Working Papers

In many areas, practitioners seek to use observational data to learn a treatment assignment policy that satisfies application-specific constraints, such as budget, fairness, simplicity, or other functional form constraints. For example, policies…

For an incompatible patient-donor pair, kidney exchanges often forbid receipt-before-donation (the patient receives a kidney before the donor donates) and donation-before-receipt, causing a double-coincidence-of-wants problem. Our proposed…

In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation (‘cytokine storm syndrome’), which can lead to acute respiratory distress syndrome, multi-organ failure,…

We introduce a new class of methods for finite-sample false discovery rate (FDR) control in multiple testing problems with dependent test statistics where the dependence is fully or partially known. Our approach separately calibrates a data-…

There has been an increase in interest in experimental evaluations to estimate causal effects, partly because their internal validity tends to be high. At the same time, as part of the big data revolution, large, detailed, and representative,…

We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including…

How costly is foreclosure? Estimates of the social cost of foreclosure typically focus on financial costs. Using random judge assignment instrumental variable (IV) and propensity score matching (PSM) approaches in Cook County, Illinois, we find…

Modern applications in statistics, computer science and network science have seen tremendous values of finer matrix spectral perturbation theory. In this paper, we derive a generic ℓ2→∞ eigenspace perturbation bound for symmetric random matrices…

We study how opening to trade affects economic growth in a model where heterogeneous firms can adopt new technologies already in use by other firms in their home country. We characterize the growth rate using a summary statistic of the…

We consider a variant of the contextual bandit problem. In standard contextual bandits, when a user arrives we get the user’s complete feature vector and then assign a treatment (arm) to that user. In a number of applications (like health…

We model a simple market setting in which fragmentation of trade of the same asset across multiple exchanges improves allocative efficiency. Fragmentation reduces the inhibiting effect of price-impact avoidance on order submission. Although…

Adaptivity is an important yet under-studied property in modern optimization theory. The gap between the state-of-the-art theory and the current practice is striking in that algorithms with desirable theoretical guarantees typically involve…

Adaptive experiment designs can dramatically improve statistical efficiency in randomized trials, but they also complicate statistical inference. For example, it is now well known that the sample mean is biased in adaptive trials. Inferential…

In many models, economic growth is driven by people discovering new ideas. These models typically assume either a constant or a growing population. However, in high income countries today, fertility is already below its replacement rate: women…

The allocation of decision authority by a principal to either a human agent or an artificial intelligence (AI) is examined. The principal trades off an AI’s more aligned choice with the need to motivate the human agent to expend effort in…

We develop an equilibrium theory of business cycles driven by spikes in risk premiums that depress business demand for capital and labor. Aggregate shocks increase firms’ uninsurable idiosyncratic risk and raise risk premiums. We show that risk…

For many machine learning algorithms, two main assumptions are required to guarantee performance. One is that the test data are drawn from the same distribution as the training data, and the other is that the model is correctly specified. In real…

This paper provides a positive identification result for first-price procurement models with asymmetric bidders, statistically dependent private signals,
and interdependent costs. When bidders are risk neutral, the model’s payoff-relevant…

A transplant can improve a patient’s life while saving several hundreds of thousands of dollars in healthcare expenditures. Organs from deceased donors, like many other scarce public resources (e.g. public housing, child-care, publicly funded…

We develop a valuation model for venture capital-backed companies and apply it to 135 US unicorns, that is, private companies with reported valuations above $1 billion. We value unicorns using financial terms from legal filings and find that…