Abstract
Power Lines and Perceived Home Prices: Isolating Elements of Easement Rights and Noise Pollution A u t h o r Michael J. Seiler This study is the first to use experimental design to look beyond the A b s t r a c t overall impact of power lines on property values by examining specific easement rights and noise pollution concerns. I find that in isolation, easement rights are associated with a non-significant reduction in property value, whereas noise pollution statistically significantly reduces property values. Interestingly, when easement rights are combined with noise pollution, the combined effect is more than additive. Results from the sample of eminent domain attorneys, who are valuation impact experts, reveals that females penalize a property more severely for being associated with power lines, and attorneys who typically represent property owners (as opposed to the condemnor) are more sympathetic to greater diminution values. The effect of the presence of power lines on home values has been examined many times and in many different contexts (e.g., Colwell and Foley, 1979; Hamilton and Schwann, 1995; Jaconetty, 2001; Des Rosiers, 2002; Wolverton and Bottemiller, 2003). Results vary tremendously from study to study and over time as well. The reason for these disparate results stems from the fact that power lines represent a multitude of concerns for the property owner. Specifically, what researchers have been unable to isolate are individual contributors such as the impact of a view, noise pollution, and a removal of specific property rights. The literature relating to the value of a view is voluminous, and researchers are clearly hampered by the difficulty in quantifying and standardizing what is meant by ‘‘view.’’ As a result, even if a power line study attempted to control for the (presumably negative) impact the view of a power line has on property values, quantifying the measure is imprecise, at best. Secondly, proximity damage and noise pollution are never mentioned in power line studies. There are many types of power lines, some of which have transformers that generate a hum, while others do not. Thirdly, power lines must be repaired and maintained by utility companies. When power lines cross over one’s property, the local utility company is typically granted an easement right, which allows them to enter the property. While the transfer of this property right to the utility company might seem trivial, property owners are indeed restricted by such easements in a meaningful way. Finally, the effect of power lines on home values is confounded by the proximity of the power lines to the home. J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u 4 8 S e i l e r The purpose of this study is to control for the ever-elusive ‘‘view’’ component, among other variables, by utilizing an experimental design. First, I create two otherwise identical power line treatments that only vary by ‘‘near versus distant’’ power lines. Next, I consider the near power lines and create additional treatments that hold all else constant except easement rights in one set of trials, and noise pollution in another. The findings show that power lines right behind the home (when compared to distant power lines) are associated with a $4,960 diminution in value on a $200,000 home. For the nearby power lines, noise pollution detracts from value in the amount of $3,920, whereas easement rights represent a nominal change in value. However, when combining the easement right transfer with noise pollution, the overall impact is a reduction in home value by $5,440 (a combined amount that is greater than the sum of its parts). While the magnitude of the results is in line with past studies (e.g., Seiler, Madhavan, and Liechty, 2012a), I offer a further contribution to the literature (beyond my ability to parse out very specific power line effects such as the testing of noise pollution and easement rights, which is simply not possible using traditional methods) in that the sample consists of true experts in the field of value impaction. Specifically, the results were collected during a live experiment at the American Law Institute-American Bar Association (ALI-ABA) conference attended by eminent domain attorneys from across the United States. Since their practices center