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Brain Drain to Brain Gain

Permanent Link: http://ufdc.ufl.edu/UFE0044744/00001

Material Information

Title: Brain Drain to Brain Gain a Comparative Local Economic Development Analysis of the Creative Class in Gainesville, Florida Using Geographic Information Systems (GIS)
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Lackey, Brett A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: analysis -- brain -- class -- comparative -- creative -- development -- drain -- economic -- employment -- florida -- gain -- gainesville -- geographic -- gis -- industry -- information -- local -- naics -- sector -- systems
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Gainesville, Florida has long suffered from “brain drain”, or the emigration of young educated professionals, mostly graduates of the University of Florida and Santa Fe College, away from the city. However, Gainesville has long shown the potential to become a flourishing town for recent college graduates to start their careers – similar to Austin, Texas or Raleigh-Durham, NorthCarolina (Florida, 2002). Despite this potential, many students continue to move away from Gainesville soon after graduation, to locate to coastal Florida or other parts of the country (Franklin, 2003). What makes graduates want to leave? What has Gainesville done right to make itself more attractive to the young professionals? In 2002, Richard Florida coined the term “creative class” to describe a socioeconomic class of professionals who are the driving economic force behind modern growing cities. The creative class is a broad group representing individuals whose jobs require applied intelligence and decision making. The creative class has grown to represent more than 35% of total employment in the U.S. in2010 and has been identified as having a strong positive impact on the growth of cities (Bureau of Labor Statistics, 2010). In August 2010, Florida published an article for The Atlantic magazine that projected a 17.65% growth in creative class employment between the years of 2008 and 2018 for Gainesville. That wasthe highest rate among metropolitan statistical areas in the nation (Florida,2010). This is concurrent with his previous analysis of Gainesville in 2002,stating that of all U.S. cities with a population under 250,000 it had the second highest potential to attract the creative class (Florida, 2002). The objective of this thesis was to find Gainesville’s industry strengths and determine how Gainesville can fully capitalize on its potential through policy and development. After the completion of analysis, it was determined that Gainesville’s strengths lie in the sectors of education and health care services and that sectors of potential growth are comprised of the real estate and rental, professional and technical services, and the public administration sectors.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Brett A Lackey.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2012.
Local: Adviser: Zwick, Paul D.
Local: Co-adviser: Bejleri, Ilir.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044744:00001

Permanent Link: http://ufdc.ufl.edu/UFE0044744/00001

Material Information

Title: Brain Drain to Brain Gain a Comparative Local Economic Development Analysis of the Creative Class in Gainesville, Florida Using Geographic Information Systems (GIS)
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Lackey, Brett A
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: analysis -- brain -- class -- comparative -- creative -- development -- drain -- economic -- employment -- florida -- gain -- gainesville -- geographic -- gis -- industry -- information -- local -- naics -- sector -- systems
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Gainesville, Florida has long suffered from “brain drain”, or the emigration of young educated professionals, mostly graduates of the University of Florida and Santa Fe College, away from the city. However, Gainesville has long shown the potential to become a flourishing town for recent college graduates to start their careers – similar to Austin, Texas or Raleigh-Durham, NorthCarolina (Florida, 2002). Despite this potential, many students continue to move away from Gainesville soon after graduation, to locate to coastal Florida or other parts of the country (Franklin, 2003). What makes graduates want to leave? What has Gainesville done right to make itself more attractive to the young professionals? In 2002, Richard Florida coined the term “creative class” to describe a socioeconomic class of professionals who are the driving economic force behind modern growing cities. The creative class is a broad group representing individuals whose jobs require applied intelligence and decision making. The creative class has grown to represent more than 35% of total employment in the U.S. in2010 and has been identified as having a strong positive impact on the growth of cities (Bureau of Labor Statistics, 2010). In August 2010, Florida published an article for The Atlantic magazine that projected a 17.65% growth in creative class employment between the years of 2008 and 2018 for Gainesville. That wasthe highest rate among metropolitan statistical areas in the nation (Florida,2010). This is concurrent with his previous analysis of Gainesville in 2002,stating that of all U.S. cities with a population under 250,000 it had the second highest potential to attract the creative class (Florida, 2002). The objective of this thesis was to find Gainesville’s industry strengths and determine how Gainesville can fully capitalize on its potential through policy and development. After the completion of analysis, it was determined that Gainesville’s strengths lie in the sectors of education and health care services and that sectors of potential growth are comprised of the real estate and rental, professional and technical services, and the public administration sectors.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Brett A Lackey.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2012.
Local: Adviser: Zwick, Paul D.
Local: Co-adviser: Bejleri, Ilir.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044744:00001


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1 BRAIN DRAIN TO BRAIN GAIN: A COMPARATIVE LOCAL ECONOMIC DEVELOPMENT ANALYSIS OF THE CREATIVE CLASS I N GAINESVILLE, FLORIDA USING GEOGRAPHIC INFORMATION SYSTEMS (GIS) By BRETT ALLEN LACKEY A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN URBAN AND REGIONAL PLANNING UNIVERSITY OF FLORIDA 2012

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2 2012 Brett Allen Lackey

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3 To my parents

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4 ACKNOWLEDGMENTS First, I would like to thank my Chair, Dr. Paul Zwick and my Co Chair, Dr. Ilir Bejliri for assistance in learning GIS and its applications in planning over the past two years. I would also like to thank my mentor Gareth Hanley an d professor Andres Blanco, both of thank you to all of my supportive classmates and engaging professors. Also, I would like to thank Gainesville Mayor Craig Lowe, Gainesville Economic Development Director Dr. Erik Bredfel d Their vision has made this thesis possible. Finally, I would like to thank my parents for raising me to who I am today.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 13 Gaines ville, Florida Profile ................................ ................................ ...................... 13 Introduction of the Creative Class ................................ ................................ ........... 14 ................................ ................................ ... 15 Justification for this Research ................................ ................................ ................. 16 Organization ................................ ................................ ................................ ........... 17 2 LITERATURE REVIEW ................................ ................................ .......................... 18 Local Economic Development Strategies ................................ ............................... 18 Sales and Promotion ................................ ................................ ........................ 19 Subsidiz ation ................................ ................................ ................................ .... 20 Making Sites and Buildings Available ................................ ............................... 21 Use of Land Use Controls and Provision of Infrastructure ............................... 21 A Final Note on Economic Development Planning ................................ ........... 22 The Creative Class ................................ ................................ ................................ 22 Occupational Classes ................................ ................................ ....................... 23 Agriculture class ................................ ................................ ......................... 24 Working class ................................ ................................ ............................. 24 Service class ................................ ................................ .............................. 24 Creative class ................................ ................................ ............................ 25 Why Focus on the Creative Class? ................................ ................................ .. 26 Impact of Location ................................ ................................ ............................ 27 Criticism of the Creative Class ................................ ................................ ......... 28 Industrial Strengths and Weaknesses ................................ ................................ .... 29 Location Quotient Analysis ................................ ................................ ............... 30 Shift Share Analysis ................................ ................................ ......................... 32 Economic growth (share) ................................ ................................ ........... 32 Mix component (proportional shift) ................................ ............................. 33 Competitive component (differential shift) ................................ .................. 33 Shift share analysis: putting it all together ................................ ................. 34 Cluster Analysis ................................ ................................ ................................ 36

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6 3 STUDY AREA ................................ ................................ ................................ ......... 39 Overview of Gainesville, Florida ................................ ................................ ............. 39 Economic History of Gainesville ................................ ................................ ....... 39 The University of Florida ................................ ................................ ................... 40 Innovation Square ................................ ................................ ............................ 40 Progress Corporate Park ................................ ................................ .................. 42 Metropolitan Statistical Areas (MSAs) ................................ ................................ ..... 42 MSAs in Florida ................................ ................................ ................................ 42 The Gainesville MSA ................................ ................................ ........................ 43 4 METHOD OLOGY ................................ ................................ ................................ ... 45 Methodology Overview ................................ ................................ ........................... 45 North American Industry Classification System (NAICS) ................................ ........ 46 Sectors ................................ ................................ ................................ ............. 46 Sub Sectors ................................ ................................ ................................ ...... 47 Beyond Three Digit NAICS Codes ................................ ................................ ... 48 Creative Sectors ................................ ................................ ................................ ..... 48 NAICS Code 51: Information ................................ ................................ ............ 48 NAICS Code 52: Finance and Insurance ................................ .......................... 49 NAICS Code 53: Real Estate and Rental and Leasing ................................ .. 49 NAICS Code 54: Professional and Technical Services ................................ .... 49 NAICS Code 55: Management of Companies and Enterprises ........................ 50 NAICS Code 61: Educational Services ................................ ............................ 50 NAICS Code 62: Health Care and Social Assistance ................................ ....... 51 NAICS Code 71: Arts, Entertainment, and Recreation ................................ ..... 51 NAICS Code 92: Public Administration ................................ ............................. 51 Datasets ................................ ................................ ................................ .................. 52 Bureau of Labor Statistics Data ................................ ................................ ........ 52 Center for Economic Studies Data ................................ ................................ ... 53 Topologically Integrated Geographic Encoding and Referencing (TIGER)/Line Data ................................ ................................ ........................ 53 Process ................................ ................................ ................................ ................... 54 Sector Score Analysis ................................ ................................ ............................. 54 5 RESULTS ................................ ................................ ................................ ............... 57 State Wide MSA Analysis ................................ ................................ ....................... 57 Information ................................ ................................ ................................ ....... 59 Finance and Insurance ................................ ................................ ..................... 60 Real Estate and Rental and Leasing ................................ ................................ 62 Professional and Technical Services ................................ ................................ 64 Management of Companies and Enterprises ................................ ................... 65 Education Services ................................ ................................ ........................... 67 Health Care and Social Assistance ................................ ................................ .. 68 Arts, Entertainment, and Recreation ................................ ................................ 70

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7 Public Administration ................................ ................................ ........................ 71 Local Analysis of Prioritized Creative Class Sectors ................................ ............... 73 Real Estate and Rental and Leasing ................................ ................................ 75 Professional and Technical Services ................................ ................................ 76 Educational Services ................................ ................................ ........................ 76 Health Care and Social Assistance ................................ ................................ .. 77 Public Administration ................................ ................................ ........................ 78 6 DISCUSSION ................................ ................................ ................................ ......... 81 A Closer Look ................................ ................................ ................................ ......... 81 Growing Base Industries ................................ ................................ .................. 82 Transforming Industries ................................ ................................ .................... 82 Decl ining Industries ................................ ................................ .......................... 84 Comparison to Other Creative Hub College Cities ................................ .................. 86 7 CONCLUSION ................................ ................................ ................................ ........ 88 Restrictions ................................ ................................ ................................ ............. 89 Further Research ................................ ................................ ................................ .... 90 Final Thoughts ................................ ................................ ................................ ........ 91 LIST OF REFERENCES ................................ ................................ ............................... 92 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 98

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8 LIST OF TABLES Table page 2 1 Employment classes as a percentage of total employment ................................ 25 2 2 Location quotient indications ................................ ................................ .............. 31 2 3 Shift share components ................................ ................................ ...................... 35 2 4 Cluster analysis ................................ ................................ ................................ .. 37 4 1 NAICS sectors and their corresponding class ................................ .................... 47 5 1 Ten largest employers in Gainesville, 2011. ................................ ....................... 58 5 2 Sector score matrix ................................ ................................ ............................. 80 6 1 Cluster analysis, applied to Gainesville ................................ .............................. 81 6 2 Health care and social assistance employment ................................ .................. 83 6 3 Professional and technical services employment ................................ ............... 84 6 4 Cluster analysis, professional and technical services ................................ ......... 85 6 5 C reative class location quotients for coll ege cities ................................ .............. 87

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9 LIST OF FIGURES Figure page 1 1 Projected Creative Class Growth between 2008 and 2018 ................................ 16 3 1 A map of Innovation Square in Gainesville. ................................ ........................ 41 3 2 ................................ .............................. 43 3 3 Gainesville Metropolitan Statistical Area. ................................ ........................... 44 4 1 Methodology Flow Chart ................................ ................................ ..................... 56 5 1 Creative c lass location quotients for Florida, 2010 ................................ ............. 57 5 2 NAICS code 51 location quotients for Florida, 2010 ................................ ........... 60 5 3 NAICS code 52 location quotients for Florida, 2010 ................................ ........... 61 5 4 NAICS code 53 location quotients for Florida, 2010 ................................ ........... 63 5 5 NAICS code 54 location quotients for Florida, 2010 ................................ ........... 64 5 6 NAICS code 55 location quotients for Florida, 2010 ................................ ........... 66 5 7 NAICS code 61 location quotients for Florida, 2010 ................................ ........... 67 5 8 NAICS code 62 location quotients for Flori da, 2010 ................................ ........... 69 5 9 NAICS code 71 location quotients for Florida, 2010 ................................ ........... 71 5 10 NAICS code 92 location quotients for Florida, 2010 ................................ ........... 72 5 11 Gainesville MSA creative c lass employme nt ................................ ...................... 74 5 12 Real estate and rental and leasing employment ................................ ................. 75 5 13 Professional and technical services employment ................................ ............... 76 5 14 Education services employment ................................ ................................ ......... 77 5 15 Health care and social assistance employment ................................ .................. 78 5 16 Public administration employment ................................ ................................ ...... 79

