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]

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Economic Growth and Income Inequality in Indiana Counties

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Economic growth and income inequality in indiana counties

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

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

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 maps

Real per capita income – maps

1980

1970

2000

1990


Real per capita income space

Real per capita income – space

1980

1970

2000

1990


Real per capita income space time

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 outliers

Real per capita income – outliers

1980

1970

2000

1990


Real per capita income inequality

Real per capita income – inequality

  • The Gini coefficient measures income inequality between counties


Real per capita income dynamics

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

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


Midwest 2003

Midwest, 2003


A simple model

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

Solow model

  • Standard neoclassical model

    • correcting for growth of capital and labor

    • note: lacking data for investments


Human capital in indiana and midwest

Human capital in Indiana and Midwest

Low,

2000

Low,

2000

High,

2000

High,

2000


Mrw model with human capital

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

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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