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Diana De Alwis, & Ilan Noy. (2018). Sri Lankan Households a Decade after the Indian Ocean Tsunami. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 339–350). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: We estimate the causal effect of the Indian Ocean tsunami in Sri Lanka on household income and consumption eight years after the event, using a quasi-experimental method. A strong association between area-wide tsunami disaster shock and increases in household income and consumption in the long-term emerged from our empirical investigation. Deviating from the common observation on short-term impacts, these results are suggestive of an optimistic potential for some long-lasting potentially successful recovery scenarios. Still, Sri Lanka received a very large amount of external transfers post-tsunami, much larger than is typical for disaster events and one which may not be replicable in other cases. Our findings suggest a more nuanced picture with respect to household consumption impacts. We observe a reduction of food consumption and only find an increase in non-food consumption. The increase in non-food consumption is much smaller than the observed increase in income. We also find that households in high-income regions experienced much better recovery from the disaster. Keywords Sri Lanka, Tsunami, disaster, household survey, long-run impact
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Ilan Noy, Jacob Pastor Paz, Olga Filippova, & Ken Elwood. (2018). A Building Inventory for Seismic Policy in an Earthquake-Prone City. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 145–152). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: We describe the creation of a building inventory database that is created for Wellington, New Zealand's earthquake-prone capital city. This database aims to assist the generation of research on the risks, impacts, and viable solutions for reducing the seismic risk of existing multi-story concrete buildings in Wellington's Central Business District. The database includes structural, economic and market information on every building in the CDB. Its primary purpose is to inform a multi-disciplinary project whose aims are: (1) to provide best scientific knowledge about the expected seismic performance of concrete buildings; (2) to assess the impact of multiple building failures including the downstream consequences of associated cordoning; (3) to provide a path for seismic retrofitting that includes prioritization of retrofits; and (4) to inform the design of a regulatory structure that can facilitate the reduction of risk associated with earthquake vulnerable concrete buildings as described in aims (1)-(3).
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Jacob Pastor, Ilan Noy, & Isabelle Sin. (2018). Flood risk and flood insurance in New Zealand. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 381–399). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: The standard framework for undertaking a risk assessment of a natural hazard involves analyzing the interaction of three components: Hazard data (in the form of maps), the elements exposed to the hazard (exposure), and measures of these elements' vulnerability (understood as the susceptibility to harm or damage). In New Zealand, national flood risk remains unquantified due to the absence of national flood inundation hazard map coverage. In this paper, we develop a methodology that aims to fill this gap by estimating instead the likelihood of a flood insurance claim for a stock of residential buildings. We estimate a non-linear limited-dependent variable model and using a set of fragility functions (also known as damage curves), we calculate the expected monetary losses under plausible flood depth scenarios. The outcome of this research could inform insurers of their potential liabilities and threats to their financial sustainability in the face of flood and storms.
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