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10 LIST OF ABBREVIATION S BLS Bureau of Labor Statistics CES Center for Economic Studies GIS Geographic Information Systems LQ Location Quotient MSA Metropolitan Statistical Area NAICS North American Industry Classification System SFC Santa Fe College UF the University of Florida

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11 Abstract of Th e sis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Urban and Regional Planning BRAIN DRAIN TO BRAIN GAIN ATTRACTING THE CREATIVE CLASS TO GAINESVILLE, FLORIDA: A LOCAL ECONOMIC DEVELOPMENT ANALYSIS UTILIZING GEOGRAPHIC INFORMATION SYSTEMS ( GIS ) By Brett Lackey August 2012 Chair: P aul Zwick Co chair: Ilir Bejliri Major: Urban and Regional Planning young educated professionals, mostly graduates of the University of Florida and Santa Fe College, away from the city. However, Gainesville has long shown the potential to become a flourishing town for recent college graduates to start their careers similar to Austin, Texas or Raleigh Durham, North Carolina Despite this potential, many student s continue to move away from Gainesville soon after graduation, to locate to coastal Florida or other parts of the country What makes graduates want to leave? What has Gainesville done right to make itself more attractive to the young pro fessionals ? In 2002, Ri creative class socioeconomic class of professionals who are the driving economic force beh ind modern growing cities. The creative class is a broad group representing individuals whose job s require applied intelligence and decision making. The creative class has grown to represent more than 35% of total employment in the U.S. in 2010 and has been identified as having a strong positive impact on the growth of cities

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12 In August 2010, Florida published an article for The Atlantic magazine that projected a 17.65% growth in creative class employment between the years of 2008 and 2018 for Gainesville. That was the highest rate among metropolitan statistical areas in the nation This is concurrent with his previous analysis of Gainesville in 2002, stating that of all U.S. cities with a population under 250,000 it had the second highest potential to attract the creative class determine how Gainesville can fully capitalize on its potential through policy and strengths lie in the sectors of education and health care services and that sectors of potential growth are comprised of the real estate and rental, prof essional and technical services, and the public administration sectors.

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13 CHAPTER 1 INTRODUCTION In an era of decline in manufacturing and other physical labor industries, many areas are going through a difficult time trying to figure out how to rejuvenate t heir economies. Some regions have been prosperous by attracting lucrative industries, with more creative companies following due to clustering around related industries or migrating towards highly knowledgeable residents. Richard Florida has repeatedly sai d that Gainesville, Florida is ripe for creative class job growth (Florida 2002 and 2010). creative class does not flourish in Gainesville. Many college graduates want to leave Gain esville and employers are reluctant to locate because they perceive that recent graduates are stoo graduates and attracting creative class employers but the difficult part is sparking this catalyst for growth. Gainesville, Florida Profile Gainesville is a city located in Alachua County, in north central Florida. Gainesville had a population of 124,354 within the city limits and 264,275 within its metropolitan area as of the 2010 Census. It was once a hub for railroad connectivity, but railroad lines have lost their nece ssity. It is not served by any water shipping routes and it contains a regional airport that is used for commercial flights. The primary means of transportation to and from Alachua County is I 75, an interstate highway that runs the length of Florida and intersects the heart of Alachua County.

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14 The University of Florida (UF) is a high ranking university of about 50,000 students located in Gainesville. Most of these students spend four or more years in Gainesville acquiring their degree, then move away. To reach its growth potential, Gainesville needs to find a way to retain more graduates. Santa Fe College (SFC), Shands Hospital, and the North Florida Regional Medical Center are three more of the larger employers in Gainesville. They contribute to the two m ain economic bases in Gainesville the education and health care industries. Introduction of the Creative Class Richard Florida, Director of the Martin Prosperity Institute and Professor of Business and Creativity at the Rotman School of Management at the University of creative class C reative class employment describes jobs in which the employee is required to apply their knowledge to make decisions. It includes people in the science an d engineering, architecture and design, education, arts, music, and entertainment fields people who are employed to innovate. It also includes creative professionals such as individuals working in business and finance, law, and healthcare (Florida 2002:8 ). The creative class had grown to represent over 35% of the total United States workforce in 2010. (Bureau of Labor Statistics, 2010) Richard Florida wrote The Rise of The Creative Class attention of policymakers, urban planners and developers throughout the United States strategy for economic development for cities seeking high paying jobs and overall growth. Certain cities and local regions have experienced prosperous growth by attracting creative class companies and industries, both naturally and via economic

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15 development planning. Unfortunately, the same solution cannot be prescribed for every region specializations and clusters will occur naturally. The key to economic development is to develop an area as unique and specialized in a certain industry or in likely to attract a high tech startup company. Like relocate to Silicon Valley either. Several factors play into where companies and jobs the other hand the region can cre ate an economic development plan to make a region more attractive. One of the more difficult factors to attract to a city is talent. Educated professionals are necessary for creative companies and local regions with colleges and universities have a distinct advantage in producing the talent that many companies are looking for. So Gainesville, Florida is ideal for companies looking to relocate, right? Not necessarily. Gainesv ain Drain a phenomen on in which young, highly educated people move away from an area. Brain drain, formally known as Human Capital Flight, has been a hindering factor of economic growth for both local regions and the immigration of young, educated people. A study in 2000 by the U.S. Census determined that areas in the Great Plains, rust belt, and the northeast United States were experiencing brain drain. The young educated population was moving to or remaini ng in the southeast and the western United States. Unfortunately for Gainesville, the areas in the southeast that were experiencing the brain gains were the larger metropolitan areas and/or the areas located along the coast.

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16 Justification for this Research Figure 1 1. Projected Creative Class Growth between 2008 and 2018 Reprinted by permission from Florida, R. (2010c, August 25). Where the Creative Class Jobs Will Be. The Atlantic. Retrieved from http://www.theatlantic.com/ Richard Florida has listed Gainesville as a potential hub for creative class type economic growth. In his 2001 book The Rise of the Creative Class he listed Gainesville as the metropolitan area with the second highest potential for creative class growth and Creative Class as having the largest percentage of creative class job growth of all metro areas at 17.65% growth between 2008 and 2018.

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17 potential and are working to harness it. On January 24 th 2012, during the State of the City address for Gainesville, Mayor Craig Lowe opened his speech with the following, Recently speaking about middle class job creation in Kansas, President with the President. He said, too. But it was what he said next that I think truly captures where we are as mat This sentiment perfect ly describes Gainesville today. Organization This work will be presented in six chapters. Chapter 2 describes the creative class and local economic development stra tegies. Chapter 3 outlines the study area. Chapter 4 provides a methodology of the economic development analyses used in conjunction with GIS. Chapter 5 details the results from the economic analyses and GIS analyses. Chapter 6 discusses the unique opportu nities of Gainesville based on the analyses and how Gainesville has already successfully attracted creative class employers Chapter 7 outlines restrictions and proposes further research into the topic.

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18 CHAPTER 2 LITERATURE REVIEW In an age of increasing ly advanced computing and manufacturing technology, coupled with rising labor costs and more restrictive governmental regulations, blue collar manufacturing jobs have left the United States by the tens of thousands (Bureau of Labor Statistics, 2010). Citie s and local regions are having a difficult time attracting jobs of any kind and are so desperate for employers that they are creating larger incentives, both policy based and physical based, to attract companies. During this economic recession, some cities have found a way to prosper by attracting a specialized set of jobs. Cities such as Portland, Oregon and Austin, Texas and the regions of Silicon Valley in California and the Research Triangle in North Carolina have shown incredible progress in attracting high paying jobs to their cities. Local Economic Development Strategies A proper approach to local economic development planning is needed for successful implementation of the economic development program. Often times, though, local economic development p lanners do not practice planning in a systematic manner. As Levy (1990) points out, in many cases communities jump into economic development programs in an effort to achieve quick results. This often is due to political reasons. It makes the local governme nt look good in the short term and gives the economic planner job security. These planners spend much more of their time working on short tern job growth, hence limiting the ability to wait for and attract the types of jobs that will truly benefit a commun ity in the best way. Proper planning includes a variety of appropriate stages. First, the program needs assessment. This determines the goal of the project, i.e. create jobs, increase tax base,

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19 etc. Further, the assessment should determine the specifics of what it wants. For example, if the decision is to create more jobs, the next task is to determine which type of jobs and why to address underemployment, unemployment, etc. Next the program must carry out a market evaluation. This involves an objective a nalysis of the but some of the most telling are employment analyses, including location quotient, shift share, cluster, and input output analyses. This type of research wi ll help the community quickly determine which types of companies or industries it should try to attract and which ones will be more likely to want to relocate to the community or expand locally. After the evaluation comes the assessment of the consequences of an economic development program. A new economic development program aims to provide new revenue but will require new expenditures. It can impact traffic, environmental quality, housing, etc. A cost benefit analysis should be performed to determine whet her an economic development plan will be beneficial and if so, what impacts it will have. Finally, the plans need to be formulated. There are four types of economic development strategies that a community can use to promote economic growth. They include sa les and promotion, subsidization, making sites and buildings available, and use of land use controls and the provision of infrastructure (Levy, 2009, p. 258). Local economic development typically includes a combination of two or more of these strategies. S ales and Promotion marketing, advertising, and public relations, a community can make itself more visible to a company than other regions. All other things being equal, a commun ity that engaged in promotion gives itself an advantage in attracting certain companies. An example of

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20 a dozen billboards around its metropolitan area in the late 1990s to promote its industry, it was a low cost way of projecting the perception that Austin was an innovative city to both residents and visitors. Subsidization There are numerous financial incentives a community can use to attract a company. These include offering tax abatements, loans, enterprise zones, and cash. Subsidizations are the quickest and simplest form of economic development strategy to develop and offer. Thes e incentives may also be based on performance quotas. For example, a city may offer a company more incentives if it creates and retains a certain number of jobs within a set number of years. Subsidizations are advantageous over other forms of incentives in that they only cost the city if the company accepts the offer. The other types of incentives require that the city initiates spending and then the decision is up to the company, with no guarantee that the incentives will produce results. Contrarily, subsi dizations cost the city a lot of money, which inevitably increases the taxes elsewhere in the city. This creates a scenario that attracts one company but may entice another to move away due to increased burden. Another problem with subsidizations is that they are only useful if they make an impact. The objective of the city is to attract the new company while offering as small a subsidy as possible. If a company had planned to invest in a locality regardless of the windfall and the community loses money unnecessarily. Additionally, every company has a threshold for the amount of subsidy

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21 not reveal how much of an incentive it wants but instead hears offers from multiple threshold price is a windfal l. John Levy (2009) explains the process as if it were a poker game, where the company holds their cards close to their chest and the community must lay their cards face up on the table for the company to see. There is only a small chance that the communit y will offer right amount of subsidy; therefore, the company is almost always the true beneficiary. Making Sites and Buildings Available An aggressive and more direct approach at local economic development includes preparing space for companies to move in. A common example of this is setting up a municipal industrial park. The locality uses public funds to acquire and prepare the land for development by prospective companies. Some communities go even further and develop buildings on the land. This approach allows a company to locate quickly. The supplying of land or building space is often provided to the company below market value and a debt is incurred by the city, as a form of subsidy. An example of a making a site available is Research Triangle Park in t he Research Triangle area of North Carolina. The Research Triangle Park was first developed as an economic development strategy Triangle Park, 2011). Use of Land Use Control s and Provision of Infrastructure In the case of using land use controls and provision of infrastructure, the land is prepared for development both physically and non physically. Physically, infrastructure

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22 may be built or altered in a way that improves its functionality and increases the land potential. This may include adding sewer, electric, railroad, and walkable connectivity to a site. Non physically, zoning and land use changes may be required to make t he land more suitable for a potential use. This strategy is similar to making sites and buildings available and the two strategies are often used together. A Final Note on Economic Development Planning By no means does this imply that implementing any of the aforementioned strategies will work. It is up to the city to create a plan using these strategies in conjunction with each other to make the city stand out to potential companies. However, by declaring its intentions of high potential land via planning zoning, and budgeting, the Local economic development is not only focused on attracting new companies but also in retaining current ones. As cities create offers t o attract established companies to their community, the original community is also trying to counter those offers to retain the company locally. For example, in 1989 Sears, Roebuck, and Company announced that it planned to relocate its headquarters from th e Sears building in downtown Chicago. Through various incentives, Illinois spent $178 million to persuade the company to remain in the Chicago area. Eventually the company moved to a suburb of Chicago and Illinois spent millions of dollars on Sears witho ut creating a single job, yet it was considered a good investment (Levy, 2009, p. 256). The Creative Class creative class The Rise of the Creative Class The creative class is comprised of employment that requires independent judgment and high levels

