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While collecting official statistics will always be a purview of state institutions, they must be governed by independent governing bodies that can ensure scientific integrity and broad oversight.

We seem fascinated with statistical soundbites, vacillating between the bizarre and the expedient. In October 2021, major newspapers featured stories that claimed that over 100 million Indians owned cryptocurrencies. This put Indians at the top of the global cryptocurrency such as Bitcoin, Dogecoin, etc. Strangely these stories exhibited no scepticism.

When Coin Crunch, a cryptocurrency news magazine, dug deeper into the source of this data, they discovered how hollow these claims were. They traced the source to data from market research, where 2,000 to 12,000 in each country were asked to complete online surveys. Generalising from Internet survey respondents to the Indian population takes quite a stretch of the imagination.

However, these outlandish statistics are not the only ones that get uncritical attention. On the release of the factsheets from the fifth round of the (NFHS-5), conducted in 2019-20, some headlines focused on increasing Severe Acute Malnutrition (SAM) in India. Between 2015-16 and 2019-21, children who are too thin for their height, identified as suffering from severe wasting, called SAM, increased from 7.5% of the population to 7.7%, although stunting (low height for age) decreased from 38.4% to 35.5%. This slight increase in SAM would be a cause of concern since these children are most at risk for nutritional failure.

Differences in methodology

However, both in the press and in the presentation of the data by researchers, differences in methodology between NFHS-4 and NFHS-5 received little attention. A paper published in the journal Plos One by Robert Johnston and others compared NFHS-3 and NFHS-4 as well as several other nutrition surveys and found that due to diarrhoea and other diseases, children are thinner in interviews conducted during the monsoon season. Studies in other countries have made similar observations. My calculations suggest that while only 12% of the NFHS-4 surveys were conducted between July and October, 40% of the NFHS-5 surveys were conducted over these months due to pandemic-related fieldwork restructuring. When we compare SAM for children surveyed during monsoon, and outside of monsoon months, we find that for each period, the prevalence of SAM was slightly lower for NFHS-5 than for NFHS-4 (7.3% in NFHS-4 vs 7% in NFHS-5 outside the monsoon period; and 8.9% vs 8.6% during monsoon interviews). This change is only minor in magnitude, but the difference between a slight increase in malnutrition and a slight decrease changes the tone of the discourse.

These challenges are not unique to India. For over a decade, the popular narrative about maternal mortality in the U.S. suggested that while globally maternal mortality was declining, in the U.S. between 2000 and 2014, it increased by 26%. It was not until Marion MacDorman and her colleagues at the National Center for Health Statistics (NCHS) carefully analysed how maternal mortality statistics were collected that a different conclusion emerged. The NCHS studies found a decrease rather than an increase in the maternal mortality rate over time. The apparent increase was entirely due to how the maternal mortality data were collected.

These examples highlight the challenges researchers, journalists, the informed public and policymakers face. We live in a world where data collectors and researchers are expected to provide data in a rapid cycle with little time to interpret the results and explore anomalies. Media rely on the data presented to them to file stories with statistical soundbites, often even uncritically accepting information provided by market research firms commissioned by industry bodies with a vested interest. In some cases, a political predisposition allows some data to be accepted uncritically while others are scrutinised extensively.

What is a way out of this conundrum? How can we build sensible public discourse and rational, evidence-informed policy design? It will require a substantial redesign of our data and evidence infrastructure with a troika of improved data collection, interpretation and reporting infrastructure.

Independent oversight

While collecting official statistics will always be a purview of state institutions, they must be governed by independent governing bodies that can ensure scientific integrity and broad oversight. The term of the National Statistical Commission (NSC) expired a few months ago. Reappointing the NSC is urgently needed. Moreover, it is also essential that publicly funded but independent data collection also find space in our statistical infrastructure. Consistent experimentation is required in a rapidly changing society and growing technical infrastructure for data collection. In most countries, publicly funded experiments in data collection are carried out by universities or research institutions.

Data collectors must develop the capacity to interpret their data carefully and responsibly. Users often do not know the sampling strategy or minute operational details of data collection. Hence, data collectors must help interpret the data they collect and provide good documentation to users. Today, the National Statistical Office has no data analytical wing. National Family Health Survey reports are simple tabulations without any information about standard errors or attempts at interpretation. These institutions must be strengthened and fully funded to provide data quality analysis and explore their results’ implications.