on eminent domain and partial takings law, this sample of experts is highly compelling. While years of experience was not found to impact the results, attorneys who typically represent the property owner indicated a more negative impaction due to the power lines, whereas those who typically represent the condemnor (the party who takes the property and has to pay ‘‘just compensation’’ to the property owner indicated a lesser impact. Finally, women penalize property values with nearby power lines significantly more so than men. L i t e r a t u r e R e v i e w Because of the extreme difficulty in measuring the impact of power lines on residential property values, very little research has been undertaken in recent years. The most recent summary article by Pitts and Jackson (2007) explains that most studies find either no effect at all or a 21% to 210% diminution impact on property values. Studies that found no impact include Kinnard (1967), Kung and Seagle (1992), Cowger, Bottemiller, and Cahill (1996), and Wolverton and Bottemiller (2003). Studies that conclude a negative influence on property values include Colwell and Foley (1979), Delaney and Timmons (1992), and Kinnard and Dickey (1995). As explained in Jackson (2004), examples of the disparate results stem from such issues as view, distance to the power lines (implying varying degrees of health concerns), and even hot versus cold markets. Specifically, during upward moving, or hot markets, buyers are less concerned with the presence of power lines, whereas when the market softens, buyers can be more selective, and would prefer a home not located next to power lines. Another example includes the work by Des Rosiers (2002), who finds that higher-end custom homes are generally more P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 4 9 sensitive to the negative impacts of power lines than lower priced homes. This may well be due to the disagreement among experts as to whether or not power lines are a health concern and / or the greater number of housing options wealthier buyers have over those who are less affluent. In a relatively recent study by Des Rosiers (2002), which examined 507 single- family homes in a suburb of Montreal, Canada, declines in property value estimates ranged from 25% to 220%. Des Rosiers explains in great detail that there are numerous confluences that make measuring the impact difficult. He goes on to say frustratingly so that ‘‘despite its inherent weaknesses, the hedonic model remains the most reliable tool for measuring environmental negative externalities. . .’’ The hedonic method does have severe limitations and it is time for a new approach to be considered. This is precisely the motivation for using an experimental design and is the expressed purpose of the current investigation. E x p e r i m e n t a l D e s i g n Traditional studies use transactions data to identify the impact of power lines on home values. This approach requires the assumption that anything that impacts home values can be held constant by including the factors on the right-hand side of a hedonic model. While in reality the complete list of variables is unknown and many times unobservable, studies do their best to measure factors like national and local market conditions, lot size, home size (square footage, number of bedrooms, and bathrooms), property condition, construction quality, age, view, neighborhood characteristics (crime rates, school quality), and so forth. Still, no study is able to control for everything. By contrast, an experimental design creates an artificial environment where everything else is truly held constant. In this sense, it is the perfect design for studies that cannot possibly control for outside influences like view and specific power line characteristics. The drawback to using an experimental design, however, is whether or not the results found in the lab translate into the real world. In short, an experimental design is an alternative approach to traditional hedonics, and should not be viewed as either absolutely superior or inferior, but instead, should be viewed as more or less preferred within the specific context of what the researcher is examining. In the current investigation, I begin by holding constant all variables by creating a virtual home tour of a single