A theorem that under certain conditions, the ordinary least squares (OLS) estimator provides the Best Linear Unbiased Estimator (BLUE) of the linear regression coefficients. The conditions include a correct linear regression function and homoscedastic, serially uncorrelated errors for non-stochastic explanatory variables.
A method of estimation of a single equation in a linear simultaneous equations model based on the maximization of the likelihood function, subject to the restrictions imposed by the structure.
Ordinary Least Squares (OLS) is a method used in linear regression analysis to estimate the coefficients by minimizing the sum of squared residuals.
