The Classical Linear Regression Model

This introductory chapter provides the necessary background to understand the rest of the book and introduces the symbolism used elsewhere. The chapter covers the topics typically treated in a first course in econometrics at an undergraduate level; as such it can be omitted by the readers who are already knowledgeable on this subject. We present a summary of the basic multivariate linear regression model, and of the three most popular estimation methods (Ordinary Least Squares, Maximum Likelihood and Method of Moments). We then present the basic hypothesis testing procedures. We also discuss the model's assumptions, we briefly analyse the consequences of their violations and we present the alternative estimators that are necessary in these situations. Finally, the chapter contains a presentation of the codes necessary for the practical implementation of the procedures discussed in the chapter, by using the softwares R, STATA and Python.