Economic Growth and Income Inequality in Indiana Counties

Valerien O. PedeRaymond J.G.M. Florax

Dept. of Agricultural EconomicsPurdue Center for Regional Development Purdue University, West Lafayette, USA

E-mail: vpede@purdue.edu, rflorax@purdue.eduWebsite: http://web.ics.purdue.edu/~rflorax/

2 © 2006 rjgm florax, vo pede

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

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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)

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Real per capita income – maps

1970

1990

1980

2000

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Real per capita income – space

20001990

19801970

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Real per capita income – space-time

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

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Real per capita income – outliers

1970

1990

1980

2000

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Real per capita income – inequality

The Gini coefficient measures income inequality between counties

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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

Stars.lnk

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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

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Midwest, 2003

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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

OLS ML OLS ML OLS MLconstant 1.87* 1.5 3.99* 3.48* 4.62* 4.40*RPCI69 -0.15 -0.11 -0.36* -0.31* -0.43* -0.41*INVPOPEDLOWEDMEDEDHIGHlambda 0.51* 0.63* 0.57*

convergence 0.5 0.3 1.3 1.1 1.6 1.5

R2 0.02 0.22 0.26 0.50 0.34 0.51

LMERR 20.78* 322.92* 1022.96*LMLAG 21.20* 307.52* 851.82*

IN MIDWEST US

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Solow model

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

OLS ML OLS ML OLS MLconstant 4.87* 4.38* 5.33* 4.68* 5.77* 5.35*RPCI69 -0.31* -0.28* -0.44* -0.35* -0.50* -0.45*INV 0.20* 0.15* 0.12* 0.16* 0.18* 0.20*POP 0.37* 0.34* 0.15* 0.19* 0.04* 0.07*EDLOWEDMEDEDHIGHlambda 0.26* 0.80* 0.77*

convergence 1.1 0.9 1.7 1.2 2.0 1.7

R2 0.26 0.31 0.32 0.52 0.37 0.52

LMERR 4.24 594.89 2562.55LMLAG 6.94 411.04 1336.36

IN MIDWEST US

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Human capital in Indiana and Midwest

High,

2000

High,

2000

Low,

2000

Low,

2000

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MRW model with human capital

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

OLS ML OLS ML OLS MLconstant 5.55* 5.03* 6.09* 5.36* 6.30* 5.86*RPCI69 -0.42* -0.44* -0.56* -0.49* -0.62* -0.61*INV 0.09* 0.04* 0.05* 0.05* 0.10* 0.091*POP 0.23* 0.20* 0.07* 0.10* -0.03* -0.022EDLOW -0.16 -0.05 -0.10* -0.04 -0.01 0.02EDMED 0.07 0.10* 0.01 -0.01 -0.12* 0.02EDHIGH 0.09* 0.11* 0.17* 0.15* 0.24* 0.20*lambda 0.39* 0.75* 0.79*

convergence 1.6 1.7 2.3 1.9 2.7 2.7

R2 0.41 0.50 0.5 0.61 0.49 0.61

LMERR 0.01 25.99 2280.86LMLAG 10.63 154.73 1063.86

IN MIDWEST US

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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