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Theoretical Foundations and Empirical Developments in Hedonic Modeling

  • Laura O. Taylor

Although hedonic analyses have been reported as far back as Waugh’s (1928) analysis of agricultural markets, it was Rosen’s (1974) seminal work that began a rich theoretical and empirical literature exploring the role of housing attributes in consumer decision making. Housing choice not only confers to the owner/renter consumption of property and structural housing characteristics, but consumption of all location characteristics of the property such as proximity to environmental amenities and disamenities. As such, observed choices over housing reveals to the researcher information about the underlying preferences for these amenities or other characteristics of interest. In this chapter, we review the hedonic model as developed by Rosen as well as recent theoretical and empirical developments in hedonic modeling.

While most hedonic analyses only estimate a first stage hedonic price function, information from this first stage analysis may be used to complete a second stage analysis in which the underlying preferences for housing characteristics are estimated. Rosen (1974) described a two-step procedure in which implicit prices for housing characteristics recovered in the first stage analysis could be combined with observed quantities of characteristics chosen to estimate underlying demands for characteristics. In the thirty years since Rosen’s first proposed this two-stage approach, much has been written about its potential and its limitations. We review the method and recent research which indicates the promise of the method has yet to be fully exploited. We also review alternative methods of recovering demand parameters including random utility models and locational equilibrium models. Section 1.5 offers concluding statements.

Keywords

Housing Market Hedonic Price Hedonic Modeling Random Utility Model Nest Logit Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science + Business Media, LLC 2008

Authors and Affiliations

  • Laura O. Taylor
    • 1
  1. 1.North Carolina State UniversityRaleighUS

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