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- Damages and Costs of Forest Wildfires in New Zealand Using Satellite Data
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Abstract: Abstract We estimate wildfire impacts on Aotearoa New Zealand forests, focusing specifically on impacts in terms of vegetation recovery and costs. To this end, we use satellite-derived imagery of fire intensity and a vegetation index to measure burn severity and vegetation recovery. We then calculate profitability costs and post-fire remediation and clearing costs, estimated under various wildfire intensity scenarios, to determine the total cost of wildfires. We conclude, maybe unsurprisingly, that forests subject to high-intensity fires take longer to recover than those suffering medium- and low-intensity fires. The economic cost is also higher for higher-intensity fires, averaging 18,000 NZ$/Ha, but due to the small relative share of high-intensity fires, it is the medium-intensity fires that cause the most economic damages in New Zealand.
PubDate: 2024-08-19
- Poverty Impacts of the Pakistan Flood 2022
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Abstract: Abstract In the summer of 2022, devastating floods hit Pakistan with a profound negative impact on lives and livelihoods. Apart from the irreconcilable loss of life, household welfare was negatively impacted through the loss of household income, loss of assets, and rising food prices. Yet, in the absence of just-in-time household survey data, evaluating the welfare impact is challenging, particularly in terms of estimating monetary poverty. This paper demonstrates how real-time satellite data, in combination with administrative data and historical household survey data, can be used to model the impact of floods on Pakistani households. In the context of data and time constraints, we present a practical methodology to simulate the expected impact of a natural disaster on monetary poverty from an ex-ante perspective. Estimates show that, as a direct consequence of the floods, the national poverty rate would increase by 4.0 to 4.3 percentage points, pushing around 9 million people below the national poverty line. Moreover, a spatially disaggregated analysis showed that the magnitude of shocks varied across locations and households depending on the intensity of the flooding and household characteristics. These estimates, which informed the Post Disaster Needs Assessment and were later used to frame the Donor Conference for Pakistan, provide an example of rapid modeling in the absence of real-time household survey data.
PubDate: 2024-08-19
- AIS-Based Framework for Analyzing the Impacts of Passageway Disruptions
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Abstract: Abstract Passageways are critical gateways in maritime trade, providing efficient routes for global commerce. Disruptions such as natural disasters in key passageways can threaten global trade. This paper proposes an indicator-based framework for analyzing passageway disruptions using Automated Information System (AIS). This framework enables monitoring of transit operations, voyages and port calls. To demonstrate its potential, we apply the proposed framework to the Panama Canal drought in 2023. Results reveal that the reduction in transit capacity, increased waiting times, and draught limitations have disrupted traditional shipping routes, forcing vessels to seek alternative passageways, thereby increasing travel times and shipping costs. These disruptions have not only affected the efficiency of global trade but have also contributed to economic challenges such as inflation and decreased cargo volumes at major ports.
PubDate: 2024-08-06
- Understanding Evacuation Behavior During Cyclones: Evidence from
Bangladesh-
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Abstract: Abstract Due to its unique location, Bangladesh often faces devastating hydroclimatic shocks such as floods and cyclones. In the recent past, three major cyclones (Sidr in 2007, Aila in 2009, and Komen in 2015) claimed 3800 lives and damaged hundreds of thousands of houses with billions of dollars in property damages. In this paper, we focus on understanding people's evacuation behaviors in the face of approaching cyclones using survey data collected through face-to-face interviews with residents living in the coastal areas of Bangladesh. Through various statistical models, including probit, panel probit, bivariate probit, and multinomial logit models, we have explored the determinants of both past and future evacuation decisions, as well as the choice of evacuation destinations. Our findings reveal consistent patterns across different cyclone events, highlighting the significant roles played by warning time, proximity to the coast, property loss, shelter accessibility, housing structure, literacy, past evacuation experiences, and demographic factors such as age, gender, and employment status. Additionally, the analysis of evacuation destinations uncovers nuanced insights into the preferences and challenges faced by evacuees, including the need for improving shelter accessibility. With rising vulnerabilities in coastal areas in Bangladesh and worldwide, identifying what drives households' evacuation decisions and their destination choices can provide useful inputs for evacuation planning and effective disaster management.
