Download The Price of Victory: The Impact of the Olympic Games

49(5) 961–978, April 2012
The Price of Victory: The Impact of the
Olympic Games on Residential Real Estate
Markets
Constantine Kontokosta
[Paper first received, October 2010; in final form, April 2011]
Abstract
The Olympic Games have come to be viewed as an unprecedented opportunity to
leverage a short-term event into a long-term positive legacy. Although the Olympics
are assumed to yield economic benefits, there has been no rigorous analysis of the
impact of hosting on residential real estate markets. Utilising a substantial dataset
for six host cities and comparable cities between 1984 and 2000, this paper employs
an adjusted interrupted time-series approach to estimate the house price impacts of
hosting the Olympic Games. The results suggest that the Olympics are not a ‘one
size fits all’ economic development strategy and that potential outcomes are dependent on a number of factors, including the co-ordination of planning and Olympicrelated development and the relative scale of the total Olympic investment.
1. Introduction
The term ‘mega event’ was first used by
Ritchie and Yangzhou (1987, p. 20) to
describe a major, limited-duration event
that served to ‘‘enhance the awareness,
appeal, and profitability of a tourism destination in the short and/or long terms’’. By
this definition, the Olympic Games have
become the pinnacle of mega events. In the
115 years of their modern existence, the
Games have evolved from an international
competition of athletes to an international
competition of cities and nation-states. The
Olympics have come to be viewed as a
potential catalyst for urban transformation
and the impetus for social, economic and
political change.
Specific motivations for hosting an
Olympic Games are directly linked to the
political, social and economic reorganisations brought on by the effects of globalisation. Cities view the Games as an
opportunity to make a political statement,
create a lasting marketing image, encourage
foreign investment, stimulate tourism,
Constantine Kontokosta is in the Schack Institute of Real Estate, New York University, 11 West
42nd Street, Room 418, New York, 10036, USA. E-mail: [email protected].
0042-0980 Print/1360-063X Online
Ó 2011 Urban Studies Journal Limited
DOI: 10.1177/0042098011411952
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CONSTANTINE KONTOKOSTA
inspire social reforms, provide infrastructure improvements and spur economic
activity (Altshuler and Luberoff, 2003;
Castells, 2003; Roche, 1992).
The Los Angeles Games in 1984, in particular, marked a dramatic shift in the attitudes
of cities and nations towards the Olympics.
The financial success of the event provided
the incentive for cities to host the Games as
part of a strategy for economic and physical
development and not just for visibility, prestige or symbolism (Shoval, 2002). Today,
four key objectives tend to motivate cities to
host the event: the desire to gain recognition
and acceptance at the international level; the
desire to accelerate the economic transformation; the expectation of social and political reform under a unifying common goal;
and the development of social, physical and
economic infrastructure necessary for further growth.
There have been numerous attempts to
assess the impacts and effects of the
Olympic Games on the host city and
nation (Brunet, 1995; French and Disher
1997; Hiller, 1990; Hotchkiss et al., 2003;
Preuss, 2004). Private and scholarly studies
have been used to justify both sides of the
argument whether to bid for such an
event. However, there have been few
efforts to quantify the effects of hosting
the Olympics on house prices. The omission of a rigorous examination of real
estate price effects is a critical shortcoming
in the relevant literature, as residential real
estate asset markets have become an
increasingly important component of
national and personal wealth (Bostic et al.,
2009). Given the scale of housing markets,
house prices can be a primary indicator in
evaluating any economic development initiative (Baffoe-Bonnie, 1998). In the US as
of 2006, residential real estate accounted for
more than half of the nation’s fixed capital
stock, one-third of gross private domestic
investment and about one-seventh of all
personal
consumption
expenditures.
Residential real estate prices also have significant implications for the distribution of
costs and benefits among city residents—
particularly with respect to housing
affordability—and the level of tax revenues
generated to support the provision of city
services.
The economic implications of shifts in
house prices indicate the important role of
housing in industrialised societies. Housing
satisfies many basic needs and housing conditions are often used as a measure of economic development and prosperity. Hence,
governments have long intervened in housing markets to improve conditions and
expand homeownership (Megbolugbe and
Linneman, 1993). For most households,
housing represents their largest asset and,
through mortgage debt, typically their most
sizeable liability. House price movements
affect households’ net wealth and their
capacity to borrow and spend, which translates to broader macroeconomic impacts.
This paper employs an adjusted interrupted time-series approach to explore the
impact of the Olympic Games on residential
real estate prices in six host cities between
1984 and 2000. The next section presents the
existing literature related to the economic
impacts of hosting mega events, followed by
a discussion of the theoretical expectations
of the effects of hosting the Olympics on real
estate prices. The paper continues with a
detailed description of the study area, data
sources and methodology. A discussion of
the results of the analysis follows, concluding with implications and closing remarks.
2. Literature Review
The potential economic impact of the
Olympic Games has been examined with
great interest over the past 20 years.
