Pet Policy and Housing Prices: Evidence from the Condominium Market
Zhenguo Lin
Department of Finance
California State University, Fullerton
CA 92831-3599
Marcus T. Allen
Carter Real Estate Center
School of Business and Economics
College of Charleston
Charleston, South Carolina 29401
Charles C. Carter
Haint Blue Realty, LLC
9034 S.W. 7
th
Street
Boca Raton, Florida 33433
Abstract
This paper examines the economic impact of restrictions against keeping domestic
pets in residential dwellings. Using a large data sample of condominium sales, we
empirically estimate price effects associated with pet restrictions. Our results
suggest that an unrestricted pet policy creates a significant premium in
condominium price, along with discounts for condominiums that do not allow
pets or have pet restrictions. This finding is useful for policy makers, developers
of new condominium projects, and condominium owner associations in their
decisions to establish or alter laws and regulations regarding restrictions on pet
owner residents.
August 8, 2011
1
Pet Policy and Housing Prices: Evidence from the Condominium Market
[Abstract] This paper examines the economic impact of restrictions against
keeping domestic pets in residential dwellings. Using a large data sample of
condominium sales, we empirically estimate price effects associated with pet
restrictions. Our results suggest that an unrestricted pet policy creates a significant
premium in condominium price, along with discounts for condominiums that do
not allow pets or have pet restrictions. This finding is useful for policy makers,
developers of new condominium projects, and condominium owner associations
in their decisions to establish or alter laws and regulations regarding restrictions
on pet owner residents.
Data reported by the American Pet Products Association (APPA) indicates that
pet ownership in the United States increased by almost 3 percent between 2005 and 2007
(Ferrante (2007)) resulting in an all-time high of 71.1 million households owning at least
one domestic pet. Between 1997 and 2007, the number of U.S. households grew by 14
percent, while the number of pet-owning households grew by 22 percent. The APPA
(2008) estimates that total expenditures by pet owners on household pet health and
nutrition was $41.2 billion in 2007, with $16.2 billion spent on food, $10.1 billion spent
on veterinary care, $9.8 billion spent on supplies and over-the-counter medicine, $2.1
billion on live animal purchases, and $3.0 billion spent on grooming and boarding. The
rise in pet ownership and pet related expenditures is attributable to the perceived or real
satisfaction enjoyed by individuals related to pet ownership, presumably due to increased
health, safety, security, or other benefits of sharing one’s life with a pet.
Along with the increased incidence of pet ownership, some pet ownership
advocates are pushing to eliminate or at least reduce restrictions on pets in residential
dwellings. While federal laws already prohibit discrimination in housing and other
public accommodations against mentally and physically disabled persons regarding
2
“service and support” animals, efforts are underway to extend this protection to all
individuals who wish to keep “companion” or “emotional support” animals in their
dwellings even though these individuals do not have disabilities protected by federal laws.
The strategy adopted by some proponents of such a policy change is to appeal to the
medical and psychological benefits that may accrue to pet owners, regardless of their
disability (or lack thereof) status.
Irrespective of political and/or emotional motivations for eliminating or reducing
restrictions against pet ownership in residential dwellings, the primary purpose of the
current study is to consider the price effects of pet restrictions using a sample of
condominium transactions from the Fort Lauderdale, Florida metropolitan area. The
research question considered is whether or not relationships can be detected between
condominium prices and pet restrictions such as “no pets of any kind,” “small pets only,”
“large pets only,” “dogs only,” and “cats only.” Previous research on the effect of pet
restrictions on condominium prices suggests that allowing cats is related to increased
prices, but that prices are negatively related to allowing dogs. Previous research on the
effect of pet restrictions on multi-family apartment rents suggests that pet restrictions
have no significant rent effect. This study extends prior research on pet policies and
condominium prices to a different geographic area, a more current time period, and a
much larger sample of observations.
