Earthquake propensity and the politics of mortality prevention

Governments can significantly reduce earthquake mortality by implementing and enforcing quake-proof construction regulation. The authors examine why many governments do not. Contrary to intuition, controlling for the strength and location of actual earthquakes, mortality is lower in countries with higher earthquake propensity, where the payoffs to mortality prevention are higher. Importantly, however, the government response to earthquake propensity depends on country income and the political incentives of governments to provide public goods to citizens. The opportunity costs of earthquake mortality prevention are higher in poorer countries; rich countries invest more in mortality prevention than poor countries in response to a higher earthquake propensity. Similarly, governments that have fewer incentives to provide public goods, such as younger democracies, autocracies with less institutionalized ruling parties and countries with corrupt regimes, respond less to an elevated quake propensity. They therefore have higher mortality at any level of quake propensity compared to older democracies, autocracies with highly institutionalized parties and non-corrupt regimes, respectively. The authors find robust evidence for these predictions in our analysis of earthquake mortality over the period 1960 to 2005.Population Policies,Natural Disasters,Hazard Risk Management,Labor Policies,Disaster Management

Design of Flood-loss Sharing Programs in the Upper Tisza Region, Hungary: A dynamic multi-agent adaptive Monte Carlo approach

Losses from human-made and natural catastrophes are rapidly increasing. The main reason for this is the clustering of people and capital in hazard-prone areas as well as the creation of new hazard-prone areas, a phenomenon that may be aggravated by a lack of knowledge of the risks. This alarming human-induced tendency calls for new integrated approaches to catastrophic risk management. This paper demonstrates how flood catastrophe model and adaptive Monte Carlo optimization can be linked into an integrated Catastrophe Management Model to give insights on the feasibility of a flood management program and to assist in designing a robust program. As a part of integrated flood risk management, the proposed model takes into account the specifics of the catastrophic risk management: highly mutually dependent losses, the lack of information, the need for long-term perspectives and geographically explicit models, the involvement of various agents such as individuals, governments, insurers, reinsurers, and investors. Therefore, the integrated catastrophe management model turns out to be an important mitigation measure in comprehending catastrophes. As a concrete case we consider a pilot region of the Upper Tisza river, Hungary. Specifically, we analyze the demand of the region in a multipillar flood-loss sharing program involving a partial compensation by the central government, a voluntary private property insurance, a voluntary private risk-based insurance GIS-based catastrophe models and specific stochastic optimization methods are used to guide policy analysis with respect to location-specific risk exposures. To analyze the stability of the program, we use economically sound risk indicators

Uncertainty of Governmental Relief and the Crowding out of Insurance

This paper discusses the problem of crowding out of insurance by co-existing governmental relief programs - so-called 'charity hazard' - in a context of different institutional schemes of governmental relief in Austria and Germany. We test empirically whether an assured partial relief scheme (as in Austria) drives a stronger crowding out of private insurance than a scheme promising full relief which is subject to ad hoc political decision making (as in Germany). Our general finding is that the institutional design of governmental relief programs significantly affects the demand for private natural hazard insurance.Insurance demand, governmental relief, natural hazards

Advancements in Enhancing Resilience of Electrical Distribution Systems: A Review on Frameworks, Metrics, and Technological Innovations

This comprehensive review paper explores power system resilience, emphasizing its evolution, comparison with reliability, and conducting a thorough analysis of the definition and characteristics of resilience. The paper presents the resilience frameworks and the application of quantitative power system resilience metrics to assess and quantify resilience. Additionally, it investigates the relevance of complex network theory in the context of power system resilience. An integral part of this review involves examining the incorporation of data-driven techniques in enhancing power system resilience. This includes the role of data-driven methods in enhancing power system resilience and predictive analytics. Further, the paper explores the recent techniques employed for resilience enhancement, which includes planning and operational techniques. Also, a detailed explanation of microgrid (MG) deployment, renewable energy integration, and peer-to-peer (P2P) energy trading in fortifying power systems against disruptions is provided. An analysis of existing research gaps and challenges is discussed for future directions toward improvements in power system resilience. Thus, a comprehensive understanding of power system resilience is provided, which helps in improving the ability of distribution systems to withstand and recover from extreme events and disruptions

A GIS based seismic risk scenario of the cities of Santa Fé and Atarfe in Andalucía, Spain

This paper applies a GIS -based methodology to a case study in the cities of Atarfe and Santa Fé in Anadalucía (Spain) which recently suffered a seismic series with six magnitude 4 earthquakes. The framework for estimating the risk scenario essentially relates each housing building in the cadastral, to the probability of reaching different levels of seismic damage, namely negligible, slight, moderate, extensive given the seismic hazard in the area under study. It is built on the python toolbox pandas and QuantumGIS. Although only minor to light damages were observed and reported during the seismic series, this study reveals that there is a high-risk scenario in the area if the 475-year design earthquake occurred nowadays.Este artículo aplica una metodología basada en SIG a un caso de estudio en las ciudades de Atarfe y Santa Fé en Anadalucía (España) que recientemente sufrieron una serie sísmica con seis terremotos de magnitud 4. Esencialmente, se relaciona cada edificación de vivienda en el catastro con su probabilidad de alcanzar diferentes niveles de daño sísmico: insignificante, leve, moderado, extenso dada la amenaza sísmica en el área de estudio. Está desarrollado en python pandas y QuantumGIS. Aunque solo se observaron y reportaron daños menores a leves durante la serie sísmica, este estudio revela que existe un escenario de alto riesgo en el área si el terremoto de proyecto de 475 años ocurriera en la actualidad.Grant PID2020-120135RB-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by the Programa Operativo FEDER 2014-2020/Junta de Andalucía/Consejería de Transformación Económica, Industria, Conocimiento y Universidades/Proyecto B-TEP- 306-UGR18