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23 creative class not by the color of the collar but instead by the degree to wh ich they use their knowledge. Occupation fields in the creative class and design, education, arts, music and entertainment, busines s and finance, law, health care Florida points out when defining creative class and other classes lies in what they are primarily paid to do. Those in the Working Class and the Service Class are primarily paid to execute according to plan, while those in the creative class are primarily paid to create and have considerably more autonomy and flexibility than the creative class is the fastest growing class of workers in the United States. Occupa tional Classes Florida defined occupational classes differently than most in The Rise of the Creative Class The conventional way of classifying jobs was into categories based on the task performed. There was blue collar, white collar, agriculture, and ser vice workers. Service jobs included jobs in which a servic e was performed, including much of the healthcare, teaching, and dining industries and the agriculture class included workers in the farming, fishing, and forestry industries. Blue collar and white collar jobs were made up of the occupations not included in agriculture and service industries. Blue collar jobs included any occupations that required physical labor and white collar based on how they use their knowledge instead of the task performed. For the most part, blue collar and service workers remained in the working and services classes, respectively. There were some changes though. For example, educators and healthcare profe ssionals provide

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24 services, yet their occupations require education and application of higher level knowledge, so they are members of the creative class Agriculture class Slightly more than one percent of the employed population worked in the agriculture class in 2010. This class of occupations includes employment in farming, fishing, and forestry occupations. At the beginning of the 20 th century, the agriculture class was the dominant class, employing three of every eight employees in the United States. T he agriculture class is the only class that has been continuously declining since 1900. Working class In 2010, 24.6% of the employed population worked in the working class. This class, often referred to as blue collar workers, includes construction, mainte nance and repair, manufacturing, and transportation occupations. The working class has hovered at around 35 to 40% of the total employment in the United States until the 1970s, when it started to slowly, consistently decline. Service class The largest clas s, the service class, makes up 38.8% of total United States employment. This class is comprised of occupations in industries including retail, restaurants, tourism, and personal services. At the beginning of the 20 th century, only one in every six workers was in the service class, but at its peak in the 1980s, almost one half of workers were in the service class. That number declined gradually over the next 30 years. It is important to note that the service class does not include all the occupations that ma ke up the service economy. Highly educated people in a service

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25 economy with occupations in finance, health, and education are grouped in the creative class Creative class Making up 35.6% of the total United States employment in 2010, the creative class wa s the second highest occupational class. Richard Florida has further broken down the creative class into two major sub classes: the super creative core and the creative professionals. The super creative core sub class is composed of computer and mathematic al occupations, architecture and engineering occupations, life, physical and social occupations, education, training, and library occupations, and arts, design, entertainment, sports, and media occupations. These professions require creativity in its trues t sense. Table 2 1. Employment classes as a percentage of total employment Agriculture Working Service Creative 1900 37.5% 35.8% 16.7% 10.0% 1910 30.9% 38.2% 19.8% 11.1% 1920 27.0% 40.2% 21.1% 11.7% 1930 21.2% 39.6% 25.2% 13.9% 1940 17.4% 39.8% 28.6% 14.2% 1950 11.9% 41.1% 30.5% 16.6% 1960 6.1% 37.7% 33.3% 17.9% 1970 3.1% 35.9% 38.8% 19.8% 1980 2.8% 31.7% 46.2% 18.7% 1991 3.0% 26.0% 45.7% 25.4% 1999 2010 0.4% 1.0% 26.1% 24.6% 43.4% 38.8% 30.1% 35.6% Source: Florida, 2002, p. 332 and Bureau of Labor Statistics 2010 The percentage of super creative workers in the United States workforce has increased from 2.4% in 1900 to 11.7% in 1999. The creative professionals sub class includes workers in management occupations, business and financial operati ons occupations, legal occupations, healthcare practitioner and technical occupations,

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26 educational occupations, and high end sales and sales management occupations (Florida, 2002, p. 328). This group makes up the rest of the creative class not included in the super creative core. It made up 18.4% of the workforce in1999 and, contains more than ten times as many workers in 1999 than in 1900. Why Focus on the Creative Class ? Cities create economic development plans to create jobs to increase the tax base, low er the unemployment rate, and spur growth, but specifically why do planners want to attract creative class jobs? Creative class jobs help lower unemployment, provide higher wages, and produce higher input output ratios better than other classes. The creati ve class has been identified as the driving force of innovation and economic growth (Florida, 2010). Unemployment nationwide in 2010 was at about 10%, but unemployment for creative class jobs was only 5% while it was at 15% for the working class population The creative class it increased from 3% at its lowest point but it is more immune to volatility and swings of the economy than the other occupational classes. More than any other class, Richard Florida is certain tha t the creative class industries will outpace the other classes in economic growth as the economy recovers from recession (Florida, 2010). Also, creative class occupations offer higher wages than employment in the other classes. In 2010, creative class jobs made up roughly a third of total national employment, yet they accounted for over half of the total income in the United States (Florida, 2010). Creative class employees, like everyone else, use that income for necessities and non necessities, such as hou sing, food, and leisure activities. Those expenditures are dispersed and redistributed throughout the rest of the economy in the

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27 form of, for example, retail services, rental services, and food services. Since creative class wages offer more to spend, more money is free to trickle down through the economy which creates more employment overall. Additionally, planners like having creative class employment because it generally has a high multiplier in input output analyses. Creative class employers, like all companies, tend to cluster with related industries. As an example, a research group may need to outsource website development that it cannot perform. It hires a web development firm to create a website for their company and pays the firm for their services Therefore, the input of funds to the economic research group is turned into an output in the form of buying website services. That output is the input for the website development firm. The website development firm may buy software from a software develop ment company. Once again, the output from the website firm becomes the input for the software company. All three companies are comprised of creative class employment and all three rely on each other for economic sustainability. Impact of Location It would make sense that a global economy would level the playing field and break down distance barriers, but that is hardly the case. Creative class employers cluster just as much as any other industry. In The Rise of the Creative Class Florida provided a list of its potential to attract tech economy, innovation, gay couples, Bohemians, and talent. Three of th e indexes that are most telling are called the three Ts technology, talent, and tolerance (Florida, 2000, p. 365). The cities with the highest creative index a product of the three Ts have shown the greatest strength in creative class employment.

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28 Fl orida pointed out a first hand example of this. During his time as a professor at Carnegie Mellon University in Pittsburgh, Pennsylvania, Florida noticed a recent graduate being recruited by Trilogy, a software firm from Austin, Texas (Florida, 2002, p. 21 5). How could it be that firms from Austin were plucking students right out of the great city of Pittsburgh a large established city with plenty of promise for a career? It turns out that of the 49 metropolitan areas with a population of more than one mi llion, Austin ranked second in creativity and Pittsburgh ranked 36 th Austin scored much better than Pittsburgh in all factors of the creativity index creative class employment, high tech presence, innovation, and diversity. The only region to have a bet ter creativity score was the San Francisco metropolitan area, just up the road from the burgeoning high tech hub Silicon Valley (Florida, 2002, p.246). Criticism of the Creative Class One of the main criticisms of the creative class is that its composition of occupations is loosely defined (Long, 2008, p. 54). The creative class is defined as a group of people in the arts (writers, actors, and musicians), knowledge workers (software engineers, architects, and scientists), and service professionals (lawyers, business managers, and health professionals). Although this seems like an unlikely occupation in which the person uses their intelligence to make decisions necessary to the job. Additionally, Florida does not change the requirements for inclusion over the course of his study. This group of occupations has risen in size and percentage of the economy as evidenced in Figure 2 1. This increase also undeniably relates to ec onomic growth and attractive cities (Florida, 2002).

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29 Further, an issue with using employment data for analysis is that the data is grouped together based on the establishment. For example, a library employing twenty people will aggregate twenty jobs as lib rarians even though, for example, three may be managers, three may be janitors, and another two employers may be security guards. This issue occurs across all industries and it is difficult to gather employment data that has this error corrected (Blanco, 2 horizontally across all regions equally, so if an aggregation error in calculating Another criticism is that public offici als who have been convinced by Florida have tried to implement policies and incentives to attract the creative class talent instead of focusing on attracting creative class of the American Planning Associati on points out: Our goal is not to dismiss the creative class argument, but rather to bring wider attention to its more traditional and less publicized tenets. Our creative class notion is incorporated into many development plans across the country, we have little empirical evidence that his arguments are grounded in economic reality. As a result, creative class c and may actually do harm by misallocating scarce public resources. (p. 181) Florida argues that an economic development plan must be developed uniquely by the local region and that the loc ality must determine how to allocate funding towards creating a region that is both attractive to companies and to educated professionals. Industrial Strengths and Weaknesses detailed analytical understanding of the strengths and weaknesses of the local

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30 strengths and w eaknesses of the local economy is to look at raw employment numbers over a given period of time. If the employment is growing in a particular industry, that industry is growing and if the employment is declining, the industry is shrinking. To truly underst and strengths and weaknesses of a local economy, it must be measured against a reference, or base, economy. Economic development planners will typically compare the strengths and weaknesses of their locality with a much larger area, depending on the contex t of the analysis. Two common examples of strength analysis include the location quotient analysis and the shift share analysis. Location Quotient Analysis weaknesses again st the base economy. It is useful in determining comparisons among regions but does not allow for a dynamic analysis of change over time. The formula used to calculate the location quotient values is as follows: where tion quotient of 1.00 indicates that the local area is on par with the base indicates an export industry for the local area and less than 1.00 indicates an import industr y. Values of more than 1.25 and less than .75 are considered significant: LQ values of 1.25 or more show that the area is specialized in a certain industry, indicating a local strength. LQ values of .75 or less show a significant local disadvantage to cert ain

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31 industries, showing that those industries are not significant to the local economy (Blanco, 2011a). It would seem ideal for a locality to have an LQ of 1.00 for all of its industries, representing that it is self sustaining, but that is not the case. D ue to economies of scale it is more efficient to specialize and use the profits from the specialized industries to supplement the industries that are not specialized locally. Table 2 2. Location quotient indications LQ Value What is means LQ = 1 The local industry has the same percentage of employment as the base economy. It is neither an export nor an import industry. LQ > 1 The local industry has a higher percentage of employment than the base economy. It is an export industry and locally a strength. I t should be maintained, and if possible, grown. Depending on the exact LQ, total employment, and change over time, this industry may indicate a cluster locally. LQ < 1 The local industry has a lower percentage of employment than the base economy. It is an import industry and a weakness locally. It should be analyzed further to determine if growth in this industry would be efficient. LQ < 0.75 The economy relies on importing the goods or services of this industry. It will require the most effort to grow this industry locally. Analysis should be done on whether it is more efficient to continue importing this industry's services or to invest in this industry locally. LQ > 1.25 The economy relies on exporting the goods or services of this industry. Typica lly this indicates an industry cluster. Clusters attract related industries naturally and therefore this industry should be maintained locally. Source: Blakely 2010, Blanco 2011a A LQ analysis is useful in determining strengths and weaknesses but planning should also incorporate actual employment numbers. For example, agriculture industries only make up a small percentage of employment nationally and likely locally. If an area has s lightly more agricultural employment than the national average, it will

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32 indicate a very strong industry, though it only represents a small amount of the local employment. and weaknesses at one given point in time without relation to the overall trend. For successful planning it is also important to understand where the economy is going and where the jobs will be. Having this information allows for the appropriate allocation of public resources and public infrastructure (Blanco, 2011b, slide 3). Shift Share Analysis The shift share analysis is a dynamic analysis, meaning it represents change over time. This analysis is necessary to determine trends in the local economy relative to the base area. The same data needed for location quotient information is also needed for a shift share analysis but data from two points in time are needed. The purpose of shift share analysis is to disaggregate the growth of an industry into its three contributing parts: Economic Growth (Share) Mix Component (Proportional Shift) Competitive Component (Differential Shift) Economic growth (share) The change in employment of an industry locally is primarily impacted by the overall economic change of the base area. When an economy is growing or shrinking it is expected that local industries are changing proportionally. Strengths and weaknesses vary across different regions so the economic growth share is first calculated to determine how much change the ov erall economy can account for. The economic growth of a local economy is calculated using the following formula:

