Front Cover
 Table of Contents
 List of Tables
 List of Figures

Group Title: Economic information report
Title: The effects of hydrilla infestation in Lake Harris on the market price of adjacent residential property
Full Citation
Permanent Link: http://ufdc.ufl.edu/UF00026500/00001
 Material Information
Title: The effects of hydrilla infestation in Lake Harris on the market price of adjacent residential property
Series Title: Economic information report - University of Florida. Food and Resource Economics Dept. ; 262
Physical Description: iv, 11 p. : ill. ; 28 cm.
Language: English
Creator: Milon, J. Walter
University of Florida -- Food and Resource Economics Dept
Publisher: Food & Resource Economics Dept., Agricultural Experiment Stations, Institute of Food and Agricultural Sciences, University of Florida
Place of Publication: Gainesville <Fla.>
Publication Date: August, 1989
Copyright Date: 1989
Subject: Real property -- Valuation -- Florida -- Lake County   ( lcsh )
Hydrilla -- Florida   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
non-fiction   ( marcgt )
Statement of Responsibility: J. Walter Milon.
Bibliography: Includes bibliographical references (p. 9).
General Note: "August 1989."
General Note: Cover title.
 Record Information
Bibliographic ID: UF00026500
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: notis - AGZ0265
alephbibnum - 001478335
oclc - 20942291

Table of Contents
    Front Cover
        Front Cover
        Page i
    Table of Contents
        Page ii
    List of Tables
        Page iii
    List of Figures
        Page iv
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
Full Text

_. J. Walter Milon Economic Information
Report 262

The Effects of Hydrilla Infestation
In Lake Harris On the Market Price
of Adjacent Residential Property

Food & Resource Economics Department
Agricultural Experiment Stations
Institute of Food and Agricultural Sciences August 1989
University of Florida, Gainesville 32611


This paper reports the results of a statistical analysis of 72 sale-resale property transactions

in the Leesburg area during the period 1982 to 1989 in order to evaluate the effects of the hydrilla

infestation in Lake Harris in 1986 and 1987 on the sales prices of properties adjoining the Lake. A

sale-resale regression model is used to isolate the effects of changes in environmental amenities on

residential property prices. The statistical results indicate that the hydrilla infestation did not have

an impact on property sales prices in 1986 or 1987. Residential property sales in these years were

consistent with other property sales during the 1982 to 1989 period. While there was no statistical

evidence to indicate a negative impact from the hydrilla infestation, the analysis did not consider the

possible effects on properties due to longer listing times or for those that were withdrawn from sale

due to unsatisfactorily low offer prices. In addition, the analysis does not consider the costs incurred

by individual property owners who did not sell their property during the hydrilla infestation.

Key words: property sale-resale analysis, property values, amenity values, hydrilla, aquatic plant


Table of Contents


Abstract ................. .......................... .......... . i

L ist of Tables .............................................. ....... iii

List of Figures ............. .... ................... .............. iv

1. Introduction .................... ............................ 1

2. Techniques for Evaluating the Effects of Amenities
on Property Prices ................. . . .... ..... ...... 2

3. Sale-Resale Data Used for the Analysis .............. ....... . . 3

4. Statistical Model Estimation and Results ............................. 5

5. Limitations of the Analysis and Conclusions .......................... 7

References ...................................................... 9

Appendix ........................................................ 10


List of Tables

Number Page

1 Average Prices of Resale Properties by
Location Zone, 1982-1989 ....................................... 5

2 Regression Models Measuring Effects of Time and Location
on Property Resale Prices, 1982-1989 ............................. 6


List of Figures

Number Page

1 Map of Lake Harris and surrounding area in
Lake County, Florida ...................................... ... 4


J. Walter Milon*

1. Introduction

Real estate prices are commonly regarded as accurate measures of the economic value of

residential property. Housing prices reflect the quality of construction, level of maintenance, and

the amenities associated with particular neighborhoods and locations. Two houses with identical

design and construction located on adjoining lots that share the same visual and environmental

amenities will most likely have identical market prices. However, even identical houses will have

different prices if the visual and environmental amenities of the lot are different. Houses located

in desirable locations will bring higher market prices than comparable housing in less desirable

locations. These differences in market real estate prices can be evaluated to determine how specific

amenities influence the value of property.

