Analyzing the Olympic Games // GIS Final Project

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ANALYZING THE 1996

OLYMPIC GAMES AND

ITS EFFECT ON THE

QUALITY OF LIFE

Benjamin Bromberg Gaber

GIS Methods & Case Studies Final Project December 2013


Executive Summary This report analyzes census data from 1990 to 2010 to analyze if the 1996 Atlanta Olympic Games impacted the quality of life of residents. Through this analysis, this report also seeks to determine the utility of the UN Human Development Index as a method of evaluating the quality of life of a people in a specific location.

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Page 3 • Background Page 4 • Research Questions • Scope • Hypothesis • Limitations

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Table of Contents

Page 5 • Summary of Key Findings • Equations • Primary Data Sources • Methodology Pages 6-8 • Discussion of Findings

Executive Summary, Table of Contents

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Page 9 • Conclusions Page 10 • Data Sources • Step-by-step Methodology Page 11 • Text and Image Sources


Background Every two years, the international sporting community descends on a single city for the Olympic Games. With the Olympics come a considerable number of visitors, scrutinizing media attention, and massive construction and logistical projects. While the Olympic movement is centered on personal improvements and notions of peace, the Olympics have “come to be viewed as a potential catalyst for urban transformation and the impetus for social, economic, and political change.”2 It has also been concluded that the 1996 Olympic Games had a “significant positive impact” on areas that hosted Olympic events, though a definite conclusion about wages could not be made.3 In his masters’ degree thesis, Constantine Kontokosta also finds that the Olympic Games seem to have a “generally positive impact on housing prices.”4 Other reports have concluded, however, that this is not necessarily the case; as stadiums in cities around the world lie empty after hosting the Olympics,5 residents are evicted from their homes to make way for the Games, and the logistical nightmares of hosting millions of people threaten the way of life in the city, not only for those few weeks during competitions, but for many years after.6 Some have found that the boost in visitors due to the Games isn’t even that great as compared to other cities during the same period of summer.7 With ongoing debate on the residual effects of the Olympics, and reports on the lasting economic impact a mega-event like the Olympics leaves on a city, it should be considered whether or not the Olympics actually improves the quality of life in the host city. Despite the huge influx of spending on infrastructure, an increase in tourism, and other “improvements” of the city, one may wonder if the average citizen’s life is impacted.

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Augusta

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Macon

Savannah

Columbus

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Map 2: Georgia with Major Cities, 2010 Census Boundaries, and 1996 Olympics Venues

Background

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Research Questions

Through GIS analysis, this project aims to answer the following questions:

• How was the quality of life of Georgia impacted by the 1996 Olympics? • Is the UN Human Development Index an appropriate tool for analyzing quality of life? While a report analyzing trends and patterns in every host city in the world or even limited to the United States would be interesting, for the purposes of this class final project, it is an impossible task, and the project has been limited to analysis of the years 1990-2010 and only the state of Georgia. For future research, a wider time and spatial frame for additional Olympic Games should be used.

Hypothesis

Based on my pre-project research, I predicted that I would not expect to see a great improvement in the quality of life for inhabitants in Georgia during the time analyzed. I also predicted that the areas immediately surrounding the venues would have a better quality of life index than the state average.

Scope

In considering the impact of the Olympic Games, it is important to understand the metrics used to measure quality of life. For the purposes of this project, quality of life is measured based on median household income, average educational attainment, and median age. These metrics are used since this type of data is readily available via the United States Census Bureau, and these are the types of data used for the Human Development Index, a statistic used by the UN (explained on page 5).

Limitations

Photo 1: Atlanta 1996 Logo8

Photo 2: Georgia Dome (basketball, artistic gymnastics, and handball venue) with downtown Atlanta in background, 19969

Due to the unavailability of data, differences in measurements between countries, lack of digital data, and the time commitment that would be necessary to produce a full report looking at multiple cities across many years, this project has been limited to looking at the quality of life index in Georgia between 1990 and 2010. While this is examined further in the discussion the findings below, the data for this project is limited to the frequency of the surveys—censuses are only taken every ten years in the United States—which severely impacts the data and findings. The data used is also limited to the data collected by the US Census Bureau, thus the types of data used in this quality of life index differ from the UN index. Again, this has implications for the project’s conclusions, but for the purposes of this class project, these alternates will have to take the place of the UN index’s data.