The next section of this paper reviews the legalities and politics involved in the
initiative to reduce or even eliminate restrictions on pet ownership in dwelling units. In
Section 2, we develop a model to study the economic impact of pet policy on housing
prices. The third section describes the methods used in this study to empirically examine
3
the price effects of pet restrictions. The fourth section discusses the results of the analyses.
The final section provides interpretations and potential policy directions suggested by the
results of this study.
1. The Legalities and Politics of Pet Restrictions
The federal Fair Housing Amendments Act of 1988, Section 504 of the
Rehabilitation Act of 1973, and Title II of the Americans with Disabilities Act protect
against discrimination of persons who need the assistance of service or support animals
as a result of conditions that substantially limit major life activities. This protection from
discrimination has been upheld in various courts. The 7th Circuit Court of Appeals ruled
in favor of a deaf person’s right to keep a service/support animal in a dwelling, opining
that:
“[b]alanced against a landlord’s economic or aesthetic concerns as
expressed in a no-pets policy, a deaf individual’s need for the
accommodation afforded by a hearing dog is, we think, per se reasonable
within the meaning of the” Fair Housing Act. (Bronk v. Ineichen, 54 F.3d
425, 429 (7
th
Cir. 1995)).
A similar ruling was handed down by the U.S District Court of Oregon in Green v.
Housing Authority of Clackamas County, 994 F.Supp. 1253 (Or. 1998). In 2003,
however, a court ruled against the plaintiff on the grounds that the animal possessed “no
abilities assignable to the breed or to dogs in general” that would assist the plaintiff
(Prindable v. Ass’n of Apartment Owners of 2987 Kalakaua, 304 F. Supp. 2d 1245, 1256-
57 (D. Hawaii 2003)). In 2004, another court rejected the plaintiff’s claim to the right of
a service or support animal on the grounds that the plaintiff could not sufficiently prove
that such an animal would provide the needed benefits (Oras v. Housing Authority of City
4
of Bayonne, 861 A.2d 194,203 (N.J. Super. Ct. 2004)). Each of these rulings are
premised on the idea “…that the animal be (1) individually trained, and (2) work for the
benefit of an individual with a disability” (Poliakof (2008)).
Going beyond accommodation for disabilities, federal law provides some
protection for the elderly whose emotional support is enhanced by ownership of pets.
Part of the Housing and Urban-Rural Recovery Act of 1983 includes a rule titled Pet
Ownership in Assisted Rental Housing for the Elderly or Handicapped (POEH) (12
U.S.C. § 1701r-1 (2000)). The legislation recognizes the support that pets can provide
the elderly by providing that owners and managers of federally assisted housing for the
elderly or handicapped cannot prohibit or prevent tenants from owning common
household pets. The rule applies only to those apartments receiving federal subsidies, but
it nonetheless reflects the benefits expected for elderly residents from the accompaniment
of pets.
At the state legislative level, California enacted a law effective January, 2001,
(California Civil Code Section 1360.5) that permits each owner in common interest
developments (such as condominiums and mobile home parks) to keep at least one pet,
subject to reasonable rules and regulations of the homeowners’ association. Notably, the
California law makes no reference to the owner’s need for a mental or physical disability,
instead permitting pets for all owners who desire to maintain a pet in their common
interest home. Efforts are underway in Florida to adopt similar legislation, though this
legislation does make reference to need beyond simply the preference for a household pet
in condominium properties.
5
In Florida, Citizens for Pets in Condos, Inc., a non-profit organization, is lobbying
for consideration of a proposed bill (Emotional Support Animal Bill) in the state
legislature that would permit “emotional support” animals in condominiums throughout
the state. Anyone with approval from a qualified medical professional, regardless of the
disabilities recognized in federal law, who could benefit from having an emotional
support animal, could keep a pet in their dwelling regardless of community or
homeowner association rules. The proposed law in Florida would allow a variety of
medical professionals (doctors, nurses, social workers, etc.) to grant approval for
individuals who express a preference to maintain a pet in their condominium unit,
effectively overriding condo association rules against pets in the units.
