Abstract: We study the effects of intensifying competition for contracts in the context of U.S. Defense procurement. Conceptually, opening contracts up to bids by more participants leads to lower awarding prices, but may hinder buyers' control over non-contractible characteristics of prospective contractors. Leveraging a regulation that mandates agencies to publicize certain contract opportunities, we document that expanding the set of bidders reduces award prices, but deteriorates post-award performance, resulting in more cost overruns and delays. To further study the scope of this tension, we develop and estimate a model in which the buyer endogenously chooses the intensity of competition, invited sellers decide on auction participation and bidding, and the winner executes the contract ex-post. Model estimates indicate substantial heterogeneity in ex-post performance across contractors, and show that simple adjustments to the current regulation that account for adverse selection could provide 2 percent of savings in procurement spending, or $104 million annually.

Abstract: Attempts to curb undesired behavior through regulation get complicated when agents can adapt to circumvent enforcement. We test a model of enforcement with learning and adaptation, by auditing vendors selling illegal fish in Chile in a randomized controlled trial, and tracking them daily using mystery shoppers. Conducting audits on a predictable schedule and (counter-intuitively) at high frequency is less effective as agents learn to take advantage of loopholes. We observe the specific defensive actions vendors adopt to circumvent fines, and their pattern of adoption over time is consistent with the model of learning. A consumer information campaign proves to be almost as cost-effective at curbing illegal sales, and obviates the need for complex monitoring and policing. The Chilean government subsequently chose to scale up the information campaign.  

Media: Yale Insights, VoxDev, J-PAL [Summary], [Blog], [Case Study]

Abstract: This paper examines the determinants of public procurement prices using comprehensive data on pharmaceutical purchases by the Chilean public sector. We start by estimating the extent to which different public agencies pay different prices for the same product. These buyer effects are sizable, and the difference between average prices paid by buyers at the 10th and 90th percentiles is 16%. Our main set of results is related to the role of market structure. The variation in market structure explains three times more variation in procurement prices than buyer effects. Moreover, using exogenous variation from patent expirations, we estimate that the entry of an additional vendor decreases average procurement prices by 11.7%, which is 72% of the gap between average prices paid by buyers at the 10th and 90th percentiles of the distribution of buyer effects. These results suggest that supply-side factors are key determinants of public procurement prices and that their quantitative importance may exceed that of demand-side factors previously emphasized in the literature. 

Abstract: Product complementarities can shape market patterns, influencing the demand for related products and their accessories. This study examines complementarities in the demand for rooftop solar and an accessory, battery energy storage. Using nationwide administrative data, we estimate a dynamic nested-logit model of solar and storage adoption. We quantify the demand complementarity between solar and storage, and find that if storage was not available, 20% of households who coadopt solar and storage would not adopt anything. We find that the demand for solar and storage bundles increases with power outages, with a larger effect in California.

Abstract: This paper studies regression discontinuity (RD) designs in settings where the assignment variable is mismeasured. In addition to the standard sources of classical measurement error, we allow the assignment variable to be affected by the treatment. We first establish how to recover the RD parameters of interest in this case, given the distributions of measurement error and treatment effects. We then show that these objects can be nonparametrically recovered from the densities of the mismeasured running variable conditional on treatment status. In the absence of mismeasurement, the conditional densities of the running variable for treatment and control units should each be sharply discontinuous at the threshold. The difference between these sharp benchmarks and the observed densities reveals the extent of mismeasurement, and can be used to adjust the RD estimates. Imposing further assumptions, identification is possible even in the presence of “manipulation” of the running variable. We develop a method to estimate treatment effects in this context based on our results. We discuss examples of settings that fit within our framework, and illustrate our method with a particular empirical application on the effect of a policy to increase competition for public procurement contracts.