About this product

Product Identifiers

PublisherEmerald Publishing The Limited

ISBN-100762306882

ISBN-139780762306886

eBay Product ID (ePID)1847153

Product Key Features

Number of Pages350 Pages

Publication NameNonstationary Panels, Panel Cointegration, and Dynamic Panels

LanguageEnglish

SubjectEconometrics

Publication Year2001

TypeTextbook

Subject AreaBusiness & Economics

AuthorBadi Baltagi

SeriesAdvances in Econometrics Ser.

FormatHardcover

Dimensions

Item Height0.9 in

Item Weight9.6 Oz

Item Length9 in

Item Width6 in

Additional Product Features

Edition Number2

Intended AudienceScholarly & Professional

ReviewsB.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, ...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 B.H. Baltagi.

Series Volume Number15

Table Of ContentNonstationary 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).

SynopsisIncludes 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., 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: investigate better methods of estimating dynamic panels; develop methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels; extend the concept of serial correlation common features analysis to nonstationary panel data models; study the local power of panel unit root test statistics; derive the asymptotic distributions of various estimators for the panel cointegrated regression model; propose a unit root test in the presence of structural change; develop a new limit theory for panel data that may be cross-sectionally heterogeneous; propose stationarity tests for a heterogeneous panel data model; derive instrumental variable estimators for a semiparametric partially linear dynamic panel data model; and 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.