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/6 NMARSTON SCIENCE LIBRA
JUN 2 9 0
,2/ UNIVERSITY OF
J853 FLORIDA
Effects of Relandscaping on the Perceived Market
Value of Single Family Residential Property
FAMRC Industry Report 98-1
June 1998
A study sponsored by the FNGA Action Chapter
By
Robert L. Degner
Susan D. Moss
Florida Agricultural Market Research Center
Food and Resource Economics Department
Institute of Food and Agricultural Sciences
University of Florida, Gainesville, FL 32611
ABSTRACT
Professional nurserymen selected four single-family residences in the greater Orlando
area that were judged to be in need of relandscaping. Local landscape architects worked with
resident owners of the four properties to develop designs that were adapted to each micro
environment and each homeowners' needs and preferences. Each homesite was
photographed from the front (street) exposure prior to relandscaping and again after plant
material had been allowed to "grow in", a period of approximately 60 days. The "before"
and "after" photographs were shown to a random sample of 104 licensed real estate
professionals. The photos were shown in random order interspersed throughout a portfolio
of 35 photos of other single family residences of varying ages in the central Florida area.
The real estate professionals were asked to view each photo for 30 seconds and give an
estimate of the current market value and number of days-to-sale. The average perceived
market values of all four properties were greater after relandscaping, but the average
increases in value were sufficient to cover the costs of relandscaping in only two of the four
properties. Days-to-sale were significantly reduced for two properties.
FLORIDA AGRICULTURAL MARKET RESEARCH CENTER
The Florida Agricultural Market Research Center is a service of the Food and
Resource Economics Department. Its purpose is to provide timely, applied research on
current and emerging marketing problems affecting Florida's agricultural and marine
industries. A basic goal of the Center is to provide marketing research and related
information to producer organizations, trade associations, and governmental agencies
concerned with improving and expanding markets for Florida's agricultural and marine
producers.
Client organizations are required to pay direct costs associated with their research
projects. Such costs include labor for personnel and telephone interviewing, mail surveys,
travel and computer analyses. Professional time and support is provided to organized
producer groups at no charge by IFAS.
Professional agricultural economists with specialized training and experience in
marketing participate in every Center project. Cooperating personnel from other IFAS units
are also involved, whenever specialized technical assistance is needed.
Dr. Robert L. Degner, Director
Florida Agricultural Market Research Center
1083 McCarty Hall
University of Florida
Gainesville, Florida 32611-0240
(352) 392-1871 (Voice)
(352) 392-1886 (Fax)
DEGNER(FRED.IFAS.UFL.EDU (E-mail)
PREFACE
Over the past several years, results of this research have been formally presented to
members of the Action Chapter of the Florida Nurserymens and Growers Association
(FNGA), to hundreds of Central Florida residents at two annual Greater Orlando Home and
Garden Shows, and to members of the Florida State Horticultural Society.
Findings have been disseminated through a video tape entitled "Your Florida Home:
The Value of Relandscaping", through a paper published in the Proceedings of the Florida
State Horticultural Society, and a press release which was published by 23 newspapers
nationwide. This report provides methodological and analytical detail not previously
published.
We are very indebted to the Action Chapter of the Florida Nurserymens and Growers
Association their financial support of this pioneering effort to evaluate the economic benefits
of relandscaping single family residences. We also appreciate the Chapter's collective
patience with a project that had more than its share of setbacks and delays. We especially
thank Action Chapter members Bob Wiederhold, Pat Dehlinger, Charlie Brown, Mark Byrd
and Mike Rinck for their help throughout the project. Charlie Brown deserves special thanks
for his efforts in obtaining and providing plant material and installation labor for the four
subject properties. Thanks are also due Garth Schweitzer of Schweitzer Design Group
(Sanford) and Stephen Pategas, ASLA (Winter Park) for their design expertise in planning
the relandscaping of the subject properties.
Thanks are also extended to Dr. Robert Black, Consumer Horticulturist, University
of Florida, and to Al Williamson and Bill Abrams, of the Educational Media and Services
Department at the University of Florida for producing a video documentary of the
relandscaping process. The documentary is entitled "Your Florida Home: The Value of
Relandscaping" and is available through the Florida Agricultural Market Research Center.
The authors express gratitude to the four homeowners for their cooperation
throughout the entire relandscaping project. They are Mr. and Mrs. Keith Thomas, Mr. and
Mrs. Walter Cutler, Mr. and Mrs. Earl Latham, and Dr. Isaac Angel. Without their
cooperation, the project would not have been possible. We are also thankful for the
cooperation of Belton Jennings and Mike Roth of the Greater Orlando Association of
Realtors for their assistance in obtaining the cooperation of area realtors.
EXECUTIVE SUMMARY
S This study evaluates the affect of relandscaping on the perceived market value of
single-family residences.
S An "Ugly Yard" contest sponsored by the Action Chapter of the Florida Nurserymen
and Growers Association was advertised in the Orlando Sentinel. Participants
submitted color photographs of their properties. Out of 300 entries, 10 finalists were
selected by a committee from the Action Chapter. The committee then conducted
on-site inspections to choose the final four properties to be used in the study.
S Local landscape architects worked with homeowners to develop designs adapted to
each micro-environment and each homeowners' needs and preferences.
S Each homesite was then photographed from the front (street) exposure prior to
relandscaping and again after plant material had been established for two months.
S The "before" and "after" photographs were shown to a sample of 104 licensed real
estate professionals which had been randomly selected from the membership list of
the Greater Orlando Association of Realtors. Trained interviewers conducted face-
to-face interviews in respondents' offices.
S The eight photos of subject properties ("before" and "after" photos of the four
properties) were strategically placed within a portfolio of 35 color photos of single
family residences of varying ages in the central Florida area. The order in which the
portfolio was shown to respondents was rotated to reduce order bias. The real estate
professionals viewed each photo for 30 seconds and were then asked to estimate the
current market value and estimated days-to-sale for each property shown in the
portfolio.
S Analyses were conducted for each property to determine if the "before" and "after"
relandscaping values were statistically different. Days-to-sale were similarly
evaluated.
S This study indicates relandscaping can have a positive effect on real estate
professionals' perceived values and marketability of single family residences.
S While relandscaping increased the perceived value of all four properties and reduced
the "time-to-sale" for three properties, the increased value covered relandscaping
costs for only two of the four properties. However, this finding is significant for
homeowners contemplating reselling since real estate professionals can influence
listing prices and potential home buyers' perception of value.
