Some Impacts of Industry Clusters in Missouri Dr. Diane Primont Professor of Economics & Associate Director, CEBR April 11, 2008

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

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”

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

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

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

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

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

Statistical Analysis Summary Statistics for Missouri Counties VariableObsMeanStd. Dev. Min. Max. Growth in logarithm of real per capita income grpcinc Logarithm of real per capita income lnpcinc Index of relative rurality Irr Specialize dummy variable Specialize

Statistical Analysis: Conditioning the growth model Conditional Growth Model Growth in real per capita income 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

Statistical Analysis: Conditioning the growth model grpcinc | Coef. Std. Err. t P>|t| lnpcinc2000 | lnirr | specialize | constant | R-squared = Adj R-squared =

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

Growth by Rurality of County Monroe Shelby Scotland Reynolds Carter Wayne

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

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

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

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

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

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

Measuring Specialization

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

Industry Cluster Bubble Chart Hypothetical Data LQ in 2005 % Chg. in LQ Stars EmergingTransforming Mature

Industry Cluster Bubble Chart

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

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

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

Industry Cluster Bubble Chart

Agribusiness Transportation and Logistics Biomedical/Biotechnical Manufacturing Supercluster

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

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