# RECORD 51b11fac87d973139852a88a8c12a9cdbf87b57a
# TITLE: Hedonic Analysis of Forest Pest Invasion: the Case of Emerald Ash Borer
# YEAR: 2019.0  VENUE: Forests  DOI: 10.3390/f10090820
# AUTHORS: Xiaoshu Li; T. Holmes; Kevin J. Boyle; E. Crocker; C. Nelson
# PAGES: 15  CANDIDATE TABLE PAGES (1-based): [7, 10, 11, 12]
# ABSTRACT: The emerald ash borer (EAB) was first detected in North America in 2002, and since its introduction, this invasive pest has killed millions of ash trees. While EAB kills native North American ash trees in all settings, its impacts have been especially large in urban areas where ash has been a dominant street tree, especially in residential areas. While some management costs, such as insecticide treatment, tree removal, or tree replacement, are relatively straightforward to compute, the impact that EAB has had on residential property values is less clear. To better understand the economic cost of EAB in urban settings, we conducted a hedonic property value analysis to evaluate the impact of ash tree damages due to EAB infestation on housing sales prices. This study was conducted in the city of Milwaukee, Wisconsin, which had high stocking levels of ash trees prior to EAB’s arrival. The objectives of the study are to investigate: (1) how EAB-infested ash trees affect property values; (2) whether the benefits from healthy ash trees to property value change after arrival of EAB; and (3) whether healthy ash trees located within infested neighborhoods provide the same benefits as the healthy ash trees located outside of infested neighborhoods. In general, our results show that the EAB outbreak has had a negative impact on home values for properties located in close proximity to the ash tree component of the urban forest. This result holds true for neighborhoods where EAB does not yet pose an imminent threat, and is amplified for neighborhoods where EAB has been detected. Our results highlight the early stages of a dynamic economic process that impacts urban residential property owners subject to the risk of EAB or other tree pests and diseases. In general, we find that forward-looking behavior of residential property owners is capitalized into property values during the process of forest pest infestation.


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Article
Hedonic Analysis of Forest Pest Invasion: the Case of
Emerald Ash Borer
Xiaoshu Li 1,*
, Thomas P. Holmes 2
, Kevin J. Boyle 3, Ellen V. Crocker 4
and C. Dana Nelson 5
1
Center for Health Services Research, University of Kentucky, 740 South Limestone, J515 Kentucky Clinic,
Lexington, KY 40536, USA
2
Forestry Sciences Lab, Southern Research Station, USDA Forest Service, Research Triangle Park, NC 27709,
USA; tom.holmes@usda.gov
3
Agricultural and Applied Economics Department, Virginia Polytechnic Institute and State University, 430A
Bishop Favrao Hall, Blacksburg, VA 24060, USA; kjboyle@vt.edu
4
Department of Forestry and Natural Resources, University of Kentucky, 121 Thomas Poe Cooper Building,
Lexington, KY 40546, USA; e.crocker@uky.edu
5
Forest Health Research and Education Center, Southern Research Station, USDA Forest Service, 208 Thomas
Poe Cooper Building, Lexington, KY 40546, USA; charles.d.nelson@usda.gov
*
Correspondence: Xiaoshu.li@uky.edu; Tel.: +86-859-323-7078
Received: 29 July 2019; Accepted: 17 September 2019; Published: 19 September 2019





Abstract: The emerald ash borer (EAB) was first detected in North America in 2002, and since its
introduction, this invasive pest has killed millions of ash trees. While EAB kills native North American
ash trees in all settings, its impacts have been especially large in urban areas where ash has been a
dominant street tree, especially in residential areas. While some management costs, such as insecticide
treatment, tree removal, or tree replacement, are relatively straightforward to compute, the impact
that EAB has had on residential property values is less clear. To better understand the economic cost
of EAB in urban settings, we conducted a hedonic property value analysis to evaluate the impact of
ash tree damages due to EAB infestation on housing sales prices. This study was conducted in the
city of Milwaukee, Wisconsin, which had high stocking levels of ash trees prior to EAB’s arrival. The
objectives of the study are to investigate: (1) how EAB-infested ash trees affect property values; (2)
whether the benefits from healthy ash trees to property value change after arrival of EAB; and (3)
whether healthy ash trees located within infested neighborhoods provide the same benefits as the
healthy ash trees located outside of infested neighborhoods. In general, our results show that the
EAB outbreak has had a negative impact on home values for properties located in close proximity to
the ash tree component of the urban forest. This result holds true for neighborhoods where EAB does
not yet pose an imminent threat, and is amplified for neighborhoods where EAB has been detected.
