Does Economic Geography Matter for Pakistan? A Spatial Exploratory Analysis of Income and Education Inequalities.

Sofia Ahmed

Abstract


Generally, econometric studies on socio-economic inequalities
consider regions as independent entities, ignoring the likely
possibility of spatial interaction between them. This interaction may
cause spatial dependency or clustering, which is referred to as spatial
autocorrelation. This paper analyses for the first time, the spatial
clustering of income, income inequality, education, human development,
and growth by employing spatial exploratory data analysis (ESDA)
techniques to data on 98 Pakistani districts. By detecting outliers and
clusters, ESDA allows policy makers to focus on the geography of
socio-economic regional characteristics. Global and local measures of
spatial autocorrelation have been computed using the Moran‘s I and the
Geary‘s C index to obtain estimates of the spatial autocorrelation of
spatial disparities across districts. The overall finding is that the
distribution of district wise income inequality, income, education
attainment, growth, and development levels, exhibits a significant
tendency for socio-economic inequalities and human development levels to
cluster in Pakistan (i.e. the presence of spatial autocorrelation is
confirmed). Keywords: Pakistan, Spatial Effects, Spatial Exploratory
Analysis, Spatial Disparities, Income Inequality, Education Inequality,
Spatial Autocorrelation

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DOI: https://doi.org/10.30541/v50i4IIpp.929-953

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