PubDate: 2024-08-03
- Correction to: Assessing “Invisible Loss” during Medium‑Term
Earthquake Recovery: The Case of Indonesia’s 2016 Aceh Earthquakes-
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PubDate: 2024-08-01
- Impact of Social Connections on Flood-induced Migration Among Rural
Agricultural Households: Empirical Evidence from India-
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Abstract: Abstract Frequent flooding due to climate change poses significant challenges for rural populations, often forcing them to adopt migration as a coping strategy. However, while the impact of flood on migration is well documented in the literature, very little is known about the role of households’ social capital, in terms of collective efficacy, on flood-induced migration. Our study aims to fill this gap in the literature. We use 30 years of district level rainfall data from the Indian Meteorological Department to construct an objective measure of flood. Furthermore, two rounds of household data from the India Human Development Survey are employed to construct a subjective perception-based flood measure at the village level. We employ both Dose–response and Triple-Difference (DDD) models to investigate the role of social capital in flood-induced migration. Our empirical results show that while the objective measure of flood has an insignificant impact on migration, the subjective measure has a significant positive impact, after controlling for household socio-economic and demographic factors. Furthermore, intensity of migration among socially connected households is found to be more compared to their counterparts who are not socially connected. The findings of the DDD analysis are robust to the Placebo test of fake treatment analysis. Overall, our results highlight that households are more likely to undertake migration when they are confident about relying on their community networks for support during floods. The policy implications include the need to improve community bonding, trust, and reciprocity among households through the introduction of community development programs and social services.
PubDate: 2024-07-29
- Indian Agriculture Under Climate Change: The Competing Effect of
Temperature and Rainfall Anomalies-
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Abstract: Abstract The latest generation of global climate models robustly projects that monsoon rainfall anomalies in India will significantly increase in the 21st century due to global warming. This raises the question of the impact of these changes on the agricultural yield. Based on annual district data for the years 1966-2014, we estimate the relationship between weather indices (amount of seasonal rainfall, number of wet days, average temperature) and the most widely grown kharif crops, including rice, in a flexible non-parametric way. We use the empirical relationship in order to predict district-specific crop yield based on the climate projections of eight evaluated state-of-the-art climate models under two global warming scenarios for the years 2021-2100. We find that the loss in rice yield by the end of the 21st century lies on average between 3 - 22% depending on the underlying emission scenario. For the sustainable scenario impacts range from an increase of 3.2% to a decrease of 12.1% for individual districts. In the worst-case scenario, all districts are negatively affected, with a predicted decrease in rice yield ranging from 34% to a decrease of 11.5% in the long run. Potential gains due to increasing rainfall are more than offset by the negative impacts of increasing temperature. Adaptation efforts in the worst-case global warming scenario would need to cut the negative impacts of temperature by 50% in order to reach the outcome of the sustainable scenario.
PubDate: 2024-07-15
- Valuing the Economic Impact of River Floods and Early Flood Warning for
Households in Bangladesh-
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Abstract: Abstract Flood early warning systems have the potential to mitigate damages for vulnerable populations that experience river flooding in Bangladesh. We conducted a 2,247 household survey and series of focus groups to estimate the economic damages from 2016 river floods and the hypothetical savings of a 3- and 8-day warning for households living in the Jamuna River floodplain. Households were identified using geo-sampling, a novel geographic information system (GIS)–based sampling methodology that facilitates probability-based sampling where data are insufficient. Total damages for the entire flood plain in 2016 totaled to $1.3 billion, or 25% of household income and assets. Respondents estimated avoided damages from a hypothetical 3- and 8-day warning to be $73m and $85m, respectively, reflecting diminishing returns to additional days of early warning. With the hypothetical early warning, respondents derived the greatest savings from protecting their land, household/dwelling, and livestock. The greatest savings to households receiving a hypothetical additional 5 days of warning (from a 3- to an 8-day warning) would be realized in protecting agricultural production. Selling assets/livestock and employing protective sandbags were the preventative actions with the highest benefit–cost ratios that households said they would undertake. Importantly, only 11% of households received any early warning at all during the 2016 flood season, suggesting that the greatest benefits moving forward would be achieved by communicating existing or improved warnings more effectively to households in the floodplain.
