An exercise demonstrating the operation of free markets: Explaining housing price differentials within a historic landmark district

Richard J. Cebula, Patricia E. Gaynor, Michael Toma

Research output: Contribution to book or proceedingChapterpeer-review

Abstract

This study provides an example of the operation of free markets by applying a hedonic pricing model to explain housing price differentials within a historic landmark district. By considering home sales solely within such a district, in principle the market experiment transpires within an institutionally homogenous framework, i.e., all sales share a common characteristic in that they occur within a land area designed as "historic." This exercise demonstrating the operation of free markets involves in the Savannah Historic Landmark District, which is located in and adjacent to the downtown of Savannah, Georgia. Estimating the model in semi-log form reveals that the natural log of the real sales price of a house in this particular environment was positively affected by the number of bathrooms, fireplaces, rooms, stories in structure, garage car spaces, and square feet of finished living space, the presence of a custom kitchen, a deck, a private courtyard, an exterior construction of brick or stucco, an underground sprinkler system, and whether or not the house was new. The real sales price was negatively affected by the presence of a rental apartment on the premises and by an exterior of either vinyl or wood siding. Listing a house for sale during the peak selling season from May through July also acts to raise the real sales price of the house. Finally, the analysis also demonstrates that property taxes are capitalized into housing prices. Ultimately, the analysis demonstrates the efficiency of free markets within a model which systematically permits the evaluation of a host of housing characteristics within a somewhat homogeneous context.

Original languageEnglish
Title of host publicationHousing, Housing Costs and Mortgages
Subtitle of host publicationTrends, Impact and Prediction
PublisherNova Science Publishers, Inc.
Pages121-133
Number of pages13
ISBN (Print)9781607418139
StatePublished - Jan 2013

Scopus Subject Areas

  • General Social Sciences

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