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Measuring Households' Vulnerability to Idiosyncratic and Covariate Shocks – the case of Bangladesh

Author

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  • Md. Shafiul Azam

    (Economics, School of Social Sciences, University of Manchester, UK)

  • Katsushi S. Imai

    (Economics, School of Social Sciences, University of Manchester (UK) and RIEB, Kobe University (Japan))

Abstract

The paper examines the level and sources of vulnerability in rural Bangladesh using a household survey. We use a simple two-level random intercept model to estimate expected mean and variance in consumption as well as to decompose the variance into idiosyncratic and covariate components. Our results indicate that both idiosyncratic and covariate shocks have considerable impact on household's vulnerability and idiosyncratic shocks seem to have greater impact on household's consumption vulnerability than the covariate shocks. Furthermore, idiosyncratic shocks appear to have a relatively higher impact on relatively well endowed (i.e. in terms of human capital, land holdings, activity status etc.), well off households and covariate shocks seem to have a relatively higher impact on poorer, less educated, household's vulnerability. Our results also reveal that rural vulnerability in Bangladesh is mainly poverty induced rather than risk induced. Around 78 per cent all who are vulnerable is accounted for by low expected mean consumption and only 22 per cent of them are due to high consumption volatility. Overall vulnerability in rural areas is estimated to be 50 per cent. The categorization of poverty into transient and chronic poverty is even more insightful. The study finds that those without education or agricultural households are likely to be the most vulnerable. The geographical diversity of vulnerability is considerable. It is suggested that ex ante measures to prevent households from becoming poor as well as ex post measures to alleviate those already in poverty should be combined.

Suggested Citation

  • Md. Shafiul Azam & Katsushi S. Imai, 2012. "Measuring Households' Vulnerability to Idiosyncratic and Covariate Shocks – the case of Bangladesh," Discussion Paper Series DP2012-02, Research Institute for Economics & Business Administration, Kobe University.
  • Handle: RePEc:kob:dpaper:dp2012-02
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Anh Thu Quang Pham & Pundarik Mukhopadhaya & Ha Vu, 2021. "Estimating poverty and vulnerability to monetary and non-monetary poverty: the case of Vietnam," Empirical Economics, Springer, vol. 61(6), pages 3125-3177, December.
    3. Azomahou T.T. & Yitbarek E., 2015. "Poverty persistence and informal risk management: Micro evidence from urban Ethiopia," MERIT Working Papers 2015-006, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    4. Murata, Akira & Miyazaki, Suguru, 2014. "Ex-post Risk Management Among Rural Filipino Farm Households," Working Papers 67, JICA Research Institute.
    5. Peter Nwachukwu Mba & Emmanuel O. Nwosu & Anthony Orji, 2021. "Effects of Exposure to Risks on Household Vulnerability in Developing Countries: A New Evidence From Urban and Rural Areas of Nigeria," SAGE Open, , vol. 11(1), pages 21582440211, March.
    6. Sweta Sen & Narayan Chandra Nayak & William Kumar Mohanty, 2023. "Impact of tropical cyclones on sustainable development through loops and cycles: evidence from select developing countries of Asia," Empirical Economics, Springer, vol. 65(5), pages 2467-2498, November.
    7. Azeem, Muhammad Masood & Mugera, Amin W. & Schilizzi, Steven, 2016. "Poverty and vulnerability in the Punjab, Pakistan: A multilevel analysis," Journal of Asian Economics, Elsevier, vol. 44(C), pages 57-72.
    8. Sayema Haque Bidisha & Tanveer Mahmood & Md. Biplob Hossain, 2021. "Assessing Food Poverty, Vulnerability and Food Consumption Inequality in the Context of COVID-19: A Case of Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 187-210, May.
    9. Khac Linh Bui & Thanh Hang Bui, 2022. "Does Rural Credit Mediate Vulnerability Under Idiosyncratic and Covariate Shocks? Empirical Evidence from Vietnam Using a Multilevel Model," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(1), pages 172-224, February.
    10. Rashida Haq, 2012. "Shocks as a Source of Vulnerability: An Empirical Investigation from Pakistan," Poverty and Social Dynamics Paper Series 2012:06, Pakistan Institute of Development Economics.
    11. Rashida Haq, 2015. "Shocks as a Source of Vulnerability: An Empirical Investigation from Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(3), pages 245-272.
    12. Liebenehm, Sabine, 2018. "Temporal Stability of Risk Attitudes and the Impact of Adverse Shocks—A Panel Data Analysis from Thailand and Vietnam," World Development, Elsevier, vol. 102(C), pages 262-274.
    13. GRIES, Thomas & PALNAU, Irene, 2016. "Distress Beyond Poverty: Spatial Patterns And Geographic Aspects Of Vulnerability In Brazil," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 16(2), pages 53-70.

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    More about this item

    Keywords

    Poverty; Vulnerability; Risks; Poverty dynamics; Bangladesh;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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