The bill proposed by the Citizens for Pets In Condos group died in committee
during the 2007 legislative session and was not considered by the legislature in 2008,
2009, or 2010, due to the lack of a sponsor of the bill in the state senate. Even so, the
group’s efforts are continuing as of this writing and there is some probability, given the
widely-held opinion of a need for condominium association reform that currently exists
in Florida, that the legislation will eventually make it to the floor of the legislature. (See
http://petsincondos.org for a current update on the group’s activities to promote their
cause as part of the broader effort to reform condominium association regulations).
Supporters of legislation prohibiting pet restrictions in dwelling units frequently
cite the physical and emotional health benefits of pet ownership reported in numerous
research studies conducted or supported by such entities as the Center for Disease
Control, U.S. Department of Health, American Association of Retired Persons, American
Society for the Prevention of Cruelty to Animals, Humane Society of the United States,
6
American Heart Association, and Baker Medical Research Institute, as well as numerous
research reports published in a variety of research outlets. For examples of such research
reports, see (among many others) Allen, et al. (1991), Barker and Dawson (1998),
Duncan (2000), Endenburg, ‘t Hart, and Bouw (1994), Hirschman (1994), Mallia (2006),
and Raina, et al. (1999), and Schwarz, Troyer, and Walker (2007).
Opponents, or at the very least, non-supporters, of the proposed Florida bill
maintain that individual owner associations should be entitled to democratically
determine, within the associations’ bylaws, whether pet ownership rights are a desirable
“amenity” of the condominium community. Possible negative effects cited by opponents
of the Florida bill include odor, noise, waste disposal, and damage to the common areas
of the property.
On the presumption that housing market dynamics should determine the economic
effect of pet restrictions on condominium prices, a statistically rigorous analysis of the
potential relationship between prices and pet restrictions may provide market-supported
evidence of the price effects of pet restrictions. The results may be used by one side of
this debate or the other to bolster its position and to possibly affect decisions of
developers, owner associations, and policy makers regarding pet restrictions.
2. The Model
To study the economic impact of a particular pet policy on housing prices, we
develop a simple model based on a set of equations proposed by Malpezzi and
Maclennan (2001):
DPQ
D 210
(1)
7
PQ
S 10
(2)
SD
QQ (3)
The variables in Equations (1) – (3) are defined as follows:
D
Q
is housing demand,
P
is
house price, and D is a demand factor that is determined by demand variables such as
income and population.
S
Q is housing supply.
1
(
1
) represents the price elasticity of
housing supply (housing demand).
By equating supply and demand in Equation (3) and solving for the house price,
we can obtain a reduced form of the system,
DP
11
2
11
00
(4)
Now suppose that a pet policy
i
pp is introduced in the housing market. Assume
that this policy immediately affects the demand side: buyers who like the policy will have
higher values for properties with such a policy. The demand function (1) then becomes
)()(
210 iiD
ppDPppQ
(5)
Since the buyers who like the policy are less sensitive to price increase, we thus have
11
)(
i
pp . Suppose that the supply function (2) stays the same for the moment. From
Equations (2) and (3), we can rewrite Equation (4) as,
)(
)()(
)(
11
2
11
00
i
ii
i
ppD
pppp
ppP
(6)
If the demand factor does not change, i.e., DppD
i
)( , the difference between Equations
(4) and (6) yields,
0
))()((
))()((
)(
1111
11200
i
i
i
pp
ppD
ppPP
(7)
8
Equation (7) suggests that the pet policy
i
pp will result in a higher house price, i.e.
PppP
i
)( . Now suppose that the pet policy causes the demand factor to change. When
)(
))()(())((
)(
11
110011
ii
i
ppDpp
ppD
, we can show that
0)(
i
ppPP (8)
Equation (8) implies that the pet policy
i
pp may also result in a lower house price, i.e.
PppP
i
)( , if the pet policy reduces the demand factor significantly.
