Effects of Relandscaping on the Perceived Market Value of Single Family Residential Property
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Effects of Relandscaping on the Perceived Market Value of Single Family Residential Property

   

Effects of Relandscaping on the Perceived Market Value of Single Family Residential Property1

Robert L. Degner and Susan D. Moss2

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 homeowner's needs and preferences. Each homesite was photographed from the front (street) exposure before 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 Department of Food and Resource Economics at the University of Florida. 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 Nurserymen 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 Nurserymen and Growers Association for 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 of 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 Department of Educational Media and Services 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

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.

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 re-sale, 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's 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, 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 homeowner's needs and preferences. Each homesite was photographed from the front (street) exposure before 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 (see Appendix for Figures 1 , 2 , 3 and 4 ).

The "before" and "after" photographs were shown to a random sample of 104 licensed real estate professionals who 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 a questionnaire.

The eight photos of subject properties ("before" and "after" photos of the four properties) were included in a portfolio of 35 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 that included the year built; the number of bedrooms, baths, and covered parking spaces; heated and cooled square footage; lot size; and the general income 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. 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.

Finally, realtors' ages 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-daysij = f (agei or experiencei, educationi, genderi)

where

D-valueij = 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-daysij = difference in days-to-sale estimates, i.e., post-relandscaping estimate minus pre-relandscaping estimate for individual i and property j

agei = age of individual i in years

experiencei = years experience in real estate profession for individual i

educationi = years of formal education for individual i

genderi = 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.

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 before relandscaping. Thus, negative values indicate a reduction in days-to-sale, hypothesized to be attributable to relandscaping.

Results of t-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 Tables 4 through 11.

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. 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.

In general, the OLS models explained little of the variation observed in the dependent variables, i.e. differences in pre- and post-relandscaping 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' ages, years experience, educational attainment, or gender.

The following subsections present detailed findings for each of the subject properties that were evaluated in this study (see Appendix for Figures 5 , 6 , and 7 ).

Property A

Built in the 1950s, 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 and 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 ).

On average, the realtors estimated that property A would sell for $88,887 before relandscaping and $97,237 after relandscaping (Table 1, Figure 5 ). 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 6 ). 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 7 ).

Because of the relatively large differences in pre- and post-relandscaping values for property A, many of the demographic categories reflected statistically significant 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.

Property B

Property B was built in the early 1980s. It was situated on a corner 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 2 ).

On average, the realtors estimated that property B would sell for $128,454 before relandscaping and $129,512 after relandscaping (Figure 5 ). 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 7 ).

Few statistically significant differences in pre- and post-relandscaping values were found for the various demographic categories (Table 7). 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 respondents with more formal education took greater note of the effects of relandscaping and reduced their days-to-sale estimates accordingly.

Property C

Property C was built in the mid-1980s 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 3 ).

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 5). 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 days-to-sale was 110, for a net increase of three days. However, this unexpected increase was not statistically significant (Table 1, Figure 7 ).

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 (Tables 8 and 9). 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).

Property D

Property D was the newest subject property included in this study. Built in the early 1990s, 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 4 ).

The realtors estimated that property D would sell for $103,208 before relandscaping and $110,757 after relandscaping (Table 1, Figure 5 ). 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 7 ).

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 (Tables 7 and 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 was "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).

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, that 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, roof condition, general condition, and neatness and cleanliness of the exterior, each was 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).

Conclusion

In conclusion, this study indicates that relandscaping can have positive effects on real estate professionals' perceived values and the marketability of single-family residences. Relandscaping increased the perceived value of all four properties 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 unavailable 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, landscape probably warrants greater attention from homeowners preparing their properties for re-sale.

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.

References

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Gillmeister, William J., Robert D. Yonkers, and James W. Dunn, "Hedonic Pricing of Milk Components at the Farm Level," Review of Agricultural 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. and Veraphol Suvannunt, "A Model of Consumer Goods Characteristics," American Journal of Agricultural 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, Statistical Methods, The Iowa State University Press, Ames, Iowa, 1967.

Tronstad, Russell, Lori Stephens Huthoefer, and Eric Monke, "Market Windows and Hedonic Price Analyses: An Application to the Apple Industry," Journal of Agricultural 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.

Appendix
Figure 1. Property A before and after relandscaping.
Figure 2. Property B before and after relandscaping.
Figure 3. Property C before and after relandscaping.
Figure 4. Property D before and after relandscaping.
Figure 5. Average perceived changes in home values compared with relandscaping costs.
Figure 6. Average perceived values of subject properties before and after relandscaping.
Figure 7. Average estimated number of days-to-sale for subject properties before and after relandscaping.

