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   https://doi.org/10.1257/pandp.20241100  

   Comin, Diego; Johnson, Robert C; Jones, Callum (May 2024, AEA Papers and Proceedings)

   Johnson, William R (Ed.)

   During the recovery from the COVID-19 pandemic, international shipping and logistics capacity was strained, limiting the quantity of imports. We investigate the impact of an import constraint on inflation, following an increase in domestic demand. Whether the binding import constraint raises inflation depends on how it affects trade intermediation costs. If the binding constraint raises trade costs, then import price inflation also increases. In this case, however, foreign producer price inflation falls and import quantities rise more for inputs than final goods. Both these model results appear counterfactual, which suggests that import constraints may not explain observed import price inflation. 

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2. Inference Under Information Constraints II: Communication Constraints and Shared Randomness

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3. Locally Balanced Constraints

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4. Planning with Participation Constraints

   https://doi.org/10.1609/aaai.v36i5.20462  

   Zhang, Hanrui; Cheng, Yu; Conitzer, Vincent (June 2022, Proceedings of the 36th AAAI Conference on Artificial Intelligence)

   We pose and study the problem of planning in Markov decision processes (MDPs), subject to participation constraints as studied in mechanism design. In this problem, a planner must work with a self-interested agent on a given MDP. Each action in the MDP provides an immediate reward to the planner and a (possibly different) reward to the agent. The agent has no control in choosing the actions, but has the option to end the entire process at any time. The goal of the planner is to find a policy that maximizes her cumulative reward, taking into consideration the agent's ability to terminate. We give a fully polynomial-time approximation scheme for this problem. En route, we present polynomial-time algorithms for computing (exact) optimal policies for important special cases of this problem, including when the time horizon is constant, or when the MDP exhibits a "definitive decisions" property. We illustrate our algorithms with two different game-theoretic applications: the problem of assigning rides in ride-sharing and the problem of designing screening policies. Our results imply efficient algorithms for computing (approximately) optimal policies in both applications. 

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5. Ranking with Slot Constraints

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   Guo, Wentao; Wang, Andrew; Thymes, Bradon; Joachims, Thorsten (August 2024, ACM Conference on Knowledge Discovery and Data Mining (KDD))