Research

We examine international regulatory agreements that are negotiated under lobbying pressures from producer groups. The way in which lobbying influences the cooperative setting of regulatory policies, as well as the welfare impacts of international agreements, depend crucially on whether the interests of producers in different countries are aligned or in conflict. The former situation tends to occur for product standards, while the latter tends to occur for process standards. We find that, if producer lobbies are strong enough, agreements on product standards lead to excessive deregulation and decrease welfare, while agreements on process standards tighten regulations and enhance welfare.

Structural transformation in most currently developing countries takes the form of a rapid rise in services but limited industrialization. In this paper, we propose a new methodology to structurally estimate productivity growth in service industries that circumvents the notorious difficulties in measuring quality improvements. In our theory, the expansion of the service sector is both a consequence—due to income effects—and a cause—due to productivity growth—of the development process. We estimate the model using Indian household data. We find that productivity growth in nontradable consumer services such as retail, restaurants, or residential real estate was an important driver of structural transformation and rising living standards between 1987 and 2011. However, the welfare gains were heavily skewed toward high-income urban dwellers.

This paper studies the optimal determination of deposit insurance when bank runs are possible. We show that the welfare impact of changes in the level of deposit insurance coverage can be generally expressed in terms of a small number of sufficient statistics, which include the level of losses in specific scenarios and the probability of bank failure. We characterize the wedges that determine the optimal ex ante regulation, which map to asset- and liability-side regulation. We demonstrate how to employ our framework in an application to the most recent change in coverage in the United States, which took place in 2008.

This article studies the optimal design of corporate taxes when firms have private information about future investment opportunities and face financial constraints. A government whose goal is to efficiently raise a given amount of revenue from its corporate sector should attempt to tax unconstrained firms, which value resources inside the firm less than financially constrained firms. We show that a corporate payout tax (a tax on dividends and share repurchases) can both separate constrained and unconstrained firms and raise revenue and is therefore optimal. Our quantitative analysis implies that a revenue-neutral switch from profit taxation to payout taxation would increase the overall value of existing firms and new entrants by 7%⁠. This switch could be implemented in the current US tax system by making retained earnings fully deductible.

We present a new class of methods for identification and inference in dynamic models with serially correlated unobservables, which typically imply that state variables are econometrically endogenous. In the context of Industrial Organization, these state variables often reflect econometrically endogenous market structure. We propose the use of Generalized Instrument Variables methods to identify those dynamic policy functions that are consistent with instrumental variable (IV) restrictions. Extending popular “two-step” methods, these policy functions then identify a set of structural parameters that are consistent with the dynamic model, the IV restrictions and the data. We provide computed illustrations to both single-agent and oligopoly examples. We also present a simple empirical analysis that, among other things, supports the counterfactual study of an environmental policy entailing an increase in sunk costs.

This paper studies leverage regulation when equity investors and/or creditors have distorted beliefs relative to a planner. We characterize how the optimal regulation responds to arbitrary changes in investors'/creditors' beliefs, relating our results to practical scenarios. We show that the optimal regulation depends on the type and magnitude of such changes. Optimism by investors calls for looser leverage regulation, while optimism by creditors, or jointly by both investors/creditors, calls for tighter leverage regulation. Our results apply to environments with (i) planners with imperfect knowledge of investors'/creditors' beliefs, (ii) monetary policy, (iii) bailouts and pecuniary externalities, and (iv) endogenous beliefs.

This paper studies the welfare effects of encouraging rural–urban migration in the developing world. To do so, we build and analyze a dynamic general-equilibrium model of migration that features a rich set of migration motives. We estimate the model to replicate the results of a field experiment that subsidized seasonal migration in rural Bangladesh, leading to significant increases in migration and consumption. We show that the welfare gains from migration subsidies come from providing better insurance for vulnerable rural households rather than from correcting spatial misallocation by relaxing credit constraints for those with high productivity in urban areas that are stuck in rural areas.

We develop an axiomatic theory of information acquisition that captures the idea of constant marginal costs in information production: the cost of generating two independent signals is the sum of their costs, and generating a signal with probability half costs half its original cost. Together with Blackwell monotonicity and a continuity condition, these axioms determine the cost of a signal up to a vector of parameters. These parameters have a clear economic interpretation and determine the difficulty of distinguishing states.

We study dynamic matching in exchange markets with easy- and hard-to-match agents. A greedy policy, which attempts to match agents upon arrival, ignores the positive externality that waiting agents provide by facilitating future matchings. We prove that the trade-off between a “thicker” market and faster matching vanishes in large markets; the greedy policy leads to shorter waiting times and more agents matched than any other policy. We empirically confirm these findings in data from the National Kidney Registry. Greedy matching achieves as many transplants as commonly used policies (1.8% more than monthly batching) and shorter waiting times (16 days faster than monthly batching).