Developing Econometrics

• Provides a detailed description of computer algorithms.
• Provides recently developed computational tools useful for data mining
• Highlights recent advances in statistical theory and methods that benefit econometric practice.
• Features examples with real life data.
• Accompanying software featuring DASC (Data Analysis and Statistical Computing).

Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.Content:
Chapter 1 Introduction (pages 1–28):
Chapter 2 Independent Variables in Linear Regression Models (pages 29–81):
Chapter 3 Alternative Structures of Residual Error in Linear Regression Models (pages 83–127):
Chapter 4 Discrete Variables and Nonlinear Regression Model (pages 129–192):
Chapter 5 Nonparametric and Semiparametric Regression Models (pages 193–214):
Chapter 6 Simultaneous Equations Models and Distributed Lag Models (pages 215–251):
Chapter 7 Stationary Time Series Models (pages 253–295):
Chapter 8 Multivariate and Nonstationary Time Series Models (pages 297–355):
Chapter 9 Multivariate Statistical Analysis and Data Analysis (pages 357–414):
Chapter 10 Summary and Further Discussion (pages 415–460):