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Why merit alone does not explain who succeeds in Indian economics
Why merit alone does not explain who succeeds in Indian economics Premium
I studied economics in different parts of India, across institutions that looked similar on paper but felt profoundly different in practice. Over time, I realised I wasn't merely moving between campuses or classrooms. I was moving between two distinct worlds of Indian economics education.
Economics is among the most sought-after disciplines in the social sciences. It sits at a rare intersection —between mathematical formalism and social relevance, between theory and policy, between abstraction and consequence. Students with diverse intellectual interests are often drawn to it precisely because it promises multidisciplinarity and mobility.
And yet, in India today, economics education and the economics profession are increasingly bifurcated. This is not just heterogeneity. It is a structural divide. One way to understand this divide—imperfect but useful—is through what can be informally called “averages” and “causals.” These are not moral categories, nor precise methodological boundaries. They are shorthand for two epistemic ecosystems that now coexist within Indian economics.
In one ecosystem, students are trained early in causal inference—not as an advanced specialisation, but as a default way of thinking. From the beginning of their doctoral training, they are exposed to multiple datasets, replication exercises, and empirical strategies that emphasise identification over association. They learn to exploit natural experiments, policy shocks, and institutional discontinuities, and to ask questions framed around counterfactuals: what would have happened in the absence of an intervention? This training is cumulative.
Coursework, seminars, peer discussions, and supervision all reinforce a shared language of causality, gradually lowering the cost of producing research that aligns with contemporary global standards. By the time these students enter conferences or the job market, their methodological orientation is already legible and familiar to evaluators.
In the other ecosystem, students often find themselves confined to estimating averages—simple regressions, descriptive relationships, and correlations—not because of intellectual limitation, but because of the environments in which they are trained. Exposure to causal methods arrives late, if at all, and often without the surrounding ecosystem that makes such tools usable in practice. Limited access to datasets, software, computational support, and methodologically trained supervisors further constrains what kinds of questions can be asked. Over time, students internalise these constraints as personal limitations rather than structural ones. What appears externally as a methodological preference is, in reality, an outcome of delayed exposure, uneven infrastructure, and the absence of mentoring pathways that would allow them to transition toward causal work.
Curriculum plays a decisive role here. While some institutions rapidly align their syllabi with global research frontiers—causality, computation, even AI-adjacent tools—many state, central, and private universities struggle to move beyond foundational econometrics. Students rarely choose these worlds knowingly. By the time differences become visible, mobility between them is already costly.
Conferences reinforce this separation. They are not just venues for presenting work; they are gateways to feedback, networks, confidence, and publication pipelines. Attendance patterns reveal a quiet concentration of representation. Those outside this circle often do not apply. Those who do apply are frequently filtered out. And those who make it through often experience these spaces as isolating rather than integrative.
The consequences compound at the job market stage.
Academic hiring increasingly rewards signals associated with the “causal” world: publications shaped by particular methods, familiarity with global norms, and institutional pedigree. This is where one mechanism becomes especially revealing—letters of recommendation. Letters of recommendation are a standard feature of the U.S. and Western academic markets. They serve an important signaling function, conveying information about a candidate's skills, research depth, and preparedness. I do not dispute their value in principle.
But when imposed as a mandatory requirement in the Indian context, they often function less as filters and more as barriers.
In large parts of Indian academia, LoRs are not discussed, trained for, or normalised. Faculty members may be unfamiliar with what such letters are expected to contain. Students may not even know when or how to ask for them. As a result, many capable candidates never apply for positions—not because they lack merit, but because they cannot furnish a signal they were never taught to produce.
This is not an individual failure. Nor is it the fault of those who can produce strong letters. On the contrary, exploiting all available resources is a rational response to the incentives one faces. The issue is structural. Over time, differences in curriculum, research exposure, conference access, and signaling mechanisms sort economists into parallel tracks with unequal visibility and mobility.
Economists, perhaps more than any other social scientists, dedicate their careers to studying inequality. Yet within the discipline itself, inequality is quietly regenerated—through institutions rather than intentions. This pattern is not unique to India, nor is it new. As documented in Pedigree, elite training ecosystems tend to reproduce elite outcomes. What is striking in the Indian context is how clearly this reproduction maps onto two divergent Indias of economics education and academic life.
Recognising this divide is not about choosing sides. It is about acknowledging that merit does not operate in a vacuum. If Indian economics is to remain intellectually vibrant and socially relevant, it must confront the inequalities it produces within itself—before they harden into destiny.
(Kaibalyapati Mishra is Senior Research Fellow at the Centre for Economic Studies and Policy at the Institute for Social and Economic Change)
(Sign up for THEdge, The Hindu's weekly education newsletter.)
Published - January 07, 2026 07:25 pm IST
education / economics (education) / employment / students / higher education / universities and colleges
Source: TheHindu
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