“We need to recognise that the construction of public statistics is informed by political commitments that must be aired and critiqued for good policymaking”
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How should India approach data collection and statistics for the next five years? Measures and datasets tell the stories of a country’s growth and are important to citizens, policymakers, and the international audience. In the last few years, the accuracy and quality of India’s statistical systems have been questioned. Economists and policymakers have lamented the “decade without data” since the Census has not been conducted and the release of National Sample Survey (NSS) data faced delays. They have advocated for more independence and neutrality in data collection, interpretation, and release.
Are numbers objective?
However, simply championing values like independence and neutrality overlooks the contextual and political nature of statistics. We need to recognise that the construction of public statistics is informed by political commitments that must be aired and critiqued for good policymaking. Unless the politics are transparent, the statistics will not be as useful as they could be.
Statistics, first and foremost, are attempts at numerical representations of complex social experiences. Choices about what to count are simultaneously choices about what not to count. Consider welfare policies such as the financial inclusion scheme, Jan Dhan Yojana. India broke the Guinness World Record in 2014 for opening the maximum number of bank accounts in a week. At what cost was such speed achieved? A leader of an activist group based in Hyderabad explained that a bank had set up camps in Adivasi villages of Andhra Pradesh, hastily opened accounts for citizens, and left. “Accounts were opened but people did not know details about their accounts, and were never given passbooks,” he said. Although direct benefits transfers were being sent to those accounts, they were inaccessible. Cases of the poor being unable to access their bank accounts and welfare subsidies due to illiteracy, documentation issues, and harassment are plentiful despite the statistical narrative that numbers of bank accounts are rising. In another example, the kilogrammes of foodgrains distributed under the Pradhan Mantri Garib Kalyan Yojana are widely shown across billboards. The Global Hunger Report of 2023 records that India’s ranking had slipped from 55th in 2014 to 111th in 2023. Fixating on the number of bank accounts and kilogrammes of foodgrains distributed as metrics of state success can conceal the darker story of limited banking access and poor nutrition.
Second, meeting statistical targets should not be confused with the achievement of development objectives. This is an issue across multilateral institutions, but India must take a more nuanced approach. Consider the eShram unorganised workers’ database, set up by the Ministry of Labour and Employment after the COVID-19 pandemic to collect data on migrant workers. A Common Service Centre operative in Gurugram explained how the database relies on self-declaration, and that many who were not eligible for the workers’ database, such as housewives, teachers, and farmers, had signed up in the hope of future benefits. While eShram has rapidly met enrolment targets and been extolled as successful, the emphasis on data obscures whether eShram is reaching its target population. Documenting anecdotes, conducting audits, and collecting citizens’ experiential feedback is crucial to making good development policy.
Third, scrutinising data is tougher with the digitisation of governance. For most of the 20th century, socioeconomic data-gathering in India was the work of public institutions including the National Sample Survey Organisation and the Central Statistical Office, which had robust details on research methods. With Aadhaar, the state has more data on citizens than ever before. Despite the possibility of anonymizing and aggregating for privacy protection, it has become more difficult for citizens and researchers to access this data. Most eGovernance data is stored in State Data Centres accessed by government divisions and their private partners, and data is irregularly published online. On the flipside, data collected through payment apps such as Google Pay and PhonePe are used by FinTech start-ups to create financial products to sell to citizens. Data collected on citizens is not available to citizens or journalists to hold institutions accountable; only government and private actors have access.
Strengthening data systems
What are the implications of this politics of data, and how can we strengthen our data systems? Without denigrating quantification, we can create data systems to be more citizen-serving. A first step involves changing our orientation from asking whether we have the “right” data or technical methods to asking what kind of data are most useful for citizens’ well-being. For instance, while the statistics on the number of newly opened bank accounts are likely to be correct, it may be useful to measure the proportion of poor who access their bank accounts.
Second, digitally collected data should not exclusively be designed for the use of the government and start-ups. It is vital to set up porous institutional structures that give civil society a voice in designing data infrastructure.
Third, policymakers need to expand their views of data collection from a mere technical exercise to a social and political undertaking that would benefit from the inputs of social scientists, citizens and activists. Ultimately, statistics ought to serve citizens; citizens should not serve the achievement of statistical targets.
Pariroo Rattan, PhD candidate at Harvard University and a Non-Resident Research Associate at the Centre for Social and Economic Progress. Views expressed are personal
Published – October 31, 2024 04:32 am IST
