Tishara Garg

This paper introduces a method to study the impact of policy events on equilibrium selection in settings where strong complementarities may lead to multiple equilibria and coordination failures. Many industrial policies are rooted in the idea of coordination failures and big-push' theories, yet empirical evidence on their effectiveness remains limited, since distinguishing equilibrium shifts from direct changes in fundamentals is challenging. Leveraging tools from industrial organization and algebraic geometry, I develop an approach to study coordination effects without imposing strong assumptions on the distribution or responsiveness of economic fundamentals. The method identifies the `types' of factual and counterfactual equilibria through a three-step procedure: model estimation and inversion, equilibrium enumeration, and type assignment. Types of factual equilibria may be used to examine how events, like urban infrastructure, subsidy drives, or trade liberalization, affect equilibrium selection. Types of counterfactual equilibria further allow decomposition of observed effects into fundamentals- versus coordination-driven. I apply this method to study industrial zones in India. Using a newly assembled dataset, I find that municipalities receiving an industrial zone see a 60% increase in non-farm employment over 15 years, with significant spillovers to non-targeted sectors and municipalities. Combining the methodology with event study designs, I find that industrial zones increase the probability of escaping a low-industrialization equilibrium by 38%, with coordination effects explaining roughly one-third of the observed change in outcomes.

This paper investigates how immigration-induced wage shocks can propagate beyond the regions receiving immigrants through the production network. Using the Syrian refugee crisis in Turkey as a quasi-experiment and the near universe of domestic firm-to-firm transaction data from VAT records, we show that the immigration shock propagates both forward and backward along the supply chain. Firms in non-host regions who directly or indirectly buy from host regions demand more labor. Firms who sell to host regions weakly increase their sales. Estimates imply an elasticity of substitution between labor and intermediate goods of 0.76 and an elasticity of substitution of nearly 1 between intermediates. Counterfactual analyses show that the spillover effects on non-host regions are economically meaningful when the host regions are central nodes of the domestic trade network. For example, a 1% increase in labor supply in Istanbul decreases real wages in Istanbul by 0.56% and increases real wages in the average non-host city by 0.38%.

Economic distortions—such as market power, taxes, credit constraints, etc.—are fundamental in understanding the difference between developing and developed economies. Recent work has documented the pervasive extent of economic distortions and how they lead to substantial misallocation, or aggregate productivity loss. Far less well understood is how these phenomena affect members of society differently. In this paper we combine unique datasets from Chile, linking workers and owners to firms, firms to each other, firms to consumers, and firms and consumers to the government, in order to quantify the full incidence of distortions for the first time.

In real-world settings, a firm's application for industrial policy incentives must be approved by multiple actors, including politicians, bureaucrats, and firms themselves (through self-selection). Who ultimately picks winners, whom they favor, and how favoritism interacts with incentive design remain open questions. Using confidential data on industrial subsidy applications and decisions in a large Indian state, we document several stylized facts. First, most variation in winning subsidies is conditional on final bureaucrat approval. While bureaucrats approve over 90% of applications, less than 30% of approved subsidies are paid, with an average delay of 3.5 years among winners. Second, winners are actively chosen at the payment stage: each subsidy release order covers either a single high-profile plant or an industrial cluster. Firm bargaining power (proxied by size and in-state headquarters) predicts earlier payments. Third, payments support struggling firms: in a shift-share design based on firms' pre-pandemic product mixes, those facing larger negative demand shocks in 2020 are more likely to receive payments in 2023 for investments made years earlier. Favoritism is more pronounced for subsidies on variable inputs (e.g., sales tax and electricity), which can be filed years after the eligible investment. These results underscore the challenge of insulating industrial policy from political influence, as constrained funds controlled by politicians lead to favoritism in a black box, years after investments.

We study the benefits of economic integration from reducing policy-induced barriers to trade. A landmark 2017 fiscal reform in India substantially reduced barriers to crossing internal state borders. Using the reform as a natural experiment and aggregate data on trade flows, we estimate gravity regressions and find that each additional border in a shipping route reduces trade by 15%. Calibrating a quantitative trade model to this elasticity, we find that reducing all such border frictions would increase GDP by 3%. To examine how supply chains may have reorganized, and the implications this has for gains from trade, we intend to exploit detailed micro-level data which we constructed from the universe of VAT records in India.

We examine the impact of trade liberalization on structural change patterns in India. Leveraging district-level variations in sectoral composition, we find that districts with greater tariff reductions experienced larger declines in manufacturing employment shares. By extending Matsuyama’s 1992 model of deindustrialization to include a non-tradable service sector, we demonstrate analytically and through simulations that India's observed deindustrialization and service-led growth can be qualitatively attributed to trade liberalization. We aim to structurally estimate the model parameters to quantify the role of trade liberalization in driving these structural changes.