residence with distant power lines, and then present another treatment associated with nearby power lines. A simple difference-in- difference comparison of their respective average home prices attributes a change in price to the sole attribute that was altered between the treatments (i.e., power line location—nearby vs. distant). After this effect is measured, I focus only on the nearby power line scenario. To examine the impact of easement rights, I again create two treatments: one where the attorneys are told easements are given to the local utility company and one where they are not. In a similar fashion, to examine the noise pollution aspect of power lines, participants are told that the transformers associated with the power lines do versus do not make a load humming noise. J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u 5 0 S e i l e r Exhibit 1A u Home Exterior with No Power Lines This is an image showing the exterior of the 3-D modeled home without power lines. Exhibit 1B u Home Exterior with Distant Power Lines This is an image showing the exterior of the 3-D modeled home with distant power lines. In rounding out the 2 3 2 matrix, the effects are combined to create the four combinations for nearby power lines: no easement, no humming; easement, no humming; no easement, humming; and easement, humming. All data were collected using a ‘‘within subjects’’ design. Screen captures of the three treatments are provided in Exhibit 1. P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 5 1 Exhibit 1C u Home Exterior with Near Power Lines This is an image showing the exterior of the 3-D modeled home with near power lines. D a t a All data were collected at the American Law Institute-American Bar Association (ALI-ABA) annual conference, which is attended by leading eminent domain lawyers from all across the U.S. During a regularly scheduled session, I conducted a live experiment incorporating instant feedback via technology known as an instant response device (IRD). An IRD is a credit card-sized device that allows participants to respond in real time to questions posed by the administrator. The responses to each question are received at the front of the room and stored in a Turning Technologies software program that can later be exported to Excel, and then imported into any statistical software package. As seen in Exhibit 2, Panel A, valid responses were obtained from 82 attorneys, 62 of which typically represent the property owner in eminent domain cases, the remainder of which typically represent the condemnor. Twelve of the attorneys were females, and the average eminent domain experience was over 18 years. Seventy-nine of the 82 attorneys were current homeowners. Because of the near unity of this variable, it was dropped from all subsequent analysis. R e s u l t s Panel B of Exhibit 2 reports the minimum, maximum, standard deviation, and mean property diminution values for a base case (a home without power lines) value of $200,000 on a scale from 1 ($204,000) to 9 (less than $172,000). When I consider the overall impact of power lines versus no power lines, I observe an effect no less than 24.9% (by comparing distant power lines to no power lines). J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u 5 2 S e i l e r Exhibit 2 u Descriptive Statistics Min. Max. Std. Dev. Mean Panel A: Sample demographic variables Current Homeowner 1 2 0.19 1.04 Gender 1 2 0.36 1.15 Years of Eminent Domain Experience 1 7 2.12 4.04 Attorney Type 1 2 0.43 1.24 Panel B: Power Line control variables Distant Power Lines 2 9 2.08 5.56 Near Power Lines—No easement; No humming 2 9 2.23 6.80 Near Power Lines—Easement; No humming 2 9 2.43 6.83 Near Power Lines—No easement; Humming 2 9 1.63 7.78 Near Power Lines—Easement; Humming 2 9 1.44 8.16 Notes: This exhibit displays minimum, maximum, standard deviation, and mean values for the five power line control variables, as well as for the four demographic control variables. Current Homeowner is set to 1 for those who currently own a home; 2 otherwise; Gender is set to 1 for males, and 2 for females; Years of Eminent Domain Experience is on a scale from 1 5 0–5 years, to 7 5 more than 30 years; and Attorney Type is set to 1 for attorneys who typically represent the property owner, and 2 if the attorney typically