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Main description:
This volume is dedicated to two recent intensive areas of research in the econometrics of panel data, namely nonstationary panels and dynamic panels. It includes a comprehensive survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration
tests. In addition, it provides recent developments in the estimation of dynamic panel data models using generalized method of moments.
The volume includes eleven chapters written by twenty authors. These chapters (i) investigate better methods of estimating dynamic panels; (ii) develop methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels;
(iii) extend the concept of serial correlation common features analysis to nonstationary panel data models; (iv) study the local power of panel unit root test statistics; (v) derive the asymptotic distributions of various estimators for the panel cointegrated regression model; (vi) propose a unit root test in the presence of structural change; (vii) develop a new limit theory for panel data that may be cross-sectionally heterogeneous; (viii) propose stationarity tests for a heterogeneous panel data model; (ix) derive instrumental variable estimators for a semiparametric partially linear dynamic panel data model; and (x) conduct Monte Carlo experiments to study the small sample properties of a growth convergence equation. This collection of papers should prove useful for practitioners and researchers working with panel data.
Review quote:
B.H. Baltagi
...The subject area that the volume deals with has many potential applications, and is currently evolving very fast. As a result, this collection of timely surveys and new results will be a very useful handbook to anyone interested in current developments in the econometrics of panel data.
Mathematical Reviews, 2002
Table of contents:
Nonstationary panels, cointegration in panels and dynamic panels: a survey (B.H. Baltagi, C. Kao). Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator (R. Blundell, S. Bond and F. Windmeijer). Fully modified OLS for the heterogeneous cointegrated panels (P. Pedroni). Testing for common cyclical features in nonstationary panel data models (A. Hecq, F.C. Palm and J-P. Urbain). The local power of some unit root tests for panel data (J. Breitung). On the estimation and inference of a cointegrated regression in panel data (C. Kao, M-H. Chiang). Testing for unit roots in panels in the presence of structural change with an application to OECD unemployment (C. Murray, D.H Papell). Panel data limit theory and asymptotic analysis of a panel regression with near integrated regressors (H. Kauppi). Stationary tests in heterogeneous panels (S. Wu, Y. Yin). Instrumental variable estimation of semiparametric dynamic panel data models: Monte Carlo results on several new and existing estimators (M. Douglas Berg, Q. Li and A. Ullah). Small sample performance of dynamic panel data estimators in estimating the growth-convergence equation: A Monte Carol study (N. Islam).
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
This volume is dedicated to two recent intensive areas of research in the econometrics of panel data, namely nonstationary panels and dynamic panels. It includes a comprehensive survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration
tests. In addition, it provides recent developments in the estimation of dynamic panel data models using generalized method of moments.
The volume includes eleven chapters written by twenty authors. These chapters (i) investigate better methods of estimating dynamic panels; (ii) develop methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels;
(iii) extend the concept of serial correlation common features analysis to nonstationary panel data models; (iv) study the local power of panel unit root test statistics; (v) derive the asymptotic distributions of various estimators for the panel cointegrated regression model; (vi) propose a unit root test in the presence of structural change; (vii) develop a new limit theory for panel data that may be cross-sectionally heterogeneous; (viii) propose stationarity tests for a heterogeneous panel data model; (ix) derive instrumental variable estimators for a semiparametric partially linear dynamic panel data model; and (x) conduct Monte Carlo experiments to study the small sample properties of a growth convergence equation. This collection of papers should prove useful for practitioners and researchers working with panel data.
Review quote:
B.H. Baltagi
...The subject area that the volume deals with has many potential applications, and is currently evolving very fast. As a result, this collection of timely surveys and new results will be a very useful handbook to anyone interested in current developments in the econometrics of panel data.
Mathematical Reviews, 2002
Table of contents:
Nonstationary panels, cointegration in panels and dynamic panels: a survey (B.H. Baltagi, C. Kao). Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator (R. Blundell, S. Bond and F. Windmeijer). Fully modified OLS for the heterogeneous cointegrated panels (P. Pedroni). Testing for common cyclical features in nonstationary panel data models (A. Hecq, F.C. Palm and J-P. Urbain). The local power of some unit root tests for panel data (J. Breitung). On the estimation and inference of a cointegrated regression in panel data (C. Kao, M-H. Chiang). Testing for unit roots in panels in the presence of structural change with an application to OECD unemployment (C. Murray, D.H Papell). Panel data limit theory and asymptotic analysis of a panel regression with near integrated regressors (H. Kauppi). Stationary tests in heterogeneous panels (S. Wu, Y. Yin). Instrumental variable estimation of semiparametric dynamic panel data models: Monte Carlo results on several new and existing estimators (M. Douglas Berg, Q. Li and A. Ullah). Small sample performance of dynamic panel data estimators in estimating the growth-convergence equation: A Monte Carol study (N. Islam).
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.