作者：(美)杰弗里·M.伍德里奇
页数：612
出版社：清华大学出版社
出版日期：2022
ISBN：9787302603771
电子书格式：pdf/epub/txt
内容简介
《计量经济学导论:现代观点:第7版:英文》由(美)杰弗里·M.伍德里奇著
作者简介
杰弗里·M. 伍德里奇（Jeffrey M. Wooldridge）,密歇根州立大学经济学教授，1991年以来一直在该校任教。1986—1991年伍德里奇博士曾任麻省理工学院经济学助教授。1982年他以计算机科学与经济学为主攻方向而获加州大学伯克利分校艺术学士学位，并于1986年于加州大学圣迭戈分校获经济学博士学位。伍德里奇博士曾在国际知名期刊发表学术论文二三十篇，参与过多种书籍的篇章写作。他的获奖项目包括： Alfred P.斯隆(Sloan)研究员基金，计量经济理论Multa Scripsicl奖金，应用计量经济学期刊的R.斯通(Stone)爵士奖，以及三次获MIT 当年研究生班优秀教师奖。他还是计量经济学期刊(Journal of Econometrics)的资深会员。
本书特色
本书是在伍德里奇教授撰写的经典计量经济学原版教材的基础上，根据国内教学实践进行精简的影印删减版教材。作者用简洁、准确的语言阐述了计量经济学研究的新特点。与传统的教材不同，在陈述和解释假定时，作者完全放弃了非随机的或在重复样本中加以固定的回归元假定。这种方法更便于读者对计量经济学的理解和运用，是对传统计量经济学教学和研究的一个突破。读者不需要具备高深的数学知识，只要掌握大学所学的线性代数和概率统计基础知识即可。强调计量经济学在实际问题中的应用，书中含有大量例题，许多是取自或受启发于应用经济学或其他领域的新作品。 本书适合各大专院校经济管理类专业本科生用作教材，也可供经济管理类教师及科研人员用作参考书。
目录
About the Author
CHAPTER 1 The Nature of Econometrics and Economic Data
1-1 What Is Econometrics?
1-2 Steps in Empirical Economic Analysis
1-3 The Structure of Economic Data
1-3a Cross-Sectional Data
1-3b Time Series Data
1-3c Pooled Cross Sections
1-3d Panel or Longitudinal Data
1-3e A Comment on Data Structures
1-4 Causality, Ceteris Paribus, and Counterfactual Reasoning
Summary
Key Terms
Problems
Computer Exercises
PART 1 Regression Analysis with Cross-Sectional Data
CHAPTER 2 The Simple Regression Model
2-1 Definition of the Simple Regression Model
2-2 Deriving the Ordinary Least Squares Estimates
2-2a A Note on Terminology
2-3 Properties of OLS on Any Sample of Data
2-3a Fitted Values and Residuals
2-3b Algebraic Properties of OLS Statistics
2-3c Goodness-of-Fit
2-4 Units of Measurement and Functional Form
2-4a The Effects of Changing Units of Measurement on OLS Statistics
2-4b Incorporating Nonlinearities in Simple Regression
2-4C The Meaning of”Linear” Regression
2-5 Expected Values and Variances of the OLS Estimators
2-5a Unbiasedness of OLS
2-5b Variances of the OLS Estimators
2-5C Estimating the Error Variance
2-6 Regression through the Origin and Regression on a Constant
2-7 Regression on a Binary Explanatory Variable
2-7a Counterfactual Outcomes, Causality, and Policy Analysis
Summary
Key Terms
Problems
Computer Exercises
CHAPTER 3 Multiple Regression Analysis: Estimation
3-1 Motivation for Multiple Regression
3-1a The Model with Two Independent Variables
3-1b The Model with k Independent Variables
3-2 Mechanics and Interpretation of Ordinary Least Squares
3-2a Obtaining the OLS Estimates
3-2b Interpreting the OLS Regression Equation
3-20 On the Meaning of “Holding Other Factors Fixed” in Multiple Regression
3-2d Changing More Than One Independent Variable Simultaneously
……
CHAPTER 4 Multiple Regression Analysis: Inference
CHAPTER 5 Multiple Regression Analysis: OLS Asymptotics
CHAPTER 6 Multiple Regression Analysis: Further Issues
CHAPTER 7 Multiple Regression Analysis with Qualitative Information
CHAPTER 8 Heteroskedasticity
CHAPTER 9 More on Specification and Data Issues
PART 2 Regression Analysis with Time Series Data
CHAPTER 10 Basic Regression Analysis with Time Series Data
CHAPTER 11 Further Issues in Using OLS with Time Series Data
CHAPTER 12 Serial Correlation and Heteroskedasticity in Time Series Regressions
PART 3 Advanced Topics
CHAPTER 13 Pooling Cross Sections across Time: Simple Panel Data Methods
CHAPTER 15 Instrumental Variables Estimation and Two-Stage Least Squares
CHAPTER 16 Simultaneous Equations Models
CHAPTER 19 Carrying Out ah Empirical Project
ADVANCED TREATMENT E The Linear Regression Model in Matrix Form
