CPTs decrease property values

Some days ago, I was sent some links and a request to do a post on how CPTs would affect real estate property values within the neighborhood.

There is one name that kept popping up when searching for property value and CPT (mast, base stations). And that is Dr Sandy Bond.

This is part 1 of real estate property post. This post discusses published papers. Part 2 will discuss SMS neighborhood.

http://www.lincoln.ac.nz/staff-profile?staffId=Sandy.Bond

More information about Dr Sandy Bond:

http://www.buildingchi.com/meet.htm
http://www.buildingchi.com/contact.htm

Papers:

http://www.buildingchi.com/research.htm

Bond, S.G. (2007). “Cell Phone Tower Proximity Impacts on House Prices: a New Zealand Case Study”, Pacific Rim Property Research Journal, vol. 13, no. 1, pp. 63-91.

2006
Bond, S.G. and Squires, L. “Using GIS to Measure the Impact of Distance to Cell Phone Towers on House Prices in Florida”, American Real Estate Society Conference, April 19-22, Key West Florida.


Note: 650 feet ~= 200 meters
Note: 985 feet ~= 300 meters
Note: 1310 feet ~= 400 meters

Both papers state that negative media and, perceptions and sentiments of residents and buyers may play a more important role than what the governments say ("inconclusive"). The both state that property prices decreased after CPTs wer built around the neighborhood.

The papers diverge on how much property values decrease by and the distance from CPTs. In summary:
In NZ - Average 15% decrease until about 300 meters.
In FL - Average 2% decrease until about 200 meters.


I think there are serious limitations of these papers:
1. They don't tell us about the demographics, in particular, the age groups and ages of the occupants of the properties, bought before and bought after the towers were built.
Why do I ask? > Buyers of different age groups have different criteria when choosing a property. Those with young children will have yet other different criteria. (During the second Neighborhood Meeting, didn't an old gentleman who opposed the CPT at SMS said to "bring it on" to the old age home?)
Why do I ask? > Demographic profiles can also affect skepticisms, choice and ability to pay more expensive houses outside the control areas.
2. They don't tell us whether the CPTs are situated at school or park land, etc.
Why do I ask? >Buyers will not care if they don't have to get anywhere close to the CPTs. On the other hand, if the occupants are at school or frequent the park, the sentiments of the buyers can be very different.
Why do I ask? > Even hobbies and availability of other forms of entertainments around the area affect decisions.
3. They don't tell us the property price or property price to take home personal income ratio.
Why do I ask? > Buyers will care more about depreciation if the properties cost more and if price-income ratio is bigger.
Why do I ask? > Even sales tax percentage and income tax levels affect decisions.


If the papers were to take into account all these variables I mentioned, and more to give an accurate picture, they would be too complex to analyze fairly.




Here are the papers: (There are many versions of them, these 2 are the official or published ones, I think.)

For the New Zealand study: http://www.prres.net/Papers/PRPRJ_No_1_2007_Bond.pdf

Excerpt:

Interestingly, the effect of a tower on price (a decrease of between 20.7% and 21%) was very similar in the two suburbs where the towers were built in the year 2000, after the negative media publicity given to towers following the two legal cases outlined above. The other two suburbs that indicated a tower was either insignificant or increased prices by around 12%, had towers built in them in 1994, prior to the media publicity.

(Summary & Conclusion)
The results indicate that property prices decrease by around 15% after a CPBS is built. This effect generally reduces with distance from the CPBS and is almost negligible after about 300 meters. However, this result varied between neighbourhoods, with a positive impact on price being recorded in one neighbourhood, possibly due to the CPBS being built before there was any negative media publicity towards CPBSs and that the CPBS is better concealed than in the other neighbourhoods.


http://www.entrepreneur.com/tradejournals/article/171851340_1.html

Excerpt:

(ABSTRACT)
This article outlines the results of a study carried out in Florida in 2004 regarding the effect that cell phone tower proximity has on residential property prices. The study involved an analysis of residential property sales transaction data. Both GIS and multiple regression analysis in a hedonic framework were used to determine the effect of linear distance of homes to towers on residential property prices. The results of the research show that prices of properties decreased by just over 2%, on average, after a tower was built. This effect generally diminished with distance from the tower and was almost negligible after about 656 feet.

(in NZ)
The Bond and Beamish opinion survey study included residents in ten suburbs: five case study areas (within 100 feet of a cell phone tower) and five control areas (over 0.6 of a mile from a cell phone tower). Eighty questionnaires (7) were distributed in each of the ten suburbs in Christchurch (i.e., 800 surveys were delivered in total). An overall response rate of 46% was achieved.

What happened to the land and properties between 100 feet and 0.6 miles?

The survey study results were mixed, with responses from residents ranging from having no concerns to being very concerned about proximity to a tower. In both the case study and control areas, the impact of proximity to towers on future property values is the issue of greatest concern for respondents. If purchasing or renting a property near a tower, over one-third (38%) of the control group respondents would reduce the price of their property by more than 20%. The perceptions of the case study respondents were less negative, with one-third of them saying they would reduce price by only 1%-9%, and 24% would reduce price by between 10% and 19%.

