We develop a framework to characterize strategic behavior in sequential markets under imperfect competition and restricted entry in arbitrage. Our theory predicts that these two elements can generate a systematic price premium. We test the model predictions using microdata from the Iberian electricity market. We show that the observed price differences and firm behavior are consistent with the model. Finally, we quantify the welfare effects of arbitrage using a structural model. In the presence of market power, we show that full arbitrage is not necessarily welfare-enhancing, reducing consumer costs but increasing deadweight loss.

We develop an optimal policy assignment rule that integrates two distinctive approaches commonly used in economics—targeting by observables and targeting through self‐selection . Our method can be used with experimental or quasi‐experimental data to identify who should be treated, be untreated, and self‐select to achieve a policymaker's objective. Applying this method to a randomized controlled trial on a residential energy rebate program, we find that targeting that optimally exploits both observable data and self‐selection outperforms conventional targeting. We use the Local Average Treatment Effect (LATE) framework (Imbens and Angrist (1994)) to investigate the mechanism in our approach. By estimating several key LATEs based on the random variation created by our experiment, we demonstrate how our method allows policymakers to identify whose self‐selection would be valuable and harmful to social welfare.

International transboundary air pollution poses a significant threat to the global economy and health, yet conventional economic analyses seldom incorporate this phenomenon. By integrating transboundary particle trajectory data with individual-level mortality and emergency department visit records, we find that air pollution from China significantly increases mortality and morbidity in South Korea. We evaluate the spillover benefits of recent Chinese environmental regulations and find that a country's environmental policies could generate substantial hidden benefits for neighboring countries. Finally, we demonstrate that China's potentially strategic reductions in pollution could have undermined these benefits, highlighting the implications for additional gains through Coasian bargaining.

We study a problem in which policymakers need to screen self-selected individuals by unobserved heterogeneity in social welfare gains from a policy intervention. In our framework, the marginal treatment effects and marginal treatment responses arise as key statistics to characterize social welfare. We apply this framework to a randomized field experiment on electricity plan choice. Consumers were offered welfare-improving dynamic pricing with randomly assigned take-up incentives. We find that price-elastic consumers—who generate larger welfare gains—are more likely to self-select. Our counterfactual simulations quantify the optimal take-up incentives that exploit observed and unobserved heterogeneity in selection and welfare gains.