Beginning with the 1984 Los Angeles
Games, the Olympics (and sports events, in
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THE OLYMPIC GAMES AND HOUSE PRICES
general) have been viewed as a viable strategy for the economic development of a city
in the context of an international competition for investment (Baade, 2008). The
Olympics are expected to bring tourists,
investment and attention to the host city
and, in certain cases, the host nation. Yet
are these expectations justified? The economic and cost–benefit analyses produced
by private and government agencies to
evaluate possible impacts have often been
cited for their thinly veiled subjectivity
(Matheson, 2002). The studies themselves
can become a politically expedient means
to validate the claims made by growth
regimes eager to pursue a local development agenda (Burbank et al., 2001).
Scholarly ex post studies of the impact of
hosting the Olympics indicate mixed or
insignificant economic outcomes, while ex
ante studies, subject to the weaknesses
already identified, reveal expectations for
long-term economic benefits (French and
Disher, 1997; Kasimati, 2003). Particular
areas of concern in these economic impact
studies revolve around the omission of
opportunity cost analyses and the limited
post-Olympic period data, which often
constrain a full exploration of ‘legacy’
effects.
2.1 Empirical Evidence
In general, studies that analyse the impacts
of sporting events and stadium construction, find that their economic impact is
negligible. Baade and Dye (1988) used
regression analysis to examine the relationship of stadium construction and the addition of a sports team in a city to area
income growth. Their results indicate five
negative and only two positive statistically
significant correlations out of nine cities
studied. Employment growth has been
another subject of examination, as job creation is often said to be one of the critical
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benefits of event- and stadium-centric economic development strategies (Baade and
Matheson, 2000; Burton, 2003; Noll and
Zimbalist, 1997). The results of studies on
employment have been mixed. Baade and
Matheson (2000) found that hosting the
Super Bowl produced only 500 jobs, onetenth of the jobs predicted by the National
Football League. On the other hand, a
study of the impact of the 1996 Atlanta
Olympic Games on employment indicated
a 17 per cent increase in total employment
pre- versus post-event in counties which
contained an Olympic venue relative to
counties which did not (Hotchkiss et al.,
2003). However, the analysis includes several elements which raise concerns about
the validity of its results; these possible
sources of error and appropriate corrections will be discussed later in this paper.
Surprisingly limited attention has been
given to the effect of mega events on real
estate, particularly house prices. House
prices and residential real estate markets can
be a powerful primary indicator of economic development and quality-of-life
initiatives (Baffoe-Bonnie, 1998). With
respect to the Olympics, the expected economic benefits (such as employment
growth, increased investment and stronger
retail sales) should, in turn, produce a
noticeable shift in area house price levels
and trends through the capitalisation of
such positive amenities as the creation of
employment opportunities, higher-quality
infrastructure and improved quality of life.
To examine the potential effect, the determinants of real house price appreciation can
be divided in two groups: one that explains
equilibrium price and one that explains
deviations from the equilibrium (Abraham
and Hendershott, 1996). Determinants of
equilibrium house price level have been
shown to include employment level, real
income, construction activity, population
and interest rates (Baffoe-Bonnie, 1998). In
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CONSTANTINE KONTOKOSTA
evaluating the Olympic Games with respect
to house prices, one must examine both
components as it can be assumed, given
anticipated changes in economic variables,
that the mega event will result in a shift in
the equilibrium price level and a temporary
shock to prices raising them above their
equilibrium value.
Despite the importance of housing markets in the general economy, there have been
only a few empirical studies of the impact of
mega events or Olympic Games on residential real estate markets. For example, Preuss
(2004, pp. 263–264) devotes only two pages
of his 332-page book to real estate, discussing possible impacts on market rents. Much
of the literature has focused on the house
price impacts of stadium construction and
new sports franchises. In a study conducted
on the impact of National Football League
franchises on rents in cities, Carlino and
Coulson (2004) find that rents in metropolitan areas with franchises are about 4 per
cent higher than those without franchises.
Using a difference-in-difference approach,
Tu (2005) finds a price premium for houses
proximate to the FedEx Field stadium in
Washington, DC. These results suggest a
possible positive impact of sport-related
infrastructure on house prices.
Two studies have attempted to analyse
the impact of the Olympic Games specifically on real estate markets. Both studies
were conducted by private institutions and
both are limited by the scope of their methods. The first, a cursory analysis of house
price data, was completed by HBOS plc, the
result of the merger of the Halifax plc and
the Bank of Scotland, in 2004. The report
examines house prices in the five-year
period prior to each of the 1992 Barcelona,
1996 Atlanta, 2000 Sydney and 2004 Athens
Olympic Games. As part of a discussion of
the possible impacts of the London 2012
bid, the report claims that house prices in
Olympic host cities increased, on average,
by 19 per cent more than in the host nation.
These results are weak for several reasons.
First, the comparison between host city and
host nation does not provide an adequate
control to determine possible causation. It is
possible that growth in these cities outpaced
national growth simply as function of their
respective size and scale within the host
nation. It would be more appropriate to use
comparable cities in evaluating any price
differentials. Secondly, the report looks only
at a period five years preceding the event,
ignoring previous trends and post-event
outcomes and provides no satisfactory
explanation of why this period was chosen.
Thirdly, there is no consideration of the
effect of other explanatory variables on the
price movements observed. The report attributes any price differential between the host
city and host nation to the Olympic Games;
there is no indication that any controls were
used to account for differences in specific
economic and demographic conditions
between city and nation.
