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Identification and Inference for Econometric Models : Essays in Honor of Thomas Rothenberg - Donald W. K. Andrews

Identification and Inference for Econometric Models

Essays in Honor of Thomas Rothenberg

By: Donald W. K. Andrews (Editor), James H. Stock (Editor)

Paperback

Published: 24th June 2010
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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.

"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

Identification and Efficient Estimation
Incredible structural inference
Structural equation models in human behavior genetics
Unobserved heterogeneity and estimation of average partial effects
On specifying graphical models for causation and the identification problem
Testing for weak instruments in linear IV regression
Asymptotic distributions of instrumental variables statistics with many instruments
Identifying a source of financial volatility
Asymptotic Approximations
Asymptotic expansions for some semiparametric program evaluation estimators
Higher-order improvements of the parametric bootstrap for Markov processes
The performance of empirical likelihood and its generalizations
Asymptotic bias for GMM and GEL estimators with estimated nuisance parameters
Empirical evidence concerning the finite sample performance of EL-type structural equation estimation and inference methods
How accurate is the asymptotic approximation to the distribution of realised variance?
Testing the semiparametric Box-Cox model with the bootstrap
Inference Involving Potentially Nonstationary Time Series
Tests of the null hypothesis of cointegration based on efficient tests for a unit MA root
Robust confidence intervals for autoregressive coefficients near one
A unified approach to testing for stationarity and unit roots
A new look at panel testing of stationarity and the PPP hypothesis
Testing for unit roots in panel data: an exploration using real and simulated data
Forecasting in the presence of structural breaks and policy regime shifts
Nonparametric and Semiparametric Inference
Nonparametric testing of an exclusion restriction
Density weighted linear least squares
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780521154741
ISBN-10: 052115474X
Audience: Professional
Format: Paperback
Language: English
Number Of Pages: 588
Published: 24th June 2010
Publisher: Cambridge University Press
Country of Publication: GB
Dimensions (cm): 22.9 x 15.2  x 3.3
Weight (kg): 0.85