Thus far, we assume that the pet policy
i
pp does not affect the supply function
(2). Generally speaking, the pet policy may also affect the supply side. If this is the case,
we can similarly show that housing prices will decrease (or increase) if there is
oversupply (or less supply) of houses with such pet policy. In sum, the model suggests
that the impact of a particular pet policy on housing prices can be positive or negative
depending on the changes of supply and demand due to the pet policy. In other words,
whether pet restrictions create a premium in housing prices becomes an empirical
question. By using a large data sample of condominium sales in the Fort Lauderdale,
Florida metropolitan area, we will provide an answer to this question in the next section.
3. Data Description and Empirical Model
Previous empirical research on the relationship between pet restrictions and
housing prices (and rents) includes Sirmans, Sirmans, and Benjamin (1989) and
Cannaday (1994).
1
Sirmans, Sirmans and Benjamin report no statistically significant
1
The Cannaday (1994) article also cites a study done by the Minnesota Real Estate Research Center (1990)
on renters whose empirical findings were the same (cats “yes,” dogs “no”).
9
relationship at even the 10 percent level between “no pets” restrictions and multi-family
rents using a sample of 188 apartment rental transactions from 92 apartment complexes
in Lafayette, Louisiana. All observations were of rents, physical characteristics, location,
amenities, services, occupancy restrictions, and external factors as of September 1986.
The amenity in question was the allowance or disallowance of pets, without
discrimination between dogs and cats. Cannaday’s analysis employs a data sample of
1,061 condominium sales that occurred in Chicago between 1988 and 1991, and
considers four types of pet restrictions: no pets allowed, cats only allowed, small dogs
allowed, and large dogs allowed. He concludes that in the market area and time period he
studied, condo prices are positively related to “cats allowed,” but negatively related to
“dogs allowed,” and that the net effect on prices related to pet restrictions ultimately
depends on what type of pets are allowed.
Extending previous analysis to a different market, a larger sample, a more recent
time period, and slightly different pet policies, a sample of condominium sales drawn
from the local MLS for the Fort Lauderdale, Florida metropolitan area, the present study
provides a sizeable data sample for analyzing the relationship between pet restrictions
and condominium prices. The sample collected for this study contains 19,324
condominium transactions that occurred between the 1
st
quarter of 2005 and the 2
nd
quarter of 2007 with sufficient information regarding the selected independent variables
to be included in the analysis. Table 2 provides descriptive statistics for variables from
the condominium transactions used in the analysis, while Table 1 gives definitions for
those variables.
10
Table 1: Variables Definitions
age Age of the unit.
age2 Squared age.
beds # of bedrooms.
baths # of bathrooms.
style Codes indicating property style.
waterfr yes if the property is exposed to waterfront.
area
MLS-defined, corres
p
ondin
g
to housin
g
sub-markets; more than 120 areas in our datase
t
income median household income ($) on the zipcode level
vacant yes if the proeprty is vacant.
mom months on the market.
yq year and month of the sale.
pets_allowed yes if the property allows pets.
pets_allowed_with_restriction yes if the property allows pets with certain restrictions.
cats_only yes if the property only allows cats.
dogs_only yes if the property only allows dogs.
small_pets_only yes if the property only allows small pets less than 20 pounds.
large_pets_only yes if the property only allows large pets heavier than 20 pounds.
ln(P) Sale price in natural logarithm.
Dependent Variable
Condo Property Characteristics Variables
Neighborhood Characteristic, Location and Other Variables
11
Table 2: Summary Statistics
Mean Std Dev. Mean Std Dev. Mean Std Dev.
