Research

Weak contract enforcement may reduce the efficiency of production in developing countries. I study how contract enforcement affects efficiency in procurement auctions for the largest power projects in India. I gather data on bidding and ex post contract renegotiation and find that the renegotiation of contracts in response to cost shocks is widespread, despite that bidders are allowed to index their bids to future costs like the price of coal. To study heterogeneity in bidding strategies, I construct a new measure of firm connectedness, based on whether a firm has been awarded coal concessions by the Government. Connected firms choose to index less of the value of their bids to coal prices and, through this strategy, expose themselves to cost shocks to induce renegotiation. I use a structural model of bidding in a scoring auction to characterize equilibrium bidding when bidders are heterogeneous both in cost and in the payments they expect after renegotiation. The model estimates show that bidders offer power below cost due to the expected value of later renegotiation. The model is used to simulate bidding and efficiency with strict contract enforcement. Contract enforcement is found to be pro‐competitive. With no renegotiation, equilibrium bids would rise to cover cost, but markups relative to total contract value fall sharply. Production costs decline, due to projects being allocated to lower‐cost bidders over those who expect larger payments in renegotiation.

This paper examines the prices of basic staples in rural Mexico. We document that nonlinear pricing in the form of quantity discounts is common, that quantity discounts are sizable for basic staples, and that the well-known conditional cash transfer program Progresa has significantly increased quantity discounts, although the program, as documented in previous studies, has not affected unit prices on average. To account for these patterns, we propose a model of price discrimination that nests those of Maskin and Riley (1984) and Jullien (2000), in which consumers differ in their tastes and, because of subsistence constraints, in their ability to pay for a good. We show that under mild conditions, a model in which consumers face heterogeneous subsistence or budget constraints is equivalent to one in which consumers have access to heterogeneous outside options. We rely on known results to characterize the equilibrium price schedule, which is nonlinear in quantity.

We study the theoretical properties and counterfactual predictions of a large class of general equilibrium trade and economic geography models. By combining aggregate factor supply and demand functions with market-clearing conditions, we prove that existence, uniqueness, and—given observed trade flows—the counterfactual predictions of any model within this class depend only on the demand and supply elasticities (“gravity constants”). Using a new “model-implied” instrumental variables approach, we estimate these gravity constants and use these estimates to compute the impact of a trade war between the United States and China.

After decades of supporting free trade, in 2018 the United States raised import tariffs and major trade partners retaliated. We analyze the short-run impact of this return to protectionism on the U.S. economy. Import and retaliatory tariffs caused large declines in imports and exports. Prices of imports targeted by tariffs did not fall, implying complete pass-through of tariffs to duty-inclusive prices. The resulting losses to U.S. consumers and firms that buy imports was $51 billion, or 0.27% of GDP. We embed the estimated trade elasticities in a general-equilibrium model of the U.S. economy. After accounting for tariff revenue and gains to domestic producers, the aggregate real income loss was $7.2 billion, or 0.04% of GDP. Import tariffs favored sectors concentrated in politically competitive counties, and the model implies that tradeable-sector workers in heavily Republican counties were the most negatively affected due to the retaliatory tariffs. JEL Code: F1.

We consider a game between a principal, an agent, and a monitor in which the principal would like to rely on messages by the monitor (the potential whistleblower) to target intervention against a misbehaving agent. The difficulty is that the agent can credibly threaten to retaliate against the monitor in the event of an intervention. In this setting, intervention policies that are responsive to the monitor’s message provide informative signals to the agent, which can be used to target threats efficiently. Principals that are too responsive to information shut down communication channels. Successful intervention policies must therefore garble the information provided by monitors and cannot be fully responsive. We show that policy evaluation on the basis of non-verifiable whistleblower messages is feasible under arbitrary incomplete information provided policy design takes into account that messages are endogenous.

This article sets recent expressions of alarm about the monopoly power of technology giants such as Google and Amazon in the long history of Americans' response to big business. I argue that we cannot understand that history unless we realize that Americans have always been concerned about the political and economic dangers of bigness, not just the threat of high prices. The problem policymakers faced after the rise of Standard Oil was how to protect society against those dangers without punishing firms that grew large because they were innovative. The antitrust regime put in place in the early twentieth century managed this balancing act by focusing on large firms' conduct toward competitors and banning practices that were anticompetitive or exclusionary. Maintaining this balance was difficult, however, and it gave way over time—first to a preoccupation with market power during the post–World War II period, and then to a fixation on consumer welfare in the late twentieth century. Refocusing policy on large firms' conduct would do much to address current fears about bigness without penalizing firms whose market power comes from innovation.

We develop a dynamic trade model with spatially distinct labor markets facing varying exposure to international trade. The model captures the role of labor mobility frictions, goods mobility frictions, geographic factors, and input-output linkages in determining equilibrium allocations. We show how to solve the equilibrium of the model and take the model to the data without assuming that the economy is at a steady state and without estimating productivities, migration frictions, or trade costs, which can be difficult to identify. We calibrate the model to 22 sectors, 38 countries, and 50 U.S. states. We study how the rise in China’s trade for the period 2000 to 2007 impacted U.S. households across more than a thousand U.S. labor markets distinguished by sector and state. We find that the China trade shock resulted in a reduction of about 0.55 million U.S. manufacturing jobs, about 16% of the observed decline in manufacturing employment from 2000 to 2007. The U.S. gains in the aggregate, but due to trade and migration frictions, the welfare and employment effects vary across U.S. labor markets. Estimated transition costs to the new long-run equilibrium are also heterogeneous and reflect the importance of accounting for labor dynamics.

Large and regular seasonal price fluctuations in local grain markets appear to offer African farmers substantial intertemporal arbitrage opportunities, but these opportunities remain largely unexploited. Small-scale farmers are commonly observed to “sell low and buy high,” rather than the reverse. In a field experiment in Kenya, we show that credit market imperfections limit farmers’ abilities to move grain intertemporally. Providing timely access to credit allows farmers to buy at lower prices and sell at higher prices, increasing farm revenues and generating a return on investment of 29%. To understand general equilibrium (GE) effects of these changes in behavior, we vary the density of loan offers across locations. We document significant effects of the credit intervention on seasonal price fluctuations in local grain markets, and show that these GE effects shape individual-level profitability estimates. In contrast to existing experimental work, the results indicate a setting in which microcredit can improve firm profitability, and suggest that GE effects can substantially shape microcredit’s effectiveness. In particular, failure to consider these GE effects could lead to underestimates of the social welfare benefits of microcredit interventions.