Background for Questions $15.$

In the first portion of this assignment, you are tasked with estimating the positive $/$ negative externality of living in Waterloo, Ontario compared to Kitchener, Ontario as measured through real estate prices.

To accomplish this, we have collected data on listed prices of $30$ houses in Waterloo and $30$ houses in Kitchener. The data were collected from www$.$realtor.ca in $2017/18.$

We have collected the associated data on these $60$ homes for the following standard explanatory variables in the housing market:

$$ Square footage, Lot size, # of bedrooms, # of bathrooms, and Age of the home

The Waterloo variable takes the value of $1$ for all houses in Waterloo $(30)$ and the value of $0$ for all houses in Kitchener $(30).$ All our data are given in the file named $$Kitchener$\_$Waterloo$$ posted on LEARN.

Our model takes the form:

Listed Pricei $=\backslash$beta $0+\backslash$beta $1$ Waterloo $+\backslash$Sigma $\backslash$beta Other Variables $+\backslash$epsi i where $$i$$ refers to the ith observation

Your econometrician $($me$)$ has supressed the constant, $\backslash$beta $0,$ when he estimated the regression. Effectively, forcing a property with no features to have a value of zero...makes sense.

Your coefficient estimate of $\backslash$beta $1$ is what you are primarily interested in since it measures the price differential of an average house in Waterloo relative to Kitchener, controlling for everything else $($your other explanatory variables$).$