper on August 23, 2017, and can also be read here

It’s All In The Sequencing

There is silence on how the digital payments universe will foster competition, spur innovation and design a regulatory framework to protect consumers

Public policy discussions globally have often debated the role and sequencing of regulatory reforms in the series of structural changes necessary for introducing market dynamics to state-controlled economies. In India, post 1991 reforms, this critical issue was not adequately deliberated; worse, the government’s piecemeal approach to reforms and policy planners’ disregard for prioritizing regulatory reform inevitably led to regulatory capture and crony capitalism.

The demonetisation exercise is another pertinent example of how non-systemic reforms, without preceding regulatory reform, lead to chaos and economic dislocation. The withdrawal of 86% currency overnight was accompanied by a steady stream of shifting narratives: launched initially to curtail counterfeiting and currency hoarding, the objective soon segued to facilitating a digital payments infrastructure. But the lack of any planning before introducing this coercive shock, or the absence of preparatory infrastructure build-up and roll-out, has nullified all initial benefits.

Digital payments values and volumes went up between 8 November and 31 December 2016 because people had no other options. A recent research report from securities firm Motilal Oswal estimates that digital payments reduced substantially by May. For example, Motilal Oswal’s calculations show cumulative value of transactions across all digital payments channels during May at Rs111.55 trillion, down from the December 2016 peak of Rs131.45 trillion. The report disregards the Rs180.73 trillion spike during March, attributed primarily to seasonal phenomena.

Even a senior executive from the National Payments Corporation of India (NPCI) was quoted in this newspaper as saying the December spike in digital payments had ebbed by April.

So, what has demonetisation achieved? Observers cite two tangible, but divergent, results: a political victory through electoral gains in Uttar Pradesh and deepening agricultural distress leading to widespread farmer unrest. While there is no detailed, granular research linking demonetisation and these two outcomes, there is one noteworthy collateral benefit though: casting a wider net exposes the asymmetrical regulatory landscape in the payments and settlement ecosystem.

Soon after demonetisation, the Ratan Watal committee on digital payments advanced its deadlines and rushed through its report submission. Another committee of chief ministers was set up by Niti Aayog under Andhra Pradesh chief minister N. Chandrababu Naidu. This committee spawned another committee for digital payments security under IT secretary Aruna Sundararajan. Niti Aayog has set up another committee helmed by chief executive officer Amitabh Kant to “enable 100% conversion of government-citizen transactions to the digital platform”. Meanwhile, the ministry of electronics and information technology (Meity) has issued its own guidelines to facilitate adoption of electronic payments and receipts for various government services. Before all this, in June 2016, the Reserve Bank of India (RBI) had set up an inter-regulatory working group on fintech and digital payments, though the fate of this committee is not yet known. Besides, demonetisation also occasioned a host of other private reports.

Predictably, such a surfeit of committees and reports has led to overlaps and repetition. A cursory reading might even give the idea that committees are competing among themselves to say the same things. However, the burst of reports and recommendations in the first flush of demonetisation seems to have petered out: nobody seems to be listening and there doesn’t seem to be any urgency to implement many of the suggestions.

For example, the Watal committee’s recommendation of carving payments regulation out of RBI’s jurisdiction and making it into an independent body met with resistance from the central bank; eventually, finance minister Arun Jaitley announced the setting up of a payments regulatory board in his 2017-18 Budget speech (to replace the existing Board for Regulation and Supervision of Payment and Settlement Systems, or BPSS) on the lines suggested by the committee, but with one critical exception: the board will have three members from RBI and an equal number from the government, thereby diluting its independent status.

Many other skews in the regulatory architecture have been pointed out but remain unresolved. For example, as owner and operator of the retail digital payments network, the NPCI is a provider of critical infrastructure; but, simultaneously, it also competes with users by pushing its own payment products and services. In addition, its entire equity capital is owned by 56 banks, which automatically puts non-bank payment service providers at a distinct disadvantage and raises questions of infrastructure neutrality.

There is also complete silence on how the digital payments universe and its regulators will foster competition, encourage innovation and design a regulatory framework to protect consumers. Currently, allowing only banks to access the payments network—and denying that to non-banks—seems to be the default regulatory design.

The attention of policy planners and administrators might have been temporarily diverted to the other elephant in the room: goods and services tax, which goes live from 1 July. But, GST’s success is also predicated on a robust and secure digital payments network; an ad hoc digital payments network spells only provisional success for GST.