represents the condemnor. The overall mean scores from each column (C1 , C5) are compared using a series of paired-samples t-tests. Pair C2 & C3 is not statistically different from each other. Pair C4 & C5 is significant at 95%. All other pairings are significantly different at 99%. In a strictly within power line examination, nearby power lines are associated with a significantly greater mean diminution value when compared to distant power lines. When specifically examining easement and noise pollution effects, noise pollution significantly lowers property values, whereas a loss of easement rights does not. Taken together, the combined effect of noise pollution and easement loss is greater than the individual additive effects. Having confirmed my central supposition that more than the mere presence or absence of power lines matters, I now take a deeper examination of the responses in Exhibit 3. Exhibit 3 reports a breakdown of property value estimate responses by power line treatment. When moving from C1 to C5, there is a consistent downward shift in answers from prior ranges. Modal responses follow this general trend as the mode for C1 is 24%, the mode for C2 is 210%, and the modes for C3–C5 are less than 214%. But, might it be possible that the demographic characteristics of the attorneys are partially responsible for variations in these columns? To answer this question, I turn to Exhibit 4. Exhibit 4 segments the results from the prior exhibit by attorney type (whether the attorney typically represents the property owner or the condemnor) in Panel P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 5 3 Exhibit 3 u Breakdown of Power Line Controls by Frequency of Price Decline Distant Near Estimated Home Value C1 C2 C3 C4 C5 $204,000 (12%) 0.0% 0.0% 0.0% 0.0% 0.0% $200,000 (0%) 8.8% 7.6% 7.5% 1.3% 1.3% $196,000 (22%) 8.8% 0.0% 6.3% 0.0% 0.0% $192,000 (24%) 21.3% 15.2% 12.5% 3.8% 2.5% $188,000 (26%) 7.5% 5.1% 1.3% 7.5% 2.5% $184,000 (28%) 13.8% 5.1% 7.5% 5.0% 5.1% $180,000 (210%) 18.8% 20.3% 12.5% 13.8% 12.7% $176,000 (212%) 15.0% 15.2% 12.5% 12.5% 11.4% Less than $176,000 (214%) 6.3% 31.6% 40.0% 56.3% 64.6% Overall Mean Score 5.56 6.80 6.83 7.78 8.16 Notes: This exhibit reports the respondents’ opinion of the impact of each power line treatment on the value of the home. C1 represents Distant Power Lines; C2 represents Near Power Lines—No easement and No humming; C3 represents Near Power Lines—Easement, but No humming; C4 represents Near Power Lines— No easement, but with Humming; and C5 represents Near Power Lines—Easement and Humming. The overall mean scores from each column are compared using a series of paired-samples t-tests. Pair C2 & C3 is not statistically different from each other. Pair C4 & C5 is significant at 95%. All other pairings are significantly different at 99%. A and by gender in Panel B. As hypothesized, in Panel A, all mean property diminution scores are more severe for attorneys who typically represent the property owner. This can be seen in a downward shifting of values across home estimation values or by a simple comparison of overall mean scores. When comparing results by gender in Panel B, these differences are even more pronounced as evidenced by being statistically significant in four of the five comparisons. Until now, consistent with the experimental design methodology, univariate statistics have been used to measure the effects of the hypotheses. While these are sufficient given that an experimental design holds all else constant, I now turn to a traditional hedonic model to address the potential differences that exist amongst the respondents. Specifically, in Exhibit 5, I examine via regression if gender, years of experience in eminent domain, or attorney type (property owner vs. condemnor) influences the results. Consistent with the prior exhibit, the multivariate analysis confirms the univariate statistics that females significantly penalize more severely properties associated with power lines. Moreover, attorneys who typically represent property owners appear more sympathetic to the magnitude of valuation impaction, while experience with eminent domain has no effect. J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u 5 4 S e i l e r Exhibit 4 u Breakdown of Power Line Controls by Frequency of Price