Description

Book Synopsis
Includes a survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration tests. This book also provides developments in the estimation of dynamic panel data models using generalized method of moments. It is useful for practitioners and researchers working with panel data.

Trade Review
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).

Nonstationary Panels Panel Cointegration and

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    A Hardback by Badi H. Baltagi

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      Publisher: Emerald Publishing Limited
      Publication Date: Publication Date: 13/02/2001
      ISBN13: 9780762306886, 978-0762306886
      ISBN10: 0762306882

      Description

      Book Synopsis
      Includes a survey of the nonstationary panel literature including panel unit root tests, spurious panel regressions and panel cointegration tests. This book also provides developments in the estimation of dynamic panel data models using generalized method of moments. It is useful for practitioners and researchers working with panel data.

      Trade Review
      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).

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