INTRODUCTION
This study was sponsored by the Action Chapter (Orlando area) of the Florida
Nurserymen and Growers Association (FNGA) to determine if relandscaping could be a
viable market development option for the Central Florida woody ornamental plant industry.
Many industry leaders are of the opinion that relandscaping, if aggressively promoted, could
serve to beautify many residential areas of central Florida as well as improve financial
returns to producers of outdoor landscaping plant materials. Observation of residential
landscapes in Florida reveals that in a few short years many residential landscapes are
overgrown and in need of rejuvenation or relandscaping. Many also show the results of poor
initial design and plant selection.
Nurseries in other areas of the U.S. have successfully used visual presentations of
proposed relandscaping to increase revenues (Fenn, 1994). However, the effects of
relandscaping on market values and marketability of residential real estate have received
little attention.
OBJECTIVES
The primary objective of this study was to measure the impact of relandscaping on
the perceived market value and marketability of single-family residences. It was
hypothesized that professionally designed and installed landscaping would have a positive
effect on the perceived market values of single-family residential real estate. It was also
hypothesized that relandscaping would reduce the period of time required to sell such
property.
1
The ultimate goal of this study was to provide Florida nurserymen and landscapers
with research findings that could be used to promote relandscaping to homeowners.
Confirmation of the study's hypotheses could serve as a powerful sales tool: relandscaping
could not only serve to enhance properties' aesthetics and homeowners' satisfaction while
residing on the property, but in the event of resale, relandscaping could have financial
benefits as well.
METHODOLOGY
Professional landscapers selected four single family residences in the greater Orlando
area that were judged to be in need of relandscaping. Properties ranged in age from under
5 years to approximately 45 years. The property selection process involved participants in
an "Ugly Yard" contest sponsored by the Action Chapter of the Florida Nurserymen and
Growers Association (FNGA) and publicized in the Orlando Sentinel. Participants in the
contest were required to submit a minimum of two color photographs of their properties. Out
of 300 submitted entries, a group of 10 finalists was selected by a committee from the Action
Chapter. The committee visited each finalist property for closer inspection and interviewed
the homeowners. The committee was specifically looking for middle or upper middle
income properties with relandscaping potential. Examination of tax assessment records
revealed estimated market values of subject properties ranging from approximately $80,000
to $125,000. Homeowner cooperation with contractual conditions was also a consideration
in the final selection process. Homeowners were not permitted to make any changes in the
structure of their home for the duration of the project. They also agreed to remove vehicles,
2
garbage cans, and other unsightly items from front-street view to facilitate photography, and
they agreed to allow several photography sessions at different times of the day if necessary.
In return for their cooperation, homeowners received free design services. They also
received plant material, automatic irrigation systems and installation at cost.
Several local landscape architects worked with resident owners of the four properties
to develop designs that were adapted to each micro environment and each homeowners'
needs and preferences. Each homesite was photographed from the front (street) exposure
prior to relandscaping and again after plant material had been allowed to "grow in", a period
of approximately 60 days. The "before" and "after" photographs of each property were
carefully controlled for uniformity of exposure and viewpoint (Figures 1 and 2).
The "before" and "after" photographs were shown to a random sample of 104
licensed real estate professionals which were selected from the membership list of the
Greater Orlando Association of Realtors. Respondents were sent an official University of
Florida letter to legitimize the study, but they were not told the exact purpose. Trained
interviewers made appointments by telephone with the selected realtors, and conducted face-
to-face interviews in respondents', offices using the questionnaire found in Appendix A.
The eight photos of subject properties ("before" and "after" photos of the four
properties) were included in a portfolio of thirty-five 5"x7" color photos of single family
residences of varying ages in the central Florida area. Thus, there were eight subject photos
and 27 photos of other properties. Each photograph was accompanied by a brief, generic
description of the property which included the year built, the number of bedrooms, baths, and
covered parking spaces, heated and cooled square footage, lot size, and the general income
3
Figure 1. Properties "A" and "B" before and after relandscaping.
V Before
rAfter
3-2- 2 Built: 1952 3-2-2 Built: 1982
CH & A Lot Size: 80' 110'=8.800 sq ft CH & A Lot Size: 130'xl20'=15,600 sq ft
Square footage: Neighborhood: Square footage: Neighborhood:
1,400 + 400 garage Upper middle income, stable 2,100 + 460 garage Upper middle income, stable
Figure 2. Properties "C" and "D" before and after relandscaping.
Before Before
After After
3-2 -2 Built: 1985 3 -22 Built: 1991
CH & A Lot Size: 75'xl25'=9375 sq ft CII & A Lot Size: 80'xl20'=9,600 sq ft
Square footage: Neighborhood: Square footage: Neighborhood:
1,800 + 420 garage Upper middle income, stable 1,700 + 420 garage Upper middle income, stable
level of the neighborhood (Figures 1 and 2). These descriptions, which were brief and to the
point, were provided to add a touch of realism and to preclude realtors' questions about such
variables. The eight photos of subject properties were placed within the portfolio so that
none attracted attention due to primacy. Further, the subject properties were strategically
interspersed throughout the portfolio so that "before" and "after" photos of a given property
were separated by 15 photos of other properties. The order in which the portfolio was shown
to respondents was rotated to reduce order bias; thus half of the respondents were initially
exposed to "after" photos of each subject property and half saw "before" photos first. The
real estate professionals were allowed to view each photo for 30 seconds and then asked to
estimate the current market value and days-to-sale.
A paired t-test was conducted for each property using the difference between the
"before" and "after" relandscaping value estimates to determine if the difference in value
was statistically significant. This was defined as the "gross" change in values. A brief
review of hedonic price literature and a justification of the paired t-test is provided in
Appendix B. The same statistical procedure was used to evaluate the difference after the
costs were deducted from the "after" value estimate; this was defined as the "net" change
in value. Changes in days-to-sale estimates were also evaluated with a paired t-test.
In addition to examining the differences in overall property values, paired t-tests were
used to evaluate responses for each subject property by various demographic categories of
respondents.
6
Finally, realtors' age and years experience, education and gender were all examined
for possible associations with value and days-to-sale responses for each property using two
multiple linear regression models.
The general form of these two models was:
D-valueij or D-days i = f (agei or experience,, education,, gender,)
Where:
D-value j = differences in gross property
values, i.e., post-relandscaping value
minus pre-relandscaping value for
individual i and property j, where j =
properties A through D
D-days, = difference in days-to-sale estimates, i.e.,
post-relandscaping estimate minus pre-
relandscaping estimate for individual i
and property j
agent = age of individual i in years
experience = years experience in real estate profession
for individual i
education, = years of formal education for
individual i
gender, = 1 if male, 0 if female for individual i
Finally, each respondent was asked to name three characteristics, in order of
importance, that contribute most to a property's curbside appeal. These open-ended
responses were then categorized and ranked.