Researchers and journalists must develop the self-discipline to use and report only reliable data and be cautious of for-profit institutions with a vested interest in providing statistics and reports. The cryptocurrency example above is sobering but not the only example. Lancet, one of the most reputable journals, was forced to withdraw papers based on Hydroxychloroquine trials because the for-profit company that supplied the data was unwilling to share it for verification. Academic publishing and deadline-driven journalistic pressures must be balanced with the responsibility of not misleading the public discourse with inadequately documented information that is either unavailable for verification or is so expensive that it is effectively out of reach of most researchers.

Most importantly, we must develop professional ethics that demand sincere efforts at collecting, interpreting and reporting evidence and institutional infrastructure and public funding that makes this arduous task feasible. As any self-aware data collector and researcher will acknowledge, errors will occur even with the best efforts. Data collectors are not perfect and statistical techniques continue to evolve. However, unless we put thoughtful processes in place for evidence required to support sound policy design, we have no hopes of minimising misdirection.

Sonalde Desai is Professor and Director of NCAER National Data Innovation Centre and Distinguished University Professor at the University of Maryland. Views are personal.

In India, the inflation target (for CPI headline inflation) was set at 4%, with an upper tolerance limit of 6% and a lower limit of 2%. GoI constituted a six-member Monetary Policy Committee (MPC), including three ex-officio members from RBI with the RBI governor as its chairperson, the deputy governor in charge of monetary policy, and an officer to be nominated by its central board. The other three members were to be appointed by GoI for a non-renewable term of four years.

India moved to inflation targeting (IT) in October 2016, after experiencing double-digit inflation for several years. By doing so, it joined a growing group of more than 50 countries that adopted a similar framework to guide monetary policy. The framework has proven to be resilient and nimble, having survived global shocks including the Global Financial Crisis and Covid. There is no known case till date when a country has abandoned IT in favour of another framework.

In India, the inflation target (for CPI headline inflation) was set at 4%, with an upper tolerance limit of 6% and a lower limit of 2%. GoI constituted a six-member Monetary Policy Committee (MPC), including three ex- officio members from RBI with the RBI governor as its chairperson, the deputy governor in charge of monetary policy, and an officer to be nominated by its central board. The other three members were to be appointed by GoI for a non-renewable term of four years.

RBI was mandated to organise at least four meetings of the MPC annually. It was asked to publish a monetary policy report every six months to explain the sources of inflation and provide forecasts of inflation. It was urged to make publicly available the resolution adopted by MPC, the minutes of the meetings, the vote and statement of each MPC member, and a document explaining the steps to be taken to implement the MPC’s decisions.

Further, if RBI failed to achieve the inflation target, it had to submit a report detailing the reasons for this, the prospective remedial actions, and the estimated time period within which IT could be achieved. The agreement specified that RBI would be deemed to have missed its target if inflation exceeded 6% or declined below 2% for three straight quarters, and to have failed it when for three consecutive quarters inflation exceeded 6%.

Notwithstanding early misgivings, the IT framework has worked well. The constitution of MPC has been apolitical. Its meeting schedule has been posted in advance, and all its decisions and communications have been transparently articulated. Consequently, the suspense and surprises around monetary policy formulation have largely disappeared. RBI has not just maintained, but may have enhanced its independence since IT’s adoption. In other countries, the framework has curtailed the influence of the fiscal authorities, and achieved better coordination between the fiscal and monetary authorities. This seems to be the case for India, too.

Currently, the average inflation in India is much lower as compared to its previous trend rate, when it had averaged 10% during 2009-13. Inflationary expectations have been better anchored, and India has experienced a milder acceleration in recent months than in other comparative countries.

India has practiced a flexible IT framework. Evidence shows that the output gaps have not been neglected in policy formulation. MPC statements show that besides headline inflation and the output gap, MPC members assess a range of factors in their deliberations, including food inflation, agriculture sector, rural distress, unemployment, income inequalities, credit offtake, and the global environment. Along with the repo rate, a full policy toolkit comprising the liquidity adjustment facility (LAF) corridor, the cash reserve ratio (CRR), liquidity management, and communication is used. Thus, there is more continuity with the past frameworks than is often appreciated.

An early concern with IT was that an inflation target of 4% seemed too hawkish for a low-middle income country. Just like other countries, India targets inflation in a range, and has in-built escape clauses that allow temporary breaches. In its early years, MPC focused on strictly attaining an inflation target of 4%. Having established its credibility, it can now afford to periodically operate within the full range, while avoiding staying at either extremity of the range for long periods of time.

Ben Bernanke and Frederic Mishkin had argued in their 1997 paper, ‘Inflation Targeting: A New Framework for Monetary Policy?’ (bit.ly/3QUe3V8) that ‘inflation targeting does not represent an ironclad policy rule, as some writers on the subject and even some advocates of this approach seem to assume. Instead, inflation targeting is better understood as a policy framework, whose major advantage is increased transparency and coherence of policy, and in which fairly flexible, even ‘discretionary’ monetary policy actions can be accommodated.’ Inflation targeting has indeed operated in this spirit in India.

