Evidence-based Policy or Policy-based Evidence: What Do We Need Data For?
The Bharatiya Janata Party’s (BJP) Achilles heel in the 2019 Lok Sabha elections is the economic non-performance of the Narendra Modi government, which it has brazenly buried under its tinkered macroeconomic estimates. But the manipulated statistics fail to give the decisive punch to the allegation on the ruling government of subverting key (data) institutions because the focus of the contention has now shifted to the weak statistical capacity of the data institutions as the driver of credulous/contested estimates. Most disconcertingly, such attacks on the veracity of the Indian data system—erstwhile held in high regard for its integrity—legitimise the ruling government’s meddling in the institutional independence, relevance and trustworthiness of the statistical organisations, as well as the political expedience of concealing uncomfortable evidences of its failed promises, or tweaking evidences to downplay its political predecessor to prove its hypothetical claims of betterment.
If the sampling methodology of the 2017–18 periodic labour force survey (PLFS) of the National Sample Survey Office (NSSO) is a challenge to the reliability and comparability (with the NSSO’s archetypical employment/unemployment surveys) of these estimates, one is intrigued by tricky questions such as: Who decided upon this change and why? With the answers to these, especially the “why” question, not being in the public domain, suspicions regarding mala fide abuse of power by the ruling government are not unfounded, given that the controversy over the economic growth estimates is still lying unaddressed in the government’s backyard. What is then the efficacy of data/evidence for policymaking?
The composition of the annual outlays to the Ministry of Statistics and Program Implementation (MoSPI) in recent times shows the predominance of the program implementation wing, or more specifically the members of Parliament local area development scheme (MPLAD), over that of the key statistical organisations (namely, the Central Statistics Office (CSO) and the NSSO) and the statutory data monitoring bodies (the Indian Statistical Institute (ISI) and the National Statistics Commission (NSC) under the statistical wing), and the ministry in general. Over the past decade or so, the MPLAD’s allocation has formed over four-fifths of the annual budget of the ministry, and in the last five years, the rate of growth of these allocations has been faster than before. From 2012–13 to 2015–16, the annual outlay for the MPLAD had increased by almost 6%. The rising significance of programme implementation can potentially reduce the worth of data to mere supplements for the rhetorical narrative of the ruling government about its “welfarist” schemes.
The BJP’s impudent denial of the deficient quality of its official statistics, even in the face of widespread accusations, raises another hard question: What is the value of data in electoral politics? Evidence from cash-strapped developing economies has revealed that the data collection process is often viewed as an unnecessary expense by governments, and governments might restrict themselves to collecting only data/evidence that matters to them. Alternatively, since data are not just numbers, but rather critical observations—quantitative, qualitative, or even figurative—that need to be interpreted for information, political parties interpret these as conducive for their incumbency, often notwithstanding the quality criteria. In discursive academic spaces, on the other hand, the quality of such observations is held sacrosanct. Is it not this body of observations that determines the contours of tomorrow’s policies?
Herein lies the catch, because the body of statistics that we have today is the outcome of yesterday’s politics and policies. Thus “evidence-based” policy and “policy-based” evidence make a chicken-and-egg situation, wherein the “quality deficit” of data may not lead to the common voter’s “trust deficit” in a particular political party, because to them, data/statistics continue being just the “numbers” that all ruling governments compulsively refute and (re)create at their political expediency.
The views expressed here are personal and do not reflect the collective view of the journal.
