Statistical reform: Suggestions for the new government’s first 100 days

T. C. A. Anant | 19 Jun 2024 | LiveMint

The long gap since the 2011 Census has created many problems for statistical work, particularly those using Sample Survey data.

SUMMARY: For data-driven policymaking, in the short term, the NDA government could declare a schedule for the Census and updating of existing survey tools. Next, it could focus on making good use of administrative databases like the one we have of GST.

One of the first things the newly elected government announced was its intention to have its ministries and departments put in place a 100-day agenda of action. In this context, it is worth noting that the BJP, in its election manifesto, had promised that “we will further strengthen the capacity of statistical institutions to give impetus to data-driven policy making.” Here, I outline some measures that can be taken over the next 100 days by the government’s statistical agencies towards that goal.

Let’s begin with suggestions for the short-term.

Announce a time schedule for the Census: The 2021 Population Census got deferred because of covid and then possibly because of multiple elections for state assemblies and the Parliament. For the moment, major election clusters are behind us. Given the nature of our democratic structure, polls will keep happening. The long gap since the 2011 Census has created many problems for statistical work, particularly those using Sample Survey data. This is because the frame for all Sample Surveys is drawn from the preceding Census, and using old frames leads to poor quality aggregate estimates. If the registrar-general were to notify a calendar for Census operations in the next 100 days, we may be able to conduct it by 2026. This would ensure that before the new government’s term is complete, we would be in a position to rectify any errors that may have crept in due to obsolete multipliers used in generating survey estimates.

Announce a calendar for revision of long running statistical series: The ministry of statistics and programme implementation (Mospi), particularly the Central Statistics Office, should notify a calendar for the revision of National Accounts, Consumer Price Indices and the Index of Industrial Production (IIP). The Office of the Economic Advisor in the department of industrial policy and promotion (DIPP) should parallelly work on revising the Wholesale Price Index and core sector indices. All these series are currently being run on a 2011-12 base and are overdue for revision. The basic data for this exercise is already in place, given that Mospi has regularly been conducting the Periodic Labour Force Survey (PLFS), recently released annual surveys of unorganized sector enterprises for 2021-22 and 2022-23, as well as the Household Consumption Expenditure Survey for 2022-23, and is about to complete HCES 2023-24. It should be possible over 100 days to decide on whether the new base year should be 2022-23 or 2023-24, both of which meet the requirements of being ‘normal’ for establishing a base year. If these are initiated soon, they can be completed by 2026.

Here are my suggestions for the medium-term.

Make better use of the GST database: In addition to the above immediate tasks, it’s important for the government to initiate a programme of research and institutional development that would permit better use of the large administrative data system it has created over the past decade through various e-governance initiatives. The most useful of these is the rich database generated by the GST system. As I have argued earlier, analysis of GST data may offer us a better measure for estimating goods and services production than the existing IIP. GST data also opens up the possibility of doing a more comprehensive revision of price indices, because GST returns, at least for manufactured products, capture both the value and quantities of production. For this exercise, the GST database must be made accessible to researchers. Problems of confidentiality can be addressed by using mechanisms similar to those employed by the Directorate General of Commercial Intelligence and Statistics (DGCIS) when it works with Customs data. Both the DGCIS and Mospi have the inhouse capacity needed for the analytical exercises. Many of our domestic research and education institutions have the capacity to conduct research. Should the DGCIS and Mospi work more closely with them, it would strengthen India’s research capacity. Converting this research into regular statistical products would require creating institutional capacities, either through establishing a new arrangement, or through strengthening existing ones.

Integrate administrative e-governance data with survey data: In addition to the data gold-mine of GST, virtually every major national scheme, from Ayushman Bharat (health), PM Awas (housing) and Jal Jeevan Mission (drinking water) to Mudra and Udyam (MSMEs) and others, has evolved e-governance platforms to monitor implementation. These platforms have gathered (and continue to gather) rich data on various socio-economic attributes. They also generate complementary data to those gathered by the NSS, National Family Health Survey and surveys by the Labour Bureau. Making disaggregated data from these e-governance portals accessible to researchers would enable analytical exercises that use both administrative and survey data, which in turn would help improve these programmes. Eventually, it could also help substitute expensive Sample Surveys with indicators drawn from the administrative database. In order for this potential to be realized, it is necessary to put in place a mechanism for releasing disaggregated administrative data for research use. As above, issues of confidentiality can be addressed with well-established techniques of anonymization and masking. While much of this has been recommended in various committee reports of the National Statistical Commission, implementing this would require policy oversight at the highest level. A possible vehicle for doing so would be if the monthly Pragati meetings held by the Prime Minister’s Office (PMO) also include a module for data integration and utilization. Interest taken by the PMO is necessary for departments and ministries in our scheme of governance to give this reform exercise its due importance.

These suggestions can be implemented within the existing institutional framework. At most, they would require adaption or strengthening of our existing statistical offices to undertake additional work. I have specifically stayed away from suggestions that would require a major institutional overhaul, partly because many of them require much more detailed analysis and consensus building before they should be undertaken, an issue I may return to in later columns.