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Economic vulnerability and poverty in Tajikistan

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  • Raghbendra Jha
  • Tu Dang
  • Yusuf Tashrifov

Abstract

We examine the profile of poverty and vulnerability in Tajikistan using household level panel data for 2004 and 2005. The drop in poverty was largely due to increase in remittances from workers working overseas. People are more likely to be poor if they live in a) rural areas, b) large households, c) households with a large proportion of children; or are pensioners or live in a household whose head is a pensioner. One half of the households observed to be non-poor are vulnerable to poverty. With expected utility approach, our analysis suggests that vulnerability associated with inequality is very large, whereas that from idiosyncratic risk is moderate. Aggregate shocks have been favorable and reduced vulnerability. We advance several policy recommendations.
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Suggested Citation

  • Raghbendra Jha & Tu Dang & Yusuf Tashrifov, 2010. "Economic vulnerability and poverty in Tajikistan," Economic Change and Restructuring, Springer, vol. 43(2), pages 95-112, May.
    • Handle: RePEc:kap:ecopln:v:43:y:2010:i:2:p:95-112
    DOI: 10.1007/s10644-009-9079-3
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    Cited by:

    1. Sunil Khosla & Pradyot Ranjan Jena, 2022. "Analyzing vulnerability to poverty and assessing the role of universal public works and food security programs to reduce it: Evidence from an eastern Indian state," Review of Development Economics, Wiley Blackwell, vol. 26(4), pages 2296-2316, November.
    2. Thang T. Vo, 2018. "Social capital and household vulnerability: New evidence from rural Vienam," WIDER Working Paper Series wp-2018-167, World Institute for Development Economic Research (UNU-WIDER).
    3. Artjoms Ivlevs, 2014. "Economic Insecurity in Transition: A Primary Commodities Perspective," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S1), pages 117-140, May.
    4. Ira N. Gang & Kseniia Gatskova & John Landon-Lane & Myeong-Su Yun, 2018. "Vulnerability to Poverty: Tajikistan During and After the Global Financial Crisis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 925-951, August.
    5. Kumo, Kazuhiro, 2015. "Research on Poverty in Transition Economies: A Meta-analysis on Changes in the Determinants of Poverty," RRC Working Paper Series 51, Russian Research Center, Institute of Economic Research, Hitotsubashi University.
    6. Tomoki Fujii, 2016. "Concepts and measurement of vulnerability to poverty and other issues: a review of literature," Chapters, in: Jacques Silber & Guanghua Wan (ed.), The Asian ‘Poverty Miracle’, chapter 3, pages 53-83, Edward Elgar Publishing.
    7. Di Yang & Weixin Luan & Jun Yang & Bing Xue & Xiaoling Zhang & Hui Wang & Feng Pian, 2022. "The contribution of data-driven poverty alleviation funds in achieving mid-21st-Century multidimensional poverty alleviation planning," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    8. Emiliano Magrini & Pierluigi Montalbano, 2012. "Trade openness and vulnerability to poverty: Vietnam in the long-run (1992-2008)," Working Paper Series 3512, Department of Economics, University of Sussex Business School.
    9. Thang Vo, 2018. "Social capital and household vulnerability: New evidence from rural Vietnam," WIDER Working Paper Series 167, World Institute for Development Economic Research (UNU-WIDER).
    10. Vo, Thang T. & Van, Pham Hoang, 2019. "Can health insurance reduce household vulnerability? Evidence from Viet Nam," World Development, Elsevier, vol. 124(C), pages 1-1.
    11. Vo, Thang T., 2018. "Household vulnerability as expected poverty in Vietnam," World Development Perspectives, Elsevier, vol. 10, pages 1-14.

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    More about this item

    Keywords

    Poverty; Vulnerability; Panel data; Covariate and idiosyncratic risks; C21; C23; C26; I32;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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