7
RESULTS AND DISCUSSION
The following sections address changes in the value of each of the four subject
properties, hypothesized to be the result of relandscaping. The "gross" differences in
"before" and "after" values ignore relandscaping costs, while the "net" differences reflect the
net change in values after relandscaping costs were deducted from the "after" values.
Relandscaping's effect on marketability was also examined. "Marketability" was defined as
the change in realtors' estimated days-to-sale, calculated as days-to-sale post relandscaping
minus days-to-sale prior to relandscaping. Thus, negative values indicate a reduction in
days-to-sale, hypothesized to be attributable to relandscaping.
Results oft-tests for differences in pre- and post- relandscaping property values and
days-to-sale estimates over all observations (n=104) are shown in Table 1. Results of t-tests
for various demographic categories are found in Appendix C, Appendix Tables 1 through 8.
Differences in perceived pre- and post-relandscaping values and days-to-sale
estimates associated with respondents' demographic characteristics were examined using the
ordinary least squares (OLS) models described in the methodology section above. Realtors'
ages and years experience in real estate were both obtained during the interviews. As
expected, these variables were highly correlated. After examining various models containing
either age or experience, it was found that it made little difference as to which was used.
However, results for the models including "years experience" are reported because of slightly
greater R2 values.
8
Table 1. Gross and net changes in perceived market value, and differences in days-to-sale for the four
residential properties.
Property
A B C D
Difference in gross value(dollars)a 8,351 1,058 2,481 7,549
t-value 4.622 t 0.499 0.125 3.386 t
Cost of relandscaping (dollars) 4,722 4,999 3,876 5,870
Difference in net value(dollars)b 3,629 -3,941 -1,394 1,679
t-value 2.008* -1.859 -0.869 0.753
Difference in days to sale (days) -15 -10 +3 -2
t-value 3.217 t 2.140* -0.952 0.556
" Difference in gross value ignores relandscaping costs.
b Relandscaping costs are deducted from "after" values, resulting in a net change in value.
Note: denotes statistical significance at the 0.05 level and 1 denotes significance at the 0.10 level.
9
In general, the OLS models explained little of the variation observed in the dependent
variables, i.e. differences in pre- and post landscaping values and days-to-sale estimates. R2
values were very low; the explanatory variables age (alternatively years experience) gender
and education usually explained only one to five percent of the total variation in the variation
in value differences or days-to-sale. Further, most t-tests on the parameter estimates were
not statistically significant. Thus, there appears to be little or no evidence that the perceived
effects of relandscaping were associated with realtors' age, experience, educational
attainment or gender.
The following subsections present detailed findings for each of the subject properties
which were evaluated in this study.
10
Property A
Built in the 1950's, Property A was the oldest subject property included in this study.
It was also on the smallest lot and underwent a comparatively drastic change in landscaping.
Changes in the plant material included new turf, woody ornamentals of varying sizes and
species, as well as colorful flowering annuals. In addition to changes in the plant materials
used for property A, a retention wall was added along the front of the property, and a straight
brick walkway was replaced by a curving concrete walkway running from the sidewalk
paralleling the street to the front door. A privacy wall was also added on one side of the
house which impacted the front-street view (Figure 1, property A).
On average, the realtors estimated that property A would sell for $88,887 before
relandscaping and $97,237 after relandscaping (Table 1, Figure 3). The perceived change
in market value after relandscaping property A averaged $8,351. This was the largest
difference in market value of the four subject properties. The cost of relandscaping property
A was $4,722, which yielded a net increase in perceived market value of $3,629 (Figure 4).
Property A was the only subject property to show a statistically significant change in
perceived gross and net market values (Table 1).
Property A also showed the largest reduction in days-to-sale estimates. Before
relandscaping, the realtors' estimates of number of days-to-sale averaged 122 days. After
relandscaping, the average days-to-sale estimate was 107 days, for a net reduction of 15 days
(Table 1, Figure 5).
Because of the relatively large differences in pre- and post- relandscaping values for
property A, many of the demographic categories reflected statistically significant
11
Figure 3. Average perceived values of subject properties before and
after relandscaping.
160,000 $128,454 $129,512
$111,211 $110,757
140,000 $97,237 $108,730 $103,20
120,000" $88,887
1 80,000-
.60,000-
< 40,000-
20,000
A B C D
Subject Properties
D Before relandscapng After relandscaping
Figure 4. Average perceived changes in home values compared with
relandscaping costs.
10,000- $8,351
9,000- $7,549
8,000 $5,870
7,000
S6,000- $4,722 $4,999
5,000- $3 876
4,000 $2,481
3,000- $1,058
2,000
1,000
A B C D
Subject Properties
O Change in value a Cost of relandscaping
Figure 5. Average estimated number of days-to-sale for subject
properties before and after relandscaping.
160-
140- 122 126
117 115
120- 107 110
10o-
80-
60-
40-
0-
A B C D
Subject Properties
0 Before relandscaping U After relandscaping
12
associations between pre- and post-relandscaping values or days-to-sale estimates and
realtors' experience, gender, or educational attainment (Table 2).
However, care must be used in interpreting the statistical significance of the t-tests
associated with the individual demographic categories. For example, a statistically
significant t-value on one age category and a non-significant t-value on another age category
does not mean that the variables for the two categories are significantly different from each
other. Rather, it signifies that the variable for the category with the statistically significant
t-value is significantly different from zero.
13
Table 2. Estimated effects of realtors' experience, gender and education on perceived differences in pre- and post- relandscaping and days-to-sale.
Explanatory variables
Experience Gender Education
Mean = 14.7 0.48 15.1
Dependent variable, Dependent variable Range= 1-50 0,1 12-20
property" mean Intercept -------------Parameter estimates ---------- R2
D-value, A 8,351 -6,140 -59 3,481 907 0.0226
D-days, A -14.69 -68.23 0.53 8.85 2.75 0.0447
D-value, B 1,058 31,591 -419 5,065 -1,775 0.0500
D-days, B -10.38 101.96 -0.06 8.12 -7.64** 0.0773
D-value, C 2,481 -6,268 182 -852 429 0.0125
D-days, C 3.39 -8.67 0.25 -2.06 0.62 0.0047
D-value, D 7,549 503 559* -10,296* 249 0.0793
D-days, D -2.21 16.09 -0.02 -6.45 -0.99 0.0109
"D-value" refers to the difference between post- relandscaping values and pre- landscaping values. Thus, a positive value reflects
an increase in property value hypothesized to be a result of relandscaping. "D-days" refer to the difference in days-to-sale. A
negative value indicates a reduction in days-to-sale. A negative value indicates a reduction in days-to-sale, hypothesized to be a
result of relandscaping.