age
24.00 10.74 19.92 11.89 20.32 11.83
age2
691.28 442.87 538.33 451.98 552.74 453.73
beds
1.89 0.64 2.03 0.69 2.01 0.68
baths
1.83 0.50 1.90 0.58 1.88 0.57
waterfr
0.415 0.493 0.394 0.489 0.397 0.489
vacant 0.40 0.49 0.37 0.48 0.37 0.48
mom 2.31 2.29 2.27 2.28 2.26 2.29
style (%)
1-4 story condo 59.3% 54.0% 55.7%
5+ story condo 28.5% 24.1% 24.8%
townhouse condo 9.5% 17.6% 15.6%
villa condo 2.7% 4.3% 3.9%
pet restrictions (obs)
cats only 634
dogs only 160
small pets only 2,918
large pets onlys 1,895
others (unspecified) 3,003
income $44,806.6 $10,994.8 $47,915.9 $12,361.5 $47,786.1 $12,108.0
Sale Price $235,600.2 $194,358.4 $283,567.1 $232,877.5 $280,364.6 $228,670.2
Time of Sale (%)
2005Q1 0.6% 0.7% 0.7%
2005Q2 9.7% 8.8% 9.0%
2005Q3 17.1% 16.8% 17.0%
2005Q4 10.9% 11.0% 10.9%
2006Q1 14.9% 15.7% 15.5%
2006Q2 12.6% 13.1% 13.1%
2006Q3 10.1% 10.9% 10.7%
2006Q4 9.0% 8.8% 8.6%
2007Q1 10.3% 9.5% 9.8%
2007Q2 5.0% 4.7% 4.8%
Variables
N=19,324
Full Sample
N=9,748
Pet allowed w/ or w/o restrictions
N=8,610
Pet allowed w/ restrictions
The method of analysis is the familiar hedonic pricing model with the natural log
of transaction price as the dependent variable and property/market/amenity characteristics
as independent variables. The available information from the MLS regarding
condominiums in this market area permits analysis of (1) “no pets allowed,” (2) “any pets
12
allowed,” (3) “pets allowed with some restrictions,” (4) “only small pets allowed,” (5)
“only big pets allowed,” (6) “only dogs allowed,” and (7) “only cats allowed” pet policies.
Using the full sample, the first specification is:
allowedpetsCmom
NAgeAgeLSP
_
)ln(
876
5
2
43210
(9)
where P is the condominium price; S denotes a set of structural characteristics; L is the
location control variable. There are over 120 MLS-defined areas in the Fort Lauderdale,
Florida metropolitan area. In the opinion of brokers, the MLS-defined areas generally
correspond to housing submarkets. Similar to Carter et al (2011), we used these MLS-
defined areas to control for location. Age and Age Squared are included to account for the
possible nonlinear effect due to higher likelihood of renovations as dwellings age
(Goodman and Thibodeau (1997)); N controls for neighborhood effects; mom controls for
months on the market since listing (Cheng, Lin and Liu (2008)); C is a vector of
year/quarter of sale to control for seasonal effect and market conditions. Pets_allowed is
the dummy variable indicating whether any pets are allowed on the property.
The second specification estimates a similar model using a subsample of
pets allowed w/ or w/o restrictions to examine the impact of “pets allowed with
restrictions” on sales prices:
nsrestrictiowithallowedpetsCmom
NAgeAgeLSP
___
)ln(
876
5
2
43210
(10)
The third specification is used to estimate how different “pet restriction”
policies, such as cats only, dogs only, small pets only, large pets only, and others,
affect sales price. In our sample the categories of cats only, dogs only, small pets
13
only, large pets only, and the others (unspecified) are mutually exclusive.
