Research methods

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

Researchers are often interested in the relationship between two variables, with no single data set containing both.

We propose a new simulation-based estimation method, adversarial estimation, for structural models.

We propose a framework for estimation and inference when the model may be misspecified.

This paper builds on Bonhomme (2012) to develop a method to systematically construct moment conditions for dynamic panel data logit models with fixed effects.

In an important class of econometric problems, researchers select a target parameter by maximizing the Euclidean norm of a data-dependent vector.

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice.

This paper is concerned with learning decision makers’ preferences using data on observed choices from a finite set of risky alternatives.

We consider both l0-penalized and l0-constrained quantile regression estimators.

This paper studies inference of preference parameters in semiparametric discrete choice models when these parameters are not point-identified and the identified set is characterized by a class of conditional moment inequalities.

We provide a new full-commitment intertemporal collective household model to estimate resource shares, defined as the fraction of household expenditure enjoyed by household members.

This paper provides a method to construct simultaneous confidence bands for quantile functions and quantile effects in nonlinear network and panel models with unobserved two-way effects, strictly exogenous covariates, and possibly discrete outcome variables.

This paper demonstrates the use of bounds analysis for empirical models of market structure that allow for multiple equilibria.

In this paper we discuss the value of international comparative empirical studies within the broad field of the economics of ageing. We argue the value is particularly great when such comparative research is based on long life-history data on participants, collected using large-scale autobiographical life-history methods.

This paper examines the identifying power of instrument exogeneity in the treatment effect model.

We develop an analytically tractable method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the U.S. during the first half of March 2020.

We provide a finite sample inference method for the structural parameters of a semiparametric binary response model under a conditional median restriction originally studied by Manski (1975, 1985).

We propose a new nonparametric test of stochastic monotonicity which adapts to the unknown smoothness of the conditional distribution of interest, possesses desirable asymptotic properties, is conceptually easy to implement, and computationally attractive.

Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data.

We investigate identification of causal parameters in case-control and related studies.