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Vulnerability and Responses to Risk in Rural India

  • Raghbendra Jha

    ()

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

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.

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File URL: https://crawford.anu.edu.au/acde/asarc/pdf/papers/2012/WP2012_05.pdf
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Paper provided by The Australian National University, Australia South Asia Research Centre in its series ASARC Working Papers with number 2012-05.

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Length: 19
Date of creation: 2012
Date of revision:
Handle: RePEc:pas:asarcc:2012-05
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  1. 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.
  2. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LP, vol. 3(3), pages 278-294, September.
  3. Alwang, Jeffrey & Siegel, Paul B. & Jorgensen, Steen L., 2001. "Vulnerability : a view from different disciplines," Social Protection Discussion Papers 23304, The World Bank.
  4. Ligon, Ethan & Schechter, Laura, 2002. "Measuring Vulnerability," 2002 Annual meeting, July 28-31, Long Beach, CA 19899, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  5. 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.
  6. Canagarajah, P. Sudharshan & Siegel, Paul B. & Heitzmann, Karin, 2002. "Guidelines for assessing the sources of risk and vulnerability," Social Protection Discussion Papers 31372, The World Bank.
  7. Raghbendra Jha & Katsushi S Imai & Raghav Gaiha, 2009. "Poverty, Undernutrition and Vulnerability in Rural India: Public Works versus Food Subsidy," Working Papers id:1907, eSocialSciences.
  8. Hoddinott, John & Quisumbing, Agnes, 2003. "Methods for microeconometric risk and vulnerability assessments," Social Protection Discussion Papers 29138, The World Bank.
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