Econometrics (Advanced Economics Series Textbooks of the 21st Century)

Author: Zhang Dingsheng
Publisher:
Publish Date: 2005-04-01
Features: This book is a mid-level econometrics textbook suitable for senior undergraduate students and first-year graduate students. It systematically introduces the main contents of classical econometrics, including linear regression models, systems of linear regression equations, single-equation nonlinear regression models, simultaneous equation models, and common time series models. It provides a detailed analysis of these models and presents commonly used parameter estimation methods and statistical inference methods. The book emphasizes theoretical analysis, and once the theoretical knowledge is understood, using existing computer software to process real data becomes a straightforward task. The book consists of fifteen chapters. Chapters 1 to 3 are preparatory knowledge, primarily introducing the mathematical knowledge required for analyzing econometric models, including matrix algebra, probability and distribution theory, and statistical inference methods. Mastering this knowledge is crucial for learning econometrics. Chapters 4 to 9 mainly introduce single-equation linear regression models. Chapter 10 introduces nonlinear regression models, where parameter estimates generally need to be obtained using numerical methods. Chapter 11 introduces the Generalized Method of Moments (GMM), which is widely used in recent economic analysis, especially in macroeconomics and finance, to estimate unknown parameters. Chapter 12 presents several models for datasets that include both time series and cross-sectional data, such as systems of regression equations, including seemingly unrelated regression models, fixed-effects and random-effects models. Chapter 13 introduces simultaneous equation models, which involve multiple endogenous variables and multiple structural equations. If only a single equation is used with ordinary least squares (OLS) to estimate the unknown parameters, the resulting estimates will be both biased and inefficient. Chapters 14 and 15 mainly introduce some time series models.