We consider the problem of detecting unobserved heterogeneity, that is, the problem of testing the absence of random individual effects in an n×T panel. We establish a local asymptotic normality property–with respect to intercept, regression coefficient, the scale parameter σ of the error,...

In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis...

We show that the quantile regression estimator is consistent and asymptotically normal when the error terms are correlated within clusters but independent across clusters. A consistent estimator of the covariance matrix of the asymptotic distribution is provided and we propose a speci?cation...

This paper proposes a nonparametric test for common trends in semiparametric panel data models with fixed effects based on a measure of nonparametric goodness-of-fit (R^2). We first estimate the model under the null hypothesis of common trends by the method of profile least squares, and obtain...

We propose a consistent test for a linear functional form against a nonparametric alternative in a fixed effects panel data model. We show that the test has a limiting standard normal distribution under the null hypothesis, and show that the test is a consistent test. We also establish the...

We derive tests for heteroskedasticity after fixed effects estimation of linear panel models. The asymptotic results are based on a ‘large N–fixed T’ framework, where the incidental parameters problem is bypassed by utilizing a (pseudo) likelihood function conditional on the sufficient...

This paper proposes two Hausman-type tests respectively for individual and time effects in a two-way error component regression model by comparing estimators of the variance of the idiosyncratic error at different robust levels. They are both robust to the presence of the other effect, and the...

A dynamic panel data model is considered that contains possibly stochastic individual components and a common fractional stochastic time trend. We propose four different ways of coping with the individual effects so as to estimate the fractional parameter. Like models with autoregressive...

A dynamic panel data model is considered that contains possibly stochastic individual components and a common stochastic time trend that allows for stationary and nonstationary long memory and general parametric short memory. We propose four different ways of coping with the individual effects...

The different robust estimators for the standard errors of panel models used in applied econometric practice can all be written and computed as combinations of the same simple building blocks. A framework based on high-level wrapper functions for most common usage and basic computational...