PubDate: 2024-07-12
- Assessing “Invisible Loss” During Medium-Term Earthquake Recovery: The
Case of Indonesia's 2016 Aceh Earthquakes-
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Abstract: Abstract This study presents the results of a medium-term assessment of earthquake recovery, aiming to measure non-economic welfare losses resulting from the indirect impacts of earthquakes. While most earthquake assessments concentrate on the economic loss and damage caused by direct impacts of earthquakes, this study focuses on capturing these less visible non-economic losses. The 2016 Aceh earthquakes in Indonesia serve as the case study for this assessment. By applying the difference-in-differences method, we compared the changes in a range of non-economic welfare indicators in earthquake-affected and unaffected villages two years before (2014) and two years after (2018) the catastrophic earthquakes. In addition to administrative data, we tested the suitability of average monthly and annual night-time light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument as an alternative way to capture non-economic welfare losses. The findings from administrative data suggested a significant deterioration in, poverty, access to healthcare and access to socio-economic services in earthquake-affected villages relative to unaffected villages in 2018, compared to 2014. The analysis of nightlights data revealed contrasting results, suggesting that disaster recovery assessments using nightlights may not accurately capture non-economic welfare changes on the ground. Our research indicates that the detrimental effects of earthquakes on non-economic welfare persisted for years following the initial devastation. Utilizing administrative data can help pinpoint the nature and extent of non-economic losses and inform the development of policies to aid in the effective recovery of affected communities.
PubDate: 2024-07-02
- Are Disaster Impact Estimates Distorted by Errors in Popular Night-Time
Lights Data'-
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Abstract: Abstract Satellite-detected night lights data are widely used to evaluate economic impacts of disasters. Growing evidence from elsewhere in applied economics suggests that impact estimates are potentially distorted when popular Defense Meteorological Satellite Program (DMSP) night lights data are used. The low resolution DMSP sensor provides blurred and top-coded images compared to those from the newer and more precise Visible Infrared Imaging Radiometer Suite (VIIRS) images. Despite this, some disaster impact studies continue to use DMSP data, which have also been given a new lease of life through the use of harmonized series linking DMSP and VIIRS data to provide a longer sample. We examine whether use of DMSP data affects evaluations, using expected typhoon damages in the Philippines from 2012–19 as our case study. With DMSP data, negative impacts on economic activity from expected damages at the municipality level appear over 50% larger than when the VIIRS data are used. The DMSP data give the appearance of greater spatial autocorrelation in luminosity and through this channel may tend to spread apparent spatial impacts of shocks. Harmonized data that adjust VIIRS images to be like the DMSP data also have this spurious autocorrelation so researchers should be cautious in using these data for disaster assessments.
PubDate: 2024-06-26
- Climate-related Disaster and Human Capital Investment in the Global South
— Household Heterogeneity and Growth-
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Abstract: Abstract This study develops a dynamic model of climate-related disaster impacts, considering multidimensional household heterogeneity, for analyzing changes in growth and inequality in low-income countries. Focusing on human capital development, the study demonstrates the multiple impacts of disaster risk reduction (DRR) policies on human capital investment, including the effect of schooling opportunities for households constrained by the subsistence consumption constraint. Through numerical simulations performed for two economies that differ in terms of human capital, modeled after Madagascar and Fiji, it is illustrated that the possibilities of involuntary unemployment and the work-learning choice drive the diversity in macroeconomic impacts of a disaster. In an economy characterized by low levels of human capital, a disaster could cause an increase in labor supply in the immediate aftermath but interrupt human capital formation, impeding long-term growth and human capital formation. Such a result contradicts prevailing intuition by demonstrating that a disaster occurring in an economy under recession may not result in a large adverse GDP impact in the short run but may negatively impact growth in the long run. On such a path, a policy of development in DRR infrastructure with appropriate taxation could reduce human-capital gaps in the long run by supporting continued post-disaster human-capital-investment opportunities for the poor.