2
So,
the estimation sample is the subsample of pets allowed with restrictions and the
model can be rewritten as follows:
onlycats
onlydogsye_pets_onllonlypetssmall
CmomNAgeAgeLSP
_
_arg__
)ln(
11
1098
765
2
43210
(11)
Variables of interest are the coefficients for pets_allowed in the first specification,
pets_allowed_with_restrictions in the second specification, and small_pets_only,
large_pets_only, dogs_only, and cats_only in the third specification. Following Kennedy
(1984), the percentage change of housing price (g) due to these pet policies can be
calculated as follows:
100*]1))var(
2
1
[exp(
g
(12)
4. Regression Analysis
What distinguishes the housing market here under investigation from those of
previous studies is that it is largely a retirement community. South Florida is renowned
for being a place where seniors retire, and its housing market has been used in studies of
age-restricted housing (Allen (1997); Carter, et al. (2011)), as has Phoenix, Arizona
(Guntermann and Moon (2002), Guntermann and Thomas (2004) and Lin, Liu and Yao
(2010)). Federal legislation takes cognizance of the favorable influence of pets on
seniors in the Pet Ownership in Assisted Rental Housing for the Elderly and Handicapped
Act, mentioned above. Therefore, for condominiums in a retirement area such as South
2
Table 2 illustrates that among 8,610 observations in the sample, “cats only” has 634 observations, “dogs
only” has 160 observations, “small pets only” has 2,918 observations, “large pets only” has 1,895
observations and “others (unspecified)” has 3003 observations.
14
Florida there could be significant demand for an unrestricted pet policy. Accordingly, a
price premium is expected for allowance of pets in South Florida housing.
The empirical results are shown in Table 3. The coefficient of interest for the first
equation, pets_allowed, is 0.110 (a price premium of 11.6%),
3
statistically significant at
the 1% level, showing sales of condominiums with pets allowed with no or certain
restrictions during the observed period sell for 11.6% more than other condominiums
with no pets allowed, ceteris paribus. The coefficient for pets_allowed_with_restrictions
in the second equation is - 0.0132 (a discount of 1.3%),
4
significant at the 5% level,
demonstrating that sales of condominiums with pets allowed with certain restrictions
during the observed period suffer a price discount of 1.3% compared with other
condominiums with pets allowed with no restrictions , ceteris paribus. In the third
specification, the coefficients for cats_only, small_pets_only, dogs_only, and
large_pets_only are all negative, they are -0.071, -0.024, -0.002, and -0.004, respectively,
and the first two are significant at the 1% level. This result suggests condominiums with
cats_only and small_pets_only suffer most in price discount. Overall, we can conclude
that unrestricted pet policy creates a significant premium in condominium price, along
with discounts for condominiums that do not allow pets or have certain restrictions on
pets (cats_only and small_pets_only).
The R-squares show that the models are reasonably good fits for each of the
estimated price equations, at R
2
= 89.5 percent for the first specification (where the
number of observations was 19,324), R
2
= 89.1 percent for the second specification
(where the number of observations was 9,748), and R
2
= 89.3 percent for the third
3
11.6% is estimated using Equation (12).
4
A discount of 1.3% is estimated by using Equation (12).
15
specification (where the number of observations was 8,610). Other coefficients are
consistent with prior expectations. For example, coefficients on beds and baths are
positive and highly significant. Waterfront (waterfr) properties sell for more while
vacant (vacant) condominiums sell for less. The coefficient for age is negative and highly
significant, because a house depreciates as it ages. The age-squared term has a positive
effect on housing price, reflecting nonlinearity and vintage effect. Higher floors are
associated with price premiums. This result is consistent with the findings by So, Tse and
Ganesan (1997). The coefficients for Year and Quarter of Sale are all highly significant
and follow a distinct pattern from 2005 to 2007. Starting in 2005Q1 the coefficient is
negative, then switches to positive in 2005Q2, then grows over the next three quarters
before falling over the last four quarters. This demonstrates that housing market
conditions were changing constantly during that time period in South Florida.
5
5
At the suggestion of an anonymous reviewer, we tested for spatial autocorrelation using Moran’s I method
(Moran (1950)). The tests failed to reject the null hypothesis of zero spatial autocorrelation, indicating
there the 120 location control variables in our specifications have adequately addressed the possibility of
spatial autocorrelation. The results of the Moran’s I tests are available upon request.
16
Table 3: Regression Results
Coefficient T-Stat. Coefficient T-Stat. Coefficient T-Stat.
