When estimating a structural equation in a simultaneous-equation model (e.g., a supply-demand model), why does the use of Ordinary Least Squares (OL

Solution: The fundamental assumption for OLS consistency is that the error term (ϵi) is uncorrelated with all the independent variables (regressors) in the model: Cov(X,ϵ)=0. · Simultaneity Problem: In a system of simultaneous equations (like supply and demand), an endogenous variable (e.g., Q) is determined by the interaction of the system. If we estimate the demand equation (where Q is on the left and P is an endogenous regressor on the right), the price P is correlated with the error term (ϵ) because any unobserved shock in the demand error term (e.g., a sudden increase in taste for the good) simultaneously affects the price (P). · Result: This correlation between the regressor (P) and the error term (ϵ) leads to Simultaneous Equations Bias, which is a form of endogeneity. This bias does not disappear as the sample size increases, meaning the OLS estimator is inconsistent.