Date of Completion


Embargo Period



Curb Appeal, Cell Tower, House Flipping, Spatial Hedonic Regression, Spatial Difference-in-Differences, k-NN

Major Advisor

Dean Hanink

Associate Advisor

Chuanrong Zhang

Associate Advisor

Kenneth Foote

Associate Advisor

George Bentley

Field of Study



Doctor of Philosophy

Open Access

Campus Access


A number of structural, locational, and environmental factors impact house prices. This study attempts to quantify a few of the underlying trends that influence residential real estate markets. The impact of curb appeal on house prices is investigated in selected neighborhoods of Boston. The effect of a cellular tower as a neighborhood dis-amenity is examined in the city of Las Vegas. Finally, the present work analyzes the practice of flipping and its impact on property values in Las Vegas.

A numerical rubric is proposed to quantify curb appeal of a house based on images obtained through Google Street View. Hedonic regression modeling was used to estimate house prices. The addition of curb appeal in the model improved the adjusted R-square value of the regression model from 0.58 to 0.63. Spatial error modeling indicated that curb appeal was a statistically significant parameter impacting house prices in Boston. The model also estimated that houses with ‘good’ curb appeal were sold on average at a 23.37 percent premium in comparison to houses with ‘below-average’ curb appeal.

Cellular towers are considered as a dis-amenity due to public apprehension about visual pollution and health concerns. Results from spatial lag regression models indicated that house prices decreased with increased proximity to cellular towers. An increase in “proximity” by one meter resulted in an average 0.1 percent decrease in house prices. Furthermore, with a 1-meter increase in tower height, house prices dropped by around 0.05 percent. Camouflaged towers were found to mitigate the visual impact of cellular towers.

House flipping was found to occur in neighborhoods with higher Hispanic percentage population, higher walk score, higher transportation index and higher housing index, based on spatial probit model. A combined difference-in-difference modeling with k-NN regression was used to estimate the sales-price impact of flipping. Flipping a house in Las Vegas in the 2016-2017 period resulted in an additional increase of house price by 5.89 percent over a market change of 22.63 percent.

Available for download on Friday, May 04, 2029