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33 where Mix component (proportional s hift) As an industry in the base region changes in employment, it is expected that the local industry will change proportionally. The mix component shift of the shift share analysis is used to calculate the expected change of a local industry based on the change in employment of the same industry for the base area. If an industry is growing at a given rate overall, it is expected that the same industry is growing at the same rate locally. The mix component shift of a local economy is calculated using the fo llowing formula: where Competitive component (differential shift) The competitive component of the shift share analysis represents the difference in the local industry change and the national industry change. Unlike the economic growth share and the mix component shift, which rely on base area growth, the competitive

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34 com ponent shift calculates the change in local industry employment due to local factors. The competitive component can be calculated using the following formula: where Shift share analysis: putting it all togethe r When combined, the three components of a shift share analysis can be used to tell a story of the industries working within the local economy and which factors are causing their employment to change. The entire formula to calculate local employment change and its factors is as follows: where In the best case scenario, all three shift share components would be positive, indicating industrial growth d ue to a growing economy, a growing industry, and local Mix Component Competitive Component Economic Growth

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35 factors. In many analyses, there will be a mix of positive and negative change. When that is the case, it must be deciphered where the growth is occurring. Economic developers prefer the competitive co mponent to be positive more than the other two components, indicating that local factors are working to increase employment regardless of the base a rea. Table 2 3. Shift share components Shift Share Component Positive Negative Economic Growth The overall economy of the base area is growing and the local industry is expected to increase by this many jobs because of the overall growth The overall economy of the base area is shrinking and the local industry is expected to decrease by this many jobs because of the overall decline Mix Component The base area industry is growing and the local industry is expected to increase by this many jobs because of the industry growth The base area industry is shrinking and the local industry is expected to decrease by this many jobs because of the industry decline Competitive Component There was an increase in this many jobs due to local factors and independent of the base area's overall or industry performance There was a decrease in this many jobs due to local factors and independent of the base area's overall or industry performance Source: Blakely, 2010, p. 181 and Blanco, 2011c, slide 13 B efore creating an economic development plan, it is necessary to understand the factors leading to employment change. For example, if an industry is growing locally and declining within the base region, it may be an indication of a weak industry overall. It is possible that the decline in the industry has no t impacted the local region yet, therefore it would not be wise to invest in that industry unless more research has been done looking at it sustainability. Also, the results from the shift share analysis should be measured against the actual employment for the industries locally. If a loc al industry has

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36 only a small number of jobs, shift share results further from zero will be more substantial and will be more significant than an industry in which the local employment is large. For example, if the agriculture industry has one tenth the emp loyment as the service industry locally and both have the same growth in employment, then the growth is ten times more significant for the agriculture industry. Cluster Analysis Understanding clusters is an important part of economic development planning. Michael Porter, professor at the Harvard Business School and the most cited author in proximate group of interconnected companies and associated institutions in a particula r are formed because companies prefer to locate near their competition, their suppliers, and the industries they are supplying. Some examples of clusters in the United States include Silicon Valley (technology), Seattle (aviation), and Detroit (automobile production). Companies are attracted to clusters and the absence of a cluster is a disadvantage locally. An example of a specific type of cluster is the health care sys tem. Hospitals have the ability to attract a large amount of industries both directly and indirectly. Doctors prefer to locate near a hospital for patient efficiency. They want a competitive advantage over other doctors or, since most locate next to a hosp ital, to not be burdened by a disadvantage of locating further away. Doctors prescribe prescriptions for their patients and pharmacies are needed to fill those prescriptions. Once again, pharmacies will mpetitive advantage. These are all

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37 Clinical laboratories, pharmaceutical companies, and health insurance providers will all prefer to cluster. This example shows that not a ll clustering companies must be in the same industry. In this case, they may not even be in the same sector but by having a hospital industry, many more were attracted locally. It should also be noted that in this example, all the industries are comprised of creative class jobs (Porter, 1983, p. 271). Table 2 4. Cluster analysis Not Competitive (declining local shift) Competitive (growing local shift) High Local Concentration (LQ over 1.00) Transforming Industries Growing Base Industries Low Local Concentration (LQ less than 1.00) Declining Industries Emerging Industries Source: Blakely, 2010, p. 193 A cluster analysis can be done to determine if a cluster exists locally. It takes into component. The two values are entered into a four quadran t table and based on the result the local industry is assigned a label as a growing base industry, an emerging industry, a transforming industry, or a declining industry. For a local economic develop ment program, a cluster analysis can growing base industries, infrastructure should be enhanced to sustain the local industry advantage. For emerging industries, subsidies c an be offered to continue the growth. Transforming industries often indicate a declining cluster and the community should alter its planning policies to retain the advantage. Additionally, emerging and

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38 transforming industries are the most dynamic ones and should be examined most before developing a local economic development plan. Declining industries indicate that a cluster does not exist and should be of least priority for a community. Regardless of the state of the local industry, any economic planning p olicies developed should be focused on enhancing the cluster, not just to sustaining it. As Porter (1990, p. 75) says, The

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39 CHAPTER 3 STUDY AREA Two study areas were used for analysis. The firs t study area, Florida, was necessary for determining how the Gainesville Metropolitan Statistical Area (MSA) employment fared against other MSAs within Florida. The second study area, the Gainesville MSA, was used in determining which block groups in the G ainesville MSA contained the highest density of creative class jobs. Overview of Gainesville, Florida Gainesville, a city of 124,354 in 2010, is the primary city of the Gainesville metropolitan area. It is located in north central Florida in the southeaste rn United States. It has an area of approximately 62 square miles and is located in Alachua County. The county had a population of 247,336 in 2010 and is projected to have about 272,200 people by 2020 and 320,400 by 2040 (Enterprise Florida, 2012). Econom ic History of Gainesville When the Fernandina Cedar Key railroad was built, the residents of Alachua County decided to move the county seat from Newnansville to a location closer to the railroad in present day Gainesville. Subsequently, Gainesville was fou nded as the Alachua County seat on September 6 th 1853 and later incorporated on April 14 th 1864. Its economy was based on the cotton, citrus, and vegetable farming industries until the freezes of 1894 1895. After the freezes, the phosphate and lumber ind ustries became the economic base for Gainesville. By 1906, the University of Florida had relocated to collapsed due to World War I and the cotton industry suffered due to a boll weevil

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40 important economic industry in Alachua County (Pickard, 1991 and City of Gainesv ille, 2009). The University of Florida The University of Florida (UF) is one of the largest higher education institutions in the nation. UF was formed in 1905 under the Buckman Act, which consolidated four state schools to create the university. Gainesvill e was the site chosen as home of the university and classes in Gainesville started in 1906. Since the 21 st century, the number of enrolled students has leveled off around 50,000 students and the university has played a major economic role in Gainesville, A lachua County, and the state of Florida. In the 2009 10 fiscal year, UF generated $4.27 billion dollars of revenue for the state of Florida, with $2 billion coming from sources outside of Florida. It directly produced 41,434 jobs and an ad ditional 64,684 j obs indirectly (Hodges, 2011). Innovation Square In 2009 Alachua General Hospital closed its doors with the opening of a new hospital closer to UF. The 80 year old hospital was subsequently torn down the following year and plans were created to build a res earch park on the six blocks or 40 acres of open space. The plan was a joint project between the City of Gainesville, the Gainesville Community Redevelopment Agency, and UF. Innovation Square was awarded an $8.2 million grant in July 2009 from the Federal Economic Development Administration to create its first building, the Florida Innovation Hub at UF. The Florida Innovation Hub, at 48,000 square feet, was completed in late 2 011 with tenants moving in by early 2012. This was just the start of development with three more privately funded buildings planned for construction later in

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41 2012 (Bredfel d t, 2011). Additionally, the progress made by 2012 spurred redevelopment and renovati on for areas surrounding Innovation Square. Many of the building surrounding the site were previously fitted for medical uses due to clustering around the former hospital. As of 2012, those same buildings were being renovated for other uses. Innovation Sq project's high quality, establishment of a vision that is not only aspirational but implementable, and the collab oration of a wide Chapter, 2012). Figure 3 1 A map of Innovation Square in Gainesville. Reprinted by permission from Florida Innovation Hub at UF. (2010). Close to UF Retrieved from http://www.floridainnovationhub.ufl.edu/

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42 Progress Corporate Park Progress Corporate Park is a research park located in the City of Alachua, six miles northwest of the Gainesville city limits. The research park started as a vision by UF president Dr. Robert Marston and developed in the late 1980s on 200 acres formerly owned by the University of Florida Foundation. The park was deve loped throughout the 1990s and sold to a group of local real estate investors in 2000. Since the sale to the investors development of the property has accelerated. As of 2012, 80% of employment in the research park was provided by spinout companies from UF (Progress Energy Park, 2012). Metropolitan Statistical Areas (MSAs) Metropolitan statistical areas are defined by the U.S. Census as principal cities with at least 50,000 residents. Included in the MSA is the county that contains the principal city. Addit ional counties may be included in the MSA i f they meet specified commuting requirements. As of 2012, additional counties were included if at least 15% of their residents commuted to work to the central county. MSAs in Florida As of 2012 there were 20 MSAs in Florida. Eleven of these MSAs contained only one county and nine contained two or more counties. According to 2010 Census data the Miami Fort Lauderdale Pompano Beach MSA in South Florida, including Miami Dade, Broward, and Palm Beach Counties, had the high population of Florida MSAs with 5,564,635 residents. The Jacksonville MSA contained the most counties, including the central county, Duval, and four outlaying counties Baker, Clay, Nassau, and St. Johns Counties.

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43 Figure 3 Statistical Areas Reprinted by permission from Florida Agency for Workforce Innovation. (2011). Florida Metropolitan Areas Retrieved from http://www.docstoc.com/docs/108798945/Florida Metropolitan Areas The Gainesville MSA The Gainesville Metropolitan Statistical Area is an MSA comprised of the primary county, Alachua County, and one outlaying county, Gilchrist County. Gainesville w as first defined as an MSA in 1971, comprised of only Alachua County. In 1983 Bradford County, northeast of Gainesville, was added to the MSA and in 1993 it was removed. In 2003 Gilchrist County, to the west of Gainesville was added to the MSA and has been included since. Gilchrist County, a county of 16,939 residents, has two and a half cities and towns (Fanning Springs is split in half and shared with Levy County to the

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44 south.),only one traffic light, and no more than one lane moving in either direction o n any roads. Its economy s urely relies on Gainesville. According to the MSA standards, the Gainesville MSA had at least 2,540 residents that commuted to Alachua County from Gilchrist County. Figure 3 3. Gainesville Metropolitan Statistical Area. Source: Florida Geographic Data Library, 2012. Adapted by author using ArcMap 10.1.

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45 CHAPTER 4 METHODOLOGY Methodology Overview As stated before, a systematic approach is necessary for efficient economic development planning. Per the first step of this process, G ainesville needed the creative class provide increased employment, specifically creative class jobs, by a ttracting creative companies. Next, Gainesville needed a market evaluation. This research aimed to provide that evaluation through the use of location quotient and shift share analyses as a comparison of the Gainesville MSA against the United States and Fl orida and within the Gainesville MSA. This research was able to determine two things: which creative class industries in Gainesville had strengths and weaknesses and which areas within Gainesville should be focused on development for creative class job gro wth. To perform this research, employment data was gathered and analyzed for MSAs in Florida and for block groups within the Gainesville MSA. The analysis tools used included location quotient and shift share analyses. These analysis tools were helpful in weaknesses in employment and change in employment over time. Based on the strengths and weaknesses, suggestions were created for the City of Gainesville to t are included in the discussion and conclusion chapters. Three local reg i ons were used throughout this analysis. They are the City of

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46 for the future, based on Erik Bred fel d reflect the desired progress of the City of Gainesville, including creating creative class jobs, attracting innovative companies, redevelopment, and mixed use development. Much of the analysis has been don e for the Gainesville MSA as a whole but the recommendations have been directed towards the City of Gainesville since the city seemed to be the leading local entity in harnessing their creative potential, has more s city limits and is the principal city of the Gainesville MSA. North American Industry Classification System (NAICS) The North American Industry Classification System (NAICS) was created by the Office of Management and Budget in 1997 to allow for comparability in business statistics among the United States, Canada, and Mexico. It is the standard used by federal agencies for analysis of the Unites States economy. It classified employment at six levels of detail. At the highest level of classification, there are eleven base industries that aggregate employment based on their place in the economy and not based on the type of employment. Therefore many industries may be grouped together that provide jobs for different employment classes. Because of this, base industries are not useful for analysis as they are not specific enough in determining strengths and weaknesses. Sectors At the second highest level of classification, the census aggregates employment into sectors. These are represented by two digit NAICS codes. There are twenty sectors identified by the Census. The data used in the majority of this analysis was detailed to the sector level. Of the twenty sectors, Richard Florida classifies nine containing creative class employment.

