Showing 1 - 10 of 24
In this paper, we show that the bias-corrected first-difference (BCFD) estimator suggested by Chowdhury (1987) can be applied to the case where the error terms are cross-sectionally dependent and heteroscedastic. By deriving the finite sample bias of the BCFD estimator, we find that the BCFD...
Persistent link: https://www.econbiz.de/10005783963
In this paper, we investigate the effect of mean-nonstationarity on the first-difference generalized method of moments (FD-GMM) estimator in dynamic panel data models. We find that when data is mean-nonstationary and the variance of individual effects is significantly larger than that of...
Persistent link: https://www.econbiz.de/10008493194
In this article, we examine the usefulness of the bias-corrected first-difference (BCFD) estimator by Chowdhury (1987) from two angles: inference and testing. First, we compare the BCFD estimator with Bun and Carree's (2005) estimator and the GMM estimator in terms of accuracy of inference....
Persistent link: https://www.econbiz.de/10005265418
In this paper, we show that the order of magnitude of the finite sample bias of the estimator of Bun and Kiviet (2006) reduces from O(T/N) to O(1/N) if the original level model is transformed by the upper triangular Cholesky factorization of the inverse of the pseudo variance matrix of error...
Persistent link: https://www.econbiz.de/10008866533
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10010552471
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10010552631
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10010554827
In this paper, we consider the role of "leads" of the first difference of integrated variables in the dynamic OLS estimation of cointegrating regression models. We demonstrate that the role of leads is related to the concept of Granger causality and that in some cases leads are unnecessary in...
Persistent link: https://www.econbiz.de/10005675469
This paper complements Alvarez and Arellano (2003) by showing the asymptotic properties of the system GMM estimator for AR(1) panel data models when both N and T tend to infinity. We show that the system GMM estimator with the instruments which Blundell and Bond (1998) used will be inconsistent...
Persistent link: https://www.econbiz.de/10005675493
This paper addresses the many instruments problem, i.e. (1) the trade-off between the bias and the efficiency of the GMM estimator, and (2) inaccuracy of inference, in dynamic panel data models where unobservable heterogeneity may be large. We find that if we use all the instruments in levels,...
Persistent link: https://www.econbiz.de/10005675514