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Vulnerability and Responses to Risk in Rural India

Author

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  • Raghbendra Jha

    ()

  • Woojin Kang
  • Hari K. Nagarajan
  • Kailash C. Pradhan

Abstract

Using Vulnerability as Expected Utility (VEU) analysis that permits the decomposition of household vulnerability into its components on a unique data set this paper demonstrates that in rural India household vulnerability is most explained by poverty and idiosyncratic components. So far as risk coping strategies go households rely heavily on informal instruments such as their own saving, transfers or capital depletion. However, they also try to cope with covariate risks by participating in government programmes. Further, household consumption is highly covariate with income. This implies that existing informal insurance instruments are not sufficient to protect household consumption against income shocks. Government sponsored coping strategies reduce the idiosyncratic and risk component of vulnerability. Hence, an important policy implication of our analysis is that the government should provide readily accessible and well targeted public safety nets. The existing informal strategy is not very effective as a consumption insurance mechanism. Although the government coping programme is found to reduce vulnerability access to such programmes is constrained. Expansion of government sponsored coping programmes is likely to protect households effectively from negative shocks.

Suggested Citation

  • Raghbendra Jha & Woojin Kang & Hari K. Nagarajan & Kailash C. Pradhan, 2012. "Vulnerability and Responses to Risk in Rural India," ASARC Working Papers 2012-05, The Australian National University, Australia South Asia Research Centre.
  • Handle: RePEc:pas:asarcc:2012-05
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    File URL: https://crawford.anu.edu.au/acde/asarc/pdf/papers/2012/WP2012_05.pdf
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    References listed on IDEAS

    as
    1. Raghbendra Jha & Katsushi S. Imai & Raghav Gaiha, 2008. "Poverty, Undernutrition and Vulnerability in Rural India: Public Works versus Food Subsidy," ASARC Working Papers 2008-08, The Australian National University, Australia South Asia Research Centre.
    2. Ethan Ligon & Laura Schechter, 2003. "Measuring Vulnerability," Economic Journal, Royal Economic Society, vol. 113(486), pages 95-102, March.
    3. Alwang, Jeffrey & Siegel, Paul B. & Jorgensen, Steen L., 2001. "Vulnerability : a view from different disciplines," Social Protection and Labor Policy and Technical Notes 23304, The World Bank.
    4. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    5. Cappellari, Lorenzo & Jenkins, Stephen P., 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LP, vol. 0(Number 3), pages 1-17.
    6. Bali Swain, Ranjula & Floro, Maria, 2010. "Reducing Vulnerability through Microfinance: Evidence from Indian Self Help Group Program," Working Paper Series 2010:23, Uppsala University, Department of Economics.
    7. Hoddinott, John & Quisumbing, Agnes, 2003. "Methods for microeconometric risk and vulnerability assessments," Social Protection and Labor Policy and Technical Notes 29138, The World Bank.
    8. Canagarajah, P. Sudharshan & Siegel, Paul B. & Heitzmann, Karin, 2002. "Guidelines for assessing the sources of risk and vulnerability," Social Protection and Labor Policy and Technical Notes 31372, The World Bank.
    9. repec:ags:stataj:116022 is not listed on IDEAS
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    Cited by:

    1. Raghbendra Jha & Hari K. Nagarajan & Woojin Kang & Kailash C. Pradhan, 2014. "Panchayats and Household Vulnerability in Rural India," ASARC Working Papers 2014-08, The Australian National University, Australia South Asia Research Centre.
    2. Murata, Akira & Miyazaki, Suguru, 2014. "Ex-post Risk Management Among Rural Filipino Farm Households," Working Papers 67, JICA Research Institute.

    More about this item

    Keywords

    Vulnerability; Poverty; Covariate and Idiosyncratic shocks; REDS data; India;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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