This text introduces students with little or no previous experience in econometrics to this important discipline. It focuses on explaining why econometrics exists and how it can be used in everyday life, and addresses fundamental issues in econometrics for students.
This text introduces students with little or no previous experience in econometrics to this important discipline. It focuses on explaining why econometrics exists and how it can be used in everyday life, and addresses fundamental issues in econometrics for students.
Samuel Cameron is a Reader In Economics at the University of Bradford
Inhaltsangabe
Chapter 1:Introducing Econometrics Chapter 2:Statistical Testing and Modelling: The Basics Chapter 3:The Classical Linear Regression Model Introduced Chapter 4:Preparing and Using Data Chapter 5:What do all these tests and statistics mean? Chapter 6:Making Regression Analysis More Useful I: Transformation Chapter 7:Making Regression Analysis More Useful II: Dummies and Trends Chapter 8:Predicting and Explaining Discrete Events: Logit and Probit Models Chapter 9:More Tests: Diagnosing the results of basic models Chapter 10:Multicollinearity: Serious Worry or Minor Nuisance? Chapter 11:Problem Solving: Heteroscedasticity Chapter 12:Multiple equation models: Specification and the Identification Problem Chapter 13:Multiple equation models: Methods of Estimation Chapter 14:Problem Solving: Time-Series Chapter 15:Conclusion Appendices: 1Blank Template of Summary Sheet for Review Studies. 2Brief Description of the Excel files of Data Sets. 3The Notion of Causality 4 Statistical Tables 5 Probability 6 Standard error of the regression coefficient 7 Derivation of the normal equations for a multiple regression mode
Chapter 1:Introducing Econometrics Chapter 2:Statistical Testing and Modelling: The Basics Chapter 3:The Classical Linear Regression Model Introduced Chapter 4:Preparing and Using Data Chapter 5:What do all these tests and statistics mean? Chapter 6:Making Regression Analysis More Useful I: Transformation Chapter 7:Making Regression Analysis More Useful II: Dummies and Trends Chapter 8:Predicting and Explaining Discrete Events: Logit and Probit Models Chapter 9:More Tests: Diagnosing the results of basic models Chapter 10:Multicollinearity: Serious Worry or Minor Nuisance? Chapter 11:Problem Solving: Heteroscedasticity Chapter 12:Multiple equation models: Specification and the Identification Problem Chapter 13:Multiple equation models: Methods of Estimation Chapter 14:Problem Solving: Time-Series Chapter 15:Conclusion Appendices: 1Blank Template of Summary Sheet for Review Studies. 2Brief Description of the Excel files of Data Sets. 3The Notion of Causality 4 Statistical Tables 5 Probability 6 Standard error of the regression coefficient 7 Derivation of the normal equations for a multiple regression mode
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