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Multidimensional Poverty in Bhutan: Estimates and Policy Implications

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  • Maria Emma Santos, Karma Ura

Abstract

This paper estimates multidimensional poverty in Bhutan applying a recently developed methodology by Alkire and Foster (2007) using the 2007 Bhutan Living Standard Survey data. Five dimensions are considered for estimations in both rural and urban areas (income, education, room availability, access to electricity and access to drinking water) and two additional dimensions are considered for estimates in rural areas only (access to roads and land ownership). Also, two alternative weighting systems are used: a baseline using equal weights for every dimension and another one using weights derived from the Gross National Happiness Survey (GNHS). Estimates are decomposed into rural and urban areas, by dimension and between districts. It is found that multidimensional poverty is mainly a rural phenomenon, although urban areas present non-depreciable level of deprivation in room availability and education. Within rural areas, when equal weights are used, deprivation comes at a second place, and deprivation in water at the last one. When GNHS weights are used, income deprivation has the highest contribution, followed by deprivation education, access to roads, room, electricity, land and, finally, water. Districts are ranked by their multidimensional poverty estimate and rankings are found to be robust for a wide range of poverty cutoffs. Then, the methodology is suggested as a potential formula for national poverty measurement as well as a tool for budget allocation among districts and, within them, among dimensions.

Suggested Citation

  • Maria Emma Santos, Karma Ura, 2008. "Multidimensional Poverty in Bhutan: Estimates and Policy Implications," OPHI Working Papers 14, Queen Elizabeth House, University of Oxford.
  • Handle: RePEc:qeh:ophiwp:ophiwp014
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    File URL: https://ophi.org.uk/working-paper-number-14/
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    References listed on IDEAS

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    1. Sabina Alkire, 2007. "The Missing Dimensions of Poverty Data: Introduction to the Special Issue," Oxford Development Studies, Taylor & Francis Journals, vol. 35(4), pages 347-359.
    2. Caterina Ruggeri Laderchi & Ruhi Saith & Frances Stewart, 2003. "Does it Matter that we do not Agree on the Definition of Poverty? A Comparison of Four Approaches," Oxford Development Studies, Taylor & Francis Journals, vol. 31(3), pages 243-274.
    3. François Bourguignon & Satya R. Chakravarty, 2019. "The Measurement of Multidimensional Poverty," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 83-107, Springer.
    4. Sabina Alkire, 2007. "The Missing Dimensions of Poverty Data: An Introduction," OPHI Working Papers 0, Queen Elizabeth House, University of Oxford.
    5. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    6. Blakorby, Charles & Donaldson, David, 1980. "Ethical Indices for the Measurement of Poverty," Econometrica, Econometric Society, vol. 48(4), pages 1053-1060, May.
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    2. Dika, Galgalo & Tolossa, Degefa & Eyana, Shiferaw Muleta, 2021. "Multidimensional poverty of pastoralists and implications for policy in Boorana rangeland system, Southern Ethiopia," World Development Perspectives, Elsevier, vol. 21(C).
    3. Olagunju, K.O. & Ogunniyi, A. & Olufadewa, M.S., 2018. "Spatial Analysis of Structural Determinants of Child Poverty Incidence in Nigeria," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275996, International Association of Agricultural Economists.
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    5. Builes-Jaramillo, Alejandro & Lotero, Laura, 2020. "Closeness matters. Spatial autocorrelation and relationship between socioeconomic indices and distance to departmental Colombian capitals," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

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