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47 Table 4 1. NAICS sectors and their corresponding class NAICS Code Industry Class 11 Agriculture, forestry, fishing and hunting Agriculture 21 Mining, quarrying, and oil and gas extraction Working 22 Utilities Working 23 Construction Working 31 33 Manufacturing Working 42 Wholesale trade Working 44 45 Retail trade Service 48 49 Transportation and warehousing Working 51 Information Creative 52 Finance and insurance Creative 53 Real estate and rental and leasing Creative 54 Professional and technical services Creative 55 Management of companies and enterprises Creative 56 Administrative and waste services Service 61 Educational services Creative 62 Health care and social assistance Creative 71 Arts, entertainment, and recreation Creative 72 Accommodation and food services Service 81 92 Other services, except public administration Public Administration Service Creative Source: Florida, 2002, p. 330 Sub Sectors NAICS Codes are further separated to the three digit level. These categories were more helpful in determining specific industry strengths and weaknesses but were not freely available at any geographic level beyond the county level. NAICS Codes containing more digits allowed for more specific analysis but also came with restrictions. Some data was not released by the Bureau of Labor Statistics because of privacy concerns. Areas that had two or less employers per NAIC S code had either NC or ND listed for their local employment. NC stood for Not Calculable, which meant that the data did not exist or was zero. ND stood for Not Disclosable, which meant that there was employment in the local region but it could not be disc losed due to privacy

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48 c oncerns (Bureau of Labor Statistics, 2005). In this analysis, sub sector data was used for reference but it was too restricted to use it for a horizontal analysis. Beyond Three Digit NAICS Codes I n addition to base industry and two a nd three digit NAICS Codes, the census also classifies employment to the four five and six designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industr NC or ND at the county level, rendering it useless for analysis. Creative Sectors There are nine sectors, within five base industries, that are made up of creative class occupations. Sectors with NAICS Codes 51, 52, 53, 54, 55, 61, 62, 71, and 92 are considered creative (Florida, 2002). Analysis could not be performed at the base industry level because two of the base industries contain both creative class and non creative class employment. Specifically the l eisure and hospitality base industry is composed of mostly service workers nationally but also includes NAICS 71: Arts, entertainment, and recreation. Likewise, the information base industry includes mostly creative occupations but also NAICS Code 56: Admi nistrative and waste services. NAICS Code 51: Information The information sector is comprised of establishments that produce and distribute informational and cultural products, provide the means to transmit these products, or process data. Main components of this sector include traditional publishing, internet publishing, software publishing, motion picture and sound recording, broadcasting, data processing, web search, and information services (Census, 2012). Two examples of

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49 information establishments in G ainesville would be the University Press of Florida and Grooveshark. NAICS Code 52: Finance and Insurance The finance and insurance sector is comprised of establishments that are primarily engaged in financial transactions or facilitating financial transac tions. Its main types of insurance and annuities, and providing specialized services facilitating or supporting financial intermediation, insurance, and employee bene monetary authorities are included in this sector (Census, 2012). Some examples of finance and insurance sector establishments in Gainesville include Campus USA Credit Union and Nationwide Insurance. NAICS Code 53: Real Estate a nd Rental and Leasing The real estate and rental and leasing sector is comprised of establishments that primarily rent, lease, or otherwise allow the use of tangible and intangible assets. Tangible assets include real estate and equipment. Intangible asset s include patents buying for others, and appraising real estate (Census, 2012). In Gainesville two examples of real estate and rental and leasing sector establishments include Bosshardt Realty Services and Paradigm Properties. NAICS Code 54: Professional and Technical Services The professional and technical services sector is comprised of establishments that specialize in performing professional, scientific, and technic al activities for others. These activities require a high level of expertise and training. These services include: legal, accounting, architectural, engineering, computer, consulting, research, advertising,

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50 photographic, translation, and veterinary service s. This sector specifically excludes typical office administrative service, a sector that has its employment classified in the service class (Census, 2012). This is the sector that many localities are vying to attract because it offers a broad range of hig h paying professions. Many local economic development initiatives have professional and technical services employment in mind when planning and creating policies. Some examples of professional and technical services establishments in Gainesville include CH 2M Hill and 352 Media Group. NAICS Code 55: Management of Companies and Enterprises The management of companies and enterprises sector is comprised of controlling interest o private sector establishments. Public management and oversight is included in the public administration sector (Census, 2012). An example of a management establishment in Gainesville is th e Collier Companies, which manages residential rental service companies in college towns including their flagship company in Gainesville, Paradigm Properties. NAICS Code 61: Educational Services The education services sector is comprised of establishments that provide instruction and training. The establishments include schools, colleges, universities, and training centers. They may be privately owned and operated for profit or not for profit, or may be publicly owned and operated. Education services are ad ministered by teachers

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51 teaching ability (Census, 2012). Two examples of edu cational services sector establishments in Gainesville would be UF and the School Board of Alachua County. NAICS Code 62: Health Care and Social Assistance The health care and social assistance sector is comprised of establishments that provide health care and social assistance services administered by trained professionals. All industries within this sector require expertise and many industries within the sector are defined by the educational degree held by the practitioner. Specifically excluded from this sector are fitness instructors and weight reducing centers (Census, 2012). Some examples of health care and social assistance sector establishments in Gainesville would be Shands Hospital and the Orthopaedic Institute. NAICS Code 71: Arts, Entertainment, and Recreation The arts, entertainment, and recreation sector provides cultural, entertainment and promoting, or participating in live performances, events, or exhibi ts intended for public viewing, establishments that preserve and exhibit objects and sites of historical, cultural, or educational interest, and establishments that enable patrons to participate in recreational activities or pursue amusement, hobby, and le specifically excludes establishments in the food and accommodation services industry (Census, 2012). Examples of arts, entertainment, and recreation sector establishments in Gainesville would include the University Athletic As sociation and the Hippodrome Theater. NAICS Code 92: Public Administration The public administration sector is comprised of establishments of local, state, and

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52 power and Generally, these establishments oversee governmental programs and activities that are organize and finance the production of public goods and services, often for free or at examples of public administration employers would be the City of Gainesville and Alachua Coun ty. Datasets Economic Studies (CES). The BLS data was more detailed in the depth of the NAICS code given but only provided data at the county level. Contrarily, the CES data only provided two digit NAICS codes but provided data for individual blocks. Furthermore, the CES data included public and private sector employment but the BLS data only included privat e employment. Bureau of Labor Statistics Data The BLS data was obtained for various NAICS code employment sectors at the two digit and three digital NAICS Code levels. To allow for shift share analysis, data from 2001 and 2010 was used. Data for these year s was chosen because it was the earliest and latest data available, respectively, and offered the most compete time period for analysis. BLS data was only obtained for Alachua County and was used for reference, not analysis, due to it being vastly not calc ulable or not disc l osable in Gilchrist County and not including location more detailed than at the county level.

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53 Center for Economic Studies Data CES data was obtained at the two digit NAICS code level for every block in Florida. This data was better suite d for giving an overall diagnosis of the Gainesville MSA in comparison to the rest of the MSAs in Florida. Additionally, it was helpful for location specific analysis within the Gainesville MSA. The CES data was aggregated and analyzed using GIS. Additiona lly, the CES data provided employment information for NAICS 92: Public Administration, a creative class NAICS 92: Public Administration employment information because it is comprised of public sector employment. To allow for shift share analysis, data from 2002 and 2010 was used. These years were chosen because they were the earliest and latest years for which data was available, respectively, and offered the most compete time period for analysis. Topologically Integrated Geo graphic Encoding and Referencing ( TIGER ) /Line Data Geographical data was obtained from the U.S. Census' TIGER/Line shapefile set. Every feature in the CES data had a unique 15 digit ID that geographically corresponded to its respective block. The first two digits were made up of the state FIPS Code and the next three were the county FIPS code. The following six digits represented the census block and the final four digits represented the block code, with the first digit of the block code representing the bl ock group within the census tract. There were over 484,000 blocks in the state of Florida and about a third of them contained employment in either 2002 or 2010.

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54 Process TIGER /Line shapefile. The blocks were then dissolved based on their block group and the employment data based on NAICS sector was summed. Next, a select by attributes was performed to select the block groups in Alachua and Gilchrist Counties. Those blocks were exported as a new shapefile. In the block group shapefile, the block groups were dissolved based on their county and the employment data based on NAICS sector was summed. The counties not belonging to any MSAs were deleted and the rest of the counties were dissolved based on their MSA and the employment data based on NAICS sector was summed. The attribute tables of the Florida MSA shapefile and the Gainesville MSA block group shapefile were exported to Microsoft Excel. In Excel, location quotient and shift share analyses were performed. The base region used in the analyses was the United States. The United States was chosen as the base region because it provided a more comprehensive analysis, though regions within Florida can be compared against each other u sing their location quotient and shift share results. Once the analyses were performed, the tables were loaded back into ArcGIS and joined k groups, with both files containing actual employment numbers, location quotients, and shift share results for all nine creative class sectors and the total of all creative class employment. Sector Score Analysis To further understand the importance for e ach sector within Gainesville, five importance indicators were ranked among the nine creative class sectors. They include the actual local employment for 2010, the location quotient for 2010, the location

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55 ion quotients for 2010, the national growth rate between 2002 and 2010, and the local growth rate between 2002 and 2010 (the last two are variations of the mix and competitive component shifts respectively but have the local employment factor removed to of fset the bias already captured in total employment). These five factors were measured and the nine creative class sectors were ranked based on how they performed in Gainesville. The rankings were totaled up and an overall rank was given to each sector. Th is informal matrix helped measure the importance of each sector to Gainesville while incorporating all factors into it. For example, a sector may have been growing quickly locally, but if it was declining nationally, offered low employment, or had a low lo cation quotient, it was easy to determine that the city should not have prioritized it.

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56 Figure 4 1. Methodology Flow Chart

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57 CHAPTER 5 RESULTS State Wide MSA Analysis Overall, Gainesville is a hub for creative class employment, both nationally and within Florida. It had a 1.26 location quotient for creative class jobs which meant that proportionally it had 26% more creative class jobs than the U.S. average in 2010. Figure 5 1. Creative class location quotients for Florida, 2010

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58 Gainesville had the second highest creative class location quotient of the twenty Florida MSAs. The only MSA in Florida with a higher location quotient was Tallahassee ing a college town and it being the state capital. As the capital, it had a secure economic base of public administration jobs something that Gainesville did not have. Other than the two prominent college towns in Florida, the rest of the MSAs had locati on quotients ranging from 0.83 to 1.15. In a shift share analysis, Gainesville had an economic growth share of 741 but had a mix component shift of 7,998, meaning that although there was an economic decline nationally, the class grew. The competitive comp onent shift was 2,613, meaning that the national growth outpaced the local growth. When all three factors of the shift share analysis were combined, it was revealed that Gainesville gained 4,644 creative class jobs between 2002 and 2010, an increase of 7. 4%. Table 5 1. Ten largest employers in Gainesville, 2011. 2011 2002 Employer Employees Percentage of employment Employees Percentage of employment University of Florida 14,723 12.88 11,870 11.11 Shands Hospital 12,588 11.01 7,986 7.47 VA Hospital 4,317 3.78 1,627 1.52 Alachua County School Board 4,299 3.76 4,209 3.94 City of Gainesville 2,200 1.92 1,863 1.74 Publix Supermarkets 2,056 1.80 n/a n/a North Florida Regional Medical Center 1,700 1.49 900 0.84 Nationwide Insurance 1,300 1.14 1,065 1.00 Alachua County 1,120 0.98 783 0.73 Santa Fe Community College 796 0.70 800 0.75 Source: City of Gainesville, 2011.

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59 Of the top ten employers in Gainesville in 2011, nine were comprised of creative class jobs with three contributing to the education services sector, three contributing to the health care and social services sector, two contributing to the public administration sector, and one contributing to the finance and insurance sector. The only other employer in the top ten locally was Publix, which was comprised of employment in the retail trade sector, in the service class. Information Having a 0.71 location quotient, the Gainesville MSA did not fare well against the rest of the country or against important to keep in mind that although many professors at UF and SFC publish text and video, they were included in the educational services sector instead. The shift share analysis of this sector showe d that between 2002 and 2010, the Gainesville MSA had an economic growth share of 32, meaning that the total employment decline in the United States accounted for 32 lees jobs in this sector in the Gainesville MSA. It had a mix component of 497, meaning that the decline in national employment in the Information sector accounted for 497 less jobs in the Gainesville MSA. Tellingly though, it had a competitive component shift of 333, meaning that the local sector lost 333 jobs due to local factors, regardle ss of the national trends. These losses in jobs represented a 32%, or 862 job, drop in employment between 2002 and 2010 in the Gainesville MSA. Attracting the information sector to Gainesville should not be a priority of the city. Although information sect or jobs represent the creative class they are moving away from Gainesville. This is not likely to entice information companies to cluster in Gainesville. Information companies looking to move to Florida would be better suited to

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60 Figure 5 2. NAICS code 51 location quotients for Florida, 2010 move elsewhere in Florida the Palm Coast, Orlando, and Sarasota MSAs are very attractive to the information sector, both statewide and nationally. F inance and Insurance The finance and insurance sector also did not perform well in the Gainesville MSA. It received a 0.76 location quotient, the median location quotient for MSAs in Florida.