Note: ** denotes statistical significance at the 0.01 level, significance at the 0.05 level, and t significance at the 0.10 level.
Property B
Property B was built in the early 1980's. It was situated on a corer lot that was
approximately one-third of an acre in size, considerably larger than the other subject
properties. Changes in the plant material included new turf and woody ornamentals of
varying sizes and species. Because of the larger lot size and two street exposures, the
changes were not as striking in the photographs as with property A (Figure 1, property B).
On average, the realtors estimated that property B would sell for $128,454 before
relandscaping and $129,512 after relandscaping (Figure 3). Thus, the perceived change in
market value after relandscaping property B averaged $1,058. This was the smallest change
in market value of the four subject properties. The cost of relandscaping property B was
$4,999 which yielded a net loss in perceived market value of $3,941. Property B did not
show statistically significant changes in estimated gross or net market values (Table 1).
However, property B did show a statistically significant reduction in days-to-sale estimates.
Before relandscaping, the realtors' estimates of number of days-to-sale averaged 136 days.
After relandscaping, the average days-to-sale estimate was 126 days for a net reduction of
10 days. Compared to the other three subject properties, only property A showed a greater
reduction in days-to-sale (Table 1, Figure 5).
Few statistically significant differences in pre- and post-relandscaping values were
found for the various demographic categories (Appendix Table 4). Also, no statistically
significant associations were found between value estimates and realtors' demographic
variables. However, there was a statistically significant negative association between days-
to-sale estimates and realtors' educational attainment (Table 2). This could mean that
15
respondents with more formal education took greater note of the effects ofrelandscaping and
reduced their days-to-sale estimates accordingly.
Property C
Property C was built in the mid 1980's on a modest sized lot. Changes in plant
material for property C were modest; two small trees were removed and a larger tree added
near the road. The turf, already in good condition, was not replaced. Existing foundation
plantings of woody ornamentals were replaced by newer, low-growing varieties and colorful
annuals in a more aesthetically pleasing design (Figure 2, property C).
Realtors estimated on average that property C would sell for $108,730 before
relandscaping and $111,211 after relandscaping, resulting in a change in the perceived gross
market value after relandscaping of $2,481 (Table 1, Figure 3). The cost of relandscaping
property C was $3,876 which yielded a net loss of $1,394. These changes in gross or net
estimated market values were not statistically significant (Table 1).
Pre- relandscaping, realtors' estimates of days-to-sale averaged 107. Post-
relandscaping, the average estimated dayo-to-sale was 110, for a net increase of three days.
However, this unexpected increase was not statistically significant (Table 1, Figure 5).
There were no statistically significant gross or net pre- and post-relandscaping values
for property C or for days-to-sale estimates for any of the demographic categories of
respondents (Appendix Tables 5,6). Further, the OLS models revealed no statistically
significant associations between changes in perceived property values or days-to-sale
estimates and realtors' experience, gender or educational attainment (Table 2).
16
Property D
Property D was the newest subject property included in this study. Built in the early
1990's, it was also situated on a modest sized lot, 80'x120'. Like property A, the
relandscaping effort was comparatively dramatic. Before relandscaping, the only plant
material in front of the home was healthy turf and small foundation plantings along the street
side perimeter of the house and garage. The most noticeable relandscaping effort included
the addition of pine trees, palm trees and some low-growing perennial plant material situated
in a large island in the center of the front yard and near the street. The monotonous
foundation plantings were replaced with a greater variety of woody ornamentals as well
(Figure 2, property D).
The realtors estimated that property D would sell for $103,208 before relandscaping and
$110,757 after relandscaping (Table 1, Figure 3). The perceived change in market value
after relandscaping property D averaged $7,549, the second highest difference in market
value of the four subject properties. The cost of relandscaping property D was $5,870 which
yielded net increase in perceived market value of $1,679. Property D showed a statistically
significant change in perceived gross market value, but not after the cost of relandscaping
was subtracted (Table 1).
Before relandscaping, the realtors' estimates of number of days-to-sale averaged 117
days for property D. After relandscaping, the average days-to-sale estimate was 115 days
for a net reduction in time-to-sale of two days. However, this difference was not statistically
significant (Table 1, Figure 5).
17
Because of the large variability for value and relatively small numbers of observations
for days-to-sale estimates, within the various demographic categories, few of the t-tests were
statistically significant (Appendix Tables 7,8). However, the OLS model indicated that the
change in property D's pre- and post-relandscaping value was positively associated with
realtors' professional experience. On average, a one year increase in realtors' experience was
associated with an increase of nearly $660 in the gross value of property D. Another
statistically significant finding was that males tended to evaluate property D rather harshly.
On average, male realtors' perceived change in value for property D was about $10,000
lower than that of females' (Table 2). One possible explanation for this large gender
difference is thought to lie in the new relandscaped design; several casual observers (not
respondents) have commented that the new design is "cutesy" and possibly high
maintenance. Male respondents may have held similar views, and since males are
frequently responsible for landscape maintenance, they may have consciously or
subconsciously reduced their estimates of the relandscaped property D. There were no
statistically significant relationships between days-to-sale estimates and any of the realtors'
demographic variables (Table 2).
18
After viewing photos of all the properties in the study portfolio, respondents were asked
to list the three most important characteristics, in order of importance, which contribute to
the "curbside appeal" of any given property (Table 3). The question was posed as strictly
open-ended. By far, landscaping ranked as the number one response, even though
respondents had not been told the specific purpose of the study in an effort to reduce
response bias. Out of 104 responses, 100 (96 percent) mentioned landscaping as the first,
second, or third most important characteristic affecting curbside appeal. Fifty-four (52
percent) ranked landscaping as the one most important home characteristic affecting
curbside appeal. Other commonly mentioned attributes included the condition of the paint,
the roof condition, general condition, and neatness and cleanliness of the exterior, each
mentioned by about 30 percent of all respondents. Other less commonly mentioned
characteristics were architectural aspects, paint color, neighborhood condition, location, lot
size, construction quality, age and the front door (Table 3).
19
Table 3. Realtors' rankings of"curbside appeal" characteristics.