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Research Questions, Scope, Hypothesis, Limitations


Summary of Key Findings

• Quality of Life generally improved in Georgia between 1990 to 2010 • Quality of Life index increased more between 2000 and 2010 than 1990 and 2000, but no patterns or conclusive findings • No spatial-based patterns or conclusive findings • Index requires more detailed data and further testing to determine utility as a tool • Larger outside patterns and trends may be affecting quality of life in the areas studied • Lack of pattern may be due to the Atlanta Games’ use of preexisting venues and their locations

Photo 3: The Olympic Flag10

Quality of Life Index Quality of Life Index = ( Age Index x Income Index x Education Index ) (1/3) Median Age

Age Index = Income Index =

Education Index =

34.34 ( LN(Median Household Income) - LN(107721) ) ( LN(107721) - LN(100) )

√((

# of people in category x years 13.2

13 ) ( 20.6 )

Primary Data Sources • US Census Bureau 1990 Decennial Census Data • US Census Bureau 2000 Decennial Census Data • US Census Bureau 2010 American Community Survey 5-Year Estimate Data • US Census Bureau 2010 Census boundaries • UN Human Development Index

.951 34.34 = Georgia Median Age

Attainment Category / Years for Index Less than high school / 11

(Dropout (16) Enrollment age (5))

High school / 13 Less than BA / 15 BA / 17 More than BA / 20

Methodology

107721 = Median income of country with the highest median household income 100 = Median income of country with the lowest median household income 13 = Expected educational attainment for Georgia (high school diploma) 13.2 = Expected educational attainment for country with the lowest expected attainment 20.6 = Expected educational attainment for country with the highest expected attainment .951 = Given

Photo 4: The Olympic Torch11

For the purposes of this project, the most essential conclusions were based on how the quality of life index changes over time. In order to understand the data and organize it in a systematic way, the 1990 and 2000 US Census data and 2010 ACS data were spatially organized according to 2010 census boundaries. Due to the Modifiable Aerial Unit Problem, it had to be assumed for the purposes of this project that the data is consistent across the census tracts when reconciling differences in shape, size, and number of census tracts. After the data was fully organized, the quality of life per census tract was calculated for each year, and then the datasets were merged together. The quality of life calculation used here is based off of the UN index and assumes that the data used and index changes made are close enough to the original index. Change over time within the index was calculated and then compared spatially based on distance from the Olympic venues as compared to the state-wide mean.

Key findings, Primary Data Sources, Quality of Life Index, Methodology

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Discussion of Findings

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When looking closer, for those census tracts that hosted Olympic venues, the quality of life improved 51.73% between 1990 and 2000, and 20.98% between 2000 and 2010. Of the 18 census tracts that contained an Olympic venue in Georgia, five had a quality of life index higher than the state mean between 1990 and 2000 while only two tracts were above the state mean between 2000 and 2010.

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Census tracts within 5 miles from an Olympic venue include far more census tracts than likely directly impacted by an Olympic venue, yet the quality of life increased 44.44% between 1990 and 2000, and 50.60% between 2000 and 2010; higher than the tracts that hosted and those only 1 mile apart. Of the 381 tracts located within 5 miles from a venue, 113 had an index higher than the state mean between 1990 and 2000, while 66 had an index higher than the state mean between 2000 and 2010 (see maps 9, 11, 13 & 15). While generally the trends that prove that the quality of life on an area containing an Olympic venue increased, the spatial analysis of where these increases take place does not back this up. In fact, no pattern seems to emerge from the analysis of the census tracts by distances from venues. This may not necessarily disprove any kind of connection between a region hosting the Olympics and seeing an improvement in the quality of life of its citizens, and may just be a sign that more rigorous and detailed data is required to connect the

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Discussion of Findings

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2000

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2010

For census tracts within 1 mile of an Olympic venue, the quality of life increased 29.19% between 1990 and 2000—less than the exact tracts that hosted a venue, and 26.86% between 2000 and 2010—higher than the tracts containing a venue. Of the 85 tracts located less than 1 mile from an Olympic venue, 19 were higher than the state mean between 1990 and 2000; while 11 tracts had a higher index than the state mean between 2000 and 2010. So the quality of life actually improved in more places during the 19902000 decade than 2000 to 2010 (see maps 8, 10, 12 & 14).