Tables

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*

0.499

0.125

3.386**
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**

2.140***

-0.952

0.556

a 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 0.01 level, ** denotes statistical significance at the 0.05 level,

*** denotes significance at the 0.10 level.

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


Range =

1-50

0,1

12-20
Dependent variable, propertya

Dependent variable 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-value, 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-value, 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-value, D

-2.21

16.09

-0.02

-6.45

-0.99

0.0109

a "D-value" refers to the difference between post-relandscaping values and pre-landscaping values.

"D-days" refers to the difference in days-to-sale. A negative value indicates a reduction in days-to-sale.

Note: * denotes statistical significance at the 0.01 level, ** denotes statistical significance at the 0.05 level,

*** denotes statistical significance at the 0.10 level.

Table 3. Realtors' rankings of "curbside appeal" characteristics.

Ranking of curbside appeal characteristics


Characteristics

First

Second

Third

All responses

Percent of totalb

Number of respondents


Landscaping

54

25

21

100

96.2

General Maintenance:






Paint condition

8

17

8

33

31.7

Roof condition

6

15

13

32

30.8

General condition

6

15

13

32

30.8

Neatness, cleanliness

12

5

8

25

24.0

Front door

1

2

2

5

4.8

Design, Quality and 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

a Percentages are based on 104 respondents.

Table 4. Realtors' estimates of "before" and "after" values by demographic categories, Property A.

Demographic Categories

Number

Percent of Total

Average Value Before

Average Value After

Average

Gross Value

Average

Net Value

Paired t-test Gross Value

Paired t-test

Net Value




(dollars)

(dollars)

(dollars)

(dollars)

t

Prob>t

t

Prob>t
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

1.7769***

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

1.7698***

0.0985

0.4907

0.6313
6-10

22

21.2

88,136

97,818

9,682

4,960

1.7977***

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

1.9800***

0.0945
26-30

5

4.8

103,980

107,600

3,620

-1,102

0.3664

0.7326

-0.1115

0.9166
Over 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 0.01 level, ** denotes statistical significance at 0.05 level, *** denotes statistical significance at 0.10 level.

Table 5. Demographic categorization of realtors participating in the study and their average responses regarding days-to-sale for Property A.

Demographic Categories

Number

Percent of Total

Average Days-to-Sale Before

Average Days-to-Sale After

Average Difference Days-to-Sale

Paired t-test Difference Days-to-Sale



(days)

(days)

(days)

t

Prob>t
Female

54

51.9

135

113

-22

-2.8300*

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

-1.8368***

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

-1.7225***

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

Over 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 0.01 level, ** denotes statistical significance at 0.05 level, *** denotes statistical significance at 0.10 level.

Table 6. Realtors' estimates of "before" and "after" values by demographic categories, Property B.

Demographic Categories

Number

Percent of Total

Average Value Before

Average Value After

Average

Gross Value

Average

Net Value

Paired t-test

Gross Value

Paired t-test

Net Value



(dollars)

(dollars)

(dollars)

(dollars)

t

Prob>t

t

Prob>t
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

0.3150
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***

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

-4.049

-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

Over 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

-1.8588***

0.065

Note: * denotes statistical significance at 0.01 level, ** denotes statistical significance at 0.05 level, *** denotes statistical significance at 0.10 level.

Table 7. Demographic categorization of realtors participating in the study and their average responses regarding days-to-sale for Property B.

Demographic Categories

Number

Percent of Total

Average Days-to-Sale Before

Average Days-to-Sale After

Average Difference Days-to-Sale

Paired t-test Days-to-Sale



(days)

(days)

(days)

t

Prob>t
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

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***

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

Over 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 0.01 level, ** denotes statistical significance at 0.05 level, *** denotes statistical significance at 0.10 level.

Table 8. Realtors' estimates of "before" and "after" valued by demographic categories, Property C.

Demographic Categories

Number

Percent of Total

Average Value

Before

Average

Value

After

Average

Gross

Value

Average

Net Value

Paired t-test

Gross Value

Paired t-test

Net Value



(dollars)

(dollars)

(dollars)

(dollars)

t

Prob>t

t

Prob>t
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***

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***

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***

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
Over 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 0.01 level, ** denotes statistical significance at 0.05 level, *** denotes statistical significance at 0.10 level.

Table 9. Demographic categorization of realtors participating in the study and their average responses regarding days-to-sale for Property C.

Demographic Categories

Number

Percent of Total

Average Days-to-Sale Before

Average Days-to-Sale After

Average Difference Days-to-Sale

Paired t-test Days-to-Sale



(days)

(days)

(days)

t

Prob>t
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