(1992) Spatial dependence and spatial heterogeneity: model specification issues in the spatial expansion paradigm. Journal of Regional Science 30, 185–207.Īnselin, L. (1990) Spatial dependence and spatial structural instability in applied regression analysis. Dordrecht: Kluwer Academic Publishers.Īnselin, L. (1988) Spatial Econometrics: Methods and Models. (1991) Heteroscedasticity and autocorrelation consistent covariance matrix estimation. Journal of Real Estate Finance and Economics 11, 137–51.Īndrews, D.W. Waller (1995) Implicit pricing across residential rental submarkets. This process is experimental and the keywords may be updated as the learning algorithm improves.Īllen, M.T., T.M. These keywords were added by machine and not by the authors. We review and discuss the treatment of spatial dependence (including space-time dynamics) and spatial heterogeneity with selective illustrations from the empirical literature. In this chapter we provide a review of the principles underlying the hedonic house price model, and continue to extensively discuss spatial econometric aspects due to spatial models and spatial data specific to house price applications.
As defined in Anselin (2006), spatial econometrics “consists of a sub-set of econometric methods that is concerned with spatial aspects present in cross-sectional and spacetime observations.” These methods focus in particular on two forms of so-called spatial effects in econometric models, referred to as spatial dependence and spatial heterogeneity. In these, the locational aspects of the observations are treated explicitly, and the estimation of the models is an application of spatial econometrics. Greater effort therefore needs to be made to establish a set of best practices within the second stage, many of which can be developed using methods established in the extensive first-stage literature.In this chapter, we focus on some econometric aspects related to a sub-set of hedonic house price models, which we refer to as spatial hedonic models. As policies increasingly seek to deliver large, nonmarginal changes in public goods, the need to estimate the hedonic second stage is becoming more poignant. Researchers have rarely implemented the second stage, however, due to limited data availability, specification concerns, and the inability to correct for simultaneity bias between price and quality. Information recovered from the first stage is then used to recover inverse demand functions for nonmarket goods in the second stage, which are required for nonmarginal welfare evaluation. The two-stage hedonic method requires the researcher to map housing attributes into housing price using an equilibrium price function. This concept was first formalized into a tractable theoretical framework by Rosen, and is known as the hedonic pricing method.
These prices are referred to as implicit prices because their value is indirectly revealed through the price of another product (typically a home) and are of interest as they reveal the value of goods, such as nearby public amenities, that would otherwise remain unknown. This concept is easily observed in housing markets where the price of a home is determined by the underlying bundle of attributes that define it and by the price households are willing to pay for each attribute. The value of a differentiated product is simply the sum of its parts.
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