Decline, Attorney Type, and Gender Estimated Home Value C1-P C1-C C2-P C2-C C3-P C3-C C4-P C4-C C5-P C5-C Panel A: Attorney type $204,000 (12%) 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% $200,000 (0%) 6.7% 15.0% 8.5% 5.0% 6.5% 11.1% 1.6% 0.0% 1.7% 0.0% $196,000 (22%) 6.7% 15.0% 0.0% 0.0% 6.5% 5.6% 0.0% 0.0% 0.0% 0.0% $192,000 (24%) 25.0% 10.0% 8.5% 35.0% 8.1% 27.8% 1.6% 11.1% 1.7% 5.3% $188,000 (26%) 6.7% 10.0% 5.1% 5.0% 1.6% 0.0% 6.5% 11.1% 1.7% 5.3% $184,000 (28%) 16.7% 5.0% 6.8% 0.0% 8.1% 5.6% 4.8% 5.6% 5.0% 5.3% $180,000 (210%) 15.0% 30.0% 25.4% 5.0% 16.1% 0.0% 14.5% 11.1% 11.7% 15.8% $176,000 (212%) 18.3% 5.0% 10.2% 30.0% 9.7% 22.2% 12.9% 11.1% 11.7% 10.5% Less than $176,000 (214%) 5.0% 10.0% 35.6% 20.0% 43.5% 27.8% 58.1% 50.0% 66.7% 57.9% Overall Mean Score 5.63 5.35 6.97 6.30 7.03 6.11 7.98 7.50 8.23 7.95 P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 5 5 J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u Exhibit 4 u (continued) Breakdown of Power Line Controls by Frequency of Price Decline, Attorney Type, and Gender Estimated Home Value C1-M C1-F C2-M C2-F C3-M C3-F C4-M C4-F C5-M C5-F Panel B: Gender $204,000 (12%) 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% $200,000 (0%) 9.1% 8.3% 7.7% 8.3% 9.0% 0.0% 1.5% 0.0% 1.5% 0.0% $196,000 (22%) 9.1% 8.3% 0.0% 0.0% 6.0% 0.0% 0.0% 0.0% 0.0% 0.0% $192,000 (24%) 24.2% 0.0% 18.5% 0.0% 14.9% 0.0% 4.5% 0.0% 3.1% 0.0% $188,000 (26%) 6.1% 16.7% 6.2% 0.0% 0.0% 9.1% 7.5% 9.1% 3.1% 0.0% $184,000 (28%) 12.1% 25.0% 6.2% 0.0% 9.0% 0.0% 6.0% 0.0% 6.2% 0.0% $180,000 (210%) 19.7% 8.3% 18.5% 16.7% 14.9% 0.0% 14.9% 0.0% 12.3% 8.3% $176,000 (212%) 16.7% 8.3% 13.8% 25.0% 10.4% 27.3% 14.9% 0.0% 13.8% 0.0% Less than $176,000 (214%) 3.0% 25.0% 29.2% 50.0% 35.8% 63.6% 50.7% 90.9% 60.0% 91.7% c c Overall Mean Score 5.44 6.25 6.60 7.83 6.60* 8.36* 7.75** 8.64** 8.05* 8.83* Notes: This exhibit reports the respondents’ opinion of the impact of each power line treatment on the value of the home. C1 represents Distant Power Lines; C2 represents Near Power Lines—No easement and No humming; C3 represents Near Power Lines—Easement, but No humming; C4 represents Near Power Lines—No easement, but with Humming; and C5 represents Near Power Lines—Easement and Humming. Panel A parses the results by attorney type where, P represents attorneys who represent property owners and C represents attorneys who represent the condemnor. Panel B segments the results by gender where M is for males and F is for females. Tests of statistically significant differences are performed between each Overall Mean Score pair (e.g., C1-P versus C1-C; C2-P versus C2-C, etc.) in both panels. All significance tests are based on independent samples t-tests after a Levene statistic is calculated to determine the appropriate assumption concerning homogeneity of variance. *Significant at the 1% level. **Significant at the 5% level. 5 6 S e i l e r Exhibit 5 u Regression Results for Power Line Controls Distant Near Estimated Home Value C1 C2 C3 C4 C5 Intercept 4.34* 5.71* 6.21* 6.79* 7.55* (1.22) (1.32) (1.45) (1.00) (0.83) Gender 1.08 1.53** 1.90** 1.17** 0.91*** (0.69) (0.74) (0.81) (0.56) (0.47) Years of Eminent Domain Experience 0.10 0.08 20.02 20.10 0.02 (0.12) (0.13) (0.13) (0.09) (0.08) Attorney Type 20.34 20.82 21.17*** 20.53 20.41 (0.55) (0.59) (0.64) (0.44) (0.39) R 0.370 0.072 0.108 0.074 0.056 P-value 0.434 0.144 0.039** 0.130 0.239 F-Statistic 0.92 1.86 2.94 1.94 1.44 Notes: This exhibit reports regression estimates where the dependent variable is one of the five power line control variables and the independent variables represent respondent demographics. Specifically, C1 represents Distant Power Lines; C2 represents Near Power Lines—No easement and No humming; C3 represents Near Power Lines—Easement, but No humming; C4 represents Near Power Lines—No easement, but with Humming; and C5 represents Near Power Lines—Easement and Humming. Gender is set to 1 for males, and 2 for females; Years of Eminent Domain Experience is on a scale from 1 5 0–5 years, to 7 5 more than 30 years; and Attorney Type is set to 1 for attorneys who typically represent the property owner, and 2 if the attorney typically represents the condemnor. *Significant at the 1% level. **Significant at the 5% level. ***Significant at the 10% level. In an exploratory