The second study was completed by Jones
Lang LaSalle, a real estate and money management firm, in 2001 (Plumb and McKay,
2001). This study provides a more detailed
review of potential Olympic impacts and
their effect on real estate markets. However,
there is limited discussion of actual price
movements in the residential sector, with
more emphasis placed on office and hotel
markets. Additionally, like the HBOS report,
there was no quantitative statistical analysis
performed to arrive at their respective conclusions. Results were reached by reviewing
previous studies and by a perfunctory examination of house price data.
3. Theoretical Expectations
General equilibrium theory suggests that
any increase in demand, holding supply
constant, will result in an increase in prices.
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THE OLYMPIC GAMES AND HOUSE PRICES
It is expected that hosting the Olympics
will result in greater demand for real estate
in the host city. One question is whether
supply increases sufficiently to balance the
potential increase in demand. Therefore,
the Olympics may result in increased real
estate prices for two main reasons. First,
infrastructure and transport projects will
result in decreased production costs for
firms, which will lead to bidding up the
price of land to access these positive externalities. If more firms locate within the host
city, then demand for housing should also
increase. Secondly, positive marketing campaigns and improvements to quality-of-life
amenities in the host city should create
increased demand for housing (Rappaport,
2009), as should the demand generated by
the increased labour force that may be
needed for Olympic-related projects. If
these demand shocks occur, it is reasonable
to expect the potential for a shift in both
the absolute level and the rate of growth of
house prices in the host city during the
pre-Olympic investment and post-Olympic
periods. In the investment period (identified as the four years preceding the event),1
Olympic-related projects and increased
speculation may fuel growth by increasing
demand faster than new supply. In the
post-Olympic period, improvements to
infrastructure and the built environment
could result in an absolute (time-invariant)
increase in house prices due to positive
amenity effects. Similarly, positive legacy
effects of marketing campaigns and political integration into world markets may
result in a lasting increased rate of price
appreciation, relative to what would have
otherwise occurred.
Two other possible price impacts are theoretically possible. From a social welfare perspective, prices may remain unchanged
when government officials and pro-Olympic
supporters are primarily concerned with residents’ welfare. In this case, the costs
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associated with the event will only be
increased to match the expected benefits to
residents. On the other hand, prices may
decrease for a number of reasons. First, if
pro-Olympic supporters derive private benefits from backing the bid, resources may be
committed to the Games beyond the
expected value of residents’ benefits. For
example, political boosters, such as Billy
Payne in Atlanta and Dan Doctoroff in New
York (during the failed 2012 bid), may have
viewed the Olympics as a personal political
challenge, one that would have resulted in
the accrual of significant political capital if
successful. Therefore, a push may be made
to host the Games without a comprehensive
strategy for integrating new development
and selecting investments that will have
long-term benefits. Secondly, if tax burdens
increase to fund the Olympics, as was the
case with the Montreal Olympics in 1976
and Athens in 2004, the capitalisation of that
increased expense may result in decreased
prices.2 Also, if new supply, fuelled by speculation and government-subsidised investment, outpaces demand, it would be
expected that a decrease in residential real
estate prices would result, at least in the
short term or until demand increases to meet
supply and absorb existing inventory. Finally,
the ‘white elephant’ effect may occur if
resources are misallocated to the Olympics
and Olympic-related development, as
opposed to other more socially and economically beneficial projects, resulting in real
estate price declines relative to comparable
cities that did not host the event and, perhaps, invested in projects that more closely
matched long-term goals.
4. Study Area and Selection of
Control Groups
The study area for this analysis consists of a
total of six host cities, including five
Summer Games and one Winter Games,
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CONSTANTINE KONTOKOSTA
held in a total of five different countries.
The cities include: Los Angeles, US; Seoul,
South Korea; Calgary, Canada; Barcelona,
Spain; Atlanta, US; and Sydney, Australia.
Olympic-related investment and GDP (or
gross state product for the US cities) for
each host city is summarised in Table 1.
For each host city, non-host comparison
cities were selected as a control group to
create a counter-factual test for house price
movements in similar cities which did not
host the Games (shown in Table 2).
Selection bias is a direct result of attempting to isolate the impact of an event that
occurs in a specific location at a specific
time. The question raised is if the impacted
city (the host city in this case) is somehow
fundamentally different from the nonimpacted (non-host) cities and, therefore, if
this difference accounts for the selection of
the impacted city for the specific intervention (Olympic Games). In the case of the
Olympics, it is possible that the cities selected
to host the Olympic Games are in some way
fundamentally different from those not
selected. More specifically, within a given
nation, the cities that are able or encouraged
to bid for the Games are typically the most
developed and, generally, have at least a
threshold level of necessary infrastructure to
host the event. The International Olympic
Committee, the organisation that selects the
Olympic host cities, utilises a candidate city
assessment decision matrix that assigns the
greatest weights to infrastructure, accommodation and security, which obviously favours
more established urban areas (International
Olympic Committee, 2003).