This report examines the effects of hydrilla infestation in Lake Harris in Lake County,

Florida on the market price of residential property bordering the Lake. This inquiry was initiated

by the Lake County Water Management Authority because of concern about the possible impact of

unusually high levels of hydrilla growth in the Lake in 1986 and 1987 on property owners near the

Lake. High levels of hydrilla interfere with normal boating activity, restrict normal shoreline uses

such as swimming, and change the visual appearance of the lake surface. These high levels of

hydrilla may have reduced the recreational and visual amenities enjoyed by property owners near

the Lake and thereby caused a decrease in the market price of these properties.

The report is organized as follows. Section 2 provides a brief overview of empirical

techniques that have been used to evaluate the effects of environmental amenities on property prices.

The primary emphasis is on the "sale-resale approach" since this technique is used in this study.

"*J. Walter Milon is a professor in the Food and Resource Economics Department, University of
Florida. Partial funding for this research was provided by the Lake County Water Management


Section 3 provides a discussion of the property sales data used in this analysis and the location of

the properties analyzed. A complete listing of the property sales data is provided in the appendix

to this report. Statistical results from the analysis are presented in Section 4 with a discussion of the

results. The last section provides a discussion of the limitations of the analysis and the conclusions

that can be drawn from the results.

2. Techniques for Evaluating the Effects of Amenities On Property Prices

There are two basic statistical techniques which have been used to evaluate the effects of

environmental amenities and disamenities on property prices. The first is commonly referred to as

"hedonic regression" analysis and involves the use of multiple regression techniques to identify the

effect of each quantifiable attribute of a property on the market price (Edmonds). For example, the

effect of attributes such as lot size, number of rooms, and condition of the structure can be

estimated. Similarly, environmental amenities such as proximity to a lake or waterway, view, or

distance to a park can also be analyzed. Disamenities that are likely to detract from a property can

also be considered and previous research has focused on the effects of water quality, air quality,

earthquakes, and floods (e.g. Brookshire et al., Graves et al., and MacDonald et al.).

The primary advantage of the hedonic regression technique is the level of detail that can be

considered in the analysis. However, this advantage is also a drawback. Hedonic regression analysis

requires complete data on each parcel included in the analysis and a large number of properties must

be included or the results are not statistically valid. A typical hedonic regression analysis would

include a minimum of 400 residential property sales and information on at least 10 attributes of the

properties (e.g. Brookshire et al. and Graves et al). Because of the extensive data requirements,

hedonic regression analysis has been used primarily for large metropolitan areas.

The second statistical technique is known as the "sale-resale" approach since it employs

consecutive sales of properties to determine how specific changes in the properties may have

influenced market prices (Palmquist). This approach does not require the same extensive level of

detail about the properties as the hedonic regression technique because it is assumed that most of the

attributes such as lot size or number of rooms will not change over time. The analysis focuses on a


specific change in environmental amenity conditions that would influence the market price of the

property but would not change any of the other property attributes. Multiple regression techniques

can be used to isolate these specific changes as they may occur over time. For example, the statistical


(1) Ri = a(YRi) + b(YRi2) + c(Amenityt)

expresses the ratio of the first and second sales prices (R) for the ith property to be a function of

the year of the first sale (YRil), the year of the resale (YRi), and the level of a specific

environmental amenity in the years of sale and resale (Amenityt). The coefficients a, b and c

measure the effects of each factor on the sales price ratio and gives information about specific causes

for changes in property prices over time. The model is usually implemented with a logarithmic

transformation of the sale-resale price ratio (R) so that the coefficients measure percentage changes

in property prices. The amenity variable can also be measured as a discrete value for a single period

in time to measure the effect of a unique environmental change that occurred only once or twice

during the period of time considered in the sale-resale analysis. Palmquist (1982) provides a

complete discussion on the theory and application of the sale-resale technique.

3. Sale-Resale Data Used for the Analysis

Sale-resale data for residential properties located near Lake Harris were collected from

transactions records maintained by the Lake County Property Appraiser's Office. Data were

collected for the period 1982 to 1989 (June). Sales data were limited to properties along the western

rim of Lake Harris in an area bordered by the City of Leesburg to the north and Helena Run to the

south (Figure 1). This general area of the Lake experienced one of the most severe hydrilla

infestations. The infestations were most severe in 1986 and 1987 although treatments with Sonar (an

aquatic herbicide) began in 1986. As a result of the Sonar treatments, the western area of the Lake

was generally free of hydrilla by 1988. The area along the northeast rim of the Lake near the Dead

River also experienced severe hydrilla infestations during the same time period but is not considered

in this analysis due to the relatively low number of property sales transactions in this area.



