Some Impacts of Industry Clusters in Missouri

1
Some Impacts of Industry Clusters in Missouri

• Dr. Diane Primont
• Professor of Economics
• Associate Director, CEBR
• email dprimont_at_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

• Are disparities in economic performance among
  counties increasing or diminishing?
• Convergence
• 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
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

7
Statistical Analysis Conditioning the growth
model

• grpcinc Coef. Std. Err. t Pgtt
  
• --------------------------------------------------
  -----------
• 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

8
Graphical evidence of convergence
Pulaski
Reynolds
Oregon
St. Louis County
Cape Girardeau
Shelby
9
Growth by Rurality of County
Reynolds
Carter
Wayne
Monroe
Scotland
Shelby
10
Conclusions

• The conditional growth model
• suggests that Missouri counties are converging
• 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

11
2. Industry Clusters in Missouri

• Measuring specialization
• Location Quotient
• Specialization in Industries
• Industry cluster bubble charts
• Northeast and South Central Missouri
• Southeast Missouri and the Bootheel

12
Measuring Specialization

• Location Quotient
• Ratio of the proportion of a regions employment
  in an industry to that of the nation as a whole
• LQ (EX/ET)/(NX/NT)
• EX is regions employment industry x
• ET is regions total employment
• NX is national employment in industry x
• NT is total national employment

13
Measuring Specialization

• LQ 1 the regions activity in the industry
  cluster is similar to the nation as a whole.
• LQ lt 1 the regions activity in the industry is
  unspecialized.
• LQ gt 1 the regions activity in the industry
  exceeds that of the nation as a whole.
• The greater LQ exceeds 1, the more specialized
  the region is in the industry cluster.

14
Measuring Specialization
15
Industry Cluster Bubble Chart

• Hypothetical Data

2
Stars
Mature
LQ in 2005
1
10
-10
Emerging
Transforming
0
Chg. in LQ 2001-2005
16
Industry Cluster Bubble Chart

Forest Wood Products
Biomedical/Biotechnical
Education Knowledge Creation
Energy
17
Industry Cluster Bubble Chart
Manufacturing Supercluster
Mining
Chemicals
Glass Ceramics
Forest Wood
18
Industry Cluster Bubble Chart
Biomedical/ Biotechnical
Transportation and Logistics
Forest Wood Products
Energy
Defense Security
Business Financial
19
Industry Cluster Bubble Chart

Agribusiness
Transportation and Logistics
Biomedical/Biotechnical
Energy
Manufacturing Supercluster
20
Conclusions

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