1. Some Impacts of Industry Clusters in Missouri Dr. Diane Primont Professor of Economics & Associate Director, CEBR email: dprimont@semo.edudprimont@semo.edu April 11, 2008

2. Introduction Economists and Economic Developers often focus on causes of disparities in economic growth rates Why? Even small differences in growth rates can lead to ever larger disparities over time, due to compounding

3. Two Research Questions 1. Are disparities in economic performance among counties increasing or diminishing?  “Convergence” 2. How is this performance effected by the presence and extent of industry clusters?  “Industry Clusters”

4. Two Research Questions Industry cluster a group of businesses linked by common supply chains, labor needs, technologies, or customers

5. 1. Are Missouri counties converging? Statistical Analysis Conditioning the growth model on: Rurality Industry cluster specialization Graphical evidence

6. 1. Are Missouri counties converging? Graphical evidence of Convergence Statistical Analysis Conditioning the growth model on: Rurality Industry cluster specialization Conclusions

7. Graphical evidence of convergence Logarithm of per capita income in 2000 poorerricher Growth in real per capita income faster slower Hypothetical Data

8. 1. Are Missouri counties converging? Graphical evidence of Convergence Statistical Analysis Conditioning the growth model on: Rurality Industry cluster specialization Conclusions

9. Statistical Analysis Summary Statistics for Missouri Counties VariableObsMeanStd. Dev. Min. Max. Growth in logarithm of real per capita income 2000-5 grpcinc115.0239.0523-.1646.1558 Logarithm of real per capita income lnpcinc20001159.402.1648 8.997 10.053 Index of relative rurality Irr 115.5351.1486.089.756 Specialize dummy variable Specialize 115.7217.4501 0 1

10. Statistical Analysis: Conditioning the growth model Conditional Growth Model Growth in real per capita income 2000-2005 depends on Real per capita income in 2000 (lnpcinc2000) Index of relative rurality (lnirr) Industry cluster specialization (specialization) 1 if county specializes in one or more industry clusters; 0 otherwise

11. Statistical Analysis: Conditioning the growth model grpcinc | Coef. Std. Err. t P>|t| ------------------------------------------------------------- lnpcinc2000 | -.2204.0342 -6.34 0.000 lnirr | -.0437.0150 -2.91 0.004 specialize |.0208.0096 2.16 0.033 constant | 2.0510.3149 6.51 0.000 ------------------------------------------------------------- R-squared = 0.3005 Adj R-squared = 0.2816

12. Graphical evidence of convergence Shelby Cape Girardeau ReynoldsOregon St. Louis County Pulaski

13. Growth by Rurality of County Monroe Shelby Scotland Reynolds Carter Wayne

14. 1. Are Missouri counties converging? Graphical evidence of Convergence Statistical Analysis Conditioning the growth model on: Rurality Industry cluster specialization Conclusions

15. Simple growth model (graph) suggests that Missouri counties are converging This conclusion is altered in the conditional growth model (regression) rural counties tend to grow more slowly – will fall further and further behind counties that specialize in one or more industry clusters tend to grow more quickly

16. 2. Industry Clusters in Missouri Measuring specialization Location Quotient Specialization in Industries Industry cluster bubble charts State of Missouri Northeast and South Central Missouri Southeast Missouri and the Bootheel

17. 2. Industry Clusters in Missouri Measuring specialization Location Quotient Specialization in Industries Industry cluster bubble charts State of Missouri Northeast and South Central Missouri Southeast Missouri and the Bootheel Conclusions

18. Measuring Specialization Location Quotient Ratio of the proportion of a region’s employment in an industry to that of the nation as a whole LQ = (E X /E T )/(N X /N T ) E X is region’s employment industry x E T is region’s total employment N X is national employment in industry x N T is total national employment

19. Measuring Specialization LQ = 1: the region’s activity in the industry cluster is similar to the nation as a whole. LQ < 1: the region’s activity in the industry is unspecialized. The greater LQ exceeds 1, the more specialized the region is in the industry cluster. In this study, a region specializes in an industry cluster if LQ >= 1.2

20. Measuring Specialization

21. 2. Industry Clusters in Missouri Measuring specialization Location Quotient Specialization in Industries Industry cluster bubble charts State of Missouri Northeast and South Central Missouri Southeast Missouri and the Bootheel Conclusions

22. Industry Cluster Bubble Chart Hypothetical Data LQ in 2005 % Chg. in LQ 2001-2005 1 0 2 10-10 Stars EmergingTransforming Mature

23. Industry Cluster Bubble Chart

24. Education & Knowledge Creation Energy Forest & Wood Products Biomedical/ Biotechnical

25. Industry Cluster Bubble Chart Mining Manufacturing Supercluster Chemicals Forest & Wood Glass & Ceramics

26. Industry Cluster Bubble Chart Transportation and Logistics Defense & Security Business & Financial Forest & Wood Product s Biomedical/ Biotechnical Energy

27. Industry Cluster Bubble Chart

28. Agribusiness Transportation and Logistics Biomedical/Biotechnical Manufacturing Supercluster

29. 2. Industry Clusters in Missouri Measuring specialization Location Quotient Specialization in Industries Industry cluster bubble charts State of Missouri Northeast and South Central Missouri Southeast Missouri and the Bootheel Conclusions

30. Achieving high economic growth is a challenge for any county or region, but particularly for rural counties Regions with a greater number of “star” and “emerging” industry clusters tend to grow faster May be useful to target these industries for further development