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Economic Growth and Income Inequality in Indiana Counties

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### Economic Growth and Income Inequality in Indiana Counties

Valerien O. Pede

Raymond J.G.M. Florax

Dept. of Agricultural Economics

Purdue Center for Regional Development

Purdue University, West Lafayette, USA

E-mail: [email protected], [email protected]

Website: http://web.ics.purdue.edu/~rflorax/

Outline

- GIScience and spatial modeling
- Background
- income inequality
- knowledge and human capital
- Indiana, the Midwest, and US counties
- Simple economic growth models
- convergence
- Solow Model
- Mankiw, Romer and Weil Model
- Conclusions

Linking GIScience and modeling

- Availability of space and place characteristics
- technology driven (GPS, RS)
- georeferenced data
- deduct information on distance and accessibility
- spatial “sorting”, spatial mismatch
- Approaches to spatial data analysis
- visualize and find spatial characteristics
- use of GIS
- explore spatial distribution (spatial statistics approach)
- explain spatial dimension with theory and modeling
- many issues are inherently spatial
- social interaction, copycatting, spatial spillovers, etc.
- explain spatial distribution (spatial econometric approach)

Real per capita income – space-time

- The Moran’s I statistic is similar to a correlation coefficient, and measures spatial clustering

Real per capita income – inequality

- The Gini coefficient measures income inequality between counties

Real per capita income – dynamics

- STARS
- Space-Time Analysis of Regional Systems
- Serge Rey, San Diego State University
- freeware
- website http://stars-py.sourceforge.net/
- Spatio-temporal dynamics
- county level
- 1969 – 2003
- weights matrix
- provides information on spatial neighborhood structure
- direct neighbors with a common border

Real per capita income – Indiana

- Developments over space and time
- dominance North and Central Indiana 1970s
- replaced by Central and South Indiana by the early 2000s
- less spatially integrated
- spatial clustering of similar per capita income levels declines
- Indianapolis stands out as an “island”
- income inequality increases over time
- especially due to some counties around Indianapolis

A simple model

- Unconditional convergence model
- income growth is a function of the initial income level
- convergence of per capita income
- poor counties grow faster, richer counties slower

Solow model

- Standard neoclassical model
- correcting for growth of capital and labor
- note: lacking data for investments

MRW model with human capital

- Mankiw, Romer and Weil model
- accounting for human capital as well
- educational level of the population in 4 categories

Conclusions

- Evidence for strong spatial clustering across counties
- extent of spatial clustering diminishes over time
- Income inequality is increasing in Indiana
- mainly due to metropolitan effect of Indianapolis
- trend not observed for the Midwest
- Development of new outliers
- Significance investment and human capital
- needs further detail in future work
- production of knowledge by universities and R&D labs
- also incorporation of agglomeration effects

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