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Poverty Dynamics in Bhutan, 2017–2022 : Evidence from Synthetic Panels

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Listed:
  • Amendola,Nicola
  • Belotti,Federico
  • Alvin Etang Ndip
  • Mancini,Giulia
  • Vecchi,Giovanni

Abstract

This paper examines the dynamics of poverty in Bhutan between 2017 and 2022, utilizing cross-sectional data from the Bhutan Living Standards Surveys. The paper constructs synthetic panels and estimates poverty transition probabilities. Three main findings emerge. First, poverty turnover in Bhutan is low overall (not many people, as a share of the population, moved in and out of poverty during the period considered). Second, chronic poverty, defined as the probability of remaining poor in both years (2017 and 2022), was also low, both in absolute terms and compared to other countries for which similar estimates are available. The probability of being poor in both years is 6 percent of households in Bhutan, compared to over 15 percent in India and 17.5 percent in Pakistan. Third, upward poverty mobility (the probability of escaping poverty between 2017 and 2022) is 20 times higher than downward poverty mobility.

Suggested Citation

  • Amendola,Nicola & Belotti,Federico & Alvin Etang Ndip & Mancini,Giulia & Vecchi,Giovanni, 2025. "Poverty Dynamics in Bhutan, 2017–2022 : Evidence from Synthetic Panels," Policy Research Working Paper Series 11031, The World Bank.
    • Handle: RePEc:wbk:wbrwps:11031
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    References listed on IDEAS

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    1. Guell, Maia & Hu, Luojia, 2006. "Estimating the probability of leaving unemployment using uncompleted spells from repeated cross-section data," Journal of Econometrics, Elsevier, vol. 133(1), pages 307-341, July.
    2. Hai-Anh H. Dang & Peter F. Lanjouw & Umar Serajuddin, 2017. "Updating poverty estimates in the absence of regular and comparable consumption data: methods and illustration with reference to a middle-income country," Oxford Economic Papers, Oxford University Press, vol. 69(4), pages 939-962.
    3. Hai‐Anh H. Dang & Peter F. Lanjouw, 2023. "Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 599-622, June.
    4. Hai-Anh H. Dang & Peter F. Lanjouw, 2018. "Poverty Dynamics in India between 2004 and 2012: Insights from Longitudinal Analysis Using Synthetic Panel Data," Economic Development and Cultural Change, University of Chicago Press, vol. 67(1), pages 131-170.
    5. Deaton, A. & Zaidi, S., 1999. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," Papers 192, Princeton, Woodrow Wilson School - Development Studies.
    6. Nicolas Hérault & Stephen P. Jenkins, 2019. "How valid are synthetic panel estimates of poverty dynamics?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(1), pages 51-76, March.
    7. Angus Deaton & Salman Zaidi, 2002. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, April.
    8. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    9. Ravallion, Martin & Bidani, Benu, 1994. "How Robust Is a Poverty Profile?," The World Bank Economic Review, World Bank, vol. 8(1), pages 75-102, January.
    10. Dang, Hai-Anh & Lanjouw, Peter & Luoto, Jill & McKenzie, David, 2014. "Using repeated cross-sections to explore movements into and out of poverty," Journal of Development Economics, Elsevier, vol. 107(C), pages 112-128.
    11. David Garcés‐Urzainqui & Peter Lanjouw & Gerton Rongen, 2021. "Constructing synthetic panels for the purpose of studying poverty dynamics: A primer," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1803-1815, November.
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