The standard LM tests for spatial dependence in linear and panel regressions are derived under the normality and homoskedasticity assumptions of the regression disturbances. Hence, they may not be robust against non-normality or heteroskedasticity of the disturbances. Following Born and Breitung (2011), we introduce general methods to modify the standard LM tests so that they become robust agai...

This paper provides a review of the literature on unit roots and cointegration in panels where the time dimension (T ), and the cross section dimension (N) are relatively large. It distinguishes between the …rst generation tests developed on the assumption of the cross section independence, and the second generation tests that allow, in a variety of forms and degrees, the dependence that might ...

Labour Market Outcomes of Immigrants in Germany: The Importance of Heterogeneity and Attrition Bias Heterogeneity in the ethnic composition of Germany's immigrant population renders general conclusions on the degree of economic integration difficult. Using a rich longitudinal data-set, this paper tests for differences in economic assimilation profiles of four groups of foreign-born immigrants a...

We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discretechoice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can be arbitrarily correlated with the observed product characteristics (including price), which accommod...

We consider a situation where a distribution is being estimated by the empirical distribution of noisy measurements. The measurements errors are allowed to be heteroskedastic and their variance may depend on the realization of the underlying random variable. We use an asymptotic embedding where the noise shrinks with the sample size to calculate the leading bias arising from the presence of noi...

A panel data regression model with heteroskedastic as well as spatially correlated disturbancesis considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are c...

This paper studies the estimation of quantile regression panel duration models. We allow for the possibility of endogenous covariates and correlated individual effects in the quantile regression models. We propose a quantile regression approach for panel duration models under conditionally independent censoring. The procedure involves minimizing l1 convex objective functions and is motivated by...

Long Term Earnings Inequality, Earnings Instability and Temporary Employment in Spain: 1993–2000 This paper provides a longitudinal perspective on changes in Spanish male earnings inequality for the period 1993-2000, by decomposing the earnings covariance structure into its permanent and transitory parts. According to the Spanish sample of the European Community Household Panel, cross-sectional...

This paper analyzes predictive regressions in a panel data setting. The standard …xed e¤ects estimator su¤ers from a small sample bias, which is the analogue of the Stambaugh bias in time-series predictive regressions. Monte Carlo evidence shows that the bias and resulting size distortions can be severe. A new bias-corrected estimator is proposed, which is shown to work well in …nite samples an...

We motivate and describe a GMM method of estimating linear dynamic models from a time series of independent cross-sections. This involves subjecting the model to a quasi-di!erencing transformation across pairs of individuals that belong to the same group. Desirable features of the model include the fact that: (i) no aggregation is involved, (ii) dynamic response parameters can vary across group...