Econometrics

Author: Lin Wenfu, Ran Qikang, Zhu Baohua
Publisher:
Publish Date: 2005-10-01
Features: As a core course for finance and economics majors in higher education institutions and an important research method in contemporary mainstream economics, econometrics has demonstrated strong vitality since its birth in the 1930s. The research work of all Nobel Prize winners in Economics has been connected to econometrics to varying degrees, highlighting its significance. This book is an excellent textbook for advanced econometrics at the graduate level. Currently, it is widely welcomed and used in universities in Western countries and other regions, and is one of the most popular textbooks reflecting the research achievements of modern econometrics.
The book introduces the econometric content that senior undergraduates and graduate students need to master, starting with the least squares method, and provides the content of a standard econometrics course, including analysis of stationary and non-stationary time series. Given that generalized method of moments (GMM) estimation has gradually become a fundamental estimation method in econometrics, the book unifies the principles of GMM estimation to handle other estimation methods such as least squares and maximum likelihood, treating commonly used econometric estimation methods as special cases of GMM. At the same time, the book not only concisely covers important topics in econometrics but also introduces the maximum likelihood estimation methods for various models such as the probit model and tobit model using extreme value estimation techniques, fully reflecting the modern approach to econometrics. The book not only describes the main findings of econometrics in the form of propositions but also provides indirect proofs or proof ideas for most propositions to help readers grasp the content discussed in each chapter.
As a core course for finance and economics majors in higher education institutions and an important research method in contemporary mainstream economics, econometrics has demonstrated strong vitality since its birth in the 1930s. The research work of all Nobel Prize winners in Economics has been connected to econometrics to varying degrees, highlighting its significance. This book is an excellent textbook for advanced econometrics at the graduate level. Currently, it is widely welcomed and used in universities in Western countries and other regions, and is one of the most popular textbooks reflecting the research achievements of modern econometrics. The book introduces the econometric content that senior undergraduates and graduate students need to master, starting with the least squares method, and provides the content of a standard econometrics course, including analysis of stationary and non-stationary time series. Given that generalized method of moments (GMM) estimation has gradually become a fundamental estimation method in econometrics, the book unifies the principles of GMM estimation to handle other estimation methods such as least squares and maximum likelihood, treating commonly used econometric estimation methods as special cases of GMM. At the same time, the book not only concisely covers important topics in econometrics but also introduces the maximum likelihood estimation methods for various models such as the probit model and tobit model using extreme value estimation techniques, fully reflecting the modern approach to econometrics. The book not only describes the main findings of econometrics in the form of propositions but also provides indirect proofs or proof ideas for most propositions to help readers grasp the content discussed in each chapter.
To help readers understand the application of econometrics, the book extensively integrates empirical analysis cases from disciplines such as labor economics, industrial organization, macroeconomic theory, and financial theory. It also provides rich exercises and hints for some exercises to aid in review and comprehension. Notably, the content of empirical analysis exercises is derived from classic cases in econometrics, while the hints for empirical analysis exercises incorporate the use of econometric analysis software such as Gauss and TSP, enabling readers to directly utilize the statistical software and estimation methods introduced in the book for empirical research.