There are a number of methods for determining a suitable comparison group. One
approach in the case of the Olympics would
be to populate the control group with cities
that lost the bid, but made it to the final selection round. This method would provide a
control group that, based on the IOC evaluation of specific criteria, were capable, to
varying degrees, of hosting the Games. The
major weakness of this approach is that the
final-round cities are always from different
nations, making often unreliable crossnational comparisons necessary (Mondello
and Rishe, 2004). Another challenge is that
final-round candidate cities can possess
widely divergent economic, political and
social characteristics (as evidenced by the
2004 bid countries of Argentina, Sweden and
South Africa).
The approach utilised in this analysis
was to use matching techniques based on
key economic and demographic indicator
variables and pre-Olympic trends. While
propensity score matching methods were
not used due to limitations in the number
of possible control cities, the control group
cities were selected by comparing population, employment, income and house price
trends prior to the Olympic event in the
host and non-host cities. These variables
have been shown to be highly correlated
with housing demand (Abraham and
Hendershott, 1996). The comparison cities
were also selected based on qualitative measures of geographical proximity to the host
city and existing levels of infrastructure.
4.1. Study Time-frame
For the purposes of this study, data were
collected and analysed for the period starting eight years prior to the event to eight
years following the event. This analysis
period captures both short- and long-term
price effects and provides a sufficient
number of data points to minimise potential coefficient errors associated with volatility in the data. The 16-year study period is
divided into three distinct phases: the preOlympic period, the investment period
(which includes the four years preceding
the event and has been shown by Preuss
(2004) and others to contain a vast majority of Olympic-related expenditures) and
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California
Seoul Teukbyeolsi
Alberta
Catalonia
Georgia
New South Wales
Los Angeles
Seoul
Calgary
Barcelona
Atlanta
Sydney
US
South Korea
Canada
Spain
US
Australia
Country
1984
1988
1988
1992
1996
2000
Olympic year
Summer
Summer
Winter
Summer
Summer
Summer
Type
4
1
10
1
2
549.5
063.0
000.0
134.2
324.4
600.6
Total investment
(US$millions)
801
300
714
735
229
388
403.0
915.7
067.0
795.0
685.0
043.0
Olympic year GDP/GSP
(US$millions)
0.07
1.35
0.14
1.38
0.58
0.67
Investment as a
percentage of GDP/GSP
Note: GSP listed for US cities is the gross state product; for non-US cities it is national GDP. All figures in constant 2000 US$.
Sources: Bureau of Economic Analysis, US Department of Commerce; Preuss (2004); Deutsche Bank Research; World Bank; Organisation for
Economic Co-operation and Development; Olds (1998).
State/Territory
Olympic host
Summary of Olympic cities, Olympic investment and gross domestic product
City
Table 1.
THE OLYMPIC GAMES AND HOUSE PRICES
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CONSTANTINE KONTOKOSTA
Table 2.
Control group cities
Olympic year
City
MSA/Province
1984
Los Angeles (host)
San Francisco
San Diego
Sacramento
Los Angeles–Long Beach–Santa Ana, CA
San Francisco–Oakland–Fremont, CA
San Diego–Carlsbad–San Marcos, CA
Sacramento–Arden–Arcade–Roseville, CA
1988
Seoul (host)
Busan
Gwanju
Inchon
Soul t’ŭkpyŏlsi
Pusan gwangyŏksi
Kwangju gwangyŏksi
Inch’ŏn gwangyŏksi
1988
Calgary (host)
Edmonton
Toronto
Montreal
Alberta
Alberta
Ontario
Quebec
1992
Barcelona (host)
Madrid
Seville
Catalonia
Comunidad Autónoma de Madrid
Andalusia
1996
Atlanta (host)
Charleston
Charlotte
Memphis
Miami
Nashville
New Orleans
Atlanta–Sandy Springs–Marietta, GA
Charleston–North Charleston, SC
Charlotte–Gastonia–Concord, NC–SC
Memphis, TN–MS–AR
Miami–Fort Lauderdale–Miami Beach, FL
Nashville–Davidson–Murfreesboro, TN
New Orleans–Metairie–Kenner, LA
2000
Sydney (host)
Melbourne
Brisbane
Canberra
New South Wales
Victoria
Queensland
Australian Capital Territory
the post-Olympic period (which extends
for eight years after the Games).
The array of locales included in this study
required an intensive search of data sources
for useable, relevant statistics. In many
instances, data collected was converted to a
comparable uniform standard. In general,
the data used were collected from official
national, regional and metropolitan statistical agencies. It should be noted this paper
does not attempt to make direct comparisons across countries and time. Given the
numerous challenges in analysing data over
time in a specific geographical area, the
added difficulties of comparing across
distinct independent regions would create
an unacceptable level of uncertainty in the
results. It is assumed that the analysis of like
data over the same time-period will eliminate much of the potential error described
earlier, as any changes in collection or definition will be equally reflected in data for all
cities included within specific iterations of
the model. An abridged description of data
sources for each Olympic (and control
group) city is provided next.
Los Angeles, 1984. The house price index
used in the study is the Conventional
Mortgage Home Price Index created by the
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THE OLYMPIC GAMES AND HOUSE PRICES
Federal Housing Finance Agency (formerly
the Office of Federal Housing Enterprise
Oversight). House price data for the index
are collected by repeat-sale mortgages purchased by Fannie Mae and Freddie Mac in
the secondary mortgage market (Stephens
et al., 1996). Statistics of population,
employment, gross state product (GSP)
and per capita personal income were found
at the Bureau of Economic Analysis of the
US Department of Commerce.
