• Augusto Ricardo DELGADO NARRO Waseda University, Japan


The concept of Multidimensional Poverty traditionally was used for comparative analysis across regions or countries. This paper uses the concept of Multidimensional Poverty for each Peruvian region to analyzes spatial patterns, spatial autocorrelation, and identifies spatial spillovers in poverty. We find evidence of statistically significant spatial autocorrelation across regions; in other words, poverty has spatial effects. In more detail, we find that those spatial spillovers are originated in the error terms rather than the endogenous variable. Also, the covariates we use in our regressions are statistically significant and stable across the models.


[1] Akinyemi, F., and Bigirimana, F. 2012. A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of household living standard. Rwanda Journal 26: 3–22. DOI:
[2] Anselin, L. 1988. Spatial Econometrics: Methods and Models. Dordrecht: Kluwer Academic Publishers. DOI:
[3] Anselin, L. 2001. Spatial effects in econometric practice in environmental and resource economics. American Journal of Agricultural Economics 83: 705–710. DOI:
[4] Anselin, L. 2010. Thirty years of spatial econometrics. Papers in Regional Science 89: 3–25. DOI:
[5] Bigman, D., and Fofack, H. 2000. Geographical targeting for poverty alleviation: An introduction to the special issue. World Bank Economic Review 14: 129–145. DOI:
[6] Brunn, S., and Wheeler, J.O. 1971. Spatial Dimensions of Poverty in the United States. Geografiska Annaler 53: 6–15. DOI:
[7] Chen, X., et al. 2015. Spatial Distribution Patterns and Influencing Factors of Poverty - A Case Study on Key Country From National Contiguous Special Poverty-stricken Areas in China. Procedia Environmental Sciences 26: 82–90.DOI:
[8] Crandall, M., and Weber, B.A. 2004. Local Social and Economic Conditions, Spatial Concentrations of Poverty, and Poverty Dynamics. American Journal of Agricultural Economics 86: 1276–1281. DOI:
[9] Duflo, Esther. 2012. Women Empowerment and Economic Development.Journal of Economic Literature 50: 1051–1079.DOI:
[10] Gräb, J. 2009. Econometric Analysis in Poverty Research: With Case Studies from Developing Countries. Frankfurt Am Main: Peter Lang AG. DOI:
[11] Holt, J.B. 2007.The Topography of poverty in the United States: a spatial analysis using county-level data from the community health status indicators project. Preventing Chronic Disease 4(4): A111.
[12] LeSage, J.P. 2008. An introduction to spatial econometrics. Revue d’Economie Industrielle 123: 19–44. DOI :
[13] Odekon, M. 2015. Multidimensional Poverty Index. In The SAGE Encyclopedia of World Poverty, Second Edition ed., 1075-1076. Thousand Oaks, CA: SAGE Publications, Inc. DOI: 10.4135/9781483345727.n567
[14] Rupasingha, A., and Goetz, S.J. 2007. Social and political forces as determinants of poverty: A spatial analysis. Journal of Socio-Economics 36: 650–671. DOI:
[15] Sen, A. 1976. Poverty: an ordinal approach to measurement. Econometrica 44: 219-231. DOI:
[16] Tanaka, T., and Lee, J.J. 2019. Spatial analysis of poverty: Combining geospatial data and survey data to study regional inequality in Ghana. World Bank: 1-32.
[17] Torres, M.O., et al. 2011. Spatial patterns of rural poverty: an exploratory analysis in the São Francisco River Basin, Brazil. Nova Economia 21(1): 45-66. DOI:
How to Cite
DELGADO NARRO, Augusto Ricardo. SPATIAL ANALYSIS OF POVERTY: THE CASE OF PERU. Theoretical and Practical Research in the Economic Fields, [S.l.], v. 11, n. 2, p. 95-104, dec. 2020. ISSN 2068-7710. Available at: <>. Date accessed: 11 may 2021. doi: