This paper reviews the recent developments in nonparametric identification of measurement 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 an observed distribution. The identification and estimation of measurement error models focus on h...

This paper considers a random coefficients panel data model with individualspecific intercepts (or fixed effects). The identification of the distribution of random slope coefficients is established in two settings: when random slope coefficients are conditionally independent from individual-specific intercepts; and when individual-specific intercepts are allowed to depend on random slope coeffi...

An estimation framework and a user-friendly software implementation are described for maximum likelihood estimation of panel data models with random effects, a spatially lagged dependent variable and spatially and serially correlated errors. This specification extends static panel data models in the direction of serial error correlation, allowing richer modelling possibilities and more thorough...

This paper considers the problem of estimating a partially linear semipara-metric fixed effects panel data model with possible endogeneity. Using the series method, we establish the root N normality result for the estimator of the parametric component, and we show that the unknown function can be consistently estimated at the standard nonparametric rate. c 2002 Peking University Press

Estimating and Testing a Quantile Regression Model with Interactive Effects This paper proposes a quantile regression estimator for a panel data model with interactive effects potentially correlated with the independent variables. We provide conditions under which the slope parameter estimator is asymptotically Gaussian. Monte Carlo studies are carried out to investigate the finite sample perfo...

We study how a provider’s technical support influences service demand in a business-tobusiness setting. The provider offers two levels of support, basic and full, reflecting its involvement with the buyer in co-producing the service. Using a unique nano-data set on public cloud infrastructure services consumption by 20,298 firms from March 2009 to April 2012, fixed effects panel data models, an...

ECON 342 J. Marcelo Ochoa Spring, 2009 Problem 1. For T = 2 consider the standard panel data model: yit = xitβ + αi + ǫit a) Numerically compare the fixed effect and first difference estimates. b) Compare the error variance estimates from the two methods. Solution. The difference estimates are obtained by taking the difference across time periods to eliminate the unobservable. Hence, for indivi...

This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynamic random effects probit model and other dynamic nonlinear panel data models using standard software. It then compares the estimators proposed by Heckman, Orme and Wooldridge, based on three alternative approximations, first in an empirical model for the probability of unemployment and then in a ...

The presence of outlying observations in panel data can affect the classical estimates in a dramatic way. Nevertheless the common practice seems to disregard the problem. The aim of this work is to study robust regression techniques in the fixed effects linear panel data framework. Robustness of the procedures is investigated by means of breakdown point computations and simulation experiments. ...

We propose outlier-robust estimators for linear dynamic fixed effects panel data models where the number of observations,N , is large and the number of time periods, T , is small. In the simple setting of estimating the AR(1) coefficient from stationary Gaussian panel data, the estimator is (a linear transformation of) the median ratio of adjacent first-differenced data pairs. Its influence fun...