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ISBN:9780521844413

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Summary: Publisher Summary 1 This collection pushes forward the research frontier in four areas of theoretical econometrics.   Publisher Summary 2 This 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 new ones. 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.  

目录


Identification and Inference for Econometric Models:
A Festschrift in Honor of Thomas J. Rothenberg
Table of Contents
Editor's Introduction
Part I. Identification and Efficient Estimation
Chapter 1. "Incredible Structural Inference," by Thomas J. Rothenberg.
Chapter 2. "Structural Equation Models in Human Behavior Genetics," by Arthur S.
Goldberger.
Chapter 3. "Unobserved Heterogeneity and Estimation of Average Partial Effects," by
Jeffrey M. Wooldridge.
Chapter 4. "On Specifying Graphical Models for Causation, and the Identification
Problem," by David A. Freedman.
Chapter 5. "Testing for Weak Instruments in Linear IV Regression," by James H. Stock
and Motohiro Yogo.
Chapter 6. "Asymptotic Distributions of Instrumental Variables Statistics with Many
Instruments," by James H. Stock and Motohiro Yogo.
Chapter 7. "Identifying a Source of Financial Volatility," by Douglas G. Steigerwald and
Richard J. Vagnoni.
Part II. Asymptotic Approximations
Chapter 8. "Asymptotic Expansions for Some Semiparametric Program Evaluation
Estimators," by Hidehiko Ichimura and Oliver Linton.
Chapter 9. "Higher-order Improvements of the Parametric Bootstrap for Markov
Processes," by Donald W. K. Andrews.
Chapter 10. "The Performance of Empirical Likelihood and its Generalizations," by
Guido W. Imbens and Richard H. Spady.
Chapter 11. "Asymptotic Bias for GMM and GEL Estimators with Estimated Nuisance
Parameters," by Whitney K. Newey, Joaquim J. S. Ramalho, and Richard J.
Smith.
Chapter 12. "Empirical Evidence Concerning the Finite Sample Performance of EL-type
Structural Equation Estimation and Inference Methods," by Ron C.
Mittelhammer, George G. Judge, and Ron Schoenberg.
Chapter 13. "How Accurate is the Asymptotic Approximation to the Distribution of
Realised Variance?" by Ole E. Barndorff-Nielsen and Neil Shephard.
Chapter 14. "Testing the Semiparametric Box-Cox Model with the Bootstrap," by N. E.
Savin and Allan H. Wurtz.
Part III. Inference Involving Potentially Nonstationary Time Series
Chapter 15. "Tests of the Null Hypothesis of Cointegration Based on Efficient Tests for a
Unit MA Root," by Michael Jansson.
Chapter 16. "Robust Confidence Intervals for Autoregressive Coefficients Near One," by
Samuel B. Thompson.
Chapter 17. "A Unified Approach to Testing for Stationarity and Unit Roots," by Andrew
C. Harvey.
Chapter 18. "A New Look at Panel Testing of Stationarity and the PPP Hypothesis," by
Jushan Bai and Serena Ng.
Chapter 19. "Testing for Unit Roots in Panel Data: An Exploration Using Real and
Simulated Data," by Brownwyn H. Hall and Jacques Mairesse.
Chapter 20. "Forecasting in the Presence of Structural Breaks and Policy Regime Shifts,"
by David F. Hendry and Grayham E. Mizon.
Part IV. Nonparametric and Semiparametric Inference
Chapter 21. "Nonparametric Testing of an Exclusion Restriction," by Peter J. Bickel,
Ya'acov Ritov, and Tom Stoker.
Chapter 22. "Pairwise Difference Estimators for Nonlinear Models," by Bo E. Honore
and James L. Powell.
Chapter 23. "Density Weighted Linear Least Squares," by Whitney K. Newey and Paul
A. Ruud.

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