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This study analyses how past tsunami-memories affect cheating in Sri Lanka. Subjects are assigned to a treatment (control) group in which they watch a video about the calamity before (after) participating in a trust game. Cheating is elicited by asking trustors how much they need to receive not to feel cheated and trustees how much they need to return not to make the trustor feel cheated. Finally, participants report whether the video mostly reminded them about solidarity, looting or the calamity. Trustors show lower cheating standards and trustees more often satisfy the trustors' cheating notion if they mostly recall solidarity. [ABSTRACT FROM AUTHOR]

Based on the statistical data of rainstorm-induced catastrophe about Shenzhen city during 1980–2014, this paper constructs a calculation model of disaster magnitude, which includes three influence factors: death toll, direct economic loss and disaster affected population. At the same time, the relationship between the disaster magnitude and the temporal, spatial and cause of the rainstorm-induced catastrophe about Shenzhen city is analysed, The results show that (1) The classification of catastrophe risk is carried out by the result of the disaster magnitude model. (2) The region where the disaster occurs frequently and seriously is located in the Midwest, and the disaster occurs infrequently and lightly is located in the south-east. (3) The rainstorm-induced catastrophe about Shenzhen City is mostly caused by persistent short-time heavy rainfall. While it occurs most frequently in July, and the most serious in September affected by the typhoon. (4) The main reasons for the occurrence of rainstorm-induced catastrophe about Shenzhen City are flood, waterlogging, tide and typhoon, of these factors waterlogging is the primary one. Finally, this paper puts forward the corresponding countermeasures of flood hazard mitigation in Shenzhen City. [ABSTRACT FROM AUTHOR]

This note shows that the inoperability input–output model (IIM) estimates only a part of mainly the negative indirect economic impacts of disasters, whereas it neglects most of the positive indirect impacts. This means that the IIM is not suited to prioritize industries for policy interventions that aim at reducing the negative impacts of such disasters. Besides, this note shows that the application of the IIM is problematic and tends to overestimate the subset of impacts that the model is able to quantify. Finally, we identify two approaches that much better capture the variety of different disaster impacts. [ABSTRACT FROM AUTHOR]

Inundations and floods were part of the everyday experiences of early modern coastal societies. While much scholarly research has focused on the immediate reactions to the seemingly extraordinary inundations, this article argues, that an investigation of the long-term perspective of flood accounts, beyond the much studied discourses of ministers, magistrates and engineers might reveal a different, but perhaps more typical response to these disasters. The discourse of resilience and stoical attention to business as usual adds an additional dimension to modern society’s scripts of disaster management. [ABSTRACT FROM PUBLISHER]

Disasters result in devastating human, economic, and environmental effects. The paper highlights women's active participation in community-based disaster recovery efforts drawing from the results of the ‘Rebuilding Lives Post-disaster: Innovative Community Practices for Sustainable Development’ by an international research partnership. Two case studies are presented from Pakistan and the USA to demonstrate how women contribute to building resilience and promoting sustainable development in diverse post-disaster contexts. The policy and practice implications are relevant for discussions regarding the post-2015 Sustainable Development Goals and framework. [ABSTRACT FROM PUBLISHER]

Recent disasters have underscored the importance of enhancing resilience in economic systems. In this work, we propose a novelshock absorption index, which provides a measure of the ability of an economic system to tolerate disruptions. It is assumed that there are externally defined initial levels of system failure or disruption, as well as maximum allowable levels of inoperability for each sector. The shock absorption index is defined as the largest fraction of the anticipated initial disruption that can be absorbed by the predefined robustness limits. It provides an overall measure of the robustness of an economic system towards a disruptive event, which is driven by both the economic structure and the individual robustness of different sectors. The results of two case studies illustrate policy-making insights in identifying and prioritizing risk management strategies for critical systems. [ABSTRACT FROM AUTHOR]

How communities respond to and recover from damaging hazard events could be contextualized in terms of their disaster resilience. Although numerous efforts have sought to explain the determinants of disaster resilience, the ability to measure the concept is increasingly being seen as a key step toward disaster risk reduction. The development of standards that are meaningful for measuring resilience remains a challenge, however. This is partially because there are few explicit sets of procedures within the literature that outline how to measure and compare communities in terms of their resilience. The primary purpose of this article is to advance the understanding of the multidimensional nature of disaster resilience and to provide an externally validated set of metrics for measuring resilience at subcounty levels of geography. A set of metrics covering social, economic, institutional, infrastructural, community-based, and environmental dimensions of resilience was identified, and the validity of the metrics is addressed via real-world application using Hurricane Katrina and the recovery of the Mississippi Gulf Coast in the United States as a case study. [ABSTRACT FROM PUBLISHER]

