Spring 2022

Document Type



School of Business

Faculty Advisor

Mitchell Priestley


This study seeks to identify relevant input variables which have an effect of closing prices in dollars in six counties in Oregon. This is done first by collecting sample data from a housing agency regarding houses listing price, closing price, Acres, Square footage, number of bathrooms, number of bedrooms, garage size, and county. Then, using the ordinary least squares method to run regressions and identify the magnitude of the effect of specific regressors on the output variable and using their standard error, an analysis is done both into the statistical and economic significance. This analysis found that when including most variables in the same regression, list price very closely modeled a house’s closing price, but none of the other factors were significant. Removing list price, it was found that acres2, totalSF2, and the effect of square footage in several counties were statistically significant, though they were of varying economic significance.

Included in

Real Estate Commons