This study followed two similarly affected, but socio-economically disparate suburbs as residents responded to and attempted to recover from the devastating 6.3 magnitude earthquake that struck Christchurch, New Zealand, on February 22, 2011. More specifically, it focuses on the role of local churches, community-based organisations (CBOs) and non-governmental organisations (NGOs), here referred to broadly as civil society, in meeting the immediate needs of local residents and assisting with the longer-term recovery of each neighbourhood. Despite considerable socioeconomic differences between the two neighbourhoods, civil society in both suburbs has been vital in addressing the needs of locals in the short and long term following the earthquake. Institutions were able to utilise local knowledge of both residents and the extent of damage in the area to a) provide a swifter local response than government or civil defence and then help direct the relief these agencies provided locally; b) set up central points for distribution of supplies and information where locals would naturally gather; c) take action on what were perceived to be unmet needs; and d) act as a way of bridging locals to a variety of material, informational, and emotional resources. However the findings also support literature which indicates that other factors are also important in understanding neighbourhood recovery and the role of civil society, including: local leadership; a shared, place-based identity; the type and form of civil society organizations; social capital; and neighbourhood- and household-level indicators of relative vulnerability and inequality. The intertwining of these various factors seems to influence how these neighbourhoods have coped with and taken steps in recovering from this disaster. It is recommended that future research be directed at developing a better understanding of how this occurs. It is suggested that a model similar to Yasui’s (2007) Community Vulnerability and Capacity model be developed as a useful way to approach future research in this area.
The lived reality of the 2010-2011 Canterbury earthquakes and its implications for the Waimakariri District, a small but rapidly growing district (third tier of government in New Zealand) north of Christchurch, can illustrate how community well-being, community resilience, and community capitals interrelate in practice generating paradoxical results out of what can otherwise be conceived as a textbook ‘best practice’ case of earthquake recovery. The Waimakariri District Council’s integrated community based recovery framework designed and implemented post-earthquakes in the District was built upon strong political, social, and moral capital elements such as: inter-institutional integration and communication, participation, local knowledge, and social justice. This approach enabled very positive community outputs such as artistic community interventions of the urban environment and communal food forests amongst others. Yet, interests responding to broader economic and political processes (continuous central government interventions, insurance and reinsurance processes, changing socio-cultural patterns) produced a significant loss of community capitals (E.g.: social fragmentation, participation exhaustion, economic leakage, etc.) which simultaneously, despite local Council and community efforts, hindered community well-being in the long term. The story of the Waimakariri District helps understand how resilience governance operates in practice where multi-scalar, non-linear, paradoxical, dynamic, and uncertain outcomes appear to be the norm that underpins the construction of equitable, transformative, and sustainable pathways towards the future.
There are many things that organisations of any size can do to prepare for a disaster or crisis. Traditionally, the advice given to business has focused on identifying risks, reducing their likely occurrence, and planning in advance how to respond. More recently, there is growing interest in the broader concept of organisational resilience which includes planning for crisis but also considers traits that lead to organisational adaptability and ability to thrive despite adverse circumstances. In this paper we examine the policy frameworks1 within New Zealand that influence the resilience of small and medium sized businesses (SMEs). The first part of the paper focuses on the New Zealand context, including the prevailing political and economic ideologies, the general nature of New Zealand SMEs and the nature of New Zealand’s hazard environment. The paper then goes on to outline the key policy frameworks in place relevant to SMEs and hazards. The final part of the paper examines the way the preexisting policy environment influenced the response of SMEs and Government following the Canterbury earthquakes.
In September 2010 and February 2011, the Canterbury region experienced devastating earthquakes with an estimated economic cost of over NZ$40 billion (Parker and Steenkamp, 2012; Timar et al., 2014; Potter et al., 2015). The insurance market played an important role in rebuilding the Canterbury region after the earthquakes. Homeowners, insurance and reinsurance markets and New Zealand government agencies faced a difficult task to manage the rebuild process. From an empirical and theoretic research viewpoint, the Christchurch disaster calls for an assessment of how the insurance market deals with such disasters in the future. Previous studies have investigated market responses to losses in global catastrophes by focusing on the insurance supply-side. This study investigates both demand-side and supply-side insurance market responses to the Christchurch earthquakes. Despite the fact that New Zealand is prone to seismic activities, there are scant previous studies in the area of earthquake insurance. This study does offer a unique opportunity to examine and document the New Zealand insurance market response to catastrophe risk, providing results critical for understanding market responses after major loss events in general. A review of previous studies shows higher premiums suppress demand, but how higher premiums and a higher probability of risk affect demand is still largely unknown. According to previous studies, the supply of disaster coverage is curtailed unless the market is subsidised, however, there is still unsettled discussion on why demand decreases with time from the previous disaster even when the supply of coverage is subsidised by the government. Natural disaster risks pose a set of challenges for insurance market players because of substantial ambiguity associated with the probability of such events occurring and high spatial correlation of catastrophe losses. Private insurance market inefficiencies due to high premiums and spatially concentrated risks calls for government intervention in the provision of natural disaster insurance to avert situations of noninsurance and underinsurance. Political economy considerations make it more likely for government support to be called for if many people are uninsured than if few people are uninsured. However, emergency assistance for property owners after catastrophe events can encourage most property owners to not buy insurance against natural disaster and develop adverse selection behaviour, generating larger future risks for homeowners and governments. On the demand-side, this study has developed an intertemporal model to examine how demand for insurance changes post-catastrophe, and how to model it theoretically. In this intertemporal model, insurance can be sought in two sequential periods of time, and at the second period, it is known whether or not a loss event happened in period one. The results show that period one demand for insurance increases relative to the standard single period model when the second period is taken into consideration, period two insurance demand is higher post-loss, higher than both the period one demand and the period two demand without a period one loss. To investigate policyholders experience from the demand-side perspective, a total of 1600 survey questionnaires were administered, and responses from 254 participants received representing a 16 percent response rate. Survey data was gathered from four institutions in Canterbury and is probably not representative of the entire population. The results of the survey show that the change from full replacement value policy to nominated replacement value policy is a key determinant of the direction of change in the level of insurance coverage after the earthquakes. The earthquakes also highlighted the plight of those who were underinsured, prompting policyholders to update their insurance coverage to reflect the estimated cost of re-building their property. The survey has added further evidence to the existing literature, such as those who have had a recent experience with disaster loss report increased risk perception if a similar event happens in future with females reporting a higher risk perception than males. Of the demographic variables, only gender has a relationship with changes in household cover. On the supply-side, this study has built a risk-based pricing model suitable to generate a competitive premium rate for natural disaster insurance cover. Using illustrative data from the Christchurch Red-zone suburbs, the model generates competitive premium rates for catastrophe risk. When the proposed model incorporates the new RMS high-definition New Zealand Earthquake Model, for example, insurers can find the model useful to identify losses at a granular level so as to calculate the competitive premium. This study observes that the key to the success of the New Zealand dual insurance system despite the high prevalence of catastrophe losses are; firstly the EQC’s flat-rate pricing structure keeps private insurance premiums affordable and very high nationwide homeowner take-up rates of natural disaster insurance. Secondly, private insurers and the EQC have an elaborate reinsurance arrangement in place. By efficiently transferring risk to the reinsurer, the cost of writing primary insurance is considerably reduced ultimately expanding primary insurance capacity and supply of insurance coverage.