Ranking of curbside appeal characteristics
Characteristics First Second Third All responses Percent ofTotala
(---------- Number of respondents ------------)
Landscaping 54 25 21 100 96.2
General Maintenance:
Paint condition 8 17 8 33 31.7
Roof condition 4 15 13 32 30.8
General condition 6 15 10 31 29.8
Neatness, cleanliness 12 5 8 25 24.0
Front door 1 2 2 5 4.8
Design, Quality & Age:
Architectural aspects 9 4 11 24 23.1
Paint color 3 9 4 16 15.4
Construction quality 1 2 1 4 3.8
Age 1 2 1 4 3.8
Neighborhood condition 2 3 11 16 15.4
Location 3 1 2 6 5.8
Lot characteristics 0 1 5 6 5.8
Size of lot 0 1 0 1 1.0
" Percentages are based upon 104 respondents.
20
CONCLUSIONS
In conclusion, this study indicates that relandscaping can have positive effects on real
estate professionals' perceived values and marketability of single family residences.
Relandscaping increased the perceived value of all four and reduced the estimated "time-to-
sale" for three of the four properties. However, the increases in perceived values were
sufficient to cover relandscaping costs for only two of the four properties. This finding is
significant for homeowners contemplating selling their property, because real estate
professionals can influence listing prices and potential home buyers' perception of value as
well. Further, the "Ugly Yard" contest used to select the subject properties for this study
revealed considerable interest in relandscaping among central Florida residents. This
interest may indicate an unmet need among homeowners for professional assistance with
relandscaping. Experience among nursery operators in other areas has shown that
homeowners are more likely to purchase relandscaping when dramatic "before" and "after"
results can be demonstrated. Although it was not available for this study, the advent of
digital photography has made customized "before" and "after" demonstrations practical and
feasible for homeowners' specific properties. This technique has been used as a very
effective sales tool (Fenn, 1995). Further, there was a strong consensus among realtors that
landscaping was the most significant factor affecting curbside appeal. Thus, the landscape
probably warrants greater attention from homeowners preparing their property for resale.
The results of this study, coupled with appropriate relandscaping planning and digital
photography, could be used as effective market development tools for the Florida nursery
industry.
21
BIBLIOGRAPHY
Coulson, N. Edward, Eric W. Bond, A Hedonic Approach to Residential Succession," The
Review of Economics and Statistics 72 (August 1990), 433-444.
Fenn, D. 1994. "Picture This." Inc. magazine. Boston, MA.
Gillmeister, William J., Robert D. Yonkers, James W. Dunn, "Hedonic Pricing of Milk
Components at the Farm Level," Review ofAgricultural Economics 18 (May 1996),
181-192.
Kim, Sunwoong, "Search, Hedonic Prices and Housing Demand," The Review of Economics
and Statistics 74 (August 1992), 503-508.
Ladd, George W., Veraphol Suvannunt, "A Model of Consumer Goods Characteristics,"
American Journal ofAgricultural Economics 58 (August 1976), 504-510.
Lancaster, Kelvin J., "A New Approach to Consumer Theory," The Journal of Political
Economy 74 (April 1966), 132-157.
Palmquist, Raymond B., "Estimating the Demand for the Characteristics of Housing," The
Review of Economics and Statistics 66 (August 1984), 394-404.
Rosen, Sherwin, "Hedonic Prices and Implicit Markets: Product Differentiation in Pure
Competition," Journal of Political Economy 82 (January 1974), 34-55.
Snedecor, George W. and William G. Cochran (1967), Statistical Methods, The Iowa State
University Press, Ames, Iowa.
Tronstad, Russell, Lori Stephens Huthoefer, Eric Monke, "Market Windows and Hedonic
Price Analyses: An Application to the Apple Industry," Journal ofAgricultural and
Resource Economics 17 (December 1992), 314-322.
Waugh, Frederick V., "Quality Factors Influencing Vegetable Prices," Journal of Farm
Economics 10 (1928), 185-196.
Witte, Ann D., Howard J. Sumka, and Homer Erekson, "An Estimation of a Structural
Hedonic Prices Model of the Housing Market: An Application of Rosen's Theory
of Implicit Markets," Econometrica 47 (September 1979), 1151-1173.
22
APPENDIX A: Survey Instrument
23
Name:_
Firm:
Street Address:
Mailing Address:
Phone:
Contacted:
Interview Date:
RELANDSCAPING PROJECT
REAL ESTATE AGENT/APPRAISER SURVEY
INTRODUCTION
The Florida Agricultural Market Research Center at the University of Florida in Gainesville is
conducting a survey of licensed real estate professionals in the greater Orlando area. The purpose of
the study is to estimate the relationship between "curbside appeal" and actual sales prices of
selected residential properties shown in a series of photographs.
You are one of only 100 people randomly chosen to participate in this study, so your responses are
especially important to us. You and your company will receive an acknowledgement in our final
report, if you like, and you will receive a copy of the findings for your use as well.
I will show you a series of 35 photographs of residential properties that have been especially selected
for this study. All subject properties are single family residences in middle to upper-middle income
areas. Square footage and amenities are "average" for neighborhoods on subdivisions where they are
located.
You will be given 30 seconds to view each property, at the end of which time you are to tell me your
best specific estimate (not a range) of its current value. After you have studied a photo, you will not
have a chance to go back for a second look. Immediately after you have given me you estimate of the
value of the property, give me an estimate of the number of days the property would have to be on the
market to obtain the price you gave. DO NOT GET "BOGGED DOWN" with data on specific
properties. All properties are in stable, desirable neighborhoods. Again, we are trying to determine
the correlation between curbside appeal and market value.
Your price estimates and any other information will remain strictly confidential.
25
Version 1 Relandscaping Project
Real Estate Agent Questionnaire
Photo Order Estimated Value Days to Photo Order Estimated Value Days to
Dollars Sale Dollars Sale
01 31
02 32
03 33
04 34
05_ 35
06
07
08 Note: A second version of this questionnaire
09 reversed the order in which the 35 photos were
10 shown.
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
26
Additional Questions
1. With respect to "curbside appeal", what three things do you feel are most important (in order)
[Probe].
(1)
(2)
(3)
2. How many years, in total, do you have in the real estate business? How many years as a
licensed real estate agent or broker? How many additional years in real estate experience
(specify)?
Total years
Years as licensed agent/broker
Years other experience
What professional certifications) do you hold?
[Make certain total years experience is the sum of all others!]
3. In what type of housing do you currently reside (primary residence)? (Circle one)
(a) single family
(b) duplex
(c) multi-family apartments
(d) multi-family condo
(e) Other (Hotel, etc.)
