This paper reviews recent developments in nonparametric identi.cation of mea- surement error models and their applications in applied microeconomics, in particular, in empirical industrial organization and labor economics. Measurement error models describe mappings from a latent distribution to...

This paper proposes a new semi-parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is based on cyclic monotonicity, which is a defining convex-analytic feature of the random utility framework...

Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models when the choice utilities are nonseparable in observed attributes and multidimensional unobserved heterogeneity with...

Nonparametric efficiency analysis has become a widely applied technique to support industrial benchmarking as well as a variety of incentive- based regulation policies. In practice such exercises are often plagued by incomplete knowledge about the correct specifications of inputs and outputs....

Nonparametric efficiency analysis has become a widely applied technique to support industrial benchmarking as well as a variety of incentive- based regulation policies. In practice such exercises are often plagued by incomplete knowledge about the correct specifications of inputs and outputs....

In this paper, we consider a class of time-varying panel data models with individual-specific regression coefficients and common factors where both the serial correlation and cross-sectional dependence among error terms can be present. Based on an initial estimator of factors, we propose a...