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61 Figure 5 3. NAICS code 52 location quotients for Florida, 2010 After doing a shift share analysis, its economic gro wth share was 49 and its mix component was 90, meaning that between 2002 and 2010, 49 jobs were lost due to the total national employment decreasing and 90 were lost due to the sector decreasing in employment nationwide. On a positive note, the competiti ve shift indicated that local factors created five new sector jobs in the Gainesville MSA, bringing the total job loss to

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62 134 jobs between 2002 and 2010. Overall, this represented a 3% drop in jobs for finance and insurance in the Gainesville MSA. Nationwi de Insurance was the eighth largest employer and the second largest private sector employer in Gainesville in 2011. It operates one of its five regional offices in Gainesville (Nationwide Insurance, 2012). Between 2002 and 2011 it added 235 jobs to Gainesv ille and as of 2011 it employed 1300 people, or 1.14% of the total workforce in Gainesville (City of Gainesville, 2011). Other than Nationwide Insurance, Gainesville was not conducive to attracting the finance and insurance sector. Companies looking to loc ate in Florida may be better suited to cluster in the Jacksonville, Tampa, or Lakeland MSAs where the location quotients are much higher. Attracting finance and insurance companies should not be a priority for Gainesville. Real Estate and Rental and Leasin g The real estate and rental and leasing sector performed well in the Gainesville MSA based on its location quotient of 1.32. Even though the region had such a high location quotient, it only ranks 9th out of the 20 MSAs in Florida. The location quotient m ay have been high because Gainesville has a high number of apartments per capita compared to elsewhere in the state due to its college student population. Though Tallahassee is also a college town and had the second lowest location quotient in the state am ong MSAs. Between 20 02 and 2010, employment in the r eal estate and rental and leasing sector increased from 2,059 to 2,408, an increase of 17%, or 349 jobs. The economic growth share was 24 and the mix component was 90, but the competitive component was 463, the 7 th highest competitive shift in the state despite Gainesville

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63 Figure 5 4. NAICS code 53 location quotients for Florida, 2010 The real estate and rental and leasing sector should be a priority for economic deve lopment in Gainesville. Although it only employs 2% of the total Gainesville MSA workforce, the sector is doing much better in Gainesville than throughout the rest of the nation and state. Companies in the sector should look to move to Florida, given its g rowth in a sector that is in decline nationally, and should look specifically at Gainesville

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64 given its high location quotient and stable base of potential customers UF and SFC students. Professional and Technical Services Figure 5 5. NAICS code 54 loca tion quotients for Florida, 2010 The professional and technical services sector is full of occupations that cities are eager to attract, including lawyers, engineers, architects, scientists, and consultants.

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65 Gainesville received a 0.89 location quotient in this sector, which shows that it was not a strong sector locally but may have potential. It ranked 8 th out of the 20 MSAs in Florida. Between 2002 and 2010, the sector increased its employment by 6% locally from 5,965 to 6,315. In the shift share analysis, this was represented by an economic growth of 71, a mix component of 790, and a competitive component of 370, meaning that the total national employment was declining as well as the local sector employmen t, but overall the sector is growing nationally. Additionally, the sector represented 5.5% of the total employment in the Gainesville MSA, 4 th among creative class sectors behind education, healthcare, and public administration. Overall the professional an d technical services sector was growing nationally, had high local employment, and was locally growing in employment despite having a low location quotient and a negative competitive shift. Additionally, it is comprised of high paying professional jobs t he kind that cities are attracted to. Gainesville should place importance on finding a way to attract employers in this sector. Management of Companies and Enterprises creative class sector, the management of companies and enterprises sector received only a 0.14 location quotient in 2010. Additionally, it only employed 247 people in Gainesville, also the weakest among creative class sectors. In the shift share analysis, national economic decline led to an economic growth of 2 but sector growth led to a mix component of 19 and local sector growth led to a competitive component of 49. The increase of 66 jobs between 2002 and 2010 earned the sector the highest percentage growth of creative class sectors in Gainesville, a 36.5% increase in employment. Even though the jump in employment was high

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66 proportionally, an increase of 66 jobs was only a fraction of the next largest growing sector locally. Figure 5 6. NAICS code 55 location quotients for Florida, 2010 Attracting the management of companies and enterprises sector should not be a

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67 creative class sectors more effectively. The sector was ranked second to last on the sector score matrix, including ranking last in three of the five fields. Education Services Figure 5 7. NAICS code 61 location quotients for Florida, 2010 The education services creative class sectors. The Gainesville MSA boasts two large higher education institutions which

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68 help attract students, money, talent, and jobs to the city. UF, SFC, the Alachua County School Board were th ree of the top ten employers in Gainesville in 2011 (City of Gainesville, 2001). Not only did the sector have the second highest location quotient among MSAs in Florida, but it also employed 20,482 people in 2010 in the Gainesville MSA. Additionally, the e ducation industry has formed the base of the local economy in Gainesville since the 1930s (Pickard, 1991). The shift share analysis resulted in an economic growth of 209 and a competitive component shift of 1,870. On the bright side it earned a mix comp onent shift of 4,835 bringing the total gain in jobs from 2002 to 2010 to 2,756, a 16% increase in employment. The sector grew nationally by 26% between 2002 and 2010, the highest percentage growth of all creative class sectors. Although the local employment increased at a slower rate than the national average, the education industries within Gainesville play a large part in shaping the local economy. Of the five factors used in the sector score matrix, it ranked highest in three and overall was the highest ranking sector locally. Gainesville should prioritize both attracting and retaining the education services sector. Health Care and Social Assistance Having a 1.43 lo cation quotient, the Gainesville MSA had the 4 th highest location quotient among Florida MSAs in 2010. In 2011, the second third and seventh largest employers in Gainesville were Shands Hospital, VA Hospital, and the North Florida Regional Medical Cen ter, respectively. The health care and social assistance sector employed a total of 22,049 people in 2010, the highest employment among creative class sectors in Gainesville.

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69 Figure 5 8. NAICS code 62 location quotients for Florida, 2010 In the shift sha re analysis, this sector had an economic growth of 237 but had a mix component shift of 4,435. The competitive component shift was 2,230, bringing the total increase in employment to 1,968 between 2002 and 2010. This represents an increase of nearly 10% in employment since 2002.

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70 Attracting and maintaining the health care and social assistance sector should be a priority for Gainesville. It is the largest employer among creative class sectors in Gainesville and has the second highest ranking in the Sector Score matrix. Employment in this sector represented 19.3% of all employment in the Gainesville MSA. Gainesville is a hub for the medical industry within both the state and the nation. Today it, along with the education industry, forms the economic base for Gainesville. Arts, Entertainment, and Recreation Florida did well as a whole in the arts, entertainment and recreation sector. This state economy. The highest locatio n quotient belonged to Orlando, the tourism capital of the world. Within Gainesville, the location quotient was 1.02, slightly higher than the national average but low compared to the rest of the MSAs in Florida. In 2010, the sector employed 1,849 people. This represents a 467 job increase, or a 34% increase from 2002. A shift share analysis revealed that the sector had an economic growth share of 16 but it had a mix component shift of 97 and a competitive component shift of 386. That means that the sector was growing nationally in a shrinking economy and that the local sector growth was outpacing the national sector growth. Unfortunately there were many other MSAs in Florida that are outperforming Gainesville. Gainesville should place emphasis on attractin g other creative class sectors rather than the arts, entertainment, and recreation sector. It does not provide as much employment as the other sectors and, although it is doing better than the national average, the sector was not performing as well in the Gainesville MSA as it was in the rest of Florida.

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71 Figure 5 9. NAICS code 71 location quotients for Florida, 2010 Public Administration and as expected, the state capital T allahassee had the highest location quotient. The Gainesville MSA also had a high location quotient at 1.45, placing fourth among

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72 making it the third largest creative class sector by employment. Although there was a decrease of 316 jobs in between 2002 and 2010, the sector only shrank by 3.7% locally. Figure 5 10. NAICS code 92 location quotients for Florida, 2010 Using a shift share analysis to analyze this decrease, it was revealed that the economic growth share was 100, the mix component shift was 562, and the

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73 competitive component shift was 778. This meant that the sector was growing nationally even though the national economy overall was shrinking. Additionally, the sector was shrinking locally due to local factors and not keeping up the pace of the national sector. Tallahassee being the state capital was significantly reflected in the results. Many public adm inistration jobs are anchored in Tallahassee. Tallahassee had the third highest amount of public administration jobs, only behind Miami and Tampa, and in 2010 had five times (8,148 to 39,641) the amount of public administration jobs of Gainesville a sect or that Gainesville in still strong in but cannot compete much in. The public administration sector was an important economic base for Gainesville supplying over 7% of the total Gainesville MSA employment. It also had a high location quotient and was a gro wing sector nationally. Overall it ranked third on the sector score matrix and based on the information available, the public administration sector should receive priority from the City of Gainesville for attracting and maintaining jobs. Local Analysis of Prioritized Creative Class Sectors Based on the results of the sector score matrix, the creative class sectors have been prioritized. The sectors of highest priority were the education services and the health care and social assistance sectors. These sect ors ranked highest primarily due to their prominence in the Gainesville MSA in 2010. It is just as important to sustain these sectors within Gainesville as it is to promote their growth. Also, three other sectors were prioritized. They include the real est ate and rental and leasing sector, the professional and technical services sector, and the public administration sector. These sectors displayed a high local concentration, strong growth between 2002 and 2010, and a strong local employment total. They have been identified as strong candidates for

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74 creative class employment growth. The five prioritized sectors were further analyzed within the Gainesville MSA. Their employment data for each block group was mapped by jobs per kilometer to detect sector concentr ations within the MSA. The following maps display total employment in 2010 within the Gainesville MSA per square kilometer for the five creative class sectors identified as a priority. They are based on the employment data from the CES at the block group l evel the smallest geographic unit that was useful for analysis. The blue line represents the boundary of Alachua and Gilchrist Counties, encompassing the entire Gainesville MSA and the red line represents the Gainesville city limit as of 2012. Figure 5 11. Gainesville MSA creative class employment In figure 5 11, it is apparent that creative class employment within the Gainesville MSA was concentrated within the city limits of Gainesville and to the west of the city,

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75 surrounding I 75. This was to be expe cted, as Gainesville is the primary city of the Gainesville MSA and therefore much of the employment is located within the city. The highest concentration of creative class employment was located on the UF campus and Real Estate and Rental and Leasing Figure 5 12. Real estate and rental and leasing employment In the real estate and rental and leasing sector it was obvious that the highest concentration of this employment was in the area immediately surrounding UF. As mentioned b efore, the presence of a university increases the demand for rental services because students need housing. The highest concentration of this sector was located to the east of the UF campus, in the downtown Gainesville area. Overall, this sector created a ring of employment around UF.

