Property Values as a Measure of Neighborhoods: An Application of Hedonic Price Theory

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Abstract

Background:

Researchers measuring relationships between neighborhoods and health have begun using property appraisal data as a source of information about neighborhoods. Economists have developed a rich tool kit to understand how neighborhood characteristics are quantified in appraisal values. This tool kit principally relies on hedonic (implicit) price models and has much to offer regarding the interpretation and operationalization of property appraisal data-derived neighborhood measures, which goes beyond the use of appraisal data as a measure of neighborhood socioeconomic status.

Methods:

We develop a theoretically informed hedonic-based neighborhood measure using residuals of a hedonic price regression applied to appraisal data in a single metropolitan area. We describe its characteristics, reliability in different types of neighborhoods, and correlation with other neighborhood measures (i.e., raw neighborhood appraisal values, census block group poverty, and observed property characteristics). We examine the association between all neighborhood measures and body mass index.

Results:

The hedonic-based neighborhood measure was correlated in the expected direction with block group poverty rate and observed property characteristics. The neighborhood measure and average raw neighborhood appraisal value, but not census block group poverty, were associated with individual body mass index.

Conclusion:

We draw theoretically consistent methodology from the economics literature on hedonic price models to demonstrate how to leverage the implicit valuation of neighborhoods contained in publicly available appraisal data. Consistent measurement and application of the hedonic-based neighborhood measures in epidemiology will improve understanding of the relationships between neighborhoods and health. Researchers should proceed with a careful use of appraisal values utilizing theoretically informed methods such as this one.

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