Although an expansive literature exists on individual experiences after a catastrophic event, there is less attention to how the community as a social structure experiences a significant tragedy. These public tragedies create disruptions across multiple domains of community functioning. Using the Community Capacity Model (Hart, 1999) as a framework for assessment, outcomes of a public tragedy are described. Additionally, community practice approaches are identified for the three phases that communities subsequently experience: crisis, processing of the event, and adaptation. [ABSTRACT FROM AUTHOR]

Input–output-based techniques have proven to be effective in modeling how disasters lead to economic disruptions, while taking into account the structural connectivity of economic systems. In particular, through the inoperability input–output model (IIM), the degree of failure in an economic system can be quantified on a scale from 0 (normal state) to 1 (complete failure). This paper develops a vulnerability index that builds upon the foundations of the Leontief input–output model and the IIM, which is capable of identifying and prioritizing the key sectors in the aftermath of disasters. The key sector prioritization framework proposed in this paper is expected to contribute to the domain of disaster preparedness planning, such as enhancing the efficiency of resource allocation across various sectors. The proposed vulnerability index is formulated in terms of three underlying components: (1) economic impact, (2) propagation length, and (3) sector size. The vulnerability index captures the impact of investments to various sectors in times of disaster in order to yield the maximum benefits to the entire economy. This paper considers a baseline scenario that assumes that the decision-maker has an equal preference for all index components. Using Monte Carlo simulation and sensitivity analysis, we investigated the extent to which the key sector rankings could fluctuate with respect to variations in the decision-maker preferences. Key sectors tend to be sensitive to the weight assignments across the three vulnerability index components; nevertheless, some sectors are less sensitive to such weight variations and may persist on their level of priority, independent of the scenario. Using the Philippine input–output data, we found that the private services sector is consistently a high-priority sector, the trade sector is a mid-priority sector while the real estate and ownership of dwellings sector tend to be a low-priority sector. [ABSTRACT FROM PUBLISHER]

Disasters damage physical infrastructure systems, disrupt the movement of people and commodities, and cause significant economic losses. This paper develops an I–O model extension using an event tree analysis to assess the propagation of disaster effects across interdependent economic sectors using the inoperability and economic loss metrics. Inoperability, a dimensionless index that ranges between 0 and 1, indicates the extent to which a sector's production deviates below its normal state. On the other hand, economic loss is the monetary worth of the drop in output incurred in each sector of the economy due to the disaster. The new dynamic I–O extension is capable of adjusting the inoperability parameters within the disaster timeline to reflect events that can either degrade or enhance the predicted paths of sector recovery. It was implemented to the Nashville region – a metropolitan area in the USA known for its vibrant music and the tourism industry. The Nashville region is frequently hit by natural disasters such as tornadoes and floods, which makes it a suitable case study site for the model application. Results of the study can help identify critical economic sectors and ultimately provide insights for formulating preparedness decisions to expedite disaster recovery. [ABSTRACT FROM PUBLISHER]

In 1995, the Kobe Earthquake occurred in the second largest economic region of Japan, and its economic damages were accounted around 10 trillion yen. A catastrophic event of this magnitude would have surely created some long-run effects to the regional economy as well as to the surrounding regions. Additionally, the recovery and reconstruction activities would have affected the economic structure of the region and interdependence between regions in a potentially different way from the original growth trend before the event. While these long-run economic effects may have become sizable, few studies have been conducted to empirically measure or evaluate such effects, due to the significant noises in economic data muddled with macroeconomic influences from the outside. This paper presents an empirical investigation of long-run economic effects of the Kobe Earthquake, using structural decomposition methods. The results indicate significant changes in economic structure of the Kobe economy, and the changes are quite different across sectors and among factors. An additional investigation using shift-share analysis yielded the regional-specific changes; the corresponding decomposed factors of structural analysis with shift-share results appear complicated, and changes in regional final demand were found to be most influential to the changes in output for many sectors. [ABSTRACT FROM PUBLISHER]