Our results highlight the early stages of a dynamic economic process that impacts urban residential
property owners subject to the risk of EAB or other tree pests and diseases. In general, we find that
forward-looking behavior of residential property owners is capitalized into property values during
the process of forest pest infestation.
Keywords: emerald ash borer; property value; forward-looking behavior; urban forests; forest health
1. Introduction
The emerald ash borer (EAB) was first detected in North America in 2002, and is thought to
have been introduced from Asia by packaging materials [1]. Since its introduction, this invasive pest
has spread out from Michigan to over 30 states and killed tens of millions of ash trees. EAB is an
invasive wood-boring beetle that can kill ash trees within 2–4 years from infestation, as larvae tunnel
into the vascular system of the tree and cut offtranspiration of water and nutrients. Ash trees are
Forests 2019, 10, 820; doi:10.3390/f10090820
www.mdpi.com/journal/forests


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Table 1. Descriptive Statistics of Property Characteristic Variables (n = 4502). (EAB = emerald ash
borer).
Variable
Means
Standard Deviations
Description
Ln(Sale price)
11.642
0.009
Log transformation of sale price ($2005)
Living area
1.462
0.010
1000 ft2
Lot size
7.647
0.106
1000 ft2
Baths
1.900
0.012
Number
Bedrooms
3.200
0.012
Number
Age
65.000
0.372
Home age at sale; Years
Stories
1.200
0.006
Number
Air conditioning
67%
0.7%
1 if air-conditioned; 0 otherwise
Fireplace
32%
0.9%
1 if has fireplace; 0 otherwise
Pool
2%
0.2%
1 if a pool present; 0 otherwise
Basement area
1.029
0.005
1000 ft2
Garage area
0.410
0.002
1000 ft2
Distance to highway
2.300
0.030
Kilometers
Distance to railway
4.700
0.100
Kilometers
Distance to Airport
16.800
0.200
Kilometers
Water
1%
0.1%
Percentage of land covered by water in 1 km buffer
of parcel
Trees/Forest %
27%
0.1%
Percentage of land covered by trees and forest in 1
km buffer of parcel
Grass/herbaceous plants %
27%
0.1%
Percentage of land covered by grass & herbaceous
plants in 1 km buffer of parcel
Ash_parcel
31%
0.7%
1 if ash trees on the parcel; 0 otherwise
Ash_buffer0.1
30%
0.2%
Percentage of properties located within 0.1 km
buffer of parcel that have ash trees
Ash_buffer0.5
28%
0.2%
Percentage of properties located within 0.5 km
buffer of parcel that have ash trees
Ash_buffer1.0
27%
0.1%
Percentage of properties located within 1 km buffer
of parcel that have ash trees
EAB_parcel
0.002
0.001
Number of EAB infested ash trees within the parcel
EAB_buffer0.1
0.047
0.011
Number of EAB infested ash trees within 0.1 km
buffer of parcel
EAB_buffer0.5
1.217
0.142
Number of EAB infested ash trees within 0.5 km
buffer of parcel
EAB_buffer1.0
3.803
0.298
Number of EAB infested ash trees within 1 km
buffer of parcel
post
0.620
0.007
1 if sale occurred after 2011; 0 otherwise
outbreak
0.033
0.003
1 if EAB infested ash tree within 1 km of parcel
Within the study area, roughly equal proportions of the land area within 1 km of sales properties
were covered by trees/forest and grass/herbaceous plants (27% each; Table 1). Nearly one third (31%)
of sales parcels contained ash trees, and similar proportions of parcels within buffers up to 1 km
surrounding sales parcels also contained ash trees (27–30% of parcels). These statistics suggest that,
in terms of the ash component of the urban landscape, sales parcels were generally representative of
other residential parcels within the study area.
