Locating Capital Cities within an Economy:

1. Locating Capital Cities within an Economy: A Study of Knowledge-Based Industry Clusters in the United States William M. Bowen Mukesh Kumar Maxine Goodman Levin College of Urban Affairs Cleveland State University International Conference on Korean Regional Development, Chung-Ang University, Seoul, South Korea. November 15, 2003, 1

2. Three Questions What industries have high industrial linkages with central government administrative functions in U.S. cities? What industries tend to locate near governmental administrative functions in the United States? What does the industrial structure of U.S capital cities indicate for how knowledge-based industrial clusters might be set up for the new capital city and adjacent cities in South Korea? 2

3. Data: 4-digit North American Industrial Classification System (NAICS) employment data from 34 U.S. cities for the years 1986, 1991, 1996 and 2001. Capital-cities (7): Atlanta, Georgia; Boston, Massachusetts; Denver, Colorado; Minneapolis-St. Paul, Minnesota; Phoenix-Mesa, Arizona; Trenton, New Jersey; Washington D.C.-MD-VA-WV. Non-capital cities (27) 3

4. Knowledge-Based Economies Conceptual definition: Knowledge and competitive advantage Trial, error and human ability Knowledge and urban areas Link to innovation and growth 4

5. Knowledge-Based Economies Types of Knowledge: Technical knowledge Customer base knowledge Financial knowledge Human capital Operational Definition: Based upon Hill (2001), OECD (2003). 72 4-digit NAICS codes 5

6. The Geography of Knowledge Relationship between R&D, knowledge generation, innovation, and economic growth Less clear geography of relationship Are clusters replicable? Mixed and inconclusive empirical evidence 6

7. Indicators of Knowledge-Based Industries 1. Location quotients: indicates local/regional specialization in particular industries LQi = (ei/e) / (Ei/E) where, ei = regional employment in industry i, e = total regional employment, Ei = national employment in industry i, and E = total national employment. Expect higher LQs for knowledge industries in Capital cities 7

8. Indicators of Knowledge-Based Industries • 2. Shift-share industry mix coefficients: indicates importance of an industry to the region • PiR = [(EiN,t – EiN,t-n)/EiN,t-n – ( EN,t – EN,t-n)/EN,t-n] EiR,t-n • where, E signifies employment, • N signifies the standard area, • R signifies the region, • t signifies the end of a time period, • t-n signifies the beginning of a time period. • Expect higher Industry mix coefficients for knowledge industries in Capital cities 8

9. Indicators of Knowledge-Based Industries • 3. Shift-share competitive effect coefficients: indicates competitive advantage for an industry in the region • DiR = [(EiR,t – EiR,t-n)/EiR,t-n – ( EN,t – EN,t-n)/EN,t-n] EiR,t-nwhere, E signifies employment, • N signifies the standard area, • R signifies the region, • t signifies the end of a time period, • t-n signifies the beginning of a time period. • Expect higher competitive effect coefficients for knowledge industries in Capital cities 9

10. Analysis Univariate Analysis: ANOVA Are the mean values of the industry-specific indicators different for capital cities than for non-capital cities? Multivariate analysis: Logistic regression analysis What combination of industry specific indicators predicts membership in the class of capital cities or not-capital cities? 10

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12. Location Quotient Results Univariate Analysis: Capital cities and not-capital cities were found to differ with respect to LQs in the following industries: Management, Scientific and Technical Consulting Services Educational Support Services Basic Chemical Manufacturing Computer Systems Design and Related Services Ventilation, Heating, Air Conditioning, and Commercial Refrigeration Architectural, Engineering, and Related Services 12

13. Location Quotient Results Other Telecommunications Colleges, Universities and Professional Services Office Administrative Services Activities Related to Credit Intermediation Services to Buildings and Dwellings Wired Telecommunications Carriers Data Processing, Hosting, and Related Services Insurance Carriers 13

14. Location Quotient Results Multivariate analysis: Logistic regression models using LQ values for the knowledge based industries perfectly predicted capital city vs. not-capital city using only the intercept term. 14

15. Industry Mix Effect Results Univariate Analysis: Capital cities and not-capital cities were found to differ on industry mix with respect to the following industries: Software Publishers Computer Systems Design and Related Services Other Telecommunications Architectural, Engineering and Related Services Management, Scientific, and Technical Consulting Services Facilities Support Services 15

16. Industry Mix Effect Results Multivariate Analysis: Logistic regression models using industry mix values for the knowledge-based industries were unable to reliably predict capital city vs. not-capital city Computer Systems Design and Related Services 16

17. Competitive Effect Results Univariate Analysis: Capital cities and not-capital cities were found to differ on industry mix with respect to the following industries: Computer and Peripheral Equipment Manufacturing Navigational, Measuring, Electromedical and Control Instrument Audio and Video Equipment Manufacturing Architectural, Engineering, and Related Services Advertising and Related Services 17

18. Competitive Effect Results Business Support Services Investigation and Security Services Petroleum and Coal Products Manufacturing Soap, Cleaning Compound, and Toilet Preparation Manufacturing Wired Telecommunications Carriers Wireless Communications Carriers (minus satellites) Telecommunications Resellers Satellite Communications Securities and Commodities Exchange Management of Companies and Enterprises. 18

19. Competitive Effect Results Multivariate Analysis: Logistic regression models using competitive effect values for the knowledge-based were not feasible given the high percentages of missing data in the data set. 19

20. Discussion • Found some potentially clustering industries in capital cities on a univariate basis using LQ, industry mix, and competitive effects • Multivariate analysis of LQs counter-indicates the presence of knowledge-based industrial clusters in US capital cities 20

21. Discussion • This is further evidenced specifically in terms of the share of knowledge based industry employment in the overall economy, by the fact that there is no clear overall difference between capital cities and not-capital cities. • Multivariate analysis indicates that a healthy Computer Systems Design and Related Services industry in a capital city is apt to be especially important for its success. 21

22. Conclusion The analysis of LQ and shift-share data is largely inconclusive On balance, in the knowledge based industries we found more evidence of similarity between capital and not-capital cities than of difference. It is unclear how knowledge based industrial clusters in US capital cities – or lack thereof -- might bear upon Korean urban spatial structure. 22