Seoul, 1988. For purposes of establishing
real estate price levels, the only available data
for the time-period required were those of
the floating rate of land. Published by the
Republic of Korea National Statistical Office,
the percentage change in land value was
converted to an index for use in this study.
Although these data do not represent house
prices, the statistics are still suitable for estimating the impact of the Olympic Games.
Population, building approval and city revenue and expenditure statistics were also
retrieved from the National Statistical Office.
Calgary, 1988. Data from the University
of British Columbia Centre for Urban
Economics and Real Estate (CUER) were
used for house prices, mortgage rates and
rates of inflation. Income, population and
employment statistics were found in the
official Statistics Canada CANSIM database.
Barcelona, 1992. House price information for Barcelona is from the Departament
Estadı́stica of the Ajuntament de Barcelona.
House price, employment and construction-starts data were found at the Instituto
Nacional de Estadı́stica (INE). Population
data were retrieved at the Instituto de
Estadı́stica de Catalũna.
Atlanta, 1996. Statistics used in the analysis of the Atlanta Games and its comparable
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cities were compiled from the same sources
as those for the Los Angeles Games.
Sydney, 2000. House price index, employment, population and income data were
retrieved from the Australian Bureau of
Statistics, the official statistical office of
Australia.
5. Methodology
There are numerous challenges to the precise
measurement of the impacts of place-based
economic development initiatives such as
the Olympic Games. One of the difficulties
in analysing the Olympics is that, while the
event occurs at a specific time, investment
and residual effects can begin long before
and continue for years afterwards. Further
challenges in this type of analysis include
effects that: occur after a significant lag; are
difficult to quantify involving shifts in attitude or expectations; vary across geographical regions that do not correspond with
statistical boundaries; are so far-reaching as
to cause indirect impacts in areas designated
in the analysis as controls; and, may interact
with other events in such a way as to minimise their singular cause (Galster et al.,
2004). With any attempt to determine the
impact of a specific intervention, the most
fundamental challenge is to establish the
counter-factual scenario. This requires establishing a baseline case of what might have
occurred ‘but for’ the intervention (Peters
and Fisher, 2003).
Difference-in-difference estimation has
become a useful quasi-experimental
research design for evaluating the impact of
public policies and economic development
strategies on a number of critical indicators
(Meyer, 1995). The benefits of differencein-difference estimation are its relatively
straightforward design and its potential to
avoid many of the endogeneity problems
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that typically appear when making comparisons between heterogeneous groups
(Bertrand et al., 2004). Long used in comparative political economy studies, recent
papers have used the procedure to estimate
the price effects of certain discrete housing
policies (Galster et al., 1999; Galster et al.,
2004; Voicu and Been, 2008; Hotchkiss
et al., 2003; Slaughter, 2001; Card and
Krueger, 1994). One paper that specifically
examines the impacts of the Olympic
Games focuses on employment and wage
effects rather than prices (Hotchkiss et al.,
2003).
The adjusted interrupted time-series
(AITS) approach used in this paper is a
variant of difference-in-difference estimation. This model consists of identifying a
specific intervention or treatment and then
comparing differences in outcomes in both
level and trend pre-intervention and postintervention for groups affected by the
treatment against those that are unaffected
(Galster et al., 2004). Building on previous
econometric studies, the AITS Olympic
impact model is estimated using ordinary
least squares regression techniques with
panel-corrected standard errors (as suggested by Beck and Katz, 1995; Beck, 2001).
Panel-corrected standard errors provide
more robust estimates where cross-section
heteroscedasticity is present. A Prais–
Winsten transformation is used to estimate
the equation parameters in the presence of
serial correlation (Prais and Winsten,
1954). In a recent study of papers employing a difference-in-difference methodology,
Bertrand and colleagues (2004) find that, of
92 papers, 65 have a potential serial correlation problem, but only five make any
attempt to correct for this source of error.
The Prais–Winsten transformation corrects
for serial correlation without dropping the
first observation, as with the common
Cochrane–Orcutt procedure for first-order
autoregressive processes.
The complete log-linear model specification combines the variables for analysing
absolute changes in house prices and those
for analysing changes in the rate of growth
of house prices both during the investment
and post-Olympic periods
ln HPIit = a + b1 X1 + b2 X2 + b3
OLYt + b4 INVOLYt + b5
POSTOLYt + b6 TREND
+ b7 TROLYt + b8
ð1Þ
TRINVOLYt + b9
TRPOSTOLYt + e
The dependent variable is the natural log of
the house price index. A semi-logarithmic
transformation provides for non-linearity of
the data and allows for coefficient results in
the form of percentage change of the dependent variable. Alpha (a) is the constant; X1
consists of quarterly dummy variables; and
X2 is a series of fixed effects for each city.
