Panel Data

Theory and Applications
Herausgegeben:Baltagi, Badi H.

• Broschiertes Buch

Produktbeschreibung

The present book is a collection of panel data papers, both theoretical and applied. Theoretical topics include methodology papers on panel data probit models, treatment models, error component models with an ARMA process on the time specific effects, asymptotic tests for poolability and their bootstrapped versions, confidence intervals for a doubly heteroskedastic stochastic production frontiers, estimation of semiparametric dynamic panel data models and a review of survey attrition and nonresponse in the European Community Household Panel. Applications include as different topics as e.g. the impact of uncertainty on UK investment, a Tobin-q investment model using US firm data, cost efficiency of Spanish banks, immigrant integration in Canada, the dynamics of individual health in the UK, the relation between inflation and growth among OECD and APEC countries, technical efficiency of cereal farms in England, and employment effects of education for disabled workers in Norway.

Produktdetails

• Studies in Empirical Economics
• Verlag: Physica / Physica-Verlag / Physica-Verlag HD
• Artikelnr. des Verlages: 978-3-7908-2455-1
• Softcover reprint of hardcover 1st ed. 2004
• Seitenzahl: 392
• Erscheinungstermin: 19. Oktober 2010
• Englisch
• Abmessung: 235mm x 155mm x 22mm
• Gewicht: 593g
• ISBN-13: 9783790824551
• ISBN-10: 3790824550
• Artikelnr.: 32211159

Autorenporträt

Badi H. Baltagi is distinguished Professor of Economics, and Senior Research Associate at the Center for Policy Research, Syracuse University. He received his Ph.D. in Economics at the University of Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory.

Inhaltsangabe

From the Contents: Analyzing the effect of dynamically assigned treatments using duration models, binary treatment models, and panel data models.- Convenient estimators for the panel probit model.- Simulation-based inference in dynamic panel probit models.- Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects.- Testing poolability in a system of dynamic regressions with nonspherical disturbances.- Tobin-q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators.- The effect of uncertainty on UK investment authorisation: Homogeneous vs. heterogeneous estimators.-Reinterpreting the performance of immigrant wages from panel data.- Inflation and growth: Explaining a negative effect.- Efficiency measurement using a latent class stochastic frontier model.- Productivity and technical change: Measurement and testing.- Modeling corner solutions with panel data: Application to the industrial energy demand in France.