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Geohazards in Social Systems: An Insurance Matrix Approach

In: Modeling Spatial and Economic Impacts of Disasters

Author

Listed:
  • Sam Cole

    (University at Buffalo)

Abstract

The principle goal of the chapter is to explore ways of solving social accounting matrices (SAMs) that may be useful for estimating the impact of natural and other disasters and the effectiveness of recovery programs. To this end my chapter introduces a model to assess the way in which disasters affect social actors and propagate through society. It adopts findings from disaster research and anthropology, to embody social transactions in an insurance accounting matrix. This assumes that the predisaster secular and spatial structure of any economy is a reflection, at least in part, of the various uncertainties associated with regular production, transportation, financing, daily survival, and so on. These may result in formal expenditures — as with insurance or stocks, or informal effort — such as maintaining social networks. Each measures the opportunity cost against other income. With a major disturbance, the proportion of failed transactions is increased beyond the capability of these afforded precautions to cushion the impacts, resulting in a “disaster” or even a “catastrophe”.

Suggested Citation

  • Sam Cole, 2004. "Geohazards in Social Systems: An Insurance Matrix Approach," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 6, pages 103-118, Springer.
    • Handle: RePEc:spr:adspcp:978-3-540-24787-6_6
    DOI: 10.1007/978-3-540-24787-6_6
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    Cited by:

    1. Albert E. Steenge & Marija Boèkarjova, 2005. "Thinking about Big Floods in a Small Country - Dutch Modelling Exercises," ERSA conference papers ersa05p314, European Regional Science Association.
    2. Asjad Naqvi & Franziska Gaupp & Stefan Hochrainer-Stigler, 2020. "The risk and consequences of multiple breadbasket failures: an integrated copula and multilayer agent-based modeling approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 727-754, September.
    3. Iman Rahimi Aloughareh & Mohsen Ghafory Ashtiany & Kiarash Nasserasadi, 2016. "An Integrated Methodology For Regional Macroeconomic Loss Estimation Of Earthquake: A Case Study Of Tehran," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(04), pages 1-24, September.
    4. Irfan Ahmed & Claudio Socci & Rosita Pretaroli & Francesca Severini & Stefano Deriu, 2022. "Socioeconomic spillovers of the 2016–2017 Italian earthquakes: a bi-regional inoperability model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 426-453, January.
    5. Naqvi, Asjad, 2017. "Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters," World Development, Elsevier, vol. 99(C), pages 395-418.
    6. Okuyama, Yasuhide & Sahin, Sebnem, 2009. "Impact estimation of disasters : a global aggregate for 1960 to 2007," Policy Research Working Paper Series 4963, The World Bank.

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