“Ordinary Least Squares (OLS) regression is a common tool used for economic forecasting when analyzing time series and cross-sectional data. It is quite common as it is one of the easiest ways of estimating parameters in a simple or multiple regression model. Generalized Least Squares (GLS) regression is used when problems occur in OLS estimation. Such problems will cause are estimators to no longer be the Best Linear Unbiased Estimate (BLUE) or efficient and so it is necessary to use a transformed model. In this essay I will show how both OLS and GLS are derived through equations and discuss the problems that may occur under OLS estimation and why it is more suitable to use GLS to estimate a linear model when certain problems occur.”