This paper studies how the risk of hold‐up affects procurement. I use data on the universe of solar power auctions in India. The Indian context allows clean estimates of counterparty risk, because solar plants set up in the same states, by the same firms, are procured in auctions intermediated by either risky states themselves or the trusted central government. I find that the counterparty risk of an average state increases solar prices by 10%. This risk premium sharply reduces investment, because demand for green energy is elastic. Contract intermediation by the central government eliminates the counterparty risk premium.

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.

High pollution persists in many developing countries despite strict environmental rules. We use a field experiment and a structural model to study how plant emission standards are enforced. In collaboration with an Indian environmental regulator, we experimentally doubled the rate of inspection for treatment plants and required that the extra inspections be assigned randomly. We find that treatment plants only slightly increased compliance. We hypothesize that this weak effect is due to poor targeting, since the random inspections in the treatment found fewer extreme violators than the regulator's own discretionary inspections. To unbundle the roles of extra inspections and the removal of discretion over what plants to target, we set out a model of environmental regulation where the regulator targets inspections, based on a signal of pollution, to maximize plant abatement. Using the experiment to identify key parameters of the model, we find that the regulator aggressively targets its discretionary inspections, to the degree that half of the plants receive fewer than one inspection per year, while plants expected to be the dirtiest may receive ten. Counterfactual simulations show that discretion in targeting helps enforcement: inspections that the regulator assigns cause three times more abatement than would the same number of randomly assigned inspections. Nonetheless, we find that the regulator's information on plant pollution is poor, and improvements in monitoring would reduce emissions.