S Harris LA



wr ^l \ \ B^ i 3 ^

Figure 1. Map of Lake Harris and surrounding area in Lake County,


Properties with sale-resale transactions during the 1982 1989 period were classified

according to 4 zones of proximity to Lake Harris: 1) Lake front, 2) Canal front, 3) Near the Lake

but no direct access or view of the Lake, and 4) Away from the Lake. Summary statistics for

properties in the four zones are reported in Table 1. The number of properties in each group reflects

the relative scarcity of properties in the different zones. There are relatively few waterfront parcels

compared to parcels in other areas away from the Lake. The data also show that parcels with water

front or canal frontage have higher average prices than parcels in other locations. These price

differences may be due to differences in lot size, structures, or environmental amenities across the

four zones. For the purpose of sale-resale analysis, the specific reasons for these price differences

are not important since lot size and structural characteristics of the parcels did not change during the

period. The issue is whether the prices of properties in the lake front and canal location zones were

adversely impacted by the hydrilla infestations in Lake Harris during 1986-1987. A complete listing

of the property data used for the analysis is provided in the appendix.

Table 1. Average Prices of Resale Properties by Location Zone, 1982-1989
Number of
Location Zone Properties Mean Median Std. Dev.

Lake Front 8 $101,875 $109,500 28,916

Canal 10 $107,160 $ 93,050 43,762

Near Lake-No Access 22 $ 68,532 $ 55,750 46,789

Away from Lake 32 $ 56,656 $ 52,200 23,528

4. Statistical Model Estimation and Results

The property sale-resale data for the 1982 1989 period were analyzed using the statistical

model described in equation 1 above. The index value R was created by dividing the resale price

by the first sales price for each property. Additional variables were then created to reflect the initial

sale year of the property and the year of the resale. The effects of the hydrilla infestation on lake

front and canal properties were measured by creating two dummy variables to reflect the interaction


of the year of the infestation with location. These variables were created by grouping lake front

and canal properties into a single property group and then multiplying a dummy variable

representing the group by the year dummy variable for 1986 and 1987. These interaction dummy

variables are labelled Location-86 and Location-87 in Table 2. The coefficients for these variables

give the percentage change in price in 1986 or 1987 for lake front and canal parcels. If these

variables are statistically significant, they provide a quantitative measure of the effect of the hydrilla

infestations in these years.

Table 2. Regression Models Measuring Effects of Time and Location on Property Resale

Prices, 1982-1989
Variable Model 1 Model 2

YR 83 0.12 0.11
(0.45)a (0.90)

YR 84 0.16 0.16
(1.46) (1.43)

YR 85 0.32** 0.30**
(2.50) (2.44)

YR 86 0.15 0.16
(1.45) (1.53)

YR 87 0.28** 0.29**
(2.13) (2.01)

YR 88 0.44*** 0.42***
(3.64) (3.57)

YR 89 0.33** 0.33**
(2.21) (2.20)

Location 86 0.07

Location 87 -- -0.05

R2 0.31 0.30
MSE 0.23 0.23

"T values in parentheses below the coefficients.
*, **, *** indicate significance at the .10, .05 and .01 levels, respectively.


Results from the multiple regression analysis of the sales-resale data are presented in Table

2. Two models are presented to account for the possibly different effects of hydrilla in 1986 and

1987. Each year coefficient of the model (YR83, YR84, etc.) measures the percentage change in

price in that year relative to the base year, 1982. The statistical significance of each year coefficient

is indicated by the asterisks above the coefficient. Thus, property prices in 1985 were approximately

30 to 32 percent higher than 1982. Since the coefficients for '83, '84, and '86, were not statistically

different from zero, the prices of all properties sold in these years were no different from prices in

the base year.

The coefficients for the two variables constructed to measure the effects of the hydrilla

infestation are also not statistically different from zero. This means that the sales data do not reveal

any unique effects of the hydrilla on lake front and canal properties. Prices for these properties

increased at the same rate as other properties in the study area. Therefore, there is no statistical

evidence to indicate that sales of lake front and canal properties were adversely impacted by the

hydrilla infestation.