The summary statistics which describe the spread of EAB are listed in Table 2. These measurements
were based on the field surveys consistently conducted over four years. It shows that 16 ash trees were
infested in 2012, with 34 infested trees in 2013, 240 infested trees in 2014, and 528 infested trees in 2015
(Table 2). The sizes of the infested ash trees ranged from 3 to 40 inches, with a mean of 17.0 inches.
However, very few EAB-infested trees occurred on sales properties. In 2015, there were only four
property sales with infested ash trees identified on the parcel. If we assume the sale price could be
impacted by the EAB infested ash trees located within a 1 km buffer, there would be 222 property sales
impacted in 2015.


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Table 2. The Number of emerald ash borer (EAB) Infested Ash Trees and Impacted Properties with Sales.
Year
Total EAB
Parcel
Buffer 0.1 km
Buffer 0.5 km
Buffer 1 km
2012
16
0
1
13
32
2013
34
1
7
29
66
2014
240
0
12
81
164
2015
528
4
34
137
222
Total
5
54
260
484
4. Model Specification
4.1. Traditional Hedonic Model
A fixed-effect hedonic model was estimated to address the potential for spatially correlated
omitted variables in the model specification. The base model used to estimate the effects of ash trees
ln Pit = Ziα + Liβ + Ashiγ + τt + ωi + σit
(1)
where Pit is the sale price for property i at time t, Zi is a vector of property-specific characteristics and
distance measurements, measurements (distance to road, railway, and airport) are included in the
model in both linear and quadratic functional forms, τt is the time fixed-effect for the year of sale, ωi
is the spatial fixed effect specified based on the zip code of the sales property, and σit is the equation
error. This model is estimated for the years 2008–2011 to test the hypothesis that ash trees enhanced
residential property values prior to the EAB outbreak.
After the outbreak of EAB, the damages from EAB infestation would impact the property sales. In
Model 2, we constructed a fixed-effect hedonic model following the previous literature, which linked
the forest pest infestation together with property sale values.
ln Pit = Ziα + Liβ + EABitδ + τt + ωj + σit
(2)
The property sale data for estimating Model 2 run from 2012 to 2015. A statistically significant
negative coefficient estimate associated with EABit would suggest that the presence of infested trees in
the vicinity of residential properties decreases property value. The model is separately estimated for
each of the four different spatial specifications—parcel level, and the 0.1 km, 0.5 km, and 1.0 km buffers
(Table 1).
4.2. Quasi-Experimental Design
A limitation of the Model 2 specification is that it does not provide information on whether the
capitalized value of the entire stock of ash trees is affected by the EAB outbreak. After the arrival of
EAB, both infested and healthy ash trees had the potential to affect property values. This limitation
is addressed in Model 3, which estimates whether a structural change occurred in the capitalized
value of ash trees after the arrival of EAB. We construct a difference-in-difference model following the
quasi-experiment design, which could test the specific treatment effect by comparing the changes in sale
prices before and after the outbreak of EAB between the properties with ash trees in the neighborhood
and the other properties in the study area.
The property sale data for estimation is from 2008 to 2015. The hypothesis being tested here is
that the presence of infested ash trees within a 1 km buffer of the sales parcel provides a signal that
other ash trees near the property are at risk of becoming infested in the near future.
ln Pit = Ziα + +Liβ + Ashiγ + Ashi ∗posttρ + Ashi ∗outbreakitθ + τt + ωj + σit
(3)


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Table 3. Coefficient Estimates of Hedonic Model 1, Home Sales 2008–2011 (N = 1710).