OLY is a dummy variable equal to 1 if the
city hosted the Olympics at any time and
zero otherwise. INVOLY is equal to 1 for the
host city during the investment period and
0 otherwise; POSTOLYt is equal to 1 for the
host after the Olympic year and 0 otherwise;
TREND is a time trend incremented by 1 for
each period beginning with the first timeperiod of the data; TRINVOLYt is the trend
associated with the host city during the
investment period and equal to 0 otherwise;
TRPOSTOLYt is a time-trend variable incremented by 1 for each time-period after the
Olympic year for the host city, and equal to
0 otherwise; and e is the error term.
The coefficients of interest in the model
are b4, b5, b8 and b9, where b4 represents
the change in house price level in the host
city relative to the comparable cities during
the investment period versus prior and b5
during the post-Olympic period relative to
prior. The coefficient b8 indicates the
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THE OLYMPIC GAMES AND HOUSE PRICES
change in the rate of growth of house
prices in the host city in comparison with
the control group during the investment
period relative to prior, and b9 during the
post-Olympic period relative to prior.
6. Results: Summary and
City-specific Analysis
The results of the analysis (as shown in Table
3) indicate that the Olympic Games have a
varied impact on house prices in the host
city. Of the six Olympic cities studied,
Barcelona and Sydney were shown to have
statistically significant positive impacts, Los
Angeles, Calgary and Atlanta had results that
indicate negative effects and Seoul resulted
in no statistically significant impact. Figure
1 shows the ratio of house prices from the
base year in the six Olympic cities, using the
year eight years prior to the Games (t-8) as
the base year.
The cities included in this analysis can be
divided into two broad categories based on
the motivation for hosting and the level
resources allocated to the event. The first
group, which was motivated by regional
competitiveness, experienced few or negative
price impacts from hosting. These cities
viewed the Olympics as an opportunity to
upgrade urban infrastructure and establish or
re-establish their respective position among
other cities in the region and nation. From
the study group, Los Angeles, Atlanta and
Calgary can be classified as being in this
regional competitiveness group, given the
maturity of their housing markets, the city’s
relative position within the primary cities of
their respective country and the scale of the
urban transformation and investment associated with the Olympics.
The second category, which focused on
global emergence, includes Barcelona,
Seoul and Sydney. These cities, while established as primary economic hubs within
971
their respective countries, attempted to use
the Olympic event as an opportunity to
increase the standing of the city within the
global marketplace of tourists, investors
and corporations (Mannheim, 1992).
Barcelona allocated substantial capital to
implementing its urban planning scheme,
which was designed to create the necessary
infrastructure to accommodate and
encourage foreign investment and visitors.
Similarly, the marketing campaign for the
Sydney 2000 Games was predicated on selling the nation, not just the city, to the
world (Waitt, 1999). Cities that fall into
this global emergence category require
both substantive urban plans to guide new
development efficiently and significant
investment in new infrastructure to create
the necessary capacity to engage and compete with other global cities.
The next section provides a detailed
analysis of the city-specific impacts and the
political, economic and social context for
the Games in Atlanta, Georgia, US in 1996
and Sydney, Australia, in 2000. These cities
provide a particularly useful examination
of the specific factors influencing the range
of observed outcomes.
6.1 City-specific Results and Discussion
Atlanta, US, 1996. Atlanta had long
aspired to recognition beyond the regional
boundaries of the south-eastern US.
Atlanta positioned itself and its Olympic
bid to achieve ‘international’ status for the
city as a global business and tourist destination (Whitelegg, 2000). Central to its
strategy was the effective use of marketing
to create a distinct urban image that could
be relayed to the millions of visitors and
spectators of the Games. In September
1990, Atlanta was awarded the bid for the
1996 Summer Games, largely due to its
existing sports infrastructure, numerous
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972
CONSTANTINE KONTOKOSTA
Table 3. Impacts of the Olympic Games on house prices: results of difference-in-difference
(AITS) estimation
Olympic host city and year
OLY
INVOLY
POSTOLY
TROLY
TRINVOLY
TRPOSTOLY
R
2
1984
(n = 272)
Los Angeles
1988
(n = 76)
Seoul
1988
(n = 272)
Calgary1
1992
(n = 39)
Barcelona
1996
(n = 749)
Atlanta
2000
(n = 272)
Sydney
0.4573**
20.0267
20.1928***
0.0076***
20.0097**
20.0055**
20.7939
0.1799**
20.0664*
0.1901
20.0096*
0.0185
0.0034
0.1872*
0.0970**
20.0033
20.0987**
20.0009
20.0039*
20.0016
0.0984
0.0138
0.1341**
20.0001
0.0074**
0.0023
0.978
20.1023
20.0171
20.0259
0.953
0.973
20.0966
0.0133
0.0277*
0.976
0.971
0.991
a
Calgary hosted the 1988 Winter Olympics.
Notes: The analyses for Seoul and Barcelona utilise annual data; all others are quarterly.
* coefficient significant at the 90 per cent confidence level; ** coefficient significant at the 95 per
cent confidence level; *** coefficient significant at the 99 per cent confidence level.
Figure 1. Ratio of house prices in Olympic cities for the Olympic analysis period.
hotel accommodations and international
accessibility (French and Disher, 1997).
The financing model for the event
included private funding for development
and an entirely self-supporting operating
scheme.
