Publications

This paper revisits the simple, but empirically salient, problem of inference on a real-valued parameter that… Continue reading.

We present a new class of methods for identification and inference in dynamic models with serially… Continue reading.

Conditional distribution functions are important statistical objects for the analysis of a wide class of problems… Continue reading.

We provide estimation methods for panel nonseparable models based on low-rank factor structure approximations. The factor… Continue reading.

Consider a bipartite network where N consumers choose to buy or not to buy M different… Continue reading.

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is… Continue reading.

Economists are often interested in estimating averages with respect to distributions of unobservables. Examples are moments… Continue reading.

This paper describes a method for carrying out inference on partially identified parameters that are solutions… Continue reading.

We propose a robust method of discrete choice analysis when agents’ choice sets are unobserved. Our… Continue reading.

We develop new tools for causal inference in settings where exogenous shocks affect the treatment status… Continue reading.

Multidimensional heterogeneity and endogeneity are important features of models with multiple treatments. We consider a heterogeneous… Continue reading.

This paper develops identification and estimation methods for dynamic structural models when agents’ actions are unobserved… Continue reading.

Many empirical questions concern target parameters selected through optimization. For example, researchers may be interested in… Continue reading.

We introduce a test for whether agents’ preferences over network structure are interdependent. Interdependent preferences induce… Continue reading.

We show that a standard linear triangular two equation system can be point identified, without the… Continue reading.

This paper analyzes Structural Vector Autoregressions (SVARs) where identification of structural parameters holds locally but not… Continue reading.

We propose a new simulation-based estimation method, adversarial estimation, for structural models. The estimator is formulated… Continue reading.

This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for… Continue reading.

We propose a framework for estimation and inference when the model may be misspecified. We rely… Continue reading.

We study the effects of counterfactual teacher-to-classroom assignments on average student achievement in elementary and middle… Continue reading.