Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters
Authored by Asjad Naqvi
Date Published: 2017
DOI: 10.1016/j.worlddev.2017.05.015
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Model Documentation:
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Pseudocode
Mathematical description
Model Code URLs:
https://ars.els-cdn.com/content/image/1-s2.0-S0305750X16302169-mmc1.zip
Abstract
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 interconnected 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. (C) 2017 The Author. Published by Elsevier Ltd.
Tags
Agent-based model
Migration
Risk
growth
income
Earthquake
Consequences
Insurance
Countries
Geography
Macroeconomic model
Pakistan
Economic-development
Food insecurity
Liquidity constraints