Interestingly, the effect of a tower on price (a decrease of between 20.7% and 21%) was very similar in the two suburbs where the towers were built in 2000, after the negative media publicity given to towers following the two legal cases outlined above. In the other two suburbs, the results indicated a tower was either insignificant or increased prices by around 12%, where the towers had been built in 1994, prior to the media publicity.

In terms of the effect that proximity to a tower has on price the overall results indicate that this is statistically significant and negative. Generally, the closer a property is to the tower, the greater the decrease in price. The effect of proximity to a tower reduces price by 15% on average. This effect is reduced with distance from the tower and is negligible after 1000 feet.

(in Florida)
Variables
The study investigates the potential impact of proximity to a tower on the price of residential property, as indicated by the dependant variable SALE_PRICE. (10) The study controls for site and structural characteristics by assessing the impact of various independent variables. The independent data set was limited to those available in the data set and known to be related to property price, based on other well-tested models reported in the literature and from valuation theory. The independent variables selected include lot size in square feet (LOT), floor area of the dwelling in square feet (SQFT), age of the dwelling in years (AGE), the time of construction (AFTER_TWR), the closest distance of each home to the associated tower (DISTANCE), and the dwelling's absolute location is indicated by the Cartesian coordinates (XCOORD) and (YCOORD). (11)

Based on the parcel and tower data for Orange County, the mean sale price of single-family, residential property that sold between 1990 and 2000 is $115,850. The mean square footage is 1535 square feet, the mean lot size is 8525 square feet, and the mean age is 14 years. The mean distance from a residential property to a tower is 1813 feet. (13) Descriptive statistics for select variables are presented in Table 1.

Unfortunately, one has to pay to get Table 1.

The study hypothesis is that in areas where a tower is constructed, it will be possible to observe discounts made to the selling prices of homes located near these structures. Such a discount will be observed where buyers of homes close to the towers perceive them in negative terms due to, for example, the risk of adverse health, or aesthetic and property value effects.

To address the many difficulties in estimating the composite effects of externalities on property price an interactive approach is adopted. (18) To allow the composite effect of site, structure, and location attributes on the value of residential property to vary spatially, they are interacted with the Cartesian coordinates that are included in the model. (19)

To test the belief that the relationship between SALE_PRICE and other specific independent variables such as SQFT, AGE, and DISTANCE is not a linear function of SALE_PRICE, the variables were transformed to reflect the correct relationship. It was found that the best result was obtained from using the log of SALE_PRICE and the square of SQFT, AGE, and DISTANCE.

The results clearly show that the price of residential property increases with the distance from a tower. The independent variable, DISTANCE, estimates a coefficient with a positive sign, which increases with increasing distance from the tower (i.e., DISTANCE = 5.69E-05). As distance from the tower increases by 10 feet, price of a residential property increases by 0.57%. Moreover, the t-statistic associated with the estimated coefficient indicates the significance of the explanatory power of this variable (i.e., t-statistic = 10.751).

Limitations
This study analyzed residential property sales from different but neighboring suburbs as an entire data set, i.e., the suburbs were grouped together and analyzed as a whole. The absolute location was included in the model to take into account composite externalities as well as to allow these and other independent variables in the model to vary spatially, and therefore preclude the need to analyse neighborhoods separately. However, it is possible that not all neighborhood differences were accounted for.

For example, when comparing these results to those from the NZ study by Bond and Xue, it appears the results from both studies based on an analysis of the whole data set were similar. Towers have a statistically significant, but minimal, effect on the prices of proximate properties. However, what the NZ study showed by analyzing the suburbs separately was that substantive differences exist in the effect that towers have on property prices between suburbs, since the distribution of the property sale prices is quite different in each. It is possible that if the current study had analyzed suburbs separately that similar differences would have been found.

Summary and Conclusions
This article presents the results of a study carried out in Florida in 2004. The study involved the analysis of market transaction data of single-family homes that sold in Orange County between 1990 and 2000 to investigate the effect on prices of property in close proximity to a tower. The results showed that while a tower has a statistically significant effect on prices of property located near a tower, this effect is minimal.

So the conclusion for Florida is as claimed in abstract, "The results of the research show that prices of properties decreased by just over 2%, on average, after a tower was built. This effect generally diminished with distance from the tower and was almost negligible after about 656 feet."

Each geographical location is unique. Residents' perceptions and assessments of risk vary according to a wide range of processes including psychological, social, institutional, and cultural. The results of this study may vary with the NZ results not only due to the differences in study design (for example, this study excluded an analysis at a neighborhood level), but also due to differences in the landscape. In New Zealand, there are fewer structures such as high voltage overhead transmission lines, cell phone towers, and billboards than there are in the United States. As a result, it is possible that U.S. residents simply have become accustomed to these features and so notice them less.

The value effects from towers may vary over time as market participants' perceptions change due to increased public awareness regarding the potential (or lack of) adverse health and other effects of living near a towers. Further research into factors that impact on the degree of negative reaction from residents living near these structures could provide useful insights that help explain the effects on property price. Such factors might include, for example, the kinds of health and other risks residents associate with towers; the height, style, and appearance of the towers; how visible the towers are to residents and how they perceive such views; and the distance from the towers residents feel they have to be to be free of concerns.

As the results reported here are from a case study conducted in 2004 in a specific geographic area (Orange County, Florida) the results should not be generally applied. As Wolverton and Bottemiller explain,