Variable
Parcel
Buffer 0.1 km
Buffer 0.5 km
Buffer 1 km
Living area
0.212 ***
0.214 ***
0.215 ***
0.214 ***
(0.029)
(0.029)
(0.029)
(0.029)
Lot size
0.006 ***
0.004 **
0.004 **
0.004 **
(0.001)
(0.002)
(0.002)
(0.002)
Baths
0.069 ***
0.070 ***
0.068 ***
0.068 ***
(0.014)
(0.014)
(0.014)
(0.014)
Bedrooms
0.010
0.008
0.010
0.008
(0.012)
(0.012)
(0.012)
(0.012)
Age
−0.002 ***
−0.002 ***
−0.002 ***
−0.002 ***
(0.0004)
(0.0004)
(0.0004)
(0.0004)
Stories
0.082 ***
0.084 ***
0.081 ***
0.083 ***
(0.029)
(0.029)
(0.029)
(0.029)
Air conditioning
0.105 ***
0.106 ***
0.105 ***
0.105 ***
(0.015)
(0.015)
(0.015)
(0.015)
Fireplace
0.092 ***
0.089 ***
0.091 ***
0.092 ***
(0.016)
(0.016)
(0.016)
(0.016)
Pool
0.014
0.007
0.013
0.011
(0.052)
(0.052)
(0.052)
(0.052)
Basement area
0.125 ***
0.131 ***
0.124 ***
0.127 ***
(0.037)
(0.037)
(0.036)
(0.036)
Garage parking area
0.329 ***
0.323 ***
0.325 ***
0.324 ***
(0.049)
(0.049)
(0.049)
(0.049)
Distance to highway
0.041 ***
0.043 ***
0.044 ***
0.043 ***
(0.014)
(0.014)
(0.014)
(0.014)
Square Distance to highway
−0.007 ***
−0.007 ***
−0.007 ***
−0.007 ***
(0.002)
(0.002)
(0.002)
(0.002)
Distance to Railway
−0.036 ***
−0.034 ***
−0.032 ***
−0.030 ***
(0.011)
(0.011)
(0.011)
(0.011)
Square Distance to Railway
0.003 ***
0.003 ***
0.003 ***
0.003 ***
(0.001)
(0.001)
(0.001)
(0.001)
Distance to Airport
−0.030 ***
−0.030 ***
−0.028 ***
−0.028 ***
(0.006)
(0.006)
(0.006)
(0.006)
Square Distance to Airport
0.001 ***
0.001 ***
0.001 ***
0.001 ***
(0.0002)
(0.0002)
(0.0002)
(0.0002)
Water
0.151
0.132
0.059
−0.009
(0.322)
(0.321)
(0.323)
(0.326)
Trees/Forest
1.664 ***
1.514 ***
1.437 ***
1.429 ***
(0.206)
(0.211)
(0.225)
(0.220)
Grass/herbaceous plants
0.517 ***
0.461 **
0.440 **
0.454 **
(0.194)
(0.194)
(0.196)
(0.195)
Ash
0.005
0.165 ***
0.757 **
0.380 ***
(0.015)
(0.056)
(0.095)
(0.129)
constant
10.678
10.700 ***
10.665 ***
10.539 ***
(0.154)
(0.154)
(0.154)
(0.161)
Adjust R2
0.7558
0.7570
0.7567
0.7570
Note: *** denotes significant at the 1% level, ** denotes significant at the 5% level, * denotes significant at the 10%
level. Standard errors in parentheses.


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5.2. After the Outbreak of Emerald Ash Borer (EAB)
The presence of EAB-infested trees in nearby locations, combined with media attention given
to the growing outbreak, likely raised awareness among city residents that the entire stock of ash
trees in Milwaukee was at risk of infestation and death. This type of forward-looking behavior might
be detected in sales data, where EAB-infested ash trees are located in relatively close proximity to
sales properties. As the impact of nearby EAB-infested ash trees on home sales prices may be rather
subtle, a substantial number of observations that possibly include forward-looking behavior would be
needed to detect a measurable effect with statistical significance. Within our data, this possibility is
suggested, as the number of property sales within 0.1–1 km of EAB-infested trees ranges from 54 to
484 observations, respectively, representing roughly 2–17% of the 2792 sales after the EAB outbreak.
Model 2 includes EAB detections in the model specification, and results indicate that residents in
the general vicinity of known EAB detections were negatively impacted in terms of property values
by the outbreak (Table 4). While results are only statistically significant at the 1 km buffer level, and
the impacts per tree on housing price are rather small, this result may reflect an inadequate number
of impacted property sales to detect significant impacts for the other buffer levels. However, Model
2 suggests that nearby EAB detections provide a signal to homeowners that ash resources in their
neighborhood are at risk of infestation.
Table 4. Coefficient Estimates of Hedonic Model 2, emerald ash borer (EAB) Detections, 2012–2015
(n = 2792).
Variable
Parcel
Buffer 0.1 km
Buffer 0.5 km
Buffer 1 km
EAB
0.0006
0.0055
−0.0005
−0.0006 ***
(0.054)
(0.0060)
(0.0005)
(0.0002)
Adjusted R2
0.7737
0.7738
0.7738
0.7742
Note: *** denotes significant at the 1% level, ** denotes significant at the 5% level, * denotes significant at the 10%
level. Standard errors in parentheses.