4. What is the highest grade of school you completed? (Circle number)
High School 9 10 11 12
College/Vocational 13 14 15 16 Degree?
Grad/Professional 17 18 19 20 Degree?
[By Observation]
5. Gender: Male Female
6. In what year were you born?
27
APPENDIX B: Hedonic Pricing
28
Hedonic Pricing Literature
To estimate the value of relandscaping, the effect of the amenity of landscaping on the
purchase price of the house must be determined. This type of analysis is typically done in the
framework of a hedonic pricing model. In hedonic pricing models, the effect of changes in
the attributes of a commodity on its market price is estimated. Research efforts aimed at
determining such effects on market price have included evaluation of characteristics such as
the fiber length of cotton, the color of asparagus, the length of the cucumber, etc. This
appendix describes the overall hedonic pricing framework and reviews the specific literature
on housing.
The literature on hedonic pricing is well established. Waugh (1927) wrote about
valuing the characteristics of vegetables such as green asparagus, long cucumbers, and the
condition of tomatoes. More recent examples include the hedonic pricing of milk components
(Gilmeister, Yonkers, and Dunn), fresh tomatoes (Bierlen and Grunewald), apples (Tronstad,
Huthoefer, and Monke), and cotton (Ethridge and Davis).
Formally, hedonic pricing literature can be traced back to Lancaster who speculated
that a good does not give utility in and of itself. Instead, the consumable attributes of the
good yields utility. Within this framework, the market price of the good can then be
decomposed into a price for each attribute. Mathematically, following Ladd and Suvannunt,
P =E +ElxI +E2X2i +...Em xi +e (1)
Where p, is the price of good i, Ej is the price of attribute j, x, is the amount of attributed
contained in good i, and ei is the error term in equation 1. The typical approach is to collect
prices for various goods. The price or value of each good can then be regressed on each
good's attributes to yield an estimated price for each attribute.
29
This approach has also been applied in the housing literature to estimate prices of
housing attributes. For example, Witte, Sumka and Erekson estimated implicit prices for
housing attributes such as dwelling quality, dwelling size and lot size. Palmquist broadened
the scope from individual housing attributes to include socio-economic variables, as well as
size, age, condition, etc. Coulson and Bond estimated how characteristics of housing units
affected neighborhood turnover in six U.S. cities, and Kim used hedonic price models in his
estimation of rental housing demand.
In this study, we look at the price difference between the same house before and after
relandscaping. Letting x, be the quantity of landscaping, the price of the house could be
expressed as
(2)
p, = E +Ex +E2x2 +E3x3 +...
If x, is the quantity of landscaping before treatment and x. is the quantity of
landscaping after treatment, the change in the price of the house becomes
p, -f, =E,(x -F) (3)
By repeated samples on the same house, the average price change can be derived as
T T
E (P-fj) =(X I-)E E, (4)
t=1 t=1
Hence, a paired t-test of price changes yields an estimate of the price effect of landscaping.
30
Appendix C: Tables
31
Appendix Table 1. Realtors' estimates of "before" and "after" values by demographic categories, Property A.
Average
Average value Average value difference in Average Paired t test of Paired t test of
Demographic Percent of before after gross value difference in difference in gross difference in net
categories Number total relandscaping relandscaping (after-before) net value value value
(dollars) (dollars) (dollars) (dollars) t Prob>t t Prob>t
Gender
female 54 51.9 91,302 97,628 6,326 1,604 2.3339* 0.0234 0.5917 0.5565
male 50 48.1 86,278 96,816 10,538 5,816 4.4916** 0.0001 2.4789* 0.0167
Age
28-39 21 20.2 86,381 99,476 13,095 8,373 5.4534** 0.0001 3.4869** 0.0023
40-49 28 26.9 88,286 95,429 7,143 2,421 1.7769t 0.0868 0.6022 0.5520
50-64 46 44.2 89,465 96,846 7,381 2,658 2.5435* 0.0145 0.9162 0.3645
65-80 9 8.7 93,644 99,644 6,000 1,278 1.0617 0.3193 0.2262 0.8268
Education
high school 13 12.5 86,500 88,615 2,115 -2,607 0.3243 0.7513 -0.3996 0.6965
some college 37 35.6 91,184 98,189 7,005 2,283 2.1687* 0.0368 0.7069 0.4842
college graduate 41 39.4 85,534 96,651 11,117 6,395 4.0930** 0.0002 2.3545* 0.0235
post baccaulareate 13 12.5 95,308 105,000 9,692 4,970 3.2049** 0.0076 1.6435* 0.0126
Years Experience
1-5 15 14.4 87,333 93,867 6,534 1,811 1.7698t 0.0985 0.4907 0.6313
6-10 22 21.2 88,136 97,818 9,682 4,960 1.7977t 0.0866 0.9209 0.3676.
11-15 27 26.0 94,500 100,778 6,278 1,556 2.4045* 0.0236 0.5959 0.5564
16-20 21 20.2 83,090 95,804 12,714 7,992 2.7324* 0.0128 1.7176 0.1013
21-25 7 6.7 75,571 89,143 13,572 8,849 3.0424* 0.0227 1.9800t 0.0945
26-30 5 4.8 103,980 1-07,600 3,620 -1,102 0.3664 0.7326 -0.1115 0.9166
>30 7 6.7 92,843 93,971 1,128 -3,593 0.2635 0.8010 -0.8389 0.4336
All respondents 104 100.0 88,887 97,238 8,351 3,629 4.6218** 0.0001 2.0084* 0.0472
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
Appendix Table 2. Demographic categorization of realtors participating in the study and their average responses
regarding days-to-sale for Property A.
Average
Average Average difference in Paired t test
Demographic Percent of days-to-sale days-to-sale days-to-sale of difference in
categories Number total before after (after-before) days-to-sale
(days) (days) (days) t Prob>t
Gender
female 54 51.9 135 113 -22 -2.8330** 0.0065
male 50 48.1 108 101 -7 -1.5753 0.1216
Age
28-39 21 20.2 128 111 -17 -1.2749 0.2170
40-49 28 26.9 117 103 -14 -2.4721* 0.0200
50-64 46 44.2 119 107 -12 -1.8368t 0.0728
65-80 9 8.7 134 111 -23 -2.4009* 0.0431
Education
high school 13 12.5 142 116 -26 -1.4338 0.1772
some college 37 35.6 126 107 -19 -2.6838* 0.0109
college graduate 41 39.4 113 101 -12 -1.7225t 0.0927
post baccaulareate 13 12.5 116 116 0 0.0000 1.0000
Years Experience
1-5 15 14.4 132 102 -30 -2.7844* 0.0146
6-10 22 21.2 115 114 -1 0.1115 0.9123
11-15 27 26.0 125 99 -26 -2.6278* 0.0142
16-20 21 20.2 107 102 -5 -0.5881 0.5631
21-25 7 6.7 150 120 -30 -1.9406 0.1004
26-30 5 4.8 120 108 -12 -1.0000 0.3739
>30 7 6.7 121 128 7 0.3169 0.7621
All respondents 104 100.0 122 107 -15 -3.2167** 0.0017
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
33
Appendix Table 3. Realtors' estimates of "before" and "after" values by demographic categories, Property B.
