Consider the following scenario: A real estate firm decides to estimate the demand for housing as a function of the location's population density and presence of shopping centers (among other things). However, the company also observes that there is a statistically significant positive correlation between population density and the presence of shopping centers. Would you recommend including both of these variables into the regression estimation? If your recommendation is no, why?
A) Yes, as both of these variables seem logical and interpreting their coefficients is important
B) No, because this would lead to multicollinearity
C) No, because this would lead to heteroscedasticity
D) No, because this would lead to autocorrelation

Question

Quizplus · Accepted Answer

Multicollinearity occurs when independent variables in a regression model are highly correlated. This can make it difficult to determine the individual effect of each variable on the dependent variable, as they may be providing redundant information. In the scenario described, the positive correlation between population density and the presence of shopping centers suggests multicollinearity, which can undermine the statistical significance of the independent variables.

Consider the Following Scenario: a Real Estate Firm Decides to Estimate