The estimation of production functions suffers from an unresolved identification problem caused by flexible inputs, such as intermediate inputs. We develop an identification strategy for production functions based on a transformation of the firm's short-run first order condition that solves the...

In this paper, we explore the role of model uncertainty in explaining the different findings in the literature regarding the effect of shall-issue right-to-carry concealed weapons laws on crime. In particular, we systematically examine how different modeling assumptions affect the results. We...

I use economic theory and estimates of a semiparametrically identified structural model to analyze the role played by credit constraints, uncertainty and preferences in explaining college attendance. A methodology for inferring information available to the agent from individual choices is...

Increasingly, grade retention is viewed as an important alternative to social promotion, yet evidence to date is unable to disentangle how the effect of grade retention varies by abilities and over time. The key challenge is differential selection of students into retention across grades and by...

We study the determinants of youth crime using a dynamic discrete choice model of crime and education. We allow past education and criminal activities to affect current crime and educational decisions. We take advantage of a rich panel dataset on serious juvenile offenders, the Pathways to...

We propose semiparametric tests of misspecification of agent's information for games of incomplete information. The tests use the intuition that the opponent's choices should not predict a player's choice conditional on the proposed information available to the player. The tests are designed to...

We study the nonparametric identification of gross output production functions under the environment of the commonly employed proxy variable methods. We show that applying these methods to gross output requires additional sources of variation in the demand for flexible inputs (e.g., prices)....

This paper develops and applies a method for decomposing cross section variability of earnings into components that are forecastable at the time students decide to go to college (heterogeneity) and components that are unforecastable. About 60% of variability in returns to schooling is...

This paper considers semiparametric identification of structural dynamic discrete choice models and models for dynamic treatment effects. Time to treatment and counterfactual outcomes associated with treatment times are jointly analyzed. We examine the implicit assumptions of the dynamic...

This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with...