5 Parameters estimation

• Depending on the model type, an appropriate estimator which gives the “best” parameter estimates should be used

• Commonly used estimator is the least squares estimator which originates from the OLS method (Ordinary Least Squares)

• Other methods based on OLS have been developed: Weighted Least Squares WLS, Generalized Least Squares GLS, Two Step Least Squares 2SLS, etc.

• In a bivariate model, OLS method is used to find the regression line that best fits the data points by minimizing residual sum of squares, hence the term “least squares”

• When the OLS method cannot be applied analytically, it is recommended to use an alternative estimator, such as the Maximum Likelihood Estimator MLE

• Both OLS and MLE provide the same parameter estimates if the normality assumption is met