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Consequences of Financial Vulnerability and Insurance Loading for the Affordability of Earthquake Insurance Systems: Evidence from Iran

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Abstract

Many governments provide financial assistance for reconstruction of damaged housing units after a disaster in order to prevent vulnerable households from falling into poverty traps or entering low growth cycles. To lessen these risks and the overall financial burden on the public sector after extreme events, private insurance schemes provide one viable solution. In this paper, the possible effects of such solutions are assessed for District 1 of Shiraz, Iran, based on recent probabilistic earthquake risk modelling. The work explicitly focuses on the financial vulnerability of different household groups as well as possible increases in premiums due to uncertainties in the underlying risk model through the use of loading factors. The results are compared with current non-probabilistic-based premiums that are used by most insurance companies in Iran, and recommendations are given as to which schemes may fit best or could be affordable for society to manage future earthquake risks.

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Notes

  1. Munich Re (2013).

  2. Government of Haiti (2010).

  3. Grossi and Kunreuther (2005).

  4. Mechler (2004).

  5. Hochrainer (2006).

  6. Lal et al. (2012).

  7. Kull et al. (2013).

  8. Tsubokawa (2004).

  9. Steven (1992).

  10. Garamendi (2003).

  11. Bommer et al. (2002).

  12. World Bank (2007).

  13. World Bank (2014).

  14. For example, see Walker (2000); Amendola et al. (2000); Scawthorn et al. (2003); Petseti and Nektarios (2012); Zhi and Ting (2011); Xue et al. (2010); Chena et al. (2011); UNISDR (2013).

  15. Ghafory-Ashtiany (2006).

  16. Pakdel-Lahiji et al. (2014).

  17. Central Insurance of Iran (2013), Annual Report.

  18. Gollier et al. (2013).

  19. Cavagnaro et al. (2013).

  20. Sutter and Poitras (2010).

  21. Walker (2000).

  22. UNISDR (2013).

  23. IPCC (2012).

  24. Ghafory-Ashtiany and Naser-Assadi (2011).

  25. Swiss Re (1996).

  26. Andersen (2001).

  27. Swiss Re (1997).

  28. Froot (1999).

  29. Sadeghi et al. (2013).

  30. Froot (2001).

  31. Iran Standard 2800 (2005).

  32. Woo (2002).

  33. Sadeghi (2013).

  34. Sadeghi et al. (2014).

  35. Grossi et al. (2005).

  36. Hessami et al. (2003).

  37. Ambraseys et al. (2005), Boore et al. (1993) and Ghodrati Amiri et al. (2007).

  38. Douglas (2006).

  39. IIEES (2013).

  40. Gutenberg and Richter (1956).

  41. JICA (2000).

  42. HAZUS (2003).

  43. Hochrainer-Stigler et al. (2014).

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Acknowledgements

This paper represents the partial results of work conducted during the Young Scientist Summer Program YSSP (2013) at the International Institute of Applied System Analysis (IIASA). The authors would like to thank Dr Joanne Linnerooth-Bayer, Professor Georg Pflug and Dr Reinhard Mechler for their support and guidance for this study. The authors would like to express their appreciation to the Municipality of Shiraz (Mr Pakfetrat and Mr Amini) for providing the city’s inventory database.

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Appendix

Appendix

Table A1

Table A1 Earthquake insurance index to compensate losses (per 1,000 value of coverage)

Table A2

Table A2 Insurance loading factors for different risk layers based and extended on Pollner (2001); Mechler (2004); Hochrainer (2006)

Table A3

Table A3 Premiums as a percentage of average annual income of household for the public–private insurance system (without loading factor)

Table A4

Table A4 Premiums based on percentage of average annual income of each household for the second suggested insurance system (without loading factor)

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Pakdel-Lahiji, N., Hochrainer-Stigler, S., Ghafory-Ashtiany, M. et al. Consequences of Financial Vulnerability and Insurance Loading for the Affordability of Earthquake Insurance Systems: Evidence from Iran. Geneva Pap Risk Insur Issues Pract 40, 295–315 (2015). https://doi.org/10.1057/gpp.2014.35

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