vein, in Panel A of Exhibit 6, I examine what might explain the differences in responses when moving from the treatment where power lines are distant versus when they are near. None of the respondent demographics are significant. As a robustness check, the same idea is measured as dummy variables where one represents the case where the respondent answered the same in both treatments, and zero otherwise. Again, none of the explanatory variables are significant. P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 5 7 Exhibit 6 u Regression Results for Differences in Power Line Controls Estimated Home Value C2-C1 C3-C1 C4-C1 C5-C1 Panel A: Difference scores Intercept 1.65*** 0.10 1.00 1.77 (0.09) (1.17) (0.91) (1.15) Gender 0.38 0.58 20.24 20.57 (0.51) (0.64) (0.50) (0.64) Years of Eminent Domain Experience 20.03 20.09 0.01 20.08 (0.09) (0.11) (0.08) (0.11) Attorney Type 20.54 20.31 0.27 0.41 (0.41) (0.51) (0.39) (0.52) R 0.031 0.033 0.010 0.022 P-value 0.516 0.503 0.874 0.661 F-Statistic 0.77 0.79 0.23 0.53 Panel B: Logistic regression dummy difference scores Intercept 4.26* 20.23 20.72 20.01 (1.56) (1.31) (1.32) (1.24) Gender 21.05 20.01 20.02 20.68 (0.78) (0.72) (0.72) (0.69) Years of Eminent Domain Experience 20.25*** 0.07 0.08 0.06 (0.15) (0.12) (0.12) (0.12) Attorney Type 20.55 20.35 0.08 0.85 (0.63) (0.58) (0.60) (0.61) 22 Log Likelihood 76.11 98.97 97.56 95.04 Cox & Snell R 0.060 0.013 0.031 0.041 Negelkerke R 0.091 0.017 0.042 0.056 Predicted Correct Percentage 77.6% 59.5% 59.5% 62.2% Notes: This exhibit reports regression estimates where the dependent variable is the difference between two of the five power line control variables and the independent variables represent respondent demographics. Specifically, C1 represents Distant Power Lines; C2 represents Near Power Lines—No easement and No humming; C3 represents Near Power Lines—Easement, but No humming; C4 represents Near Power Lines— No easement, but with Humming; and C5 represents Near Power Lines—Easement and Humming. Gender is set to 1 for males, and 2 for females; Years of Eminent Domain Experience is on a scale from 1 5 0–5 years, to 7 5 more than 30 years; and Attorney Type is set to 1 for attorneys who typically represent the property owner, and 2 if the attorney typically represents the condemnor. Panel A reports results for first difference scores, while Panel B reports the results from logistic regressions where the dependent variables in Panel A are dummied where 1 means the scores changed between the power line treatments, 0 otherwise. *Significant at the 1% level. ***Significant at the 10% level. J O S R E V o l . 6 N o . 1 – 2 0 1 4 u u 5 8 S e i l e r C o n c l u s i o n This study is the first to use an experimental design to more deeply examine the impact of power lines on property values. By using an experimental design, I am able to hold constant all outside factors and isolate the differential impact of power line location (near vs. far), easement rights, and noise pollution. In an examination of the overall impact of power lines, the findings show a diminution in value of as small as 24.9% (between no power lines and distant power lines). The distance from the home variable resulted in a price decline of approximately 22.5% ($4,960 on a $200,000 home), while noise pollution was closer to 22% ($3,920 on a $200,000 home). Easement rights are not statistically significantly different ($120), but interestingly, when combined with noise pollution, the result is more than the sum of its parts ($5,440 vs. $4,040). Because I examined very specific attributes of power lines, it is difficult to directly compare the results to other studies, which are unable to truly isolate each variable. Moreover, like any study attempting to quantify subjective pricing component variables such as power lines, view, or property rights, I am careful not to claim this one study answers all power line value questions in all geographic areas for all time to come. Instead, readers are cautioned to think of this study as the first step in what I hope other researchers will help turn into a portfolio of examinations in order to create an entire picture of the elusive relations among power lines, easement rights, noise pollution, and so forth. It should also be noted as a limitation that as