Model 3 provided a more nuanced test of the hypothesis that residential property owners were
forward-looking and perceived a risk that healthy ash trees on, or close to, their property may become
infested in the future. The results of Model 3 estimation generally indicated that the capitalized value
of the entire stock of ash trees located near sales properties decreased as the EAB infestation spread
(Table 5). Two measures illustrate this result. First, by summing the coefficient estimates obtained for
ash trees over the entire study period (γ) and during the post-outbreak period (ρ), a diminishment in
the capitalized value of ash trees is observed that is statistically significant within each of the buffer
zones (Sum 1 = γ + ρ). For example, prior to the EAB outbreak, a one percentage point increase in the
number of properties containing ash trees located within 0.5 km of sales properties increased property
values by about 0.76% (Table 3). However, after the outbreak began, the marginal percentage increase
in home value from properties containing ash located in that buffer was only about 0.20%. Both of
these parameter estimates are significant at the 0.01 level. Second, adding the parameter estimate for
the variable indicating that an EAB infected tree had been located within 1 km of the sales parcel to the
previous measure (Sum 2 = γ + ρ + θ) can be seen to further reduce the capitalized value of ash trees.
The existence of a healthy ash tree would no longer statistically beneficial to the community.


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Table 5. Coefficient Estimates of Hedonic Model 3 for Ash and emerald ash borer (EAB) variables,
2008–2015 (n = 4502).
Variable
Parcel
Buffer 0.1 km
Buffer 0.5 km
Buffer 1 km
Ash
0.007
0.183 ***
0.298 ***
0.393 ***
(0.016)
(0.049)
(0.075)
(0.101)
Ash*Post
−0.002
−0.066
−0.102
−0.204 **
(0.020)
(0.056)
(0.077)
(0.098)
Ash*Outbreak
−0.021
−0.066
−0.093 *
−0.095 *
(0.028)
(0.048)
(0.051)
(0.054)
Adjusted R2
0.7647
0.7657
0.7658
0.7657
Sum 1
−0.005
0.117 ***
0.196 ***
0.188 **
γ + ρ
(0.040)
(0.042)
(0.064)
(0.090)
Sum 2
−0.026
0.050
0.103
0.093
γ + ρ + θ
(0.043)
(0.059)
(0.078)
(0.100)
Note: *** denotes significant at the 1% level, ** denotes significant at the 5% level, * denotes significant at the 10%
level. Standard errors in parentheses.
In Model 4, which includes the severity of EAB outbreak within a 1 km buffer in the model
specification, it is noted that the coefficient estimates for Ash*Outbreak are still negative but no longer
significant (Table 6). This is due to a high degree of correlation between this interaction variable
(indicating the occurrence of EAB) and the severity of an EAB outbreak (the number of infested trees).
Further, the negative effects from EAB-infested ash trees within a 1 km buffer are shown to be significant
at the parcel level and all buffer levels. These results suggest that one additional EAB-infested ash tree
within a 1 km buffer of a property decreases sales price by 0.1%. Based upon the average home price,
this result suggests that the decrease in sales price due to one additional EAB-infested ash tree within a
1km buffer is about $114. Looking at estimates of Sum 1 and Sum 2, it can be seen that these coefficient
estimates are similar to those estimates from Model 3 and indicate that the capitalized value of nearby
stocks of ash trees diminished after the onset of the EAB outbreak.
Table 6. Coefficient Estimates of Hedonic Model 4, Ash and emerald ash borer (EAB), 2008–2015
(n = 4502).
