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Cover image for Identification and inference for econometric models : essays in honor of Thomas Rothenberg
Title:
Identification and inference for econometric models : essays in honor of Thomas Rothenberg
Publication Information:
Cambridge : Cambridge University Press, 2005
ISBN:
9780521844413
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30000010119373 HB141 I33 2005 Open Access Book Book
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Summary

Summary

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.


Table of Contents

Part I Identification and Efficient Estimation
1 Incredible structural inferenceThomas J. Rothenberg
2 Structural equation models in human behavior geneticsArthur S. Goldberger
3 Unobserved heterogeneity and estimation of average partial effectsJeffrey M. Wooldridge
4 On specifying graphical models for causation and the identification problemDavid A. Freedman
5 Testing for weak instruments in linear IV regression James H. Stock and Motohiro Yogo
6 Asymptotic distributions of instrumental variables statistics with many instrumentsJames H. Stock and Motohiro Yogo
7 Identifying a source of financial volatilityDouglas G. Steigerwald and Richard J. Vagnoni
Part II Asymptotic Approximations
8 Asymptotic expansions for some semiparametric program evaluation estimatorsHidehiko Ichimura and Oliver Linton
9 Higher-order improvements of the parametric bootstrap for Markov processesDonald W. K. Andrews
10 The performance of empirical likelihood and its generalizationsGuido W. Imbens and Richard H. Spady
11 Asymptotic bias for GMM and GEL estimators with estimated nuisance parametersWhitney K. Newey and Joaquim J. S. Ramalho and Richard J. Smith
12 Empirical evidence concerning the finite sample performance of EL-type structural equation estimation and inference methodsRon C. Mittelhammer and George G. Judge and Ron Schoenberg
13 How accurate is the asymptotic approximation to the distribution of realised variance?Ole E. Barndorff-Nielsen and Neil Shephard
14 Testing the semiparametric Box-Cox model with the bootstrapN. E. Savin and Allan H. Wurtz
Part III Inference Involving Potentially Nonstationary Time Series
15 Tests of the null hypothesis of cointegration based on efficient tests for a unit MA rootMichael Jansson
16 Robust confidence intervals for autoregressive coefficients near oneSamuel B. Thompson
17 A unified approach to testing for stationarity and unit rootsAndrew C. Harvey
18 A new look at panel testing of stationarity and the PPP hypothesisJushan Bai and Serena Ng
19 Testing for unit roots in panel data: an exploration using real and simulated dataBrownwyn H. Hall and Jacques Mairesse
20 Forecasting in the presence of structural breaks and policy regime shiftsDavid F. Hendry and Grayham E. Mizon
Part IV Nonparametric and Semiparametric Inference
21 Nonparametric testing of an exclusion restrictionPeter J. Bickel and Ya'acov Ritov and James L. Powell
22 Pairwise difference estimators for nonlinear modelsBo E. HonorÃ(c) and James L. Powell
23 Density weighted linear least squaresWhitney K. Newey and Paul A. Ruud
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