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The Value of Housing Characteristics: A Meta Analysis
Authors:G Stacy Sirmans  Lynn MacDonald  David A Macpherson  Emily Norman Zietz
Institution:(1) Department of Insurance, Real Estate, and Business Law, The Florida State University, Tallahassee, FL 32306-1110, USA;(2) Department of Economics, The Florida State University, Tallahassee, FL 32306-2045, USA;(3) Pepper Institute on Aging, Florida State University, Tallahassee, FL 32306-2045, USA;(4) Department of Finance and Economics, Middle Tennessee State University, Murfreesboro, TN 37132, USA
Abstract:This paper provides a meta regression analysis of the nine housing characteristics that are appear most often in hedonic pricing models for single-family housing: square footage, lot size, age, bedrooms, bathrooms, garage, swimming pool, fireplace, and air conditioning. Meta regression analysis is useful for comparing the estimated regression coefficients from different studies. The goal in this study is to determine if the estimated coefficients vary by geographical location, time, type of data, and model specification. The results show that the estimated coefficients for some characteristics vary significantly by geographical location. These include square footage, lot size, age, bathrooms, swimming pool, and air conditioning. Controlling for time shows that the effects of these housing characteristics on house price have not changed over time. Controlling for type of data produces differences in coefficients for bathrooms. Controlling for wealth as measured by median household income has no significant impact on the coefficients for the housing characteristics. If the study controlled for square footage, the coefficients for lot size decrease. Controlling for the size of the hedonic model affects the coefficient for square footage.
Keywords:Selling price  Time on the market  Meta regression  Moderator variables  Hedonic models
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