5. Limitations of the Analysis and Conclusions

This analysis of 72 sale-resale property transactions in the Leesburg area adjoining Lake

Harris indicates that the hydrilla infestation along the western shore of the Lake in 1986 and 1987

did not influence the sales price of residential parcels in those years. This conclusion is based on the

results of a statistical model of sale-resale property transactions during the period 1982 to 1989.

While this conclusion is based solely on the statistical results, there are certain limitations to the

analysis that should be considered. First, the analysis includes only those properties sold and then

resold during the period. Properties that had only a single sale in 1986 or 1987 were not included

in the data base for the sale-resale analysis and these properties may have had a different effect due

to the hydrilla.

Second, the sale-resale analysis does not consider lake and canal access properties that may

have been withdrawn from the market in 1986 or 1987 due to low offer prices. Since an actual sales


transaction did not occur for these properties, there is no way to assess the possible impact of the

hydrilla. In addition, the possible impact on the listing period of properties is not considered. Lake

and canal property owners may have had to list their properties for sale for an abnormally long time

due to the effects of the hydrilla. However, since longer listing time usually leads to price cutting

in order to sell the property, the fact that sale prices were not reduced in these years suggests that

the effect on listing periods was also negligible.

Finally, the sale-resale analysis used in this study cannot account for the inconvenience and

displeasure that may have been experienced by lake and canal front property owners due to the

hydrilla infestation. These impacts were certainly important to the property owners but a general

analysis of property price trends such as this cannot provide a quantitative measure of these impacts.

The analysis indicates that the hydrilla infestation had no identifiable impact on the residential

property market but this market cannot reflect the costs that may have been experienced by

individual property owners.



Brookshire, D.S., M.A. Thayer, J. Tschirhart, and W.D. Schulze. "A Test of the Expected Utility

Model: Evidence from Earthquake Risks." Journal of Political Economy 93(1985):369-389.

Graves, P., J.C. Murdoch, M.A. Thayer, and D. Waldman. "The Robustness of Hedonic Price

Estimation: Urban Air Quality." Land Economics 64(1988):220-233.

MacDonald, D.N., J.C. Murdoch, and H.L. White. "Uncertain Hazards, Insurance, and Consumer

Choice: Evidence from Housing Markets." Land Economics 63(1987):361-371.

Palmquist, R. B. "Measuring Environmental Effects on Property Values without Hedonic

Regressions." Journal of Urban Economics 11(1982):333-347.



Property Sale-Resale Data, 1982-1989

Property Location
OBS # Code Year Price

1 1 1 88 121000
2 1 1 86 110000
3 2 3 89 128000
4 2 3 85 118000
5 3 4 88 37500
6 3 4 83 33000
7 4 4 89 46000
8 4 4 86 42500
9 5 4 86 42500
10 5 4 88 50900
11 6 4 88 36500
12 6 4 84 32000
13 7 4 88 43500
14 7 4 83 28500
15 8 4 86 83500
16 8 4 87 100000
17 9 3 86 172000
18 9 3 87 165000
19 10 4 82 84300
20 10 4 85 108800
21 11 4 82 87500
22 11 4 86 107000
23 12 4 86 73500
24 12 4 87 72500
25 13 4 84 25000
26 13 4 87 40000
27 14 2 83 150000
28 14 2 84 156500
29 15 2 87 65000
30 15 2 88 91600
31 16 3 85 30600
32 16 3 88 38000
33 17 4 85 57500
34 17 4 88 53500
35 18 4 86 45000
36 18 4 89 57000
37 19 3 86 16500
38 19 3 88 55000
39 20 1 85 135000
40 20 1 86 130000
41 21 1 83 57000
42 21 1 85 67000
43 22 3 83 46000
44 22 3 86 56500
45 23 3 83 21500
46 23 3 86 25000
47 24 2 82 85000
48 24 2 84 94500


49 25 4 82 68500
50 25 4 86 70000
51 26 4 84 65000
52 26 4 86 65000
53 27 4 82 37500
54 27 4 86 57500
55 28 2 86 50000
56 28 2 87 63500
57 29 3 84 44000
58 29 3 88 52800
59 30 4 84 28500
60 30 4 89 33000
61 31 1 83 86000
62 31 1 88 109000
63 32 3 85 70000
64 32 3 88 67500
65 33 3 83 73000
66 33 3 87 80000
67 34 3 82 15000
68 34 3 84 16400
69 35 3 83 98900
70 35 3 85 118000
71 36 2 84 156500
72 36 2 88 159000

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