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

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E. Anthon Eff

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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.

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Paper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number 200406.

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Date of creation: Sep 2004
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Handle: RePEc:mts:wpaper:200406

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Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html
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Related research
Keywords: Spatial Autocorrelation; Culture; Religion;

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Find related papers by JEL classification:
R15 - Urban, Rural, and Regional 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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  1. E. Anthon Eff, 2004. "Spatial and Cultural Autocorrelation in International Datasets," Working Papers 200401, Middle Tennessee State University, Department of Economics and Finance. [Downloadable!]
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