Study Finds Cell Towers Near Homes Drops Property Value 
A 2018 study published in the Journal of Real Estate Finance and Economics found for properties located within 0.72 kilometers [2362 feet] of the closest cell tower, property values declined 2.46% on average, and up to 9.78% for homes within tower visibility range compared to homes outside tower visibility range. In aggregate, properties within the 0.72-kilometer band lose over $24 million dollars.
The authors conclude, “given the apparent social costs associated with negative price effects, local zoning and regulatory authorities should consider granting approvals that include impact-minimizing conditions.”

“This is just one of several studies finding that cell towers near homes drops property value,” stated Theodora Scarato, Executive Director of Environmental Health Trust. 

“Cellphone towers bring extra tax revenue and better reception to a section of the city, but many are skeptical because of the potential health risks and the impact on property values. Increasing numbers of people don’t want to live near cell towers. In some areas with new towers, property values have decreased by up to 20%.” -National Business Post: Your new neighbor, a cell tower, may impact the value of your home

Research Citation
This is the first study to use an hedonic spatial autoregressive model to assess the impact of wireless communication towers on the value of residential properties. Using quantile analyses based on minimum distances between sold properties and visible and non-visible towers, we examine the relationship between property values and wireless tower proximity and visibility within various specified radii for homes sold after tower construction. For properties located within 0.72 kilometers of the closest tower, results reveal significant social welfare costs with values declining 2.46% on average, and up to 9.78% for homes within tower visibility range compared to homes outside tower visibility range; in aggregate, properties within the 0.72-kilometer band lose over $24 million dollars.

In 1985, there were only 900 cell sites in the U.S., but by the end of 2014, the number had increased by 22,778% (CTIA 2015). Of the more than 298,000 cell sites in the U.S., nearly 70% are located on tower structures (Airwave Management, LLC 2013)….

Considering the expected future increases in wireless device users and the cell sites supporting them, this is a critically important question for our time. However, only a few researchers have examined this issue, all yielding somewhat mixed results. In all, the extant literature includes six relevant studies. The first is perceptions-based, offering residents’ opinions of how tower proximity influences property values (Bond and Beamish 2005). The second combines a similar perceptions-based component with an hedonic model to estimate sales price impacts (Bond and Wang 2005). The remaining four studies take a strictly empirical approach using hedonic modeling estimations and different types of spatial analysis techniques (Bond 2007a, b; Filippova and Rehm 2011; Locke and Blomquist 2016). Unfortunately, each study suffers from flaws of one sort or another—time invariant issues, inaccurate spatial modeling techniques, or other troublesome variable misspecifications. In essence, the results of these studies are either inconclusive or show only minimal negative price effects due to wireless tower proximity.

In our study though, we use a robust approach for gauging home values relative to tower proximity. Similar to others, our study includes hedonic modeling to capture distinctive property characteristics, yet it is distinctly different from others in two important respects. By performing the analysis within varying radii bands based on quartiles of the distance from the closest wireless tower, we are able to detect potential marginal price gradients of each property across the banded space. More importantly, by conducting a series of robust spatial econometric tests, we are able to identify and use the most unbiased, efficient spatial model that is best suited for the inferential analysis of our research question. The results underscore our concerns that previous studies may potentially suffer from bias due to their failures to address spatial correlation issues typical in hedonic model studies. Two significant reasons contribute to our apprehensions. The first is that Ordinary Least Squares (OLS) estimations are biased and inefficient in the presence of spatial correlations of dependent variables and residuals. The second is that by not accounting for spatial autocorrelation, it is unlikely any hedonic model can correctly disentangle either direct and/or indirect effects of (dis)amenities on housing prices. Research shows the latter is particularly useful when assessing the impact of corrective policy solutions subsequent to market failures (LeSage and Pace 2009). This is important because our research poses potentially significant policy implications, all of which we believe will most likely, yet for substantially different reasons, be of keen interest to governmental and planning officials, wireless tower operators and service providers, neighborhood activist groups, and private property rights’ advocates….


Truly, we currently live in the Age of Information. According to the International Communication Union of the United Nations, the number of wireless phone subscriptions totaled over 7 billion worldwide in 2015, with wireless coverage extending to 95% of the world’s population (United Nations, International Communication Union 2015). U.S. wireless usage is no less astounding, as evidenced by the 1045% increase in wireless device demand over the last 20 years (CTIA 2015). The future looks promising as well, with expectations that U.S. wireless industry employment will increase more than 31% from 2012 to 2017 (Pearce et al. 2013). Yet, even with the wireless industry poised for continued growth, it is unlikely it will be without consequences. Certainly, there are private benefits associated with the use of wireless service, yet there are costs as well. In this study, we examine one such cost: the impact of wireless towers on home values.

Although previous researchers have examined this issue, our study differs in two aspects. First, we address the econometric problem of spatial dependence that typically flaws hedonic price estimation analysis. We contend our empirical analyses are more efficient than those used in other studies, and as result, our results reveal greater consistency and reliability. Second, rather than rely solely on neighborhood-based property sales data, we test our hypothesis using recent property sales and current wireless tower locational data for an entire metropolitan statistical area, Footnote 13 which also happens to be one of the busiest port cities in the United States. Footnote 14

The results of a series of spatial statistical tests developed by Anselin et al. (1996) suggest that a spatial autoregressive model is the most appropriate econometric approach to test our research hypothesis. We conduct a marginal sensitivity analysis for homes within different radii of distances to the closest visible and non-visible wireless towers, basing the distance bands on quartiles of the distance to the wireless tower. Our results reveal wireless tower capitalization only in the value of those properties that are within approximately 0.72 km of a tower. On average, the potential external cost of a wireless tower is approximately $4132 per residential property, which corresponds to a negative price effect of 2.65%. The negative price impact of 9.78% is much more severe for properties within visible range of a tower compared to those not within visible range of a tower. This negative impact vanishes as radii distances exceed 0.72 km. In aggregate, the social welfare cost for the properties in our sample located within 0.72 km amounts to an approximate loss of $24.08 million dollars of value.

U.S. federal law prohibits wireless siting denial if no alternative site is available (FCC 1996; Martin 1997). However, given the apparent social costs associated with negative price effects, local zoning and regulatory authorities should consider granting approvals that include impact-minimizing conditions. For example, wireless tower construction approvals could require development and maintenance of visual or vegetative buffer screening. Concurrently or alternatively, approvals could mandate camouflaging towers to look like trees or flagpoles. Other types of approval conditions could dictate attachment of communication antennae systems to existing structures such as buildings, street light poles, electric utility poles, water towers, billboards, or even sports stadium super-structures. Clearly, society is dependent on wireless communication, and obfuscating efforts to expand or improve coverage makes little sense. Arguably, however, authorities overseeing the process have definitive obligations, perhaps even fiduciary ones, to safeguard the interests and well-being of those whom they serve.

Share Source: Environmental Health Trust