Working Papers
When Competition Compels Change: Trade, Management, and Productivity Job Market Paper
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Past work emphasizes that pro-competitive gains from trade arise from the reallocation of resources towards more productive firms. I focus on a complementary channel operating within firms, where competition induces organizational change and raises managerial efficiency. I study this mechanism by exploiting a product-specific import competition shock in India. To do so, I assemble novel data on family-managed firms—the predominant form of corporate governance worldwide—compiling tenure records and family ties for over 6 million company executives and directors. Using an event-study design, I show that the least productive firms respond to import competition by replacing family managers with non-family, professional executives. Firms that professionalize experience productivity gains of over 20 percent. To quantify the aggregate implications of these managerial adjustments, I develop a framework embedding endogenous management choice within a Melitz model, in which firms trade off the non-pecuniary private benefits and reduced contracting frictions associated with family management against the profit gains from professionalization. My model reveals that import liberalization increased aggregate productivity in India by 9 percent, with within-firm improvements in managerial allocation explaining nearly 30 percent of this increase. Bridging macro-level trade shocks with micro-level administrative data on firm organization reveals within-firm managerial reallocation as a powerful source of gains from trade, with implications for understanding other margins of adjustment to import competition.
We study the micro sources and macro consequences of worker-job matching across countries with large income differences. Using internationally comparable data on over 120,000 individuals in 30 countries, we document that workers' skills align more closely with their jobs' skill requirements in higher-income countries, indicative of more meritocratic labor market matching. We interpret this fact through an equilibrium matching model with cross-country differences in three fundamentals: (i) endowments of worker skills and job requirements determining match feasibility; (ii) technology determining the returns to matching; and (iii) idiosyncratic frictions capturing how nonproductive traits affect matching. A development accounting exercise based on the model, estimated separately for each country, shows that variation in matching frictions explains only a small share of cross-country output gaps. However, improved worker-job matching substantially amplifies the gains from adopting frontier endowments and technology.
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We estimate the aggregate impacts of court-ordered iron ore mining bans in India and consider the counterfactual welfare gains from an alternative policy to the ban. The local sectoral ban is a command-and-control (CAC) policy that is commonly applied to natural resource settings, usually when the regulator has a signal of widespread non-compliance. The Supreme Court of India imposed bans on iron ore mining and outbound iron ore trade in two states in response to reports that mines operated under fake environmental permits and underpaid mining royalties. Using firm-level industrial survey data, mine-level output data, and bilateral mine-to-firm auction data, we decompose the bans’ effects into trade, production networks, and local labor demand channels. Our results indicate persistent declines in employment, capital stock, and borrowing by iron-consuming plants, despite the temporary duration of the ban. These findings highlight the economic spillovers caused by CAC policies, especially in industries that are upstream in the supply chain.
How Much Do Firms Save? Financial Frictions and the Microeconomic Implications of the Euler Equation
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Neoclassical growth models with standard parameter values provide powerful self-financing incentives to financially constrained entrepreneurs. This fundamental prediction has important implications for capital misallocation. If entrepreneurs can indeed save themselves out of financial constraints, capital misallocation should disappear on its own and impose a small, transient cost to aggregate productivity. This is contrary to a large body of empirical work that has documented high dispersion in marginal products of resources, particularly capital. Using micro firm-level data and the staggered implementation of a financial liberalization policy in India, I provide causal evidence on the relationship between financial constraints and self-financing by individual firms. I find that the behavior of treated firms that see an easing in their financial constraints does not conform with standard predictions of the neoclassical growth model.
Work in Progress
AI and Bureaucratic Decision Making
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Excessive litigation in tax administration often stems from bureaucratic risk aversion rather than legal necessity. Tax officers, wary that exercising discretion might invite allegations of corruption or favoritism, tend to appeal every adverse decision, regardless of merit. This culture of defensive decision-making fuels administrative overload and inconsistent judgments. This project studies whether artificial intelligence can improve the quality, consistency, and efficiency of legal reasoning among tax officers handling appellate cases. We develop and deploy an AI-assisted "Tax Co-Pilot" that summarizes case histories, highlights relevant precedents, and predicts the likelihood of success on appeal. The intervention is tested through a randomized rollout among quasi-judicial officers in the tax and revenue departments of the Indian government. By combining administrative data with officer-level behavioral metrics, we plan to examine how information frictions and cognitive constraints shape state performance. The study contributes to the economics of bureaucracy, public administration, and technology adoption, offering new insights into how AI tools can enhance decision quality in complex legal and regulatory settings.
Management in India
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We study how family control and professionalization shape firm performance and organization using nationwide administrative records on over 350,000 registered Indian firms spanning the 1980s to the present, including director genealogies and tenure histories. We construct firm-year measures of family presence on boards and deploy event-study designs around leadership transitions and shifts toward professional boards. Supermajority family boards are systematically smaller and less productive: revenues, profits, and exporting are lower when more than three quarters of directors are family, relative to otherwise similar firms. Dynamic estimates around patriarch exit show post-transition improvements in operating outcomes and profitability ratios. Together, the evidence maps who professionalizes, when, and with what consequences for scale, productivity, and managerial practices in Indian firms.
FDI and Firm Organization
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This project examines how restrictions on foreign direct investment (FDI) from China affected capital inflows and firm behavior in India. Using transaction-level administrative data on FDI inflows and an event-study design, we document a sharp and sustained decline in investment originating from China and Hong Kong following a 2020 policy change, with no comparable change in inflows from other countries. We then link these FDI shocks to administrative firm-level data to study how the withdrawal of foreign capital reshaped firm ownership structures, investment behavior, and internal organization. In particular, we investigate whether reduced access to foreign partners led firms to alter managerial practices, decision-making processes, and technology adoption. Planned work seeks to combine these data sources to provide causal evidence on how sudden restrictions to international capital flows propagate through firms, shaping organizational practices and productivity in a large emerging economy.
AI and Judicial State Capacity
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Access to timely justice is a cornerstone of state capacity, yet judicial systems across the Global South face severe administrative bottlenecks and chronic backlogs- in India alone, it would take nearly 300 years to clear the backlog of over 50 million pending cases. This study evaluates whether artificial intelligence can meaningfully strengthen the state's judicial capacity through one of the largest randomized controlled trials ever conducted in courts. We partner with over 1,500 courtrooms across Andhra Pradesh and Odisha in India to introduce an AI platform that provides real-time transcription, translation, and automated case-flow management for judges and court staff. The experiment measures how workflow automation affects judicial productivity, hearing duration, and case resolution rates, using daily administrative and survey data on court proceedings and judgments. The study will provide the first causal evidence on how frontier AI technologies can improve bureaucratic efficiency in core state institutions, enhance decision quality, and inform the design of scalable digital infrastructure for justice delivery in low- and middle-income countries.
Labor Market Frictions, the Organization of Labor, and Structural Change
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This project studies the long-run effects of the 1982-1984 expansion of India's Industrial Disputes Act (IDA), which extended strict firing regulations from manufacturing firms with more than 300 workers to those with more than 100. The amendment required firms above this threshold to obtain government approval before laying off blue-collar workers, permission that was rarely granted. Using microdata from the Annual Survey of Industries from 1974 to 1990, we employ an event-study design to show that affected firms experienced substantial exit, employment losses, and capital contraction, with much larger declines in labor-intensive industries relative to capital-intensive ones. The reform therefore shifted the composition of India's industrial base toward more capital-intensive production. Ongoing work builds a structural model to quantify how such labor market distortions slowed structural transformation by impeding the movement of workers from agriculture into manufacturing and dampening overall productivity growth.
Globalization and Domestic Industrial Policy
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