Random Coefficient Panel Data Models This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficients models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using both the sampling and Bayesian approaches. The paper also provid...

This paper develops a method for testing for the presence of a single structural break in dynamic panel data models with a multi-factor error structure. The test statistic is developed by combining a modified version of the GMM approach of Robertson and Sarafidis (2015) with the testing procedure of De Wachter and Tzavalis (2012). We focus on the case where N is large and T fixed. The asymptoti...

This paper examines the asymptotics of the QMLE for unit root spatial dynamic panel data models with …xed e¤ects. When the exogenous variables or …xed e¤ects are included in the DGP, the estimate for the dynamic coe¢ cient is p nT 3 consistent and the estimates of other parameters are p nT consistent, and all of them are asymptotically normal. Also, sum of the contemporaneous spatial e¤ect and ...

We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap met...

This paper establishes the almost sure convergence and asymptotic normality of levels and differenced quasi maximum-likelihood (QML) estimators of dynamic panel data models. The QML estimators are robust with respect to initial conditions, conditional and time-series heteroskedasticity, and misspecification of the log-likelihood. The paper also provides an ECME algorithm for calculating levels ...

The system GMM estimator developed by Blundell and Bond (1998) for dynamic panel data models has been widely used in empirical work; however, it does not perform well with weak instruments. This paper proposes a variation on the system GMM estimator, based on a simple transformation of the dependent variable. Simulation results indicate that, in finite samples, this transformed system GMM estim...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the random coefficients and (ii...

An examination of the statistical accuracy and economic value of modeling and forecasting the term structure of interest rates using forecast combinations is considered. Five alternative methods to combine point forecasts from several univariate and multivariate autoregressive specifications including dynamic factor models, equilibrium term structure models, and forward rate regression models a...