Economics of disaster recovery and earthquake insurance: Five essays on New Zealand

<p>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.</p>

Economics of disaster recovery and earthquake insurance: Five essays on New Zealand

<p>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.</p>

Seismic risk management through insurance and its sensitivity to uncertainty in the hazard model

Acknowledging the devastating consequences of past earthquakes, current research efforts focus on the development of tools for assessing and controlling the risk and losses associated with future earthquakes, in addition to trying to minimize construction costs. Apart from providing a control of these levels, earthquake engineering can also provide solutions to manage the financial implications of the expected hazardous events. The first part of this article focuses on the management of the expected losses through the mechanism of transfer of the financial risk via earthquake insurance. Various insurance models are explained and applied in different case studies, and numerous analyses are performed across Europe, for a benchmark four-storey reinforced-concrete frame building. The results highlight significant variation in the premiums with seismicity, design practices and properties of the insurance model. It is crucial that any mitigation or transfer framework should use probabilistic methods to consider the uncertainties inherent in the hazard and structural response estimates. For example, different studies for the same region often indicate considerable differences in seismic hazard estimates. The uncertainty inherent in the hazard input model is transferred to and affects the results of the structural design and the performance assessment. Thus, the second part of the article investigates the impact of the epistemic uncertainty in the hazard model on the structural design and consequently the estimated future losses and risk levels, again for the benchmark building. First, a comparison is performed between the hazard data from two studies for different locations in Italy, in order to assess the possible range of variation in estimated hazard levels amongst different studies. The effects of these hazard variations on the seismic design and risk and loss metrics for the benchmark building are also investigated for these locations. Finally, a simplified approach for modelling hazard uncertainty is introduced and various sensitivity analyses are performed to investigate the effects of the hazard uncertainty across Europe. It is shown that hazard uncertainty can be of differing importance for the various involved stakeholders.

The Role of Earthquake Insurance in Earthquake Risk Reduction and Resilience Building

Resilience is defined as “The ability to prepare and plan for, absorb, recover from and more successfully adapt to adverse events” (US National Academies). Resilience has four pillars: • Anticipate: the ability to anticipate and reduce the impact of shocks through preparedness and planning, • Absorb the ability to absorb and cope with the impacts of shocks and stresses. • Adapt: the ability to change in response to multiple, long-term and future risks, and to learn and adjust after a shock materializes. • Transform: the ability to take deliberate steps to change the systems that create risk, vulnerability and or inequality. How does insurance intervene in building resilience? The outcome of insurance is to restore property and livelihoods in case of an adverse effect. It does that by providing a cash infusion into the socio-economic system of the affected communities immediately after the event. The cash is used to restore property and avoid interruption of commercial and industrial activity. Insurance also intervenes in terms of reducing impact of stresses (which are the more extensive types of risk) since it enables a system of “maintenance” by providing funds for recovery under minor but more frequent events. For most developing countries, governments have been the insurer of last resort when it comes to catastrophe risk (referred to as Cat Risk in the insurance industry). The reason is that level of cat insurance penetration in most developing countries is very low, sometimes lower than 1%. The assurance of government intervention coupled with the lack of effectiveness of the financial transaction associated with a traditional insurance policy negate any incentive for individuals to acquire a cat insurance policy. The Turkish Compulsory Insurance Program or TCIP is one of the early experiment to change that paradigm and to provide a meaningful role for cat insurance in emerging economies. After a slow start, TCIP has now developed the financial capacity and the spread of coverage to play a significant role both in the financing of risk but also in supporting earthquake risk reduction in Turkey. New cat insurance products based on parametric indexing have since emerged. These insurance products could further improve the efficiency of TCIP and other cat insurance pools by making them more attractive to individuals, thereby scaling up their contribution to building resilience.

Damage Assessment in Japan and Potential Use of New Technologies in Damage Assessment

Right after an earthquake, it is quite important to evaluate the damage level of the buildings in the affected area. In Japan, a rapid inspection is conducted to evaluate the risk of collapse due to an aftershock. If any damage is detected, it is required to conduct damage classification, which takes time but categorizes its damage into five damage categories. Japan has a standard for both rapid inspection and damage classification. They are briefed in this chapter. Similar to the damage classification, the loss of the house and home contents for the earthquake insurance. The method for earthquake insurance is also introduced. Since they are based on visual inspection, it is quite difficult to investigate the damage of the high-rise buildings and buildings covered by finishing. Recently, many kinds of research are conducted to use sensors for automatic and realtime damage classification. A structural health monitoring method with accelerometers based on the capacity spectrum method, which is currently installed into more than 40 buildings, is also introduced.

Probabilistic seismic risk assessment of India

This study presents a comprehensive open probabilistic seismic risk model for India. The proposed model comprises a nationwide residential and non-residential building exposure model, a selection of analytical seismic vulnerability functions tailored for Indian building classes, and the open implementation of an existing probabilistic seismic hazard model for India. The vulnerability of the building exposure is combined with the seismic hazard using the stochastic (Monte Carlo) event-based calculator of the OpenQuake engine to estimate probabilistic seismic risk metrics such as average annual economic losses and the exceedance probability curves at the national, state, district, and subdistrict levels. The risk model and the underlying datasets, along with the risk metrics calculated at different scales, are intended to be used as tools to quantitatively assess the earthquake risk across India and also compare with other countries to develop risk-informed building design guidelines, for more careful land-use planning, to optimize earthquake insurance pricing, and to enhance general earthquake risk awareness and preparedness.

On Modeling the Earthquake Insurance Data via a New Member of the T-X Family

Heavy-tailed distributions play an important role in modeling data in actuarial and financial sciences. In this article, a new method is suggested to define new distributions suitable for modeling data with a heavy right tail. The proposed method may be named as the Z-family of distributions. For illustrative purposes, a special submodel of the proposed family, called the Z-Weibull distribution, is considered in detail to model data with a heavy right tail. The method of maximum likelihood estimation is adopted to estimate the model parameters. A brief Monte Carlo simulation study for evaluating the maximum likelihood estimators is done. Furthermore, some actuarial measures such as value at risk and tail value at risk are calculated. A simulation study based on these actuarial measures is also done. An application of the Z-Weibull model to the earthquake insurance data is presented. Based on the analyses, we observed that the proposed distribution can be used quite effectively in modeling heavy-tailed data in insurance sciences and other related fields. Finally, Bayesian analysis and performance of Gibbs sampling for the earthquake data have also been carried out.