[图书简介]
本书是一本计量经济学基本理论的综合参考书，它一方面关注计量经济学各领域的基本问题，另一方面也为实证研究中常常遇到的困惑提供了解答。本书的每一章都由国际知名的专家撰写，并且综合了该领域中的最新研究成果，而这些新的进展往往是标准的计量经济学教科书通常并不涉及的。对于需要迅速了解计量经济学的基本理论的读者来说，本书是一本优秀的参考书。本书的每一章都提供了相关主题的清楚的信息，并指出了进一步阅读的方向。本书所包括的重要的主题有：序列相关(Serial Correlation)、异方差(Heteroskedasticity)、非参数和半参数模型(Nonparametric and Semiparametric Models)、计数数据和面板数据回归模型(Count and Panel Data Regression Models)及空间相关(Spatial Correlation)等。
【作者简介】：
　　BadiH。Baltagi是TexasA&M大学的人文学科GeorgeSummeyJr。教授及经济学教授。他是《计量经济学杂志》的编委和会员、《计量经济评论》的编委及《实证经济学》的主编，曾获得经济计量理论的MultaScripsit奖。Baltagi教授著有《面板数据分析》、《面板数据的经济计量分析》和《计量经济学》（第2版）等著作，并已经在国际知名的杂志上发表了70多篇论文。
Description
A comprehensive reference to the basics of econometrics. It focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners. The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts.
This book is a useful reference for readers who require quick access to the foundation theories in this field. Chapters are organized to provide clear information and to point to further readings on the subject. Important topics covered include: serial correlation; heteroskedasticity; nonparametric and semiparametric models; count and panel data regression models; and spatial correlation.
Content
1.Artificial Regressions: Russell Davidson and James G. MacKinnon.
2. General Hypothesis Testing: Anil K. Bera and Gamini Premaratne.
3. Serial Correlation: Maxwell L. King.
4. Heteroskedasticity: William E. Griffiths.
5. Seemingly Unrelated Regression: Denzil G. Fiebig.
6. Simultaneous Equation Model Estimators: Statistical Properties and Practical Implications: Roberto S. Mariano.
7. Identification in Parametric Models: Paul Bekker and Tom Wansbeek.
8. Measurement Error and Latent Variables: Tom Wansbeek and Erik Meijer.
9. Diagnostic Testing: Jeffrey M. Wooldridge.
10. Basic Elements of Asymptotic Theory: Benedikt M. Poetscher and Ingmar R. Prucha.
11. Generalized Method of Moments: Alastair R. Hall.
12. Collinearity: R. Carter Hill and Lee C. Adkins.
13. Non-nested Hypothesis Testing: An Overview: M. Hashem Pesaran and Melvyn Weeks.
14. Spatial Econometrics: Luc Anselin.
15. Essentials of Count Data Regression: A. Colin Cameron and Pravin K. Trivedi.
16. Panel Data Models: Cheng Hsiao.
17. Qualitative Response Models: G.S. Maddala and A. Flores-Lagunes.
18. Self-Selection: Lung-fei Lee.
19. Random Coefficient Models: P.A.V.B. Swamy and George S. Tavlas.
20. Nonparametric Kernel Methods of Estimation and Hypothesis Testing: Aman Ullah.
21. Durations: Christian Gourieroux and Joann Jasiak.
22. Simulation Based Inference for Dynamic Multinomial Choice Models: John Geweke, Daniel Houser and Michael Keane.
23. Monte Carlo Test Methods in Econometrics: Jean-Marie Dufour and Lynda Khalaf.
24. Bayesian Analysis of Stochastic Frontier Models: Gary Koop and Mark F.J. Steel.
25. Parametric and Nonparametric Tests of Limited Domain and Ordered Hypotheses in Economics: Esfandiar Maasoumi.
26. Spurious Regressions in Econometrics: Clive W.J. Granger.
27. Forecasting Economic Time Series: James H. Stock.
28. Time Series and Dynamic Models: Aris Spanos.
29. Unit Roots: Herman J. Bierens.
30. Cointegration: Juan J. Dolado, Jesus Gonzalo and Francesc Marmol.
31. Seasonal Nonstationarity and Near-Nonstationarity: Eric Ghysels, Denise R. Osborn and Paulo M.M.Rodrigues.
32. Vector Autoregressions: Helmut Luetkepohl.