15 research outputs found
Unveiling spatial inequalities: Exploring county-level disaster damages and social vulnerability on public disaster assistance in contiguous US
Understanding the dynamics between public disaster assistance, disaster damages, and social vulnerability at county-level is crucial for designing effective disaster mitigation strategies. This study utilized the Local Bivariate Moran Index (LBMI) and geographically weighted regression (GWR) models to examine spatial patterns and relationships between disaster damages, social vulnerability, and public disaster assistance in contiguous US counties from 2001 to 2021. LBMI results reveal that public disaster assistance has predominantly been directed towards post-disaster recovery efforts, with a particular focus on coastal communities affected by major declared disasters. However, the distributions of public assistance and individual housing assistance, which are the two primary sources of public disaster assistance, do not adequately cover physically and socially vulnerable communities. The distribution of pre-disaster risk mitigation also falls short of sufficiently covering vulnerable communities. Results further indicate the complex interactions between different categories of natural disasters and public assistances. The GWR model results demonstrate spatial variations in predicting each category of public disaster assistance. These findings indicate the need to address disparities in accessing public disaster assistance in the US, and advocate for more equitable disaster mitigation strategies
Citizens' preferences and valuation of urban nature: Insights from two choice experiments
Urban nature increases the liveability of cities and can improve their resilience to climate change. However, the value of urban nature often remains unknown, which results in its omission from urban planning decisions. Particularly the valuation of small-sized urban nature remains understudied. This study therefore employs a stated preference methodology to estimate the economic value of seven types of small urban nature and four associated ecosystem services. We perform two choice experiments: one with urban parks, urban forest and green corridors and another one with even smaller urban nature types (green roofs, green walls, street trees and green beds). The results of the choice analysis show that urban residents are willing to pay more for the former types of urban nature but not for the latter types. Urban parks are valued the most, followed by urban forests and green corridors. Within the category of the smallest urban nature types, street trees are valued most followed by green beds green walls, whereas green walls and green roofs are least valued. We discuss opportunities and barriers to implementing economic valuation results in urban planning practices. Several policy and future research recommendations are proposed
A Service of zbw Leibniz-Informationszentrum Wirtschaft Leibniz Information Centre for Economics Scale, Scope and Cognition: Context Analysis of Multiple Stated Choice Experiments on the Values of Life and Limb Context Analysis of Multiple Stated Choice E
Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Abstract In this paper we use data from an SP study on flood safety in the Netherlands, and elicit individual preferences for reduction of risk to life and limb. We perform context analysis to test the robustness of fatality risk valuation throughout choice experiments. The main interest of this paper is VOSL sensitivity to the valuation of correlated risks (scope effect). Besides, we explore the role of cognition on the stability of valuation across choice experiments using age and education. We pool data from multiple choice experiments and apply nested and mixed logit models in our analysis. We confirm statistically significant sensitivity to scope, comparing VOSL estimates for the test group in a choice experiment where correlated risks were present (risks of fatality, injury and evacuation) to an experiment where only fatality risk is valued. We find that the origin of differences in VOSL valuations across the choice experiments lies in differences in age and educational attainment, and may therefore be related to cognitive abilities of respondents. In particular, we conclude that higher VOSL sensitivity to scope is most prominently present among respondents of senior age (65 and older) and respondents without college education. This finding has important implications for discrete choice modeling and the use of obtained values in cost-benefit analyses. Keywords: stated preferences, value of statistical life, value of statistical injury, value of statistical evacuation, flood risk.
Valuing Urban Nature through Life Satisfaction:The Consistency of GIS and Survey Indicators of Nature
Valuing Urban Nature through Life Satisfaction: The Consistency of GIS and Survey Indicators of Nature
On direct estimation of initial damage in the case of a major catastrophe: derivation of the "basic equation"
Input-output analysis (I-O) is increasingly used in studies of sudden catastrophes such as earthquakes, hurricanes, or, in the case of The Netherlands, major flooding. Unfortunately, in catastrophe analysis, there is no general consensus over the points of departure. Therefore, we need a basic notion of “where to start from”. One task the I-O modeller faces after the disaster is to construct a plausible basis for the recovery and reconstruction efforts. Here the literature has developed the concept of the so-called event matrix. The event matrix is an I-O compatible matrix that traces the development of the situation at selected intervals after the catastrophe and during the reconstruction phase. However, the concept of I-O on the basis of a well-founded “event matrix” theory is still developing. It is the purpose of this paper to put forward a specific point of departure in disaster analysis, starting from I-O fundamentals and introducing the concept of a “basic equation” as a necessary first step in the construction of an event matrix