Measurement

We provide estimation methods for panel nonseparable models based on low-rank factor structure approximations. The factor structures are estimated by matrix-completion methods to deal with the computational challenges of principal component analysis in the presence of missing data.

Many empirical questions concern target parameters selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the best-performing investment strategy based on historical data.

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

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.

Manufacturers frequently pay fees to supermarkets when they temporarily reduce prices of their products.

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.

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

We investigate whether growing up in a socialist country affects the development of competitiveness by comparing three Korean groups in South Korea, born and raised in three countries with distinct institutional environments: South Korea, North Korea, and China.

We investigate state-dependent effects of fiscal multipliers and allow for endogenous sample splitting to determine whether the US economy is in a slack state.

In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model.

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.

Using new data from the Understanding Society: COVID 19 survey collected in April 2020, we show how the aggregate shock caused by the pandemic affects individuals across the distribution.

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

This paper uses linked survey responses and administrative hospital records to examine the accuracy of self-reported medical diagnoses.

This paper evaluates the dynamic impact of various policies, such as school, business, and restaurant closures, adopted by the US states on the growth rates of confirmed Covid-19 cases and social distancing behavior measured by Google Mobility Reports, where we take into consideration of people’s voluntarily behavioral response to new information of transmission risks.

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