Average
Average value Average value difference in Average Paired t test of Paired t test of
Demographic Percent before after gross value difference difference in difference in net
categories Number of total relandscaping relandscaping (after-before) in net value gross value value
(dollars) (dollars) (dollars) (dollars) t Prob>t t Prob
Gender
female 54 51.9 130,619 131,182 563 -4,436 0.1168 0.8681 -1.3145 0.194
male 50 48.1 126,116 127,708 1,592 -3,407 0.6321 0.5302 -1.3528 0.182
Age
28-39 21 20.2 125,381 127,095 1,714 -3,285 0.5370 0.5972 -1.0289 0.315
40-49 28 26.9 124,496 130,429 5,933 933 1.308 0.2019 0.2058 0.838
50-64 46 44.2 130,967 129,857 -1,110 -6,109 -0.3196 0.7508 -1.7578 t 0.085
65-80 9 8.7 135,089 130,533 -4,556 -9,555 -0.8348 0.4281 -1.7508 0.118
Education
high school 13 12.5 125,423 131,538 6,115 1,116 0.8789 0.3967 0.1604 0.875
some college 37 35.6 127,403 131,724 4,321 -677 1.1402 0.2617 -0.1787 0.859
college graduate 41 39.4 130,900 126,851 -4,04 -9,048 -1.4357 0.1589 -3.2084** 0.002
post baccaulareate 13 12.5 126,762 129,577 2,815 -2,184 0.4331 0.6726 -0.3359 0.742
Years Experience
1-5 15 14.4 122,667 126,133 3,466 -1,532 0.5428 0.5958 -0.2399 0.813
6-10 22 21.2 133,000 136,364 3,364 -1,635 0.9667 0.3447 -0.4700 0.643
11-15 27 26.0 128,944 132,000 3,056 -1,943 0.7559 0.4565 -0.4807 0.634
16-20 21 20.2 121,757 122,138 381 -4,618 0.0606 0.9522 -0.7351 0.470
21-25 7 6.7 125,429 123,429 -2,000 -6,999 -0.3714 0.7231 -1.2997 0.241
26-30 5 4.8 140,580 132,280 -8,300 -13,299 -1.0816 0.3403 -1.7330 0.158
>30 7 6.7 139,129 131,843 -7,286 -12,285 -0.9969 0.3573 -1.6809 0.143
All respondents 104 100.0 128,454 129,512 1,058 -3,941 0.4988 0.6190 -1.8588t 0.065
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
Appendix Table 4. Demographic categorization of realtors participating in the study and their average responses
regarding days-to-sale for Property B.
Average Average Average
days-to-sale days-to-sale difference in Paired t test of
Demographic Percent before after days-to-sale difference in
categories Number of total relandscaping relandscaping (after-before) days-to-sale
(days) (days) (days) t Prob>t
Gender
female 54 51.9 151 141 -10 -1.2228 0.2268
male 50 48.1 120 109 -11 -2.1706* 0.0348
Age
28-39 21 20.2 143 141 -2 -0.1259 0.9011
40-49 28 26.9 137 113 -24 -2.4721 0.2000
50-64 46 44.2 128 122 -6 -1.0683 0.2911
65-80 9 8.7 155 143 -12 -0.7644 0.4666
Education
high school 13 12.5 126 143 17 0.8327 0.4213
some college 37 35.6 144 137 -7 -0.9158 0.3659
college graduate 41 39.4 134 119 -15 -2.2699* 0.0287
post baccaulareate 13 12.5 126 96 -30 -3.4520** 0.0048
Years Experience
1-5 15 14.4 173 148 -25 -1.9508 t 0.0714
6-10 22 21.2 129 123 -6 -0.8019 0.4315
11-15 27 26.0 127 119 -8 -0.6200 0.5406
16-20 21 20.2 130 119 -11 -0.9840 0.3369
21-25 7 6.7 141 128 -13 -1.1619 0.2894
26-30 5 4.8 126 132 6 0.4082 0.7040
>30 7 6.7 129 118 -11 -0.6359 0.5483
All respondents 104 100.0 136 126 -10 -2.1397* 0.034
Note: denotes statistical significance at the 0.05 level and f denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
35
Appendix Table 5. Realtors' estimates of "before" and "after" values by demographic categories, Property C.
Average
Average Average difference in Average Paired t test of Paired t test of
Demographic Percent value before value after gross value difference in difference in difference in
categories Number of total relandscaping relandscaping (after-before) net value gross value net value
(dollars) (dollars) (dollars) (dollars) t Prob>t t Prob>t
Gender
female 54 51.9 110,048 112,279 2,231 -1,643 0.8807 0.3825 -0.6486 0.5194
male 50 48.1 107,306 110,056 2,750 -1,125 1.4192 0.1622 -0.5806 0.5642
Age
28-39 21 20.2 108,185 106,943 -1,242 -5,118 -0.4460 0.6604 -1.8363 t 0.0812
40-49 28 26.9 104,461 108,604 4,143 268 1.4316 0.1637 0.0926 0.9269
50-64 46 44.2 110,637 113,069 2,432 -1,442 0.8856 0.3803 -0.5253 0.6019
65-80 9 8.7 113,533 119,778 6,245 2,369 1.2204 0.2571 0.4631 0.6556
Education
high school 13 12.5 112,523 110,500 -2,023 -5,898 -0.7743 0.4537 -2.2574* 0.0434
some college 37 35.6 106,116 111,589 5,473 1,598 1.7100 t 0.0959 0.4993 0.6206
college graduate 41 39.4 111,022 111,946 924 -2,951 0.3868 0.7009 -1.2350 0.2241
post baccaulareate 13 12.5 105,146 108,523 3,377 -498 0.7967 0.4411 0.1175 0.9084
Years Experience
1-5 15 14.4 110,200 112,667 2,467 -1,408 0.4125 0.6862 -0.2355 0.8172
6-10 22 21.2 110,586 108,318 -2,268 -6,143 -0.7623 0.4543 -2.0647 1 0.0515
11-15 27 26.0 110,144 114,422 4,278 403 1.4848 0.1496 0.1398 0.8899
16-20 21 20.2 101,919 108,033 6,114 2,239 1.6191 0.1211 0.5929 0.5598
21-25 7 6.7 101,429 102,843 1,414 -2,461 0.4659 0.6577 -0.8106 0.4485
26-30 5 4.8 114,960 109,780 -5,180 -9,055 -0.9694 0.3872 -1.6946 0.1654
>30 7 6.7 117,571 123,714 6,143 2,268 0.9009 0.4024 0.3326 0.7508
All respondents 104 100.0 108,730 111,211 2,481 -1,394 1.5460 0.1252 -0.8689 0.3869
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
Appendix Table 6. Demographic categorization of realtors participating in the study and their average responses
regarding days-to-sale for Property C.