The results of the AITS analysis indicate
two statistically significant coefficients out
of the four Olympic-related variables. Both
are negative. The estimate for the POSTOLY
variable indicates a -9.4 per cent change in
price level after the Olympics in Atlanta
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THE OLYMPIC GAMES AND HOUSE PRICES
relative to the control group. During the
investment period, house prices in Atlanta
experienced a rate of price decline of 0.4 per
cent per quarter relative to the control
group. In the post-Olympic period, both
employment growth and income growth in
Atlanta slowed relative to the control group,
indicating that the control group cities, on
average, experienced faster rates of economic growth. Based on these results, it
appears that the $2.2 billon (constant 2000
dollars) of Olympic-related investment was
misallocated to projects that did not
enhance the long-term competitiveness of
Atlanta.
The negative impact of the Olympics on
house prices in Atlanta reflects the underlying discord that pervaded the city with
respect to hosting the Games. The powers
behind the economic and civic boosterism
in Atlanta have been well-documented (see
Stone, 2001; Hunter, 1980). Governing coalitions of business and political leaders created a ‘regime politics’ of pro-growth actors
(Stone, 2001). Although initially reluctant
to the idea of hosting the Olympics,
Atlanta’s élite were persuaded by the persistent efforts of a local entrepreneur, Billy
Payne (Burbank et al., 2001). Opposition
continued from local residents concerned
about the location and scale of Olympic
development. Local community groups
were poorly organised and limited to countering proposed projects on an ad hoc basis.
The success of these opposition groups,
however, was largely determined by their
socioeconomic composition and the level
of support for a specific development by
the governing élites. For example, the
Blackburn Park tennis centre was quietly
relocated from the affluent, predominantly
White suburb of Dunwoody when residents
opposed the project on the basis of traffic
congestion and effect on neighbourhood
character. Conversely, resistance to the
Olympic stadium3 was formed from the
973
majority Black, low-income communities
surrounding the proposed site. Despite sustained opposition by four community organisations, decision-makers refused to
concede many of the critical points of contention in the proposal, resulting in widespread displacement and relocation in the
minority communities (Burbank et al.,
2001).
Sydney, New South Wales, Australia,
2000. The Sydney Games highlighted the
potential of the Olympics as a tool for
urban marketing. Promotion of the city
and the event were handled by the
Australian Tourist Commission (ATC)
whose strategy included pre-event, duringevent and post-event marketing campaigns.
The ATC aimed to add depth and dimension to both Sydney’s and Australia’s international image and to maximise long-term
economic and social benefits through
increased export earnings, employment,
visitor arrivals and visitor dispersal
throughout the country (Australian Tourist
Commission, 2001; Waitt, 1999). In total,
the Games cost US$4.79 billion (constant
2000 dollars) paid for using public and private funds, as well as the revenue from the
Games themselves. Sydney benefited from a
sizeable inventory of sporting facilities and
a functional urban infrastructure, but still
invested US$2.6 billion on urban development projects (Preuss, 2004).
House prices in Australia had experienced minimal growth in the years leading
up to the Olympics. Between 1990 and 1996
(start of the Olympic investment period),
prices grew slowly in Sydney at approximately 2.5 per cent per year, compared
with an average of 2.7 per cent per year
among the study group. Beginning in 1998,
however, prices began to soar as preparations for the Olympics approached their
peak (Preuss, 2004). Melbourne led the
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974
CONSTANTINE KONTOKOSTA
boom in 1997, followed by Sydney and then
Canberra and Brisbane in 2000. After the
Olympics, house prices in the four cities
grew by an impressive 13.9 per cent, resulting in a 60 per cent increase in house prices
in Sydney between 2000 and 2004.
The AITS coefficient estimates indicate
a statistically significant increase in prices
in the post-Olympic period. In addition,
there is a statistically significant positive
change in the trend of house price in
Sydney relative to the control group in the
investment period. There is a 14.4 per cent
increase in the time-invariant level of
house prices in Sydney relative to the control group in the period following the
Olympics. The trend variable for the
investment period (TRINVOLY) also suggests a positive impact of 0.7 per cent in
the growth rate of house prices per quarter, annualised to 2.8 per cent. The results
suggest a substantial positive impact of the
Olympics on Sydney house prices.
7. Policy Implications
Over the past 20 years, the Olympic Games
have come to be perceived as a viable strategy for the economic development of a city
and even a nation. As the potential rewards
of the event have grown, cities have become
direct competitors in a global system that
bypasses national boundaries (Gordon,
1999). The frenetic pace of the bidding war
for the 2012 Summer Olympic Games,
which included global cities such as New
York, London and Paris, and continuing
with the bids for the 2016 Games, accentuated the economic value attributed to hosting the event. However, the actual impacts
of the Olympics, in economic terms, are
mixed. This study found that, while the
Olympics had the potential for a positive
impact on residential real estate prices in
the host city, it was by no means a universal
conclusion. The outcomes were found to
vary considerably, affected by the host city’s
motivation for hosting (which influences
planning and project funding allocations),
its resources and its position in a regional
and global hierarchy of cities. Broadly, cities
were grouped into two categories based on
these factors: regional competitiveness and
global emergence. While the magnitude of
the impact is significant and positive in two
cases, the negative impacts observed in Los
Angeles, Calgary and Atlanta (all cities in
the regional competitiveness category)
demand careful consideration of the opportunity cost of an economic development
strategy predicated on the Olympic event.