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1990

If one looks generally at Georgia from 1990 to 2010, there was generally an improvement in the quality of life of Georgia residents as shown in maps 3-5. Statewide, the quality of life index increased by 157.82% between 1990 and 2010. While there was a general increase in those years, when breaking down the statewide mean percentage change of the index, the state index increased 44.18% between 1990 and 2000 and 85.39% between 2000 and 2010 showing that the state’s quality of life actually increased more during the latter time period than the decade during which the Olympics took place (see maps 6 and 7).

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Maps 3-5: Quality of Life Index by Georgia Census Tract with Venues


Legend

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-.10% - -.50%

%00-10 -.50% - -.01% PCT00_10 0% -1.000000 - -0.500000 .01% - 1.00% -0.499999 - -0.000010 1.01% - 20.00%

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20.01% - 80%-0.000009 - 0.000000

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0.000001 - 1.000000 1.000001 - 20.000000

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20.000001 - 80.000000

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Map 6: Quality of Life Index Change Over Time by Georgia Census Tract with Olympic Venues, 1990-2000 ! (

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Map 7: Quality of Life Index Change Over Time by Georgia Census Tract with Olympic Venues, 2000-2010

trends. Since the United States only collected census data every 10 years, many events could have happened in the intervening years that would impact the quality of life of all citizens. Not only are national and international trends in play, for example: the general trend of suburbanization, the Dot-Com Bubble, the recent national recession, etc.; but also the effects of more spatially restricted events may be missed in the context of such a large time period. The effect the Olympics had on Georgia may have been great but may have been concealed by the large gaps in the data. A survey like the new American Community Survey would provide more specific data, but the survey did not exist until after the 1996 Olympics, and the intervening years were not included in this project. More productive analysis might be found by using this index on a host city like Salt Lake City for which the survey might register changes. Another crucial aspect to keep in mind when studying the 1996 Games is the use of preexisting stadiums, and their locations. While other Games built many venues solely for the purpose of hosting the Olympics, Atlanta used many preexisting venues. The Olympic Stadium, the Georgia Dome, and the Georgia Tech Aquatic Center are the only venues that were originally built in the 1990s. Most were improved or renovated for the Games, but some venues were built decades before, like Sanford Stadium, which hosted the 1996 soccer finals but opened in 1929. By using preexisting venues, the Games saved a significant amount of taxpayer funds, but also did not spend as much on infrastructure, thus may not have improved the quality of life as much as other host cities may have. In addition, many of the venues used were university athletic venues. Again, this may saved money, but an analysis of the quality of life based on distance from venues may be pointless, since the index of areas surrounding university venues would be based on younger people who have not completed their education in addition to generally being unemployed. For other venues such as the Olympic Stadium, located in buffer areas between residential and commercial areas, or the shooting venue located outside of central Atlanta, the population (or lack thereof) of the area surrounding the venue would also skew the data, producing analysis that may not actually reflect the true quality of life. Regardless of what venues were used, it is impossible to discern a pattern in the quality of life data used in this project. Further research needs to be done to better answer the trends of Georgia’s quality of life as it relates to the Olympics, and more precise data is necessary to understand how useful the quality of life index is in general.