Average
Average Average difference in Paired t test of
Demographic Percent days-to-sale days-to-sale days-to-sale difference in
categories Number of total before after (after-before) days-to-sale
(days) (days) (days) t Prob>t
Gender
female 54 51.9 117 120 3 0.6248 0.5348
male 50 48.1 96 99 3 0.7472 0.4585
Age
28-39 21 20.2 103 106 3 0.4452 0.6609
40-49 28 26.9 102 107 5 0.6810 0.5017
50-64 46 44.2 107 112 5 1.0399 0.3039
65-80 9 8.7 131 121 -10 -0.5547 0.5943
Education
high school 13 12.5 121 117 -4 -0.3432 0.7374
some college 37 35.6 114 125 11 1.6277 0.1123
college graduate 41 39.4 100 97 -3 -0.6779 0.5017
post baccaulareate 13 12.5 92 100 8 1.2349 0.2405
Years Experience
1-5 15 14.4 118 119 1 0.1185 0.9073
6-10 22 21.2 107 115 8 1.3559 0.1895
11-15 27 26.0 103 102 -1 -0.2336 0.8171
16-20 21 20.2 107 105 -2 -0.2769 0.7846
21-25 7 6.7 97 115 18 1.4362 0.2010
26-30 5 4.8 120 114 -6 -0.2182 0.8379
>30 7 6.7 97 117 20 1.6178 0.1568
All respondents 104 100.0 107 110 3 0.9516 0.3435
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
37
Appendix Table 7. Realtors' estimates of"before" and "after" values by demographic categories, Property D.
Average
Average Average difference in Average Paired t test of Paired t test of
Demographic Percent value before value after gross value difference in difference in difference in
categories Number of total relandscaping relandscaping (after-before) net value gross value net value
(dollars) (dollars) (dollars) (dollars) t Prob>t t Prob>t
Gender
female 54 51.9 100,756 111,811 11,055 5,186 3.1976** 0.0023 1.4998 0.1396
male 50 48.1 105,856 109,618 3,762 -2,108 1.4019 0.1672 -0.7856 0.4359
28-39 21 20.2 107,571 105,971 -1,600 -7,470 -0.4016 0.6923 -1.8750 t 0.0755
40-49 28 26.9 96,889 104,353 7,464 1,594 2.4142* 0.0228 0.5156 0.6103
50-64 46 44.2 103,235 113,000 9,765 3,895 2.4055* 0.0203 0.9595 0.3424
65-80 9 8.7 112,544 130,377 17,833 11,963 3.1614* 0.0134 2.1210t 0.0667
Education
high school 13 12.5 109,467 103,269 9,307 3,437 1.6443 0.1260 0.6073 0.5550
some college 37 35.6 102,859 113,170 11,135 5,265 3.1616** 0.0032 1.4949 0.1437
college graduate 41 39.4 106,949 111,317 4,368 -1,501 1.0600 0.2955 -0.3644 0.7175
post baccaulareate 13 12.5 103,992 109,608 5,616 -255 1.3062 0.2160 -0.0592 0.9537
Years Experience
1-5 15 14.4 109,467 111,600 2,133 -3,737 0.2893 0.7766 -0.5067 0.6202
6-10 22 21.2 102,859 108,159 5,300 -570 0.9305 0.3627 -0.1001 0.9212
11-15 27 26.0 104,481 110,666 6,185 315 3.1691** 0.0039 0.1615 0.8730
16-20 21 20.2 95,800 106,376 10,576 4,706 1.9277 t 0.0682 0.8578 0.4012
21-25 7 6.7 93,000 107,128 14,128 8,259 1.2486 0.2583 0.7299 0.4930
26-30 5 4.8 109,980 124,580 14,600 8,730 3.3442* 0.0287 1.9996 0.1162
>30 7 6.7 113,571 124,357 10,786 4,916 1.0618 0.3292 0.4839 0.6456
All respondents 104 100.0 103,208 110,757 7,549 1,679 3.3863** 0.0010 0.7532 0.4531
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
Appendix Table 8. Demographic categorization of realtors participating in the study and their average responses
regarding days-to-sale for Property D.
Average
Average Average difference in Paired t test of
Demographic Percent days-to-sale days-to-sale days-to-sale difference in
categories Number of total before after (after-before) days-to-sale
(days) (days) (days) t Prob>t
Gender
female 54 51.9 127 128 1 0.2192 0.8273
male 50 48.1 107 101 -6 -1.517 0.1357
Age
28-39 21 20.2 122 118 -4 -0.3508 0.7294
40-49 28 26.9 111 102 -9 -1.1996 0.2407
50-64 46 44.2 113 117 4 0.8861 0.3803
65-80 9 8.7 143 138 -5 -0.2980 0.7733
Education
high school 13 12.5 118 123 5 0.5962 0.5621
some college 37 35.6 124 124 0 0.0000 1.0000
college graduate 41 39.4 115 107 -8 -1.0689 0.2750
post baccaulareate 13 12.5 103 105 2 0.3526 0.7305
Years Experience
1-5 15 14.4 123 137 14 0.8379 0.4161
6-10 22 21.2 125 119 -6 -1.2085 0.2403
11-15 27 26.0 119 110 -9 -1.0563 0.3005
16-20 21 20.2 103 103 0 0.000 1.0000
21-25 7 6.7 117 116 -1 -0.0822 0.9372
26-30 5 4.8 132 114 -18 -1.5000 0.2080
>30 7 6.7 100 105 5 0.5453 0.6052
All respondents 104 100.0 117 115 -2 -0.5559 0.5795
Note: denotes statistical significance at the 0.05 level and t denotes significance at the 0.10 level.
** denotes statistical significance at the 0.01 level
39
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