This study guide was written by Christopher Dougherty for the
module "20 Elements of Econometrics" which he teaches at the
University of London and is used with kind permission from the
university. It may, therefore, contain some specific references to
the module which can be ignored by students using the book on other
courses.
The study guide includes appendices containing advice on exam preparation and practice questions.
Contents:
Introduction What is econometrics and why study it?
Review Random variables, Sampling, and Estimation
Chapter 01 Simple regression analysis
Chapter 02 Properties of the regression coefficients and hypothesis testing
Chapter 03 Multiple regression analysis
Chapter 04 Transformations of variables
Chapter 05 Dummy variables
Chapter 06 Specification of regression variables
Chapter 07 Heteroscedasticity
Chapter 08 Stochastic regressors and measurement errors
Chapter 09 Simultaneous equations estimation
Chapter 10 Binary choice and limited dependent models, and maximum likelihood estimation
Chapter 11 Models using time series data
Chapter 12 Properties of regression models with time series data
Chapter 13 Introduction to non-stationary time series
Chapter 14 Introduction to panel data models
Chapter 15 Regression analysis with linear algebra primer
Appendices Exam preparation, questions and tables
The study guide includes appendices containing advice on exam preparation and practice questions.
Contents:
Introduction What is econometrics and why study it?
Review Random variables, Sampling, and Estimation
Chapter 01 Simple regression analysis
Chapter 02 Properties of the regression coefficients and hypothesis testing
Chapter 03 Multiple regression analysis
Chapter 04 Transformations of variables
Chapter 05 Dummy variables
Chapter 06 Specification of regression variables
Chapter 07 Heteroscedasticity
Chapter 08 Stochastic regressors and measurement errors
Chapter 09 Simultaneous equations estimation
Chapter 10 Binary choice and limited dependent models, and maximum likelihood estimation
Chapter 11 Models using time series data
Chapter 12 Properties of regression models with time series data
Chapter 13 Introduction to non-stationary time series
Chapter 14 Introduction to panel data models
Chapter 15 Regression analysis with linear algebra primer
Appendices Exam preparation, questions and tables