Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg

Paperback / softback

Main Details

Title Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg
Authors and Contributors      Edited by Donald W. K. Andrews
Edited by James H. Stock
Physical Properties
Format:Paperback / softback
Pages:588
Dimensions(mm): Height 229,Width 152
Category/GenreEconometrics
ISBN/Barcode 9780521154741
ClassificationsDewey:330.015195
Audience
Professional & Vocational
Illustrations Worked examples or Exercises

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 24 June 2010
Publication Country United Kingdom

Description

This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

Reviews

"There is something here for both the econometrician and the technically oriented statistician.... I encourage those in this general area to troll the table of contents for something interesting." - Journal of the American Statistical Association