Response times contain information about economically relevant but unobserved variables like willingness to pay, preference intensity, quality, or happiness. Here, we provide a general characterization of the properties of latent variables that can be detected using response time data. Our...

Structural quantitative work in international economics typically models trade costs as a log-linear function of exogenous trade-policy variables. We propose a structural approach that allows for a nonparametric relationship and for treating tariff and nontariff trade-policy variables as...

All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct...

This paper presents an empirical model of sponsored search auctions where advertisers are ranked by bid and ad quality. Our model is developed under the 'incomplete information' setting with a general quality scoring rule. We establish nonparametric identification of the advertiser's valuation...

High-dimensional covariates often admit linear factor structure. To effectively screen correlated covariates in high-dimension, we propose a conditional variable screening test based on non-parametric regression using neural networks due to their representation power. We ask the question whether...

In this paper, we study the asymptotic behavior of specification tests in conditional moment restriction models under first-order local identification failure with dependent data. More specifically, we obtain conditions under which the conventional specification test for conditional moment...