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76 Professional and Technical Services Figure 5 13. Professional and technical services employment The professional and technical services sector seemed to be less clustered than the other creative class sectors. Although the e mployment was spread out across Gainesville and certain areas of Alachua County, the largest concentrations of employments were in the downtown area and in west Gainesville. This sector was the most diverse of the creative class sectors and therefore was n ot as prone to clustering as the others. Alternatively, it was one of the most sought after sectors of employment for localities. Educational Services As expected, the highest concentration of educational services employment was centered near the three lar

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77 stood out on its campus just west of downtown. Alachua County School Board employment was prominently represented in the downtown area, where its located in northwest Gainesville, outside of the Gainesville city limits. Outside of these three areas, the employment was spread throughout the rest of Gainesville, decreasing outside of the city limits and especially outside of Alachua County. Figure 5 14. Education services employment Health Care and Social Assistance Employment in the health care and social assistance sector was surprisingly decentralized. There were hubs for employment at Shands Hospital, the North Florida Regional Medical Center, and around the former AGH site (this is the current location of Innovation Square but the surrounding buildings still contain some healthcare related

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78 establishments). Although the health care and social assistance sector employment was decentralized, it was mostly contained within Alachua County and especially within the Gainesville City limits. Figure 5 15. Health care and social assistance employment Public Administration Public administration employment is often concentrated in the city center and Gainesville was no exception. The majority of public administration jobs were located in downtown Gainesville. This sector was also highly concentrated on the UF campus. Outside of the Gainesville city limits, public administration employment was much scarcer. Also, many of the outlaying municipalities had their own public administration employment represented, but with Gainesville being the primary city and the Alachua

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79 County sea t, Gainesville had a significant advantage in ho employment. Figure 5 16. Public administration employment

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80 Table 5 2. Sector score matrix NAICS Code Total Score Local Employment Rank LQ vs. USA Rank LQ vs. FL Rank National Growt h Rank Local Growth Rank 61 41 20,482 8 1.71 9 2 9 1.261 9 1.155 6 62 36.5 22,049 9 1.43 7 4 7.5 1.209 8 1.098 5 92 28.5 8,184 7 1.45 8 4 7.5 1.054 4 0.963 2 54 27 6,315 6 0.89 4 8 6 1.121 7 1.059 4 53 24 2,408 4 1.32 6 9 5 0.945 2 1.169 7 71 23 1,849 3 1.02 5 16 2 1.058 5 1.338 8 55 18 247 1 0.14 1 18 1 1.094 6 1.365 9 52 18 3,974 5 0.76 3 10 4 0.966 3 0.967 3 51 9 1,832 2 0.71 2 11 3 0.804 1 0.680 1 Source: Center for Economic Studies, 2010

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81 CHAPTER 6 DISCUSSION When the cluster analysis was applied to the employment data from 2010, it appeared that not all the industries labeled as a priority had shown potential for economic development. Specifically, the real estate and rental and leasing sector was the only growing base industry. The professional and technical services sector was considered a declining industry and the rest were classified as transforming industries. Table 6 1. Cluster analysis, applied to Gainesville Not Competitive (declining local shift) Competitive (growing local shift) High Local Concentration (LQ over 1.00) Transforming Industries Education Services Health Services Public Administration Growing Base Industries Real Estate and Rental Low Local Concentration (LQ less than 1.00) Declining Industries Professional and Technical Services Emerging Industries (none) Source: Blakely 2010, p. 193 A Closer Look Bureau of Labor Statistics data was used to look at these industries in detail for Alachua County. Additional LQ and shift share values were collected to paint a more detailed picture of the Gainesville economy within its industry sectors. Instead of using CES data, BLS data was used because it allowed for analysis at more detailed NAICS codes. Unfortunately, BLS dat a did not include public sector employment or employment data that could cause privacy concerns. Therefore, the BLS data was limited in further analysis, but very helpful in some cases.

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82 The BLS data was measured for Alachua County instead of the Gainesvill e MSA. Many of the industries in Alachua County did not have privacy concerns, but their Gilchrist County industry values could be deciphered by subtracting the Alachua Cou nty values from the Gainesville MSA values. Therefore, the BLS did not provide employment data as thoroughly for the Gainesville MSA as it did for Alachua County. Growing Base Industries As the only growing base industry, the real estate and rental and le asing sector was strong in Alachua County. Specifically, the main portion of the sector, NAICS 531: Real estate had a 1.59 LQ and NAICS 5311: Lessors of real estate had a 2.04 LQ. Unfortunately the other sub revealed education it has been already. Housing is a necessity and as long as Gainesville continues to attract students and companies, there will be demand in the housing market. Additionally, there has been no shortage of the development of apartment buildings around the UF campus. Gainesville should encourage development and make its economi c development plans known to the developers of these buildings so that they can locate housing adjacent to future development projects. This will reduce the strain on transportation infrastructure and decrease commute times for students and employees. Tran sforming Industries region. These sectors provide 42,531 jobs to the Gainesville MSA economy, more than

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83 37% of all employment in Gainesville and more than 63% of all local crea tive class employment. Additionally, the public administration sector provides more than 8,000 jobs locally. Unlike the case in Chicago where Sears had to be enticed to stay in Illinois, many of the companies in the education and health sectors, and especi ally the public administration sector, are tied into their location in Gainesville because of private public partnerships. Gainesville should enhance these clusters by working with the schools and hospitals to determine how they can attract more companies to cluster within Gainesville. Figure 6 2 shows how the private employment within Alachua County was distributed within the health care and social assistance sector in 2010. This detail was not available for the education services or public administration sectors because they were heavily comprised of public employment; therefore they contained too many restricted values for Alachua County. Table 6 2. Health care and social assistance employment Industry Employment LQ NAICS 62 Health care and social assist ance 19,503 1.60 NAICS 621 Ambulatory health care services 5,444 1.21 NAICS 622 Hospitals 10,241 2.93 NAICS 623 Nursing and residential care facilities 2,108 0.90 NAICS 624 Social assistance 1,711 0.92 Source: Bureau of Labor Statistics, 2010 Gainesville should try to attract medical and health related companies to the area surrounding Innovation Square. The demand for that area has decreased since AGH was demolished, leaving healthcare businesses that relied upon the hospital without a custome r base. The Ayers Medical Plaza was renovated for non medical use and renamed Ayers Plaza. It originally housed the UF Human Resources Department and soon will be the U.S. development center for MindTree Limited, a software company. Although this is an exa mple of a non medical company moving into a medical building,

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84 it is an example of the Innovation Square attracting companies to the area immediately surrounding it. Companies may want to locate next to Innovation Square instead of it because rent is likel y cheaper and because the buildings are already built. For medical purposes, many of the buildings are already ideal for medical uses. Gainesville should further develop public administration suitable buildings downtown, if needed. In an effort to attract state funding and employment, the city can prove to the state government that it is capable of handling tasks and departments, both with office space and talent. Declining Industries Although the professional and technical services sector was classified as a declining industry in the cluster analysis, it was made up of a wide range of creative class occupations. The sector included many of the types of industries that economic development programs aim to attract. This grouping included the high paying, inno vative, and highly clustered jobs that have made Austin, Texas and Silicon Valley, California hubs for innovative growth. The sector was broken up to the NAICS industry group level and it showed just as wide a range of LQ values. Table 6 3. Professional an d technical services employment Industry Employment LQ NAICS 54 Professional and technical services 5,732 1.02 NAICS 5411 Legal services 893 1.06 NAICS 5412 Accounting and bookkeeping services 433 0.65 NAICS 5413 Architectural and engineering services 1,408 1.46 NAICS 5414 Specialized design services 77 0.90 NAICS 5415 Computer systems design and related services 644 0.59 NAICS 5416 Management and technical consulting services 872 1.14 NAICS 5417 Scientific research and development services 351 0.75 NAICS 5418 Advertising, PR, and related services 267 0.87 NAICS 5419 Other professional and technical services 787 1.80 Source: Bureau of Labor Statistics, 2010

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85 Because there was such a wide range in LQ values, employment data from 2001 was collected from the BLS and used in a shift share analysis. The competitive component was coupled with the LQ value and placed in a cluster analysis for each industry group. Table 6 4. Cluster analysis, professional and technical services Not Competitive (declining local shift) Competitive (growing local shift) High Local Concentration (LQ over 1.00) Transforming Industries NAICS 5413 Growing Base Industries NAICS 5411 NAICS 5416 NAICS 5419 Low Local Concentration (LQ less than 1.00) Declining Industries NAICS 5412 NAICS 5417 Emerging Industries NAICS 5414 NAICS 5415 NAICS 5418 Source: Blakely, 2010, p. 193 Within the technical and professional services sector, the industrial groups of legal services and consulting services were growing base industries for the economy and design services, computer systems design services, and advertising and PR services were emerging industrial groups. The growth of these groups should be encouraged, especially in the emerging industries, in an effort to establish a cluster. Given its total local employment and LQ, the architectural and engineering industrial group was the strongest within its sector in Gainesville even though it has not performed as well proportionally between 2001 and 2010. Gainesville s hould act quickly to determine what local factors have hindered the growth of this industry and to fix them if advisable.

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86 Comparison to Other Creative Hub College Cities Compared to college towns of similar or larger size than Gainesville, it is appar ent that Gainesville is on par with other successful cities. Even though Austin, Texas is a mecca for creative class industries, its LQs scored poorly in half of the sectors analyzed. Granted, health care and education public employment was not represented Austin scored worst and second worst, respectively, among the eight college cities compared. None of the other seven cities examined contained LQs higher than 1.00 for all creative class Sectors. Based on this, Gainesville has a healthy creative class ec onomy compared to other college cities. It already has a strong advantage in many large creative class sectors and is developing Innovation Square in a way that is sure to bring in many more.

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87 Table 6 5 C reative class location quotients for college cities Sector Gainesville Tallahassee Austin College Station Raleigh Durham Nashville State College Information 0.71 1.08 1.30 1.24 1.65 0.70 1.34 1.07 Finance and insurance 0.89 0.74 1.02 0.99 0.87 0.86 1.06 0.64 Real estate and rental and leasing 1.50 0.77 1.21 1.17 1.13 0.69 1.07 1.07 Professional and technical services 1.02 1.35 1.42 1.61 1.38 1.55 0.86 1.07 Management of companies and enterprises 0.18 0.21 0.47 0.27 1.42 0.42 1.01 0.95 Educational services 0.86 0.94 0.69 0.70 0.84 2.38 1.28 0.62 Health care and social assistance 1.60 0.86 0.80 1.22 0.84 1.32 1.03 1.10 Arts, entertainment, and recreation 1.22 0.55 0.95 0.64 1.27 0.61 0.90 0.89 Source: Bureau of Labor Statistics, 2010

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88 CHAPTER 7 CONCLUSION Traditional economic development planning focuses on attracting companies but Richard Florida says cities should instead try to attract talent and companies will follow. In the case of Gainesville, Florida, the city has been able to attract the talent thro ugh the University of Florida but much of the talent leaves after graduating. What is the solution ? Gainesville has create d an effective economic development plan that attracts creative class employers to Gainesville. Specifically, Gainesville should prio ritize maintaining and growing the education and health sectors and it should attract the real estate, professional and technical services, and the public administration sectors. These industries have shown potential for growth and are strengths in the Gai nesville economy. The City of Gainesville has already used many economic development practices mentioned earlier. Instead of providing subsidies, Gainesville has though t of innovative ways to attract creative class jobs, such as making sites and buildings another example of successful implementation. The first building in Innovation Square was built using federal and UF funds but the market has shown demand for mixed use buildings and further development has been approved for private developers in the surrounding area (Bredfel d t, 2011). Additionally, the city has streamlined the permitting process to develop on the site. Innovatio n Square has not only shown a positive impact attracting creative class companies, but also has spurred the growth of housing, retail, and food establishments in the surrounding area. The city has found innovative ways to

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89 make Innovation Square stand out f rom other research parks, including its latest offer to supply 1Gbps speed internet to Innovation Square and its surrounding area. Restrictions The single most inhibiting factor in this research was the limited employment data. It would have been useful to identify industries at the three digit and four digit NAICS code to better understand specific industry clustering within Gainesville and throughout Florida. Although the data is available, it is protected by the government due to privacy concerns. The da ta is available through many third party suppliers at cost. Notably, sixth digit NAICS code. Also in their data, specific establishments are identified instead of aggregated per region. This is especially useful because it identifies employers and where they are located. Another tool that city planners use in economic development is the input output analysis. The input output analysis was created in 1936 as a tool to trace s ales among industries in a region. Cities prefer employment that retains money in the local economy as much as possible. Creative class jobs are known to have a high local output and therefore are more likely to retain this money locally. The city of Cinci nnati released an economic analysis report titled Identification of Industry Clusters for Guiding Economic Development Efforts in Cincinnati USA The report used total employment, and average wages and location quotient, shift share, and input output analy ses, coupled with spatial information. The result was the use of six thresholds of economic importance that were determined to be useful in evaluating sector cluster health. Of the six measures, one pertains to input output ratios, a set of data that was n ot freely accessible for this study (Blakely, 2010, p. 195).

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90 Further Research worked, directly and indirectly. Gainesville has shown that it is devoted to economic growth in and around Innovation Square. Economic development planning practices can growth. The research in this thesis was based on employment data provided by the government. It wo uld be useful to further analyze the non quantifiable factors that go into making a city attractive. The culture and reputation of cities have played a large part in making them livable. Unfortunately these factors cannot be placed into a statistical analy sis without extensive surveying. It would be helpful though to understand the factors that make a city more attractive. In an effort to delve further into statistical analysis, a geographically weighted regression could be performed to better understand cl ustering within Gainesville and other creative cities. Spatial analysis research has been done to determine indicators of creative class employment in rural areas using a locally weighted regression model (Cho 2007). The formula used in that research can b e adapted to urban use to determine indicators in MSAs. better elsewhere in Florida. Any economic growth in the state can benefit Gainesville, ttract companies from out of state and cooperate within the state. As an example, Tallahassee had a high location quotient in the professional and technical services and in the public administration sectors. Also, the Tampa, Lakeland, and Sarasota areas ha d high location quotients in the finance and insurance

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91 and in the management of companies and enterprises sectors. This data analysis could be helpful in economic growth for Gainesville but also for other parts of the state. Understanding what other region s specialize in can be used as an advantage and allow for economic partnerships to be formed between regions. Final Thoughts As this research has been analyzed and written, Gainesville has already made strides in attracting creative class employers and, sp ecifically, private development in and around Innovation Square. These actions have made this thesis time sensitive. Gainesville will be able to develop its vision to its full potential, and if that is the case, then this thesis may not be necessary in a f ew years. More than anything, this thesis serves as a snapshot in time of Gainesville as it meets a turning point in its history as a growing city.