demonstrated within the study, results can vary based upon the composition of the sample. I demonstrated the different responses from those attorneys who represent the property owner versus the condemnor. Might there also be differences between the buyers and sellers of these same properties? In general, it is reasonable to suppose that parties with a stake in the outcome of such an investigation might have different views on the magnitude of each effect. As such, readers are cautioned as to this possibility. Finally, while I was careful to design an experimental environment where everything is held constant, it is always possible that what is found in the lab might not translate into the real world. Further, not all power lines are the same in terms of size, noise, view impaction, and so forth. As such, the results are no more generalizable than any other study (such as those that use transactions data). Where the study makes a contribution is in my ability to parse out very specific power line effects, such as the testing of noise pollution and easement rights, which is simply not possible using traditional methods. E n d n o t e s The impact of proximity has been examined in reference to railways and similar means of transit in such studies as Gatzlaff and Smith (1993), Chen, Rufolo, and Dueker (1997), Haider and Miller (2000), Knaap, Ding, and Hopkins (2001), Weinberger (2001), Lin and Hwang (2003), Weinstein and Clower (2003), McMillien and McDonald (2004), Celik and Yankaya (2006), Hess and Almedia (2007), and Pan and Zhang (2008). P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 5 9 For example, consider a property owner who wants to build a fence around his property. The local utility firm has power lines that hang high overhead across the corner of his property. If the owner fences in the yard, he is responsible for taking the fence down to grant access to the power company whenever they need to repair / maintain their power lines. As a result, the property owner will either bear the expense of removing and reinstalling the fence each time the utility company wants access, or more likely, will reluctantly not build the fence. Either way, the easement right should diminish the value of the property because it restricts the use / enjoyment of the property or requires extra cost to maintain it (in the scenario where the property owner builds the fence). In experimental designs, ‘‘treatments’’ represent specific scenarios that differ only by the variable of interest. It is a way to hold everything else constant in the model except the variable being tested. See Turnbull (2012) for a discussion of eminent domain practices. It seems to be the case then that (1) attorneys gravitate to the legal side that is truly consistent with their underlying valuation impaction beliefs, (2) attorneys have come to believe the position they sell in court every day, or (3) respondents were hoping to sway public opinion by providing answers that would help support their legal positions. Based on the analyses to follow, it seems reasonable to discount the likelihood that (3) is responsible for the results. In addition to common sense, evidence that important variables may be missing include a low adjusted-R value associated with the hedonic model. For a detailed methodological discussion on behavioral methods, see Seiler, Madhavan, and Liechty (2012b) and Seiler (2014). Note that attorneys are offered the opportunity to indicate the property could either go up or down in value. The value for distant power lines is 5.56. Extrapolating, the 0.56 translates into $2,240 (0.56 3 $4,000). The ‘‘5’’ corresponds to the price of $188,000. Taken together, the estimated value is equal to $190,240 ($188,000 1 $2,240). Overall diminution is then equal to 4.9% ([$200,000 2 $190,240] / $200,000). $4,000 3 (6.80 2 5.56) 5 $4,960. The noise pollution effect is measured as $4,000 3 (7.78 2 6.80) 5 $3,920; the easement effect is quantified as $4,000 3 (6.83 2 6.80) 5 $120. $5,440 ($4,000 3 [8.16 2 6.80]) . $4,040 ($4,000 3 [7.78 2 6.80]) 1 $120 ($4,000 3 [6.83 2 6.80]). R e f e r e n c e s Celik, H. and U. Yankaya. The Impact of Rail Transit Investment on the Residential Property Values in Developing Countries: The Case of Izmir Subway, Turkey. Property Management, 2006, 24:4, 369–82. Chen, H., A. Rufolo, and K. Dueker. Measuring the Impact of Light Rail Systems on Single Family Home Values: A Hedonic Approach with GIS Application. Discussion Paper 97-3, Centre for Urban Studies, 1997. Colwell, P.F. and K.W. Foley. 