We examine the role of business interruption (BI) insurance in business recovery following the Christchurch earthquake in 2011. First, we ask whether BI insurance increases the likelihood of business survival in the immediate (3-6 months) aftermath of a disaster. We find positive but statistically insignificant evidence that those firms that had incurred damage, but were covered by BI insurance, had higher likelihood of survival post-quake compared with those firms that did not have any insurance. For the medium-term (2-3 years) survival of firms, our results show a more explicit role for insurance. Firms with BI insurance experience increased productivity and improved performance following a catastrophe. Furthermore, we find that those organisations that receive prompt and full payments of their claims have a better recovery than those that had protracted or inadequate claims payments, but this difference between the two groups is not statistically significant. We find no statistically significant evidence that the latter group (inadequate payment) did any better than those organisations that had damage but no insurance coverage. In general, our analysis indicates the importance not only of adequate insurance coverage, but also of an insurance system that delivers prompt claim payments.
This is a post-peer-review, pre-copyedit version of an article published in 'The Geneva Papers on Risk and Insurance - Issues and Practice'. The final authenticated version is available online at: https://doi.org/10.1057/s41288-017-0067-y. The following terms of use apply: https://www.springer.com/gp/open-access/publication-policies/aam-terms-of-use.
This dissertation contains three essays on the impact of unexpected adverse events on student outcomes. All three attempt to identify causal inference using plausibly exogenous shocks and econometric tools, applied to rich administrative data. In Chapter 2, I present evidence of the causal effects of the 2011 Christchurch earthquake on tertiary enrolment and completion. Using the shock of the 2011 earthquake on high school students in the Canterbury region, I estimate the effect of the earthquake on a range of outcomes including tertiary enrolment, degree completion and wages. I find the earthquake causes a substantial increase in tertiary enrolment, particularly for low ability high school leavers from damaged schools. However, I find no evidence that low ability students induced by the earthquake complete a degree on time. In Chapter 3, I identify the impact of repeat disaster exposure on university performance, by comparing outcomes for students who experience their first earthquake while in university, to outcomes for students with prior earthquake exposure. Using a triple-differences estimation strategy with individual-by-year fixed effects, I identify a precise null effect, suggesting that previous experience of earthquakes is not predictive of response to an additional shock two years later. The final chapter investigates the impact of injuries sustained in university on academic performance and wages, using administrative data including no-fault insurance claims, emergency department attendance and hospital admissions, linked with tertiary enrolment. I find injuries, including minor injuries, have a negative effect on re-enrolment, degree completion and grades in university.
The Canterbury earthquake sequence (2010-2011) was the most devastating catastrophe in New Zealand‘s modern history. Fortunately, in 2011 New Zealand had a high insurance penetration ratio, with more than 95% of residences being insured for these earthquakes. This dissertation sheds light on the functions of disaster insurance schemes and their role in economic recovery post-earthquakes. The first chapter describes the demand and supply for earthquake insurance and provides insights about different public-private partnership earthquake insurance schemes around the world. In the second chapter, we concentrate on three public earthquake insurance schemes in California, Japan, and New Zealand. The chapter examines what would have been the outcome had the system of insurance in Christchurch been different in the aftermath of the Canterbury earthquake sequence (CES). We focus on the California Earthquake Authority insurance program, and the Japanese Earthquake Reinsurance scheme. Overall, the aggregate cost of the earthquake to the New Zealand public insurer (the Earthquake Commission) was USD 6.2 billion. If a similar-sized disaster event had occurred in Japan and California, homeowners would have received only around USD 1.6 billion and USD 0.7 billion from the Japanese and Californian schemes, respectively. We further describe the spatial and distributive aspects of these scenarios and discuss some of the policy questions that emerge from this comparison. The third chapter measures the longer-term effect of the CES on the local economy, using night-time light intensity measured from space, and focus on the role of insurance payments for damaged residential property during the local recovery process. Uniquely for this event, more than 95% of residential housing units were covered by insurance and almost all incurred some damage. However, insurance payments were staggered over 5 years, enabling us to identify their local impact. We find that night-time luminosity can capture the process of recovery; and that insurance payments contributed significantly to the process of local economic recovery after the earthquake. Yet, delayed payments were less affective in assisting recovery and cash settlement of claims were more effective than insurance-managed repairs. After the Christchurch earthquakes, the government declared about 8000 houses as Red Zoned, prohibiting further developments in these properties, and offering the owners to buy them out. The government provided two options for owners: the first was full payment for both land and dwelling at the 2007 property evaluation, the second was payment for land, and the rest to be paid by the owner‘s insurance. Most people chose the second option. Using data from LINZ combined with data from Stats NZ, the fourth chapter empirically investigates what led people to choose this second option, and how peer effect influenced the homeowners‘ choices. Due to climate change, public disclosure of coastal hazard information through maps and property reports have been used more frequently by local government. This is expected to raise awareness about disaster risks in local community and help potential property owners to make informed locational decision. However, media outlets and business sector argue that public hazard disclosure will cause a negative effect on property value. Despite this opposition, some district councils in New Zealand have attempted to implement improved disclosure. Kapiti Coast district in the Wellington region serves as a case study for this research. In the fifth chapter, we utilize the residential property sale data and coastal hazard maps from the local district council. This study employs a difference-in-difference hedonic property price approach to examine the effect of hazard disclosure on coastal property values. We also apply spatial hedonic regression methods, controlling for coastal amenities, as our robustness check. Our findings suggest that hazard designation has a statistically and economically insignificant impact on property values. Overall, the risk perception about coastal hazards should be more emphasized in communities.
The standard way in which disaster damages are measured involves examining separately the number of fatalities, of injuries, of people otherwise affected, and the financial damage that natural disasters cause. Here, we implement a novel way to aggregate these separate measures of disaster impact and apply it to two catastrophic events from 2011: the Christchurch (New Zealand) earthquakes and the Greater Bangkok (Thailand) flood. This new measure, which is similar to the World Health Organization's calculation of Disability Adjusted Life Years (DALYs) lost due to the burden of diseases and injuries, is described in detail in Noy [7]. It allows us to conclude that New Zealand lost 180 thousand lifeyears as a result of the 2011 events, and Thailand lost 2644 thousand lifeyears. In per capita terms, the loss is similar, with both countries losing about 15 days per person due to the 2011 catastrophic events in these two countries.
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