Now that the framework has stabilised, it seems to be the right time to tune down the frenzy around MPC meetings. The media, experts and RBI can turn their focus to other issues of critical importance, such as the management of the exchange rate, foreign reserves, capital account liberalisation, and regulation of banks and non-bank financial institutions. RBI ought to continuously revive its regulatory and policymaking capacity on all important issues, not just monetary policy.

The writer is director general, National Council of Applied Economic Research (NCAER)

In the platform economy workers function in a formalised realm but without benefits of tenure or welfare

One of the research questions that the NITI Aayog report ‘India’s Booming Gig and Platform Economy: Perspectives and Recommendations on the Future of Work’ poses is whether platforms are formalising or informalising the economy? We attempt a conceptual answer here. We argue that the platform work moves the economy towards formality. But that does not amount to completely formalising the economy.

What is an informal or unorganised economy? The National Commission for Enterprises in the Unorganised Sector (2007) defined unorganised workers as “those working in the unorganised enterprises or households excluding regular workers with social security benefits and the workers in the formal sector without any employer/social security benefits provided by the employers.”

Unni and Naik (2013) in their article ‘Measuring Informality of Employment in Urban India’ (published in The Indian Journal of Labour Economics. 56(4): 493-508) point out that there is considerable heterogeneity in the urban informal economy in India. There is a continuum of employment relationships (see Table).

Platform work defined

Keeping this in mind let us focus on labour platforms. The Draft Code on Social Security (DCSS) 2020 defines “platform work as a work arrangement outside of a traditional employer- employee relationship in which organisations or individuals use an online platform to access other organisations or individuals to solve specific problems or to provide specific services or any such other activities that may be notified by the Central Government in exchange for payment”.

The platform acts as an intermediary between the service provider and the service seeker. The intermediary is not an employer but helps the service provider land paid tasks. The service provider is the food delivery worker in Zomato/Swiggy the cab driver in the case of Ola/Uber and the beautician/plumber/electrician in the case of Urban Company etc.

The contract between the service provider and the platform is market/transaction based. For example in the case of the food delivery platform sector a worker signs an agreement with the platform that he/she will get paid a particular amount upon delivery of food to a particular location within a particular time.

The tasks and amount that one is going to be paid for that task are pre-decided. The platform reduces transaction (search bargaining and monitoring) costs and bears the burden of transaction failure. It is in a position to verify that the transaction has been completed like Zomato/Swiggy/Ola/Uber.

Unlike the traditional informal economy the intermediary in the platform economy takes the burden of the failure of an exchange between the service provider and service seeker like Ola/Uber.

The working conditions of the worker remains essentially informal but has some ‘formal’ features such as the use of bank accounts as a result of digitised payments.

In contrast there is a contract based on a personalised understanding between a traditional informal worker and a service seeker in the regular economy. This contract becomes self- enforcing due to the mutual trust between the two parties which is formed after repeated interactions.

This holds true for our neighbourhood plumber electrician etc. If any one of the parties reneges from commitment in the transaction the relationship breaks down. This can be costly if future transactions are contingent on the success of current transactions. This creates the incentive for each party to go through the commitment.

The transactional contract (as opposed to a relational contract) makes the work done by a platform worker “formal”. The task and payments associated with it are pre-decided; all parties know the costs of failure. Here the transaction for work also may have a tax component attached as for food delivery. But to reiterate the working conditions are informal.

Whether the platform is just an intermediary or an employer is an empirical question because it will depend on the degree of autonomy the platform workers enjoys in their job. Autonomy is the choice of the worker to decide how where and when to produce. In the US and the UK platform workers in specific platforms have been deemed to be employees rather than independent contractors due to the lack of autonomy. These need to be assessed in India.

In sum the platform worker himself/herself remains informal because he/she has neither employer-provided social welfare support (such as pensions and medical insurance) nor a tenure- based job contract nor access to state pensions. Food delivery platform workers are covered by accident insurance which is a very specific form of medical insurance (covering only on-duty casualties) and not a comprehensive idea of the latter.

A policy conundrum is that if the platform worker actually starts receiving social security either from the employer or the government then will s/he become completely formal? The answer will lie in the details.

Bhandari is a Senior Fellow and Sahu and Urs are Associate Fellows at NCAER; Gupta is an Assistant Professor at Ahmedabad University and Das is a Research Fellow at the National Institute of Urban Affairs. Views are personal