A Mixed Index Approach to Identifying Hedonic Price Models

Brasington, David M.; Hite, Diane

doi:10.2139/ssrn.928252

Cited by 18 publications

(36 citation statements)

References 28 publications

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“…13 Brasington and Hite (2008) argue that housing prices link housing characteristics with household characteristics and thereby create an endogeneity problem. This problem appears in equation (15), which contains household characteristics, but disappears from equation (19) because the household characteristics have been integrated out.…”

mentioning

confidence: 99%

Hedonic Markets and Explicit Demands: Bid-Function Envelopes for Public Services, Neighborhood Amenities, and Commuting Costs

Yinger

2009

SSRN Journal

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Hedonic regressions with house value as the dependent variable are widely used to study the value of public services and amenities. This paper builds on the theory of household bidding and sorting to derive a bid function envelope, which provides a form for these regressions. This approach uses a general characterization of household heterogeneity, yields estimates of the price elasticities of demand for services and amenities directly from the hedonic with no need for a Rosen two-step procedure, and provides tests of key hypotheses about household sorting. An application to data from Cleveland in 2000 yields precise estimates of price elasticities for school quality, distance from environmental hazards, and neighborhood ethnic composition. The results support the sorting hypotheses and indicate that household preferences are very heterogeneous, with some households placing a negative value on many "amenities."

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confidence: 99%

Hedonic Markets and Explicit Demands: Bid-Function Envelopes for Public Services, Neighborhood Amenities, and Commuting Costs

Yinger

2009

SSRN Journal

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“…The sample consists of 36, 527 properties that have been professionally evaluated in the period 2012 -2016. In the majority of the studies regarding real estate value forecasting, very small datasets are used for testing the various methodologies (Landajo et al, 2012;Kilpatrick, 2011;Kusan et al, 2010;Selim, 2009;Kontrimas and Verikas, 2011;Narula et al, 2012;Brasington and Hite, 2008). An exception are the studies from Zurada et al (2011);Peterson and Flanagan (2009).…”

Section: Data Descriptionmentioning

confidence: 99%

“…Furthermore, the analysis is usually based on small samples (less than 500 properties) at regional level, (Landajo et al, 2012;Kilpatrick, 2011;Kusan et al, 2010;Selim, 2009;Kontrimas and Verikas, 2011;Narula et al, 2012;Brasington and Hite, 2008). In this study the proposed AVMs are tested in a new market still at its infancy with lots of unique characteristics.…”

Section: Introductionmentioning

confidence: 99%

Real Estate valuation and forecasting in non-homogeneous markets: A case study in Greece during the financial crisis

Alexandridis

Karlis

Papastamos³

et al. 2018

Journal of the Operational Research Society

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In this paper we develop an automatic valuation model for property valuation using a large database of historical prices from Greece. The Greek property market is an inefficient, non-homogeneous market, still at its infancy and governed by lack of information. As a result modelling the Greek real estate market is a very interesting and challenging problem. The available data covers a big range of properties across time and includes the Greek financial crisis period which led to tremendous changes in the dynamics of the real estate market. We formulate and compare linear and nonlinear models based on regression, hedonic equations, spatial analysis and artificial neural networks. The forecasting ability of each method is evaluated out-of-sample. Special care is given on measuring the success of the forecasts but also to identify the property characteristics that lead to large forecasting errors. Finally, by examining the strengths and the performance of each method we apply a combined forecasting rule to improve performance. Our results indicate that the proposed methodology constitutes an accurate tool for property valuation in non-homogeneous, newly developed markets.

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“…Endogeneity of neighborhood variables biases results, so that in uncontrolled regressions apparent willingness to pay for certain public goods like school quality tends to be significantly overestimated, while willingness to pay for others, such as environmental quality, tend to be underestimated (Brasington and Hite, 2008). To counter this problem, several methods have been developed; for example, Brasington and Hite (2008) apply a mixed index model, which includes structural models for neighborhood characteristics, and Bayer, Ferreira, and McMillan (2007) take advantage of jurisdictional discontinuities in hedonic models to control for endogeneity. Epple and Sieg (1999) and Epple, Romer, and Sieg (2001) account for sorting through use of instrumental variables.…”

Section: Sorting and Segregationmentioning

confidence: 99%

House Price Impacts of Racial, Income, Education, and Age Neighborhood Segregation

Brasington

Hite

Jauregui

2014

Journal of Regional Science

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ABSTRACT. We study housing prices and neighborhood segregation. We advance the literature by (1) studying not just racial segregation like previous studies, but also segregation by age, income, and education level, (2) using a finer unit of geography to construct segregation measures, (3) incorporating spatial statistics, and (4) separating segregation effects from underlying population level effects. We find race segregation is positively related to house prices, with an elasticity of 0.19. In contrast, income and educational segregation reduce housing values, with elasticities of −0.23 and −0.21. By comparison, house age has an elasticity of −0.15. Age segregation is not generally capitalized.

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A Mixed Index Approach to Identifying Hedonic Price Models

Cited by 18 publications

References 28 publications

Hedonic Markets and Explicit Demands: Bid-Function Envelopes for Public Services, Neighborhood Amenities, and Commuting Costs

Hedonic Markets and Explicit Demands: Bid-Function Envelopes for Public Services, Neighborhood Amenities, and Commuting Costs

Real Estate valuation and forecasting in non-homogeneous markets: A case study in Greece during the financial crisis

House Price Impacts of Racial, Income, Education, and Age Neighborhood Segregation

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