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Spatial, Cultural, and Ecological Autocorrelation in U.S. Regional Data

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  • E. Anthon Eff

Abstract

Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can be defined in many different dimensions. In a cross-section of U.S. regions, it can be defined using physical distance, cultural similarity, ecological similarity, or using frequency and intensity of interaction, such as migration or commuting relationships. Autocorrelation of regression residuals presents well-known problems in least-squares estimation, but autocorrelation also provides useful information for exploratory data analysis and model specification. The paper shows that autocorrelation is widespread in U.S. regional data.

Suggested Citation

  • E. Anthon Eff, 2004. "Spatial, Cultural, and Ecological Autocorrelation in U.S. Regional Data," Working Papers 200406, Middle Tennessee State University, Department of Economics and Finance.
  • Handle: RePEc:mts:wpaper:200406
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    File URL: http://capone.mtsu.edu/berc/working/autocorrelation%20in%20US%20regional%20data.pdf
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    1. E. Anthon Eff, 2004. "Spatial and Cultural Autocorrelation in International Datasets," Working Papers 200401, Middle Tennessee State University, Department of Economics and Finance.
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    Keywords

    Spatial Autocorrelation; Culture; Religion;

    JEL classification:

    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • Z10 - Other Special Topics - - Cultural Economics - - - General
    • Z12 - Other Special Topics - - Cultural Economics - - - Religion

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