Author: Lin Qingquan
Publisher:
Publish Date: 2006-04-01
Features: This book is divided into four parts with a total of 12 chapters. Part 1 includes Chapters 1 to 3, introducing the fundamentals of econometrics and data processing methods. The main content includes: the digital characteristics of random variables, which hold significant positions in economics, finance, and insurance, such as mathematical expectation, variance, correlation coefficient, and coefficient of variation. Additionally, this part also covers smoothing techniques for data and the basic issues of statistical inference. Part 2 includes Chapters 4 to 6, introducing linear models under classical assumptions. The main content includes: simple linear regression, multiple linear regression, and regression models with dummy variables. Part 3 includes Chapters 7 to 10, introducing linear models that do not satisfy classical assumptions. The main content includes: the causes and consequences of multicollinearity, how to detect and address it; the causes of heteroscedasticity, how to test and correct it; autocorrelation analysis and distributed lag models. Additionally, this part also discusses the properties and characteristics of simultaneous equation models with some examples. Part 4 includes Chapters 11 and 12, introducing dynamic models and applied models.
Econometrics
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