The Olympics require an immense
amount of resources, both political and
financial, to be hosted successfully.
Understanding the house price effects of
hosting provides a useful indicator for citylevel economic conditions and changes in
trends. Given the substantial investment
made by most host cities in urban development and infrastructure (a figure that continues to increase), knowledge of probable
price effects offers a meaningful parameter
for social and distributional concerns, tax
revenue implications and overall economic
impact.
The results of the impact of the Olympics
on residential real estate prices suggest several areas of concern. First, although positive results occurred in only two cases,
increases in house prices can greatly exacerbate affordability problems for lowerincome residents and can spur processes of
gentrification. Even short-term effects, such
as during the investment period, can have
significant and lasting impact on the most
vulnerable city residents, as evidenced by
resident displacement in Atlanta in 1996
and in Beijing in preparation for the 2008
Games (COHRE, 2007). While these effects
are not captured in the city-level analysis
presented here, localised price effects
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THE OLYMPIC GAMES AND HOUSE PRICES
around Olympic-related infrastructure
should be explored. Secondly, the opportunity cost of favouring Olympic-related
projects may be substantial, and the negative outcomes discovered in this analysis
suggest significant social and economic
costs associated with a misallocation of
resources. While the Olympics is often a
catalyst to complete projects expeditiously
that lacked funding or political support,4
the use of funds—particularly public
funds—to develop event-specific infrastructure can result in ‘white elephants’
that serve little purpose in building competitive capacity for the host city after the
Olympics. Last, Olympic-related investments and resultant price movements have
substantial tax revenue implications, as
most cities derive a majority of their operating revenue from real estate taxes.
Conversely, when taxes are raised to pay
down public debt floated to fund the
Olympic-related
development
(the
Montreal Games in 1976 is a widely used
example), the increase may be capitalised
into house prices, thus resulting in a substantial drag on the economy.
8. Conclusions
It appears from the headlines and statements of Olympic proponents that the
Games are often perceived as a ‘one-sizefits-all’ economic development tool. The
results of this paper suggest that this is not
the case. The outcomes for the various
cities included in this study support the
assertion that each city must appraise its
own goals, objectives and capabilities
before pursuing such a costly and resourceconsuming endeavour. Explanations for
the difference in results can be found in
variations in the level of Olympic-related
investment, the source of funds and the
tax burdens required to repay costs, the
975
scale of the planning effort and its integration into an existing planning framework, and the pre-Olympic political and
economic standing of the host city and
nation.
While the Olympic Games can have a
positive impact on the residential real estate
market of the host city, which indicates a
positive net economic effect, it has also
been shown that the event can have a significant negative impact or an outcome that is
not commensurate with the cost. Equally
important is the potential for inequitable
distributions of costs and benefits and the
negative neighbourhood or communitylevel impacts that are possible. Given the
substantial investment of capital and
resources associated with the Games, and
the significant proportion of funding (and
political capital) typically secured from
public sources, issues of equity and distributional justice become a visible and politically contentious public policy concern. A
developing nation/city that hosts the event
may be more susceptible to disregarding
social justice in its pursuit of economic
growth and a successful event. The deadlines and massive urban development plans
associated with the Olympics create powerful pressures to complete projects on time.
The international media attention on the
host adds to these pressures by scrutinising
each decision and highlighting negative
events. While on the one hand the attention
may serve to encourage decision-makers to
be more inclusive and seek consensus, on
the other hand it may further pressure
time-constrained policy-makers to downplay opposing or alternative viewpoints.
The varying degree of impact between cities
adds additional support for a thorough,
comprehensive analysis of existing economic, social and political conditions and a
realistic appraisal of expected outcomes and
alternative investments before submitting a
bid to host the Olympics.
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976
CONSTANTINE KONTOKOSTA
Notes
1. Over 90 per cent of Olympic-related investment, on average, occurs in the four years
prior to the event (Preuss, 2004).
2. The 1976 Montreal Summer Olympics provides an example of the financial and economic risk associated with hosting the
Games. Although the necessary institutions
and, to some degree, expertise were in place,
the financial failure of the event cost the city
and province more than 10 times the original budget. With public funds accounting
for 95 per cent of the $3.3 billion total final
expenditure, the final payment on the
Olympic debt was not made until 2005
(Preuss, 2004).
3. The Olympic stadium was planned with the
intention of providing a new home for the
Atlanta Braves. Ted Turner, the team’s
owner, had earlier threatened to move the
team out of the city if a new stadium, with
enhanced revenue-generating design, was not
built (Burbank et al., 2001).
4. The Barcelona Olympics in 1992 is a good
illustration of this (see Brunet, 1995).
Funding Statement
This research received no specific grant from any
funding agency in the public, commercial or notfor-profit sectors.
Acknowledgements
The author would like to thank Lance Freeman,
Moshe Adler and Robert Beauregard, as well as
four anonymous referees for their valuable comments and suggestions. All errors remain the
author’s.
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