Intercept
10.955*** 59.31 10.556 44.17 10.864 44.32
Pet Allowed
(yes)
w/o restriction
w/ restriction
(yes)
cats only -0.071*** -8.20
small pets only -0.024*** -4.94
large pets only -0.002 -0.42
dogs only -0.004 -0.27
others (unspecified) 0.000 .
age
-0.012*** -20.13 -0.014*** -19.36 -0.013*** -17.41
age2
0.000048*** 3.35 0.000113*** 6.11 0.000104*** 5.29
beds
0.192*** 54.50 0.159*** 36.94 0.156*** 34.04
baths
0.21*** 46.04 0.220*** 41.45 0.221*** 39.06
waterfr
(yes) 0.079*** 24.12 0.081*** 18.06 0.079*** 16.77
vacant
(yes) -0.032*** -11.01 -0.013*** -3.23 -0.014*** -3.48
tom
0.002*** 3.15 0.006*** 6.92 0.006*** 6.52
style
1-4 story condo
-0.148*** -15.06 -0.133*** -12.36 -0.128*** -10.86
5+ story condo
-0.076*** -7.01 -0.067*** -5.22 -0.065*** -4.72
townhouse condo
-0.120*** -12.20 -0.101*** -9.84 -0.104*** -9.2
villa condo
0.000 . 0.000 . 0.000 .
floor level
<= 6
0.000 . 0.000 . 0.000 .
7-15
0.084*** 5.42 0.068*** 3.39 0.071*** 2.90
>=16
0.154*** 12.45 0.148*** 9.92 0.141*** 8.40
log(income)
0.122*** 10.45 0.163*** 11.37 0.134*** 8.69
Year and Quarter of Sale
2005Q1
-0.085*** -3.87 -0.07** -2.4 -0.104*** -3.30
2005Q2
0.051*** 6.48 0.028*** 2.6 0.026** 2.31
2005Q3
0.101*** 13.87 0.076*** 7.66 0.077*** 7.39
2005Q4
0.141*** 18.4 0.100*** 9.75 0.104*** 9.58
2006Q1
0.148*** 20.34 0.122*** 12.53 0.123*** 11.97
2006Q2
0.134*** 18.14 0.109*** 10.97 0.115*** 11.08
2006Q3
0.103*** 13.53 0.074*** 7.3 0.075*** 6.98
2006Q4
0.069*** 8.98 0.050*** 4.83 0.052*** 4.74
2007Q1
0.041*** 5.53 0.044*** 4.26 0.040*** 3.77
2007Q2
0.000 . 0.000 . 0.000 .
Location control
R
2
89.5% 89.1% 89.3%
19,324 9,748 8,610Number of Obs.
Subsample II
Pet allowed w/ restrictions
Yes Yes Yes
0.110*** 30.20
-0.0132** -2.25
Full Sample
Pet allowed or not allowed
Subsample I
Pet allowed w/ or w/o restrictions
Note: Statistical significance is indicated as follows: *** at the 1% level and ** at the 5% level.
Dependent variable is sale price in natural logarithm. The coefficients for over 120 binary
location variables are omitted for brevity.
17
5. Conclusions and Policy Implications
While there are certainly emotional and disability-related reasons why people
prefer to have pets in their homes, the analysis presented in this study suggests that
condominium prices are significantly related to pet policies. To the extent that these
results support the contentions of anti-restriction activists, condominium developers and
owner associations might well consider changing existing prohibitions against certain
types of pets (or maintaining the status quo in the absence of such restrictions) in pursuit
of enhanced property values in South Florida. This market evidence may not, however,
be sufficient to persuade elected officials from mandating the allowance of pets in
common interest housing at the state level. As noted by Cannaday (1994), government or
condominium association regulations that result in uniform pet policies would eliminate
this amenity as a price determinant. Such interventions could result in social welfare
losses if some portion of condominium owners would pay more for units in pet restricted
condominium projects.
It would behoove those doing further research in the area of pet restrictions and
housing prices to repeat this process for other housing markets. Specifically, it would be
interesting to gauge residential demand for pets in various areas and to match those
findings with the consequences for housing prices.
18
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