Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters.
Summary Adverse post-natural disaster outcomes in low-income regions, like elevated internal migration levels and low consumption levels, are the result of market failures, poor mechanisms for stabilizing income, and missing insurance markets, which force the affected population to respond, and adap...
| Publicado en: | World Development Vol. 99; pp. 395 - 419 |
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| Formato: | Artículo |
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Elsevier B.V.
Nov2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=124741740&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 124741740 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0305750X WDV jtl: World Development issn: 0305750X maglogo: N pubinfo: dt: Nov2017 vid: 99 pid: 2410 pub: Elsevier B.V. artinfo: ui: 124741740 10.1016/j.worlddev.2017.05.015 ppf: 395 ppct: 24 formats: tig: atl: Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters. aug: au: Naqvi, Asjad affil: International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria Institute for Ecological Economics, Vienna University of Economics and Business (WU), Vienna, Austria su: Pakistan Natural disasters Internal migration Market failure Insurance exchanges Earthquakes sug: subj: Natural disasters Internal migration Pakistan All Other Insurance Related Activities Market failure Insurance exchanges Earthquakes keyword: agent-based model earthquake food insecurity geography migration agent-based model earthquake food insecurity geography migration ab: Summary Adverse post-natural disaster outcomes in low-income regions, like elevated internal migration levels and low consumption levels, are the result of market failures, poor mechanisms for stabilizing income, and missing insurance markets, which force the affected population to respond, and adapt to the shock they face. In a spatial environment, with multiple locations with independent but inter-connected markets, these transitions quickly become complex and highly non-linear due to the feedback loops between the micro individual-level decisions and the meso location-wise market decisions. To capture these continuously evolving micro–meso interactions, this paper presents a spatially explicit bottom-up agent-based model to analyze natural disaster-like shocks to low-income regions. The aim of the model is to temporally and spatially track how population distributions, income, and consumption levels evolve, in order to identify low-income workers that are “food insecure”. The model is applied to the 2005 earthquake in northern Pakistan, which faced catastrophic losses and high levels of displacement in a short time span, and with market disruptions, resulted in high levels of food insecurity. The model is calibrated to pre-crisis trends, and shocked using distance-based output and labor loss functions to replicate the earthquake impact. Model results show, how various factors like existing income and saving levels, distance from the fault line, and connectivity to other locations, can give insights into the spatial and temporal emergence of vulnerabilities. The simulation framework presented here, leaps beyond existing modeling efforts, which usually deals with macro long-term loss estimates, and allows policy makers to come up with informed short-term policies in an environment where data is non-existent, policy response is time dependent, and resources are limited. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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