本书用简洁、准确的语言阐述了计量经济学研究的最新特点。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。本书含有大量例题，许多是取自或受启发于应用经济学或其他领域的最新作品。
本书适合各大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。

杰弗里·M.伍德里奇（Jeffrey M.Wooldridge），密歇根州立大学经济学教授，曾在国际知名期刊发表学术论文三十余篇，参与过多种书籍的写作。他获得过Alfred P.Sloan研究员基金、应用计量经济学期刊的R.Stone爵士奖等奖项。他还是《商业与经济统计学》杂志（Journal of Business and Economic Statistics）的编委，并供职于《计量经济学》杂志（Journal of Econometrics）和《经济统计学评论》（Review of Economics and Statistics）的编委会。

Preface
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