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Is regional poverty converging across Indonesian districts? A distribution dynamics and spatial econometric approach

Abstract

Using a novel district-level dataset of three poverty indicators and related determinants, this paper attempts to examine the convergence process in terms of poverty reduction across 514 districts over the 2010–2018 period. The main findings of this study are fourfold. First, results of both distributional convergence and spatial convergence analyses suggest that poverty convergence takes place in all three poverty indicators. Second, there is an overall clustering pattern and a persistent West–East polarization in terms of poverty indicators. In addition, decreasing patterns of poverty inequality are significantly associated with increasing patterns of spatial dependence. Third, spatial effects are significantly low in accelerating convergence rates in poverty reduction. However, substantial differences in the speed of convergence among three poverty indicators is apparent. Under specifications of the Spatial Durbin Model as the best model, convergence regression in poverty rate model appears to generate the longest half-life for the catching-up process in poverty reduction across districts. Fourth, regression results from the spatial convergence framework suggest that mean years of schooling tend to contribute the largest effect to the catching-up process in poverty reduction.

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Correspondence to Ragdad Cani Miranti.

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Appendix

Appendix

See Table 7.

Table 7 Districts with extreme value of observations on selected variables, 2010–2018

Nduga is one of the underdeveloped districts in Papua Province which still share the the lowest extreme value (less than 1 year for mean years of schooling) for several respective years. It implies that there were still school-aged population who barely enrolled to basic (elementary) school during 2010–2014 or other possibility, they dropped out or quitted within less than a year. This fact is also supported by the publication of Welfare Statistics of Papua Province 2014 published by BPS-Papua Province, reporting that at least 82.77% of population aged 10 and over has not or never enrolled on schooling in Nduga. The data of education variable for all districts can be downloaded through https://ipm.bps.go.id/. In terms of negative growth, the growth of GRDP in Mimika (in Papua Province) and Kota Bontang (in East Kalimantan) in this paper use the GRDP growth by including mining sector.

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Miranti, R.C. Is regional poverty converging across Indonesian districts? A distribution dynamics and spatial econometric approach. Asia-Pac J Reg Sci 5, 851–883 (2021). https://doi.org/10.1007/s41685-021-00199-3

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  • DOI: https://doi.org/10.1007/s41685-021-00199-3

Keywords

  • Poverty
  • Convergence
  • Distribution dynamics
  • Spatial econometrics
  • Indonesia

JEL Classifications

  • I32
  • O10
  • O38