Discussion of Findings

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Within 1 Mile from Olympic Venue

Index % Change Above State Mean

Index % Change Below State Mean

Index % Change Below State Mean

Beyond 1 Mile from Olympic Venue

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Within 5 Miles from Olympic Venue

Index % Change Above State Mean

Beyond 5 Miles from Olympic Venue

Index % Change Above State Mean

Index % Change Above State Mean

Index % Change Below State Mean

Index % Change Below State Mean

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Map 8: Quality of Life Index % Change 1990-2000 Comparing Areas Within 1 Mile from Venue to State Mean

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Map 9: Quality of Life Index % Change 1990-2000 Comparing Areas Within 5 Miles from Venue to State Mean

Within 1 Mile from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Within 5 Miles from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Beyond 1 Mile from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Beyond 5 Miles from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

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Map 12: Quality of Life Index % Change 1990-2000 Comparing Areas Within 1 Mile from Venue to State Mean; Atlanta Metropolitan Area Detail

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Map 13: Quality of Life Index % Change 1990-2000 Comparing Areas Within 5 Miles from Venue to State Mean; Atlanta Metropolitan Area Detail

Conclusions

While the quality of life increased throughout the state of Georgia, no pattern or specific answer to the research questions emerge. A connection between quality of life and distance from an Olympic venue may exist, but with the data analyzed for this report, one is not prevalent. Further testing of this model and method is necessary not only to determine whether hosting the Olympics helped improve the quality of life of citizens of Georgia, but also to determine whether or not this quality of life model is a useful one. If the model is proven to be useful, lawmakers, citizens and other public policy stakeholders would

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Conclusions


Within 1 Mile from Olympic Venue Legend

Within 5 Miles from Olympic Venue

Index % Change Above State Mean

Index % Change Above State Mean

Index % Change Below State Mean

Index % Change Below State Mean

Beyond 1 Mile from Olympic Venue

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Index % Change Above State Mean

Index % Change Above State Mean

Index % Change Below State Mean

Index % Change Below State Mean

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Map 10: Quality of Life Index % Change 2000-2010 Comparing Areas Within 1 Mile from Venue to State Mean

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Map 11: Quality of Life Index % Change 2000-2010 Comparing Areas Within 5 Miles from Venue to State Mean

Within 1 Mile from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Within 5 Miles from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Beyond 1 Mile from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

Beyond 5 Miles from Olympic Venue Index % Change Above State Mean Index % Change Below State Mean

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Map 14: Quality of Life Index % Change 2000-2010 Comparing Areas Within 1 Mile from Venue to State Mean; Atlanta Metropolitan Area Detail

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Map 15: Quality of Life Index % Change 2000-2010 Comparing Areas Within 5 Miles from Venue to State Mean; Atlanta Metropolitan Area Detail

have a new method of understanding how mega events such as the Olympics, economic events such as recessions, and trends such as suburbanization impact the quality of life of average citizens. It is recommended that further research is undertaken that looks at more locations with a wider time frame, but with more specific data. While we may not be certain as to the quality of life of Georgia and how the Atlanta Olympic Games impacted it from this report, through further research we may learn how useful this quality of life model is, as well as whether or not the Olympics does in fact have a ‘significant positive impact’ on the host cities.

Conclusions

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Step-By-Step Methodology

1. Obtained census tract data for 1990-2010 2. Selected by location to select Georgia 3. Joined census data to tracts 4. Lined up FIPS fields according to 2010 numbers a. Used field calculator to ensure that FIPS numbers line up properly 5. Projected according to USA Contiguous Albers Equal Area Conic to ensure precise area calculations 6. Calculated area of each census tract 7. Union 1990 and 2000 to 2010 boundaries to ensure everything lines up 8. Divide new area of census tract region by original 9. Calculate the quality of life a. Age Index b. Income Index c. Age Index d. Quality of Life Index 10. Multiply Quality of Life Index by the percentage in step 8 11. Dissolve boundaries based on 2010 boundaries while taking the sum of the quality of life per census tract 12. Merge datasets to compare change over time 13. Calculate percent change subtracting earlier index from latter index and dividing by the earlier index 14. Create a buffer surrounding the venues at one mile and five miles 15. Clip the Quality of Life Indices and percent changes according to 2010 boundaries 16. Calculate the Quality of Life indices and percent changes within buffered zones as compared to state averages 17. Export maps

