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Estimation and Inference in Econometrics (英文版) 计量经济学中的估计与推断(2021)
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Author(s): Russell Davidson, James G. MacKinnon
Publisher: Oxford University Press,
Year: 2021
ISBN: 0195060113,9780195060119
本创新的计量经济学指南提供了统一的理论视角，使用简单的几何论证来培养学生对基础和高级主题的直观理解，并强调现代理论和非线性估计技术的实际应用。
Offering a unifying theoretical perspective, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation.
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Table of Contents
1. The Geometry of Least Squares
2. Nonlinear Regression Models and Nonlinear Least Squares
3. Inference in Nonlinear Regression Models
4. Introduction to Asymptotic Theory and Methods
5. Asymptotic Methods and Nonlinear Least Squares
6. The Gauss-Newton Regression
7. Instrumental Variables
8. The Method of Maximum Likelihood
9. Maximum Likelihood and Generalized Least Squares
10. Serial Correlation
11. Tests Based on the Gauss-Newton Regression
12. Interpreting Tests in Regression Directions
13. The Classical Hypothesis Tests
14. Transforming the Dependent Variable
15. Qualitative and Limited Dependent Variables
16. Heteroskedasticity and Related Topics
17. The Generalized Method of Moments
18. Simultaneous Equations Models
19. Regression Models for Time-series Data
20. Unit Roots and Cointegratiaon
21. Monte Carlo Experiments
A. Matrix Algebra
B. Results from Probability Theory
References
Author Index
Subject Index
本书为学生提供了统一的理论视角，强调非线性估计技术，包括非线性最小二乘法、非线性工具变量、最大似然法和广义矩法，但仍然严重依赖简单的几何论证来培养直觉。
本书的一个主题是使用人工回归进行非线性模型的估计、推断和规范测试，包括参数恒常性、序列相关性、异方差性和其他类型的错误指定的诊断测试。其他主题包括线性联立方程模型、非嵌套假设检验、有影响的观测和杠杆、因变量的变换、二元响应模型、时间序列/横截面数据模型、多元模型、季节性、单位根和协整以及蒙特卡罗方法，始终强调应用工作中出现的问题。
本书通篇解释了如何获得估计值以及如何进行测试，超越了单纯的代数描述，可以轻松转换为标准计量经济学软件包的命令。该教材是对当今计量经济学中最重要主题的全面而连贯的指南，对于各级别的计量经济学、经济学和统计学回归及相关主题的学生来说都是必读教材。
Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simple geometrical arguments to develop intuition. One theme of the book is the use of artificial regressions for estimation, inference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, series correlation, heteroskedasticity and other types of misspecification. Other topics include the linear simultaneous equations model, non-nested hypothesis tests, influential observations and leverage, transformations of the dependent variable, binary response models, models for time-series/cross-section data, multivariate models, seasonality, unit roots and cointegration, and Monte Carlo methods, always with an emphasis on problems that arise in applied work. Explaining throughout how estimates can be obtained and tests can be carried out, the text goes beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. A comprehensive and coherent guide to the most vital topics in econometrics today, this text is indispensable for all levels of students of econometrics, economics, and statistics on regression and related topics.
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