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David L. Barkley Clemson University Clemson, South Carolina.

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Presentation on theme: "David L. Barkley Clemson University Clemson, South Carolina."— Presentation transcript:

1 David L. Barkley Clemson University Clemson, South Carolina

2 Roberto Camagni “On the Concept of Territorial Competitiveness” Urban Studies (2002)

3 weak and lagging territories risk exclusion and decline to a larger extent than in the past.” “…weak and lagging territories risk exclusion and decline to a larger extent than in the past.”

4  Definitions, conceptualizations, and measures  Advantages and Disadvantages of Strategy  Estimation of Indices of Competitiveness  Benefits and Shortcomings of Indices

5 “…the ability of an economy to attract and maintain firms with stable or rising market shares in an activity while maintaining or increasing standards of living for those who participate in it.” (Storper, 1997) “…ultimately competitive regions and cities are places where both companies and people want to locate and invest in.” (Kitson, Martin, and Tyler, 2004)

6 Context for Firm Strategy and Rivalry Demand Conditions Related and Supporting Industries Factor Conditions Conceptualizations of Competitiveness The Porter Diamond Framework (Porter, 1998)

7 Source: National Competitiveness Council

8 Firm levelEconomy level Source: Budd and Hirmis, 2004 X-Efficiency Enhanced productivity Enhanced Economic efficiency regionnation Activity-complex economies Localization economies Urbanization economies COMPARATIVE ADVANTAGE REGIONAL COMPETITIVENESS AND ITS DYNAMICS COMPETITIVE ADVANTAGE

9 Inputs (Development Report Card for the States)  Human resources  Financial resources  Infrastructure resources  Innovation resources  Amenity resources and natural capital

10 Outputs (Krugman, Porter)  Output per worker  Output per unit of capital and labor in traded sectors Outcome (Kitson, et al. and Budd and Hirmis)  High rate of employment among labor force  High quality and high income job opportunities

11  Provides appreciation of current local economic environment  Identifies weaknesses in the local economy  Encourages a longer term perspective on economic development process  May lead to new marketing and promotional programs for the region

12  May contribute to wasteful competition among regions  May result in a re-allocation of resources from low-visibility programs to high-visibility programs  May contribute to widening social inequalities  Used as justification for policy makers pet programs

13 Development Report Card for the States (CFED)  67 measures 15 sub-indices 3 indices  no weights State New Economy Index (Atkinson and Correa)  27 indicators 5 indices  weights selected to reflect relative importance

14 Policom Economic Strength Rankings a Milken Best Performing Cities b BHI Metro Area Competitiveness Report c Washington, DCRiverside-San Bernadino, CABoston, MA Charlotte, NCPhoenix, AZRaleigh, NC Las Vegas, NVOrlando, FLSeattle, WA Nashville, TNLas Vegas, NVDenver, CO San Diego, CARaleigh, NCAustin, TX Phoenix, AZSalt Lake City, UTMinneapolis, MN Atlanta, GAAustin, TXPortland, OR Sacramento, CACharlotte, NCWashington, DC Minneapolis, MNSacramento, CASalt Lake City, UT Orlando, FLHouston, TXCharlotte, NC a Rankings for 363 Metropolitan Statistical Areas. b Rankings for 200 largest Metropolitan Statistical Areas. c Rankings for 50 largest Metropolitan Statistical Areas.

15 Policom Economic Strength Rankings a Milken Best Performing Cities b BHI Metro Area Competitiveness Report c Washington, DCRiverside-San Bernadino, CABoston, MA Charlotte, NCPhoenix, AZRaleigh, NC Las Vegas, NVOrlando, FLSeattle, WA Nashville, TNLas Vegas, NVDenver, CO San Diego, CARaleigh, NCAustin, TX Phoenix, AZSalt Lake City, UTMinneapolis, MN Atlanta, GAAustin, TXPortland, OR Sacramento, CACharlotte, NCWashington, DC Minneapolis, MNSacramento, CASalt Lake City, UT Orlando, FLHouston, TXCharlotte, NC a Rankings for 363 Metropolitan Statistical Areas. b Rankings for 200 largest Metropolitan Statistical Areas. c Rankings for 50 largest Metropolitan Statistical Areas.

16  Inclusion of relevant variables, and only relevant variables  Selection of appropriate measures for the variables  Selection of weights used to combine the variables  Is the index a good predictor

17  Ignore the region’s historical development process and industrial legacy  Suggestive of formulaic solutions for complex economic development problems  Provide little room for alternative visions in the policy discussion  May stigmatize lagging regions

18 Portland Austin Madison Raleigh/Durham Ireland

19 Policy Makers and Economic Development Agencies  Road Trips  Best Practices Regional Scientists  Conceptualizations and Models  Discourse on Competitiveness Strategies  Rankings and Indices  Discourse on Rankings and Indices

20 1. Develop indices and benchmarking methodologies that more accurately reflect competitiveness - Variables selected - Measures/data used for variables - Weighting of variables in indices

21 Location Resource Endowments Institutions Industrial Structure Economic History Social Capital

22 % College Graduates % Creative Class Sci/Eng Grad Students Raleigh/Durham Greenville, SC253716

23 % College Graduates % Creative Class Sci/Eng Grad Students Raleigh/Durham Greenville, SC Lexington, KY304128

24  Provide interpretations of lessons learned on road trips  Help identify characteristics unique to the visited region that enhanced competitiveness  Provide insights into characteristics of “home” region that may impede or facilitate the transfer of policies  Provide detailed analysis of the economies of the visited and home regions

25 Definition: “an empirical inquiry that investigates a contemporary phenomena within its real-life context, especially when the boundaries between phenomena and context are not clear.” (Yin, 2003)

26  Development of theoretical model  Research model design  Data collection and analysis

27  Individuals associated with “case”  Review of literature (industry, government, popular press, and academic papers  Secondary data on regional economy  Multiple cases, multiple units of analysis

28  Case studies are expensive and time consuming  Skeptical of information collected through interviews  Not confident in use of findings by policy makers  Perceived to be more difficult to publish in journals

29  Case studies can be fun  Provide new information and perspectives  Useful in developing or refining hypotheses  Useful in testing hypotheses  Policy makers love case studies

30  Case studies and best practices will be used in developing policy  We cannot attend every meeting of policy makers  We can improve the pool of good case studies  We can provide leadership in the design of case studies and interpretation of findings


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