Datasets

• United States Census Bureau 1990 Decennial Census boundaries12 • United States Census Bureau 1990 Decennial Census data13 • United States Census Bureau 2000 Decennial Census data and boundaries14 • United States Census Bureau 2010 American Community Survey 5-Year Estimate data15 • United States Census Bureau 2010 Census boundaries16 • UN Human Development Index17 • 1996 Atlanta Olympic Games Venue List18

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Census Tracts With Venue 1990 2000 2010

1 Mile from Venue 1990 2000 2010

5 Miles from Venue 1990 2000 2010

State-Wide Mean 1990 2000 2010

Age

Education

Income

QOL

Graph 1: Quality of life index and sub-indexes by year

Photo 5: Kerri Strug on the high beam19

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Step-by-Step Methodology, Datasets


Photo 6: Michael Johnson sets a new 200 meter world record20

Sources & Images

1. Cover Photo: http://cdnolympicfr.files.wordpress.com/2013/02/atlanta-1996-11.jpg 2. Kontokosta, Constantine E. The Price of Victory?: The Impact of the Olympic Games on House Prices. Thesis. Columbia University, 2005. N.p.: n.p., n.d. Print. – Page 2 3. Hotchkiss, Julie L., Robert E. Moore, and Stephanie M. Zobay. “Impact of the 1996 Summer Olympic Games on Employment and Wages in Georgia.” Southern Economic Journal 69.3 (2003): 691-704. JSTOR. Web. 7 Nov. 2013. – Page 703-704 4. Kontokosta Page 1 5. “Haunting Photos Of Athens Eight Years After The Olympics.” Architizer. Architizer, n.d. Web. 07 Nov. 2013. <http://architizer.com/blog/haunting-photos-ofathens-eight-years-after-the-olympics/>. 6. O’Sullivan, Feargus. “The Fuzzy Future of London’s Olympic Stadium.” The Atlantic Cities. The Atlantic, 23 May 2012. Web. 07 Nov. 2013. 7. Moss, Mitchell L., and Carson Qing. New York City Wins the Gold Medal for the Visitor Olympics. Scribd. Scribd, 13 Aug. 2012. Web. 07 Nov. 2013. <http:// www.scribd.com/doc/102849561/Rudin-Ctr-Olympics-London-v-NYC>. 8. Photo 1: http://www.currybet.net/images/articles/2008/olympic_dissent/1996_olympic-logo.jpg 9. Photo 2: http://upload.wikimedia.org/wikipedia/commons/d/db/Atlanta_skyline_with_sports_complexes.JPEG 10. Photo 3: http://upload.wikimedia.org/wikipedia/commons/d/d7/JO_Atlanta_1996_-_Drapeau.jpg 11. Photo 4: http://www.thecontemporary.org/assets/16261/Atlanta_Olympic_torch_cropped_media_cycle.jpg 12. Minnesota Population Center. National Historical Geographic Information System: Version 2.0. Minneapolis, MN: University of Minnesota 2011. 13. US Census Bureau. “Decennial Census, 1990.” Social Explorer. Web. 14. US Census Bureau. “Decennial Census, 2000.” Social Explorer. Web. 15. US Census Bureau. “American Community Survey; 5-year estimate, 2010.” Social Explorer. Web. 16. US Census Bureau. “Decennial Census Boundaries, 2010.” Social Explorer. Web. 17. Human Development Report 2013. United Nations Development Programme. United Nations, 2013. Web. 7 Nov. 2013. <http://hdr.undp.org/en/media/ HDR_2013_EN_TechNotes.pdf>. 18. The Atlanta Committee for the Olympic Games. The Official Report of the Centennial Olympic Games. Rep. Atlanta: Peachtree, 1997. Print. 19. Photo 5: http://www.dailyherald.com/storyimage/DA/20120726/NEWS/707269813/EP/1/15/EP-707269813.jpg 20. Photo 6: http://sportsmvp.files.wordpress.com/2012/09/michael_johnson_teams_with_williams_formula1.jpg 21. Back Photo: http://doyouremember.com/wp-content/uploads/2013/05/thetimes.co_.uk_.jpg

Sources and Images

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