Methods

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.

We provide simulation evidence on the small sample performance of our estimator, and we apply our method to a Chinese production dataset.

We consider nonparametric estimation of a regression function that is identified by requiring a specified quantile of the regression "error" conditional on an instrumental variable to be zero.

This paper studies the identification of partial differences of nonseparable structural functions.

This paper develops a class of first order equivalent semi-parametric efficient estimators and tests for conditional moment restrictions models based on a local or kernel-weighted version of the Cressie-Read power divergence family of discrepancies. This approach is similar in spirit to the empirical likelihood methods of Kitamura, Tripathi and Ahn (2004) and Tripathi and Kitamura (2003).

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels.

This paper provides a charaterization of the class of weights (or priors) that produce estimators that are first-order unbiased.

This paper presents new identification results for the class of structural dynamic optimal stopping time models that are built upon the framework of the structural discrete Markov decision processes proposed by Rust.

This paper studies models for discrete outcomes which permit explanatory variables to be endogenous.

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time varying heterogeneity. These include limited dependent variable models with both unobserved individual effects and endogenous explanatory variables, and sample selection models with unobserved individual effects.

In this paper I develop a new approach for identification and estimation of the parameters of an oligopoly model, without relying on a potentially unverifiable equilibrium assumption.