Variable
Parcel
Buffer 0.1 km
Buffer 0.5 km
Buffer 1 km
Ash
0.007
0.182 ***
0.301 ***
0.393 ***
(0.016)
(0.049)
(0.075)
(0.101)
Ash*Post
−0.005
−0.070
−0.104
−0.210 **
−(0.020)
−(0.056)
−(0.077)
−(0.098)
Ash*Outbreak
0.001
−0.011
−0.033
−0.044
(0.029)
(0.054)
(0.058)
(0.060)
EAB_Buffer3
−0.001 ***
−0.001 **
−0.001 **
−0.001 *
(0.0002)
(0.0003)
(0.0003)
(0.0003)
Adjusted R2
0.7650
0.7659
0.7660
0.7658
Sum 1
−0.011
0.112 ***
0.198 ***
0.183 **
γ + ρ
(0.040)
(0.042)
(0.064)
(0.090)
Sum 2
−0.010
0.100
0.164 **
0.139
γ + ρ + θ
(0.044)
(0.063)
(0.083)
(0.103)
Note: *** denotes significant at the 1% level, ** denotes significant at the 5% level, * denotes significant at the 10%
level. Standard errors in parentheses.


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6. Discussion and Conclusions
In our study, we conducted a hedonic analysis to investigate the impacts of the outbreak of EAB
on household property values in Milwaukee, Wisconsin. Our results show that, in general, tree cover
was positively capitalized into property values, and that prior to the arrival of EAB, ash trees added
a premium to the general value of tree cover. Although this value premium is not found for ash
trees located on individual sales parcels, it is consistently found for ash trees located at various buffer
distances in surrounding neighborhoods, suggesting that healthy ash trees (as well as tree cover of
general types of urban forest) provide a public good that is capitalized into home values. It is suggested
that the ash tree premium may be due to their widespread use as street trees within the study area.
Notably, the value premium attributed to ash trees throughout the study area (northern 10 zip codes
in Milwaukee) is dramatically diminished after the arrival of EAB infestation. This result holds true for
the entire study area, whether or not EAB-infested trees were found near sales properties, and suggests
that homeowners have forward-looking expectations regarding tree health in their neighborhoods.
These expectations are capitalized into diminishing values for ash trees. In general, static models that
only evaluate the impacts from existing damages to trees from insects and diseases will likely produce
downwardly-biased damage estimates in cases where biological invasions are expanding.
Although the capitalized value of ash trees diminished during the study period, our estimates
suggest they still contributed positive value to homeowners. This result may reflect the fact that
preventive measures, such as the use of insecticides, can protect ash tree health. Or, this result
may also reflect the fact that our study was conducted during the early stages of the EAB outbreak.
Whether or not ash trees retain a positive capitalized value during the later stages of an invasion is
unknown. However, we note that previous research has indicated that once an insect invasion reaches
a threshold value, all host trees, regardless of health condition, are capitalized into negative values by
homeowners [21]. The fact that our Milwaukee case study represents just one of many urban forested
areas impacted by EAB suggests that further analysis of this problem is warranted to help urban forest
managers understand the trade-offs between the cost and benefits of protective management activities.
While treatment ash trees are implemented on a two-year cycle in Milwaukee, there have not
yet been enough trees replanted for the lost ones. The plan is to replace removed ash trees with
diverse species of trees that are more resilient to biotic stressors and climate change. In our study, the
outbreak of EAB in Milwaukee is still in the early stage. Therefore, we did not consider the replacement
programs in the analysis. It will generally take a long time for the newly-planted trees to grow back.
The replacement programs should be able to increase property value in the long run. This would also
warrant further hedonic study to investigate the benefits from replacement management practices.
Our study result is highly flexible and useful for other non-native forest insects and pathogens. In
the evaluation studies of these long-lasting effects, more studies examining the dynamic response of
property values from invasive species are needed. Not only the tree health conditions, but also the
treatment and replacement procedures could impact property sale values, as they could potentially
change the expectation of property values based on our analysis results. Tracking the change of property
value related to invasive species during all the stages, including infestation, removal, treatment, and
restoration, would be useful to guide long-term management plans.
The EAB infestation is posing a significant threat of reduction in ecosystem services provided
by ash tree canopies. The value estimates from the hedonic model represent the portion of value
of ecosystem services provided by ash trees to the family residential properties, including largely
aesthetic views, recreational opportunities, and cultural values of trees. Comparing the estimates
from ash trees before and after the EAB infestation, we would be able to check the degradation of
these ecosystem services. However, the total economic value of benefits from numerous ecosystem
services provided by ash trees are not captured in the hedonic study. Further studies are needed to
investigate the reduction of value for other types of ecosystem services from EAB infestation, such as
carbon sequestration, reductions in stormwater runoff, or wildlife habitat.