Food Deserts and Residential Real Estate Prices

Abstract

The prevalence of neighborhoods with inadequate access to grocery stores, classified by the U.S. Department of Agriculture as “food deserts,” has become an issue of concern in recent years given that a growing body of research has shown that food deserts can have health-related consequences, such as heart disease, diabetes, and obesity. Despite this growing body of literature, no study to date has examined the consequences of food deserts on residential real estate prices. Using United States Census information from Shelby County, Tennessee, home to the Memphis metropolitan area, to determine whether access to a sufficient food source has an economic effect on housing prices and a dataset containing 3,298 residential real estate transactions, hedonic pricing models employing a large dataset of real estate transactions presented below in this study suggest that residential real estate prices are about 4% to 6% lower for houses located in food deserts than for their counterparts with adequate access to grocery stores.

Keywords:

• Food deserts
• grocery store access
• residential real estate prices
• hedonic pricing models

JEL Codes:

• Q10
• Q18
• R12
• R14
• R21
• R31
• R41

Acknowledgments

The authors thank two anonymous reviewers for helpful comments on a prior version. Any remaining errors are our own.

Notes

1 See ams.usda.gov.

2 Neighborhoods considered food deserts by the USDA often sit in close in proximity to one or more fast food restaurants, but are considered food deserts due to a lack of “healthy” food options nearby.

3 See ams.usda.gov.

4 According to Feeding America, food insecurity describes a household’s inability to provide enough food for every person to live an active, healthy life. Thus, food insecurity is one way to measure and assess the risk of hunger (feedingamerica.org).

5 See Feeding America (https://map.feedingamerica.org/county/2016/child/tennessee/county/shelby) for an interactive map providing these and other details regarding food insecurity in Shelby County.

6 Here, Moran’s I = 0.125, and ZI= 13.4*** (p-value < 0.001).

7 The test produced the following results: RLMλ* = 86.1*** (p-value < 0.001) > RLMρ* = 0.09 (p-value = 0.75).

8 We are grateful to an anonymous referee for pointing this out.

9 For an excellent overview of IPW and other methods, see Fortin et al. (2011).