Using Zillow data to value green space amenities at the neighborhood scale

https://doi.org/10.1016/j.ufug.2020.126794Get rights and content

Highlights

  • Zillow, Inc. open-access data offers potential for large-scale hedonic pricing analyses that inform urban greening initiatives.

  • Trees and parks add premiums to home values in metropolitan areas on average, whereas un-curated vegetation is a dis-amenity.

  • We find indications of a positive feedback loop between wealth and tree-shade in urban and suburban areas.

Abstract

It is important to quantify the value of green space amenities in order to justify the cost of their creation and maintenance; furthermore, advances in available data and methods have produced exciting ways to measure the economic values of green infrastructure. In this study, we use publicly available data from Zillow, Inc. to implement the hedonic pricing method at a novel scope and scale. We analyze over 5000 Zillow neighborhoods located in metropolitan areas across 44 states to identify the marginal value of urban green spaces with respect to median neighborhood home prices. By incorporating a vast, heterogeneous study area, we are able to gain a national-scale perspective on the effects of green spaces on home values. Furthermore, Zillow neighborhoods permit reproducible, extensible, and policy-relevant insight into the effects of green spaces on neighborhoods holistically. Our results suggest that for Zillow neighborhoods on average the normalized difference vegetation index (NDVI) and open space are dis-amenities; however, parks and tree cover add premiums to Zillow neighborhood value. By interacting tree cover with land surface temperature, we find the amenity value of trees is realized in part through shading; furthermore, we find that tree-shading has a greater amenity value in higher-income areas.

Section snippets

Introduction and background

Urban and suburban green spaces, such as trees and parks, benefit both people and nature. Green spaces, or “urban green infrastructure”, enhance the lives of community residents by promoting healthy activities, providing cleaner air, sheltering residents from negative effects of undesirable land uses, and increasing social interaction (Ayala-Azcárraga et al., 2019; Groenewegen et al., 2006). Green spaces also benefit nature by providing habitat to various species, controlling erosion and

Data scale and coverage

Zillow, Inc. is a real estate database that, in addition to estimating home values, delineates approximately 8000 neighborhoods in metropolitan areas across the United States (Fig. 1). Zillow developed neighborhood boundaries by contacting individual chambers of commerce, tourism, and convention boards, speaking with local real estate agents, and using various online sources (see https://www.zillowgroup.com/news/7000-neighborhood-boundary-files-in-shapefile-format/). We restricted our sample to

Baseline model (Model 1)

Table 2 tabulates the parameter estimates for all four models. Of the 18 structural, demographic, and community predictor variables in the baseline model, 12 are found to be statistically significant (P ˂ 0.10), including the fixed effects for U.S. state and metropolitan area, which are omitted from Table 2 for brevity. We compared models with and without fixed effects for metropolitan area; the partial F test rejected the null hypothesis with P ˂ 0.001, confirming the presence of submarket

Discussion

The signs of the estimates in the baseline model are consistent with our expectations and with previous studies (Fernandez and Bucaram, 2019). School and traffic indicators have been shown to be important variables in other studies (Czembrowski and Kronenberg, 2016; Gibbons et al., 2014), but our model estimates only college/university and development intensity to be significant, while road type, highway and k-12 school are not. Aspect is another feature that we find to be significant in the

Conclusion

Cities and neighborhoods across the United States are grappling with ways to accommodate more humans while at the same time capitalize on the economic, aesthetic, and health benefits of green spaces. We estimate the economic benefits of environmental attributes by applying the hedonic pricing method to a dataset of almost 6000 Zillow neighborhoods across the United States. The Zillow neighborhood as a unit of observation is useful not only because it is efficient and extensible, but also

Declaration of competing interests

The authors whose names appear on the title page have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or

CRediT authorship contribution statement

Jonathan R. Holt: Conceptualization, Methodology, Investigation, Data curation, Writing - original draft. Mark E. Borsuk: Supervision, Writing - review & editing.

Declaration of Competing Interest

The authors report no declarations of interest.

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