This research aims to investigate a method for estimating the production capacity loss rate (PCLR) of industrial sectors damaged by a disaster, such as an earthquake, tsunami, or nuclear radiation, particularly the 2011 Great East Japan Earthquake. PCLR is fundamental information required to gain an understanding of economic losses caused by a disaster. In particular, this paper proposes a method of PCLR estimation that considers the two main causes of capacity losses as observed from past earthquake disasters, namely damage to production facilities and disruption of lifeline systems. To achieve the quantitative estimation of PCLR, functional fragility curves considering the relationship between production capacity and earthquake ground motion and lifeline resilience factors for capturing the impact of lifeline disruptions have been adopted, while actual recovery curves are considered mainly for damaged facilities. Through the application of this method to the case study of the 2011 Great East Japan Earthquake, the PCLR in various industrial sectors is estimated; the estimated PCLR in the manufacturing sectors are then compared to the corresponding index of industrial production. The results demonstrate that the estimated values are close to the actual production indices in the overall manufacturing sector and many of the individual sectors. [ABSTRACT FROM PUBLISHER]

Macroeconomics models, such as the input–output model, the social accounting matrix, and the computable general equilibrium model, have been used for impact analysis of catastrophic disasters for some time. While the use of such models to disaster situation, which may quite differ from the ordinary economic setting, has been critiqued (for recent example, see Albala-Bertrand, 2013), there are still valuable reasons for the use of such models. In particular, such models can be used in order to quickly provide a ballpark estimate of the system-wide impact for recovery plan and finance and/or to evaluate disaster countermeasures in the pre-event period. This paper presents how these methodologies have evolved to incorporate with disaster-specific feature and discusses how far they still need to go from the current stage. This paper also serves as a preface to this special issue, which encompasses several papers devoted to the use of macroeconomic data and models to assess economic losses from disasters. [ABSTRACT FROM PUBLISHER]

Several empirical studies reveal that holidays generally create positive sentiment in the stock market, whereas negative events, such as wars or disasters, are accompanied by negative sentiment. However, what happens if a negative event occurs on a holiday? In such a case, we expect two conflicting sentiment effects, which may cancel one another out or, alternatively, one effect may dominate the other. The stock market in Israel provides a unique laboratory in which to test these two conflicting effects, as Israel faced a horrible war on the Yom Kippur holiday in 1973—a war whose influence is still strongly felt today. Indeed, we find two robust effects: A strong and significant positive holiday sentiment effect; and a negative war sentiment effect, which dominates the positive holiday effect. These results, which show how sentiment effects are created, are general and can easily be applied to other events and other markets when conflicting sentiment effects occur. [ABSTRACT FROM PUBLISHER]

The recent frequency and intensity of crises and disasters affecting the tourism industry has resulted in a growing body of research into their causes, effects and management, as the bibliographies of the ensuing papers catalogue. To date, most papers and collections of research have taken a broad approach, describing the origins of a particular event which triggered a tourism crises, followed by an examination of the differential effects of the crisis on local residents, staff', tourists and tourism organizations or the environment and infrastructure. They have also discussed rescue efforts and the complexity of management tasks in the immediate aftermath of an event, often pointing to the need for preplanning to mitigate the consequences of any future disaster. Other researchers have contributed directly to the academic debate about how to theorise tourism crisis management, often by drawing on the wider crisis management literature. The present collection of research differs in that it focuses on one phase of the tasks which managers face after the immediate consequences of a crisis have been dealt with. This phase addresses the question of how to rebuild the market for a tourism service or a destination which has experienced a significant catastrophe, and how to learn from the experience in planning for future crisis response strategies. It is suggested in this paper that the challenges are actually more varied and complex than is implied by the suggestion, found in much of the literature, that the task is about 'restoring normality.' The chaos and complexity experienced in the aftermath of a crisis raise general issues of how organizations learn and adapt to change. [ABSTRACT FROM AUTHOR]

Analyzing economic impacts of disasters has attracted interest from a wide audience in recent years, not only because of the frequent occurrence of large natural disasters worldwide but also because of the spread of terrorism to a global scale. This paper reviews past modeling studies for economic impact analysis of disasters, focusing especially on the input-output model and related modeling frameworks, such as the social accounting matrix and the computable general equilibrium model. The paper also discusses the issues of disaster modeling raised by the literature, and proposes some future directions. [ABSTRACT FROM AUTHOR]