Imagine you are studying the impact on home prices in New Bedford, Massachusetts, the site of a decommissioned Naval base widely known to have PCB contaminants and now designated as a Superfund site. You have gathered data and carefully run regressions of sales prices on home characteristics and have the results below. Say the regression equation was of following functional form: In (P)=a+b (kitchen remodel dummy )+c( lot size )+d (distance to Boston) +f( feet to Superfund site) + error where P is property value and In means the natural log. The letters a,b,c,d,f are parameters to be estimated, with a being the constant, or intercept. The table below list the coefficient estimates from the OLS regression. Use 1-2 sentences to explain how the signs on the coefficient estimates for 1) distance to Boston and 2) distance to the Superfund site make sense and what they mean on the margin for housing prices. Be specific with the data and use actual numbers in your explanation, similar to examples in class. Pay attention to which functional form is being used and how to interpret the coefficient values. Hedonic Regression Results Y-variable =ln( (home sales price (2012 dollars) )