In this paper, we consider a cointegrated panel data model with non-stationary common factors, which, because of its appeal in many economic applications, has received much attention in the recent literature. By deriving a Granger-type representation theorem, we obtain several equivalent model...

In this note we extend the method proposed in Bun and Carree (2006) to the more general PVARX(1) model and show that the iterative procedure is not consistent for fixed T. Subsequently we provide corrected version of the bias correction procedure which is fixed T consistent and robust to both...

We examine finite sample properties of estimators for approximate factor models when N is small. Contrary to the “rule-of-thumb”, we find that the principal component analysis estimator and the quasi-maximum likelihood estimator perform well even when N is small.

In an influential paper, Pesaran [Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012] proposes a very simple estimator of factor-augmented regressions that has since then become very popular. In this note...

Ng (2008) shows how the cross-sectional variance of the observed panel data can be used to construct a simple test for the proportion of non-stationary units. However, in the case with incidental trends the test is distorted. The present note shows how the distortions can be substantially...

In a recent article Bai (2013a) proposes a new factor analytical method (FAM) for the estimation of fixed-effects dynamic panel data models, which has the unique and very useful property that it is asymptotically bias free. In this paper we provide Monte Carlo evidence of the good small-sample...

We develop a sieve bootstrap range test for poolability of cointegrating regressions in dependent panels and evaluate by simulation its performances. The test seems to have good size and power properties even with small cross-sections, moderate time samples, and low heterogeneity.

This paper proposes to include the spatial time lag in empirical applications using spatial panel data models, and also explains why the coefficient of that term can be negative. We provide simple theoretical frameworks to justify the relevance of the spatial time lag to empirical...

We complement existing inferential theory for panel factor models by deriving the asymptotics for the first differences of the estimated factors and common components obtained from a non-stationary panel factor model. As an application, we propose an estimator for the long run variance of the...

In the standard generalized method of moments estimation of dynamic panel data models, the constant term is usually omitted from instrument sets. As a result, adding a constant to the dependent variable affects the estimates for models without full period dummies. Omitting the constant term from...