We study a strict version of the notion of equilibrium robustness by Kajii and Morris (1997) that allows for a larger class of incomplete information perturbations of a given complete information game, where with high probability, players believe that their payoffs are close to (but may be...

For more than a century, election officials across the United States have inspected voting machines before elections using a procedure called Logic and Accuracy Testing (LAT). This procedure consists of election officials casting a test deck of ballots into each voting machine and confirming the...

The robust multi-product pricing problem is to determine the prices of a collection of products so as to maximize the worst-case revenue, where the worst case is taken over an uncertainty set of demand models that the firm expects could be realized in practice. A tacit assumption in this...

In this study, the problem of scheduling a set of jobs and one uncertain maintenance activity on a single machine, with the objective of minimizing the makespan is addressed. The maintenance activity has a given duration and must be executed within a given time window. Furthermore, duration and...

This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996)). In our setting, economic agents...

Robustness checks, such as adding controls or sample splits, are a standard feature of reduced-form empirical research. Because of computational costs of reestimating alternative models, they are much less common in structural re- search using simulation-based methods. We propose a simple...

We study the order acceptance and resource planning problem which has applications in many industries such as healthcare, logistics, and manufacturing. We extend the recent literature by considering two new features: the number of resources is a decision and processing times are uncertain....

A seller wants to sell an indivisible item to n buyers. The buyer valuations are drawn i.i.d. from a distribution, but the seller does not know this distribution; the seller only knows the support [a,b]. To be robust against the lack of knowledge of the environment and buyers' behavior, the...

Optimization problems in operations and finance often include a cost that is proportional to the expected amount by which a random variable exceeds some fixed quantity, known as the expected loss function. Representation of this function often leads to computational challenges, depending on the...