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Transportation Research Record, 1722, Paper no. 00-0641, 2000. Hamilton, S.W. and G.M. Schwann. Do High Voltage Electric Transmission Lines Affect Property Values? Land Economics, 1995, 71:4, 436–44. Hess, D. and T. Almeida. Impact of Proximity to Light Rail Rapid Transit on Station-area Property Values in Buffalo, New York. Urban Studies, 2007, 44:5, 1041–68. Jaconetty, T.A. Do You Want Your Children Playing Under Those Things?: The Continuing Controversy About High Voltage Electromagnetic Fields, Human Health, and Real Property Values. Assessment Journal, 2001, 68:3, 23–30. Jackson, T. Surveys, Market Interviews, and Environmental Stigma. Appraisal Journal, 2004, Fall, 300–310. Kinnard, W. Tower Lines and Residential Property Values. Appraisal Journal, 1967, April, 269–84. Kinnard, W. and S. Dickey. A Primer on Proximity Impact Research: Residential Property Values Near High-Voltage Transmission Lines. Real Estate Issues, 1995, April, 23–29. Knaap, G., C. Ding, and L. Hopkins. Do Plans Matter?: The Effects of Light Rail Plans on Land Values in Station Areas. Journal of Planning Education and Research, 2001, 21: 1, 32–9. Kung, H. and C. Seagle. Impact of Power Transmission Lines on Property Values: A Case Study. Appraisal Journal, 1992, July, 413–18. Lin, J. and C. Hwang. Analysis of Property Prices Before and After the Opening of the Taipei Subway System. Annals of Regional Science, 2003, 38, 687–704. McMillen, D. and J. McDonald. Reaction of House Prices to a New Rapid Transit Line: Chicago’s Midway Line, 1983–1999. Real Estate Economics, 2004, 32:3, 463–86. Pan, H. and H. Zhang. Rail Transit Impacts on Land Use: Evidence from Shanghai, China. Transportation Research Board. Journal of the Transportation Research Board, 2008, 16– Pitts, J. and T. Jackson. Power Lines and Property Values Revisited. Appraisal Journal, 2007, Fall, 323–25. Seiler, M. Measuring the Impact of Eminent Domain Partial Takings: A Behavioral Approach. International Real Estate Review, 2014, 17:2, 137–56. Seiler, M., P. Madhavan, and M. Liechty. Ocular Tracking and the Behavioral Effects of Negative Externalities on Market Prices and Opinion. Journal of Housing Research, 2012a, 21:2, 123–37. ——. Toward an Understanding of Real Estate Homebuyer Internet Search Behavior: An Application of Ocular Tracking Technology. Journal of Real Estate Research, 2012b, 34: 2, 211–41. Turnbull, G. Delegating Eminent Domain Powers to Private Firms: Land Use and Efficiency Implications. Journal of Real Estate Finance and Economics, 2012, 45:2, 305–25. P o w e r L i n e s a n d P e r c e i v e d H o m e P r i c e s 6 1 Weinberger, R. Light Rail Proximity: Benefit of Detriment in the Case of Santa Clara County, California? Transportation Research Record. Journal of the Transportation Research Board, 2001, 1747, 104–13. Weinstein, B. and T. Clower. DART Light Rail’s Effect on Taxable Property Valuations and Transit-Oriented Development. Center for Economic Development and Research, University of North Texas, 2003. Wolverton, M.L. and S.C. Bottemiller. Further Analysis of Transmission Line Impact on Residential Property Values. Appraisal Journal, 2003, 71:3, 244–52. I would like to thank Joe Miller, President of HBA Architecture & Interior Design and Troy Hines, Designer, for providing us with the 3-D animations. I would also like to thank Maggi Davis of Keller Williams Realty in Virginia who created the voice- over recordings of the virtual home tour. I thank Turning Technologies in Youngstown, OH, for loaning me the Instant Response Devices (IRDs) and software used to collect the live sample. Finally, I thank the guest editors, Daniel Winkler and Frank Clayton, as well as the managing editor, Myla Wilson, regular editor, Norman Miller, and two anonymous referees. Michael J. Seiler, The College of William & Mary, Williamsburg, VA 23187- 8795 or Michael.Seiler@mason.wm.edu. 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Journal
Journal of Sustainable Real Estate
– Taylor & Francis
Published: Jan 1, 2014