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92 LIST OF REFERENCES Aktouf Framework. Gestao Planejamento 6, 75 94. Retrieved from http://www.revistas.unifacs.br/index.php/rgb Andersen, K & Lorenzen, M. (2005). The Geography of the Danish Creative Class : A Mapping and Analysis. Retrieved from http://cbs.academia.edu/MarkLorenzen/Papers/425591/The_Geography_of_the_D anish_Creative_Class_A_Mapping_and_Analysis Bartik, T. (2002). Evaluating the Impacts of Local Economic Development Policies on Local Economic Outcomes: What Has Been Done and What is Doable?. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=369303 Blakely, E. & Leigh, N. (2010). Planning Local Economic Development: Theory and Practice Fourth Edition. Thousand Oaks, CA: Sage Pu blications, Inc. Blanco, A. G. (2011a). 3a analytical techniques: hierarchy and location quotients [Presentation slides]. Retrieved from e mail. Blanco, A. G. (2011b). 3b analytical techniques: shift share [Presentation slides]. Retrieved from e mail. Blan co, A. G. (2011c). 3c analytical techniques: input output [Presentation slides]. Retrieved from e mail. Boston Redevelopment Authority. (2004). Retrieved from http://unitus.org/FULL/BostonCreativeEconomy.pdf Bredfeldt, E. (2011, November 9). Gainesville Economic Development. Presentation to the Urban and Regional Planning department, University of Florida, Gainesville, FL. Bureau of Labor Statistics. (2005, March 30). Location Quotient Calculator. Retrieved from http://www.bls.gov /cew/cewlq.htm Bureau of Labor Statistics. (2010). Location Quotient Calculator: 2001 and 2010 data. [Data set]. Retrieved from http://data.bls.gov/location_quotient/ControllerServlet Bureau of Labor Statistics. (2012, April 2012). About BLS. Retrieved from http://www.bls.gov/bls/infohome.htm Center for Economic Studies. (2011, September 13). OnTheMap Help and Documentation. Retrieved from http://lehd.ces.census.gov/led/datatools/onthemap.php?name=WhatisOnTheMap

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93 Cervantes, M. & Guellec, D. (2002). The Br ain Drain: Old myths, new realities. OECD Observer. Retrieved from http://www.oecdobserver.org/ Chantelot, S., Peres, S., & Virol, S. (2010). The Geography of French Creative Class: An Exploratory Spatial Data Analysis. Retrieved from http://cahiersdugreth a.u bordeaux4.fr/2010/2010 16.pdf Cho, S., Kim, S., Clark, C., & Park, W. (2007). Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model. Agricultural and Resource Economics Review, 36 24 38. Retrieved from http://econpap ers.repec.org/article/agsarerjl/10163.htm City of Gainesville. (2009). Gainesville History. About Gainesville. Retrieved from http://www.cityofgainesville.org/VISITOR/AboutGainesville/AreaHistory/tabid/343/ Default.aspx City of Gainesville. (2011). Comprehe nsive Annual Financial Report. Retrieved from http://www.cityofgainesville.org/LinkClick.aspx?fileticket=flD evBaPq8%3d&tabid=189 Clark, A. (2012, March 27). MindTree to locate center in Gainesville, create 400 jobs. Gainesville Sun. Retrieved from http:// www.gainesville.com/ Donegan, M., Drucker, J., Goldstein, H., Lowe, N., & Malizia, E. (2008). Which indicators explain metropolitan economic performance best? Traditional or creative class. Journal of the American Planning Association, 74 180 195. doi:10. 1080/01944360801944948 Florida, R. (2000). Technology, talent, and tolerance. InformationWeek, 812 365 365. Retrieved from http://search.proquest.com/docview/229139491?accountid=10920 Florida, R. (2002). The rise of the creative class, and how it's trans forming work, leisure, community and everyday life. Chicago, IL: Basic Civitas Books. Florida, R. (2007, October 14). Flawed Science and the Creative Class [Web log post]. Retrieved from http://www.creativeclass.com/_v3/creative_class/2007/10/14/flawed sci ence and the creative class/ Florida, R., Mellander, C., & Stolarick, K. (2007). Inside the Black Box of Regional Development: Human Capital, the Creative Class and Tolerance. Retrieved from http://www.creativeclass.com/rfcgdb/articles/Inside%20the%20black %20box.pdf Florida, R. (2008). Who's your city?: How the creative economy is making where to live the most important decision of your life New York: Basic Books.

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94 Florida, R., Mellander, C., & Stolarick, K. (2009). Scope Eco nomies in the Location and Clustering of the Entertainment Economy. Retrieved from http://www.creativeclass.com/rfcgdb/articles/thats%20entertainment.pdf Florida, R. (2010a). HP Input Output Interview [video]. Retrieved from http://h30565.www3.hp.com/t5/HP IO Video/Richard Florida The Creative Class Video/ba p/289 Florida, R. (2010b, August 17). Where the Jobs Will Be. The Atlantic. Retrieved from http://www.theatlantic.com/ Florida, R. (2010c, August 25). Where the Creative Class Jobs Will Be. The Atlantic. Retrieved from http://www.theatlantic.com/ Florida Agency for Workforce Innovation. (2011). Florida Metropolitan Areas [image]. Retrieved from http://www.docstoc.com/docs/108798945/Florida Metropolitan Areas Florida Geographic Data Library. (2012). FGDL Metadata Explorer: shapefile data [Data set]. Retrieved from http://www.fgdl.org/metadataexplorer/explorer.jsp Florida Innovation Hub at UF. (2010). Close to UF [map]. Retrieved from http://www.floridainnovationhub.ufl.edu/ Franklin, R. (2003, November). M igration of the Young, Single, and College Educated: 1995 to 2000. Retrieved from http://www.census.gov/prod/2003pubs/censr 12.pdf Enterprise Florida. (2012). Geography. In Alachua County Profile. Retrieved from http://www.eflorida.com/profiles/CountyRepor t.asp?CountyID=1&Display=all Gainesville CRA. (2010, September 1). Agenda: College Park University Heights Redevelopment Advisory Board. Retrieved from http://www.gainesvillecra.com/CPUHAgenda09 01 2010.pdf Gainesville CRA. (2012). Project: Innovation Squa re. In College Park / University Heights. Retrieved from http://www.gainesvillecra.com/cpuh_project_innovation_square.php Growth. International Monetary Fund, 42, 577 607. Retrieved from http://www.imf.org Hodges, A. W., Stevens, T. J., & Rahmani, M. (2011). Economic Impacts of the University of Florida 2009 10. Retrieved from http://www.fred.ifas.ufl.edu/economic impact analysis/pdf/UF%20Impact%20Report%20FY2009 1 0.pdf

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95 Huggins, R. & Izushi, H. (2011). Competition, Competitive Advantage, and Clusters: The Ideas of Michael Porter. New York, NY: Oxford University Press. Innovation Square. (2012). Innovation Square at the University of Florida: Community and Innovation Redefined [brochure]. Retrieved from http://innovationsquare.ufl.edu/system/files/1_1790163934_uof 11003 innova_sq_broch(m).pdf Innovation Square wins APA economic development award. (2012, summer). San Felasco Chapter Newsletter Retrieved from e mail. Kay, J. (2009, March 10). The Problem with Richard Florida. National Post Retrieved from http://www.nationalpost.com/ Levy, J. (1990). What Local Economic Developers Actually Do: Loca tion Quotients Versus Press Releases. Journal of the American Planning Association 56 153 160. doi:10.1080/01944369008975756 Levy, J. (2009). Contemporary Urban Planning Eighth Edition. Upper Saddle River, NJ: Pearson Prentice Hall Long, J. (2010). Wei rd city sense of place and creative resistance in Austin, Texas Austin, TX: University of Texas Press. Lowe, C. (2012, January 24). Address at the Hippodrome State Theater, City of Gainesville, Gainesville, FL. Marg aretta, J. (2012). Understanding Michael Porter: the essential guide to competition and strategy. Boston, MA: Harvard Business School Publishing NAICS Association. (2008). Industry Descriptions. In 2007 US NAICS Electronic Reference Retrieved from http: //www.naics.com/censusfiles/ Nationwide Insurance. (2012). W. Kim Austen. In About Us Retrieved from http://www.nationwide.com/newsroom/kim austen.jsp Office of Institutional Studies. (2010). Enrollment by Semester and Gender. Retrieved from http://www.ut exas.edu/academic/ima/sites/default/files/SHB98 99Students.pdf Pickard, B. (1991). A History of Gainesville, Florida. In Historic Gainesville Incorporated Retrieved from http://www.afn.org/~hgi/gnvhistory.html Porter, M. (1983). Cases in Competitive Strat egy. New York, NY: The Free Press. Porter, M. (1990). The Competitive Advantage of Nations. Harvard Business Review, 68 73 93 Retrieved from http://www.hbr.org/

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96 Porter, M. (2000a). Location, Competition, and Economic Development: Local Clusters in a Globa l Economy. Economic Development Quarterly, 14 15 34. Retrieved from http://www.edq.sagepub.com Porter, M. (2000b). Locations, Clusters, and Company Strategy (Clark, G., Feldman, M., and Gertler, M. Eds.) Oxford, England: Oxford University Press. Retrieve d from http://www.mendeley.com/research/locations clusters company strategy/ Progress Corporate Park. (2012). Park History. In Progress Corporate Park Retrieved from http://www.progresscorporatepark.com/park history/ Research Triangle Park. (2011). Backg round. In About RTP Retrieved from http://www.rtp.org/about rtp Rice, D. (2010). Creative Class Workers in Waterloo Region. Retrieved from http://workforceplanningboard.com/Files/English/WPB_Creative_Class_Report.pdf Stimson, R. J., Stough, R., & Roberts, B. H. (2006). Regional economic development: Analysis and planning strategy. Berlin, Germany: Springer. Stonehouse, G. & Snowdon, B. (2007). Competitive Advantage Revisited: Michael Porter on Strategy and Competitiveness. Journal of Management Inquiry, 16 256 273. Retrieved from http://www.jmi.sagepub.com Storper, M., & Scott, A. J. (2009). Rethinking human capital, creativity and urban growth. Journal of Economic Geography, 9 147 167. Retrieved from http://www.joeg.oxfordjournals.org/ Unites States Cens us Bureau. (1994). Geographic Area Reference Manual. Retrieved from http://www.census.gov/geo/www/garm.html United States Census Bureau. (2010). 2010 TIGER/Line Shapefiles Technical Documentation. Retrieved from http://www.census.gov/geo/www/tiger/tgrshp20 10/documentation.html United States Census Bureau. (2011). North American Industry Classification System: Frequently Asked Questions. In North American Industry Classification System. Retrieved from http://www.census.gov/eos/www/naics/faqs/faqs.html United States Census Bureau. (2012a). All Sectors. In Industry Statistics Sampler. Retrieved from http://www.census.gov/econ/industry/ United States Census Bureau. (2012b). LEHD Origin Destination Employment Statistics (LODES) Dataset Structure Format Version 6. 0 Retrieved from http://lehd.ces.census.gov/led/onthemap/LODES6/LODESTechDoc6.0.pdf

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97 United States Census Bureau. (2012c). NAICS Update Process Fact Sheet. Retrieved from http://www.census.gov/eos/www/naics/reference_files_tools/NAICS_Update_Proc ess_Fact_S heet.pdf United States Census Bureau. (2012d). Introduction to NAICS. In North American Industry Classification System. Retrieved from http://www.census.gov/eos/www/naics/ Wilmath K. (2011, September 26). UF builds innovative complex for economic development. Tampa Bay Times. Retrieved from http://www.tampabay.com/

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98 BIOGRAPHICAL SKETCH Brett Lackey was born in 1988 in Austin, Texas. He is the son of David Lackey and Karen Lynn. He earned his Master of Arts in Urban and Regional Planning degree, with an interdisciplinary concentration in (geographic information systems) GIS, in August 201 2 at the University of Florida in Gainesville, Florida. He attended the University of Florida from 2006 to 2010 as an undergraduate student pursuing his Bachelor of Arts degree in g eography. He was introduced to the University of Florida Region al Planning D epartment as a GIS analyst in the spring of 2010 and became a research assistant by that fall. Brett plans to pursue a career in GIS with urban planning and economic development applications.