The above article was originally published in Mint newspaper and can be read here as well

Road To Growth Is Paved With Low ICOR

India’s slowing investment rate and rising incremental capital output ratio, or ICOR, have led to low economic growth.

Two recent, and epochal, events deserve our unstinted attention because they mark the end of an era and the beginning of another one. These are critical because of a common thread linking both: the investment rate of the economy.

The 12th Five-year Plan has just ended, bringing down the curtain on decades of India’s planned economic growth and development. This was the last Five-year Plan; as an alternative, the Planning Commission’s successor NITI Aayog has announced the release of a three-year “action plan”, a seven-year “strategy paper” and a 15-year “vision document”. There is one key difference between these documents and Five-year Plans: The government is free to disregard the Aayog’s recommendations.

The end of a centrally planned economic system also coincides with the formal interring of the Planning Commission, an organization central to not only India’s economic strategy but also to its federal temper through the added responsibility of allocating grants, Plan and non-Plan funds to states. The commission’s federal remit was not granted through constitutional mandate and this generated sufficient heartburn, especially among non-Congress states. However, the commission’s shuttering is also due to questions raised about the relevance of centralized planning in a globalized, market-led economy. And then there is politics. The commission was created through a government resolution which makes it easy for the Narendra Modi government to bury it.

But before the institution is shut down, it might be worthwhile to examine the 12th Plan performance, especially some of its macroeconomic targets. The 12th Plan ran between April 2012 and March 2017, with a Congress-led administration in charge till April 2014 and the Bharatiya Janata Party-led government steering the Plan thereafter. Prime Minister Modi announced his intentions of abolishing the commission and ending Five-year Plans during his first Independence Day speech in 2014 but allowed the 12th Plan to formally run till its original expiry date.

The plan had set an average gross domestic product (GDP) growth target of 8% for the 2012-17 period. This growth target was not achieved in any single year by either of the two political dispensations, despite a step jump resulting from a new series introduced by the Modi government. The closest India came was in 2015-16, with 7.9% annual growth. Otherwise, the average growth for the period works out to below 7%, way lower than the average annual growth rate of 8% achieved during the 11th Plan.

A low investment rate is among the many reasons for the under-average performance. The 12th Plan envisaged an average investment rate of 34%. However, the investment rate has been declining every year, starting with 33.4% during the first year of the Plan; the Central Statistical Office’s second advance estimates for 2016-17 show gross fixed capital formation at 26.9% of GDP, the lowest in more than a decade. What’s worse, investments have not been forthcoming from either the private sector (which has historically contributed the bulk of investment as a percentage of GDP) or the government sector which should ideally be investing when private investment dries up.

In a recent newspaper article, former Reserve Bank of India governor C. Rangarajan has also pointed to low productivity of capital, captured through incremental capital output ratio, or Icor, which measures how many additional units of capital are necessary to produce one additional unit of output. India’s slowing investment rate and rising Icor have led to low economic growth.

Discussing Icor might sound anachronistic, especially since the service sector accounts for 55% of India’s GDP where the relation between capital invested and output is still unclear. In addition, supply-side thrusts (such as increased government consumption expenditure) can lead to higher GDP growth despite a depressed investment climate, which can then send garbled messages about improved capital productivity. Ordinarily, a falling ICOR should be accompanied by palpable technological improvements and skill enhancements, leading to an all-round increase in productivity and efficiency.

Discussions on capital productivity seem to be back in fashion because high ICOR in recent times (higher than six during 2013-16) have been complemented by sluggish economic growth, over-leveraged corporate balance sheets and burgeoning bad debts in the financial sector. These factors have dragged down the economy’s growth impulses. In all discussions on efficiency and factor productivity, it is usually Indian labour that has to bear the cross. But this time the focus is squarely on capital productivity.

Obsessing with high ICOR becomes necessary when resolution of non-performing assets (NPAs) tops the public policy agenda. Most of the reasons behind high Icor in India are similar to those found elsewhere in the world, but one unique Indian feature stands out: gold-plating, or padded-up project costs. This not only suppresses capital productivity but also distorts the viability of many projects. With institutions and regulators orchestrating Operation NPA Clean-Up in mission mode—for example, the newly-instituted Insolvency and Bankruptcy Board of India is already grappling with 35 transactions—it is imperative that all resolution mechanisms incorporate enough measures to deter future projects from gold-plating costs and getting away with it.

The above article was published in Mint newspaper and can also be read here