Chapter 6
Assumptions of OLS Estimation and the Gauss-Markov Theorem
In This Chapter
Defining the assumptions of ordinary least squares (OLS) regression
Illustrating the difference between good and bad statistical estimates
Understanding the role of each OLS assumption in proving the Gauss-Markov theorem
Econometricians seek to find the best way to estimate economic relationships. That best method depends on what they think the relationship is between the variables and on what type of data is being utilized for the analysis. In this chapter, I discuss the assumptions of the most basic technique used in applied econometrics, the ordinary least squares (OLS) technique, and explain how the assumptions are important in producing reliable results.
OLS is the most popular method of performing regression analysis because in standard situations, its results are optimal. In this chapter, you discover exactly which assumptions define a standard situation in econometrics and which characteristics classify an estimation technique as optimal. You also find out the role of technical assumptions in showing that OLS achieves those criteria. (Note: I’m assuming you already have a basic understanding ...
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