PubDate: 2024-05-20
DOI: 10.1007/s41885-024-00150-8
- Correction to: Shaking up Foreign Finance: FDI in a Post-Disaster World
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PubDate: 2024-05-08
DOI: 10.1007/s41885-024-00151-7
- The Impacts of Multiple Tropical Cyclone Events and Associated
Precipitation on Household Income and Expenditures-
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Abstract: Abstract Tropical cyclones (TCs) are one of the most destructive natural hazards. Damages arise from strong winds, compounded by associated flood-inducing hazards such as heavy rainfall and storm surge. Recent papers have shown that the modelled TC damage estimates fall short of the observed estimates due to the use of wind speed as a sole damage proxy. Damage estimates may be further confounded by inaccurate representations of vulnerability of people and economic sectors, for example, calling for adjusted damage thresholds in less developed regions. This paper evaluates the impacts of compounded TC hazards on household income and expenditure in the Philippines, with adjustments in vulnerability representation drawn from local information. Our results show that the omission of TC-associated precipitation leads to an underestimation of impacts, as well as the number of areas and economic sectors affected by TCs. We find that households cope through a reallocation of budgets and reliance on alternative income sources. Despite extensive public and private disaster risk reduction and management strategies, we still find significant losses in income and expenditures at any number of TC exposure.
PubDate: 2024-04-24
DOI: 10.1007/s41885-024-00149-1
- Shaking up Foreign Finance: FDI in a Post-Disaster World
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Abstract: Abstract This paper studies the effects earthquakes have on inward foreign direct investment (FDI) within a country. I use a dynamic difference-in-difference model to estimate the impact of geophysical disaster exposure in 416 Indonesian districts. The effects are only temporary: FDI inflows plummet by 90% on average in the first year after an earthquake before recovering to pre-earthquake levels. The effect is largely driven by shocks through affected upstream industries within local supply chains, and centered within the manufacturing sector. This highlights the importance to also consider indirect earthquake effects through spatial and production networks, besides the direct effects on labor and capital.
PubDate: 2024-04-11
DOI: 10.1007/s41885-024-00148-2
- Flood Impacts on Agriculture under Climate Change: The case of the Awanui
Catchment, New Zealand-
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Abstract: Abstract We assess the economic and environmental impacts on agriculture of flooding under projected climate change, including land-use change as an adaption response to floods. Our case study area is the Awanui catchment located in the far north of New Zealand, where flooding is a significant hazard. The study uses an integrated approach and combines spatial information on agricultural exposure and damage from flooding, economic land-use modelling, and valuation approaches. We analyse direct tangible and direct intangible flood impacts under various extents, frequencies, and water depth levels. Our results show areas with flood exposure and damage costs increase with projected climate change. As an adaptation measure to reduce flood damage costs, pastoral farms convert to other land uses, mainly to unfarmed land. Flooding reduces the net revenue for the catchment, while it can result in some reduction of environmental pollution. When the probability of all possible flood events are considered, the value of the changes in greenhouse gas emissions are equivalent to approximately 18% of the change in total net revenue, while the value of changes in other environmental outputs is equivalent to less than 1% of the change in total net revenue. Based on this study, the assessment of various flood impacts and adaptation responses to them can help to develop resilience strategies for the agricultural sector to future climate-induced flooding.
PubDate: 2024-03-28
DOI: 10.1007/s41885-024-00147-3
- United States Electric Utility Adaptation to Natural Hazards and Green
Power Mandates-
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Abstract: Abstract Access to electricity is a crucial determinant of quality of life and productivity. The United States has a highly reliable electricity grid, but it faces new resilience challenges due to more intense disasters and ambitious green power requirements. Over the past decade, utilities have faced tradeoffs between achieving carbon mitigation goals, offering reliable power access, and keeping retail prices low. Using a generator panel dataset from 2013 to 2022, we document that electricity generation from renewables declines during extreme weather events. Based on an electric utility panel dataset over the same period, we find that disasters also disrupt electricity distribution. Although utilities have made some adaptation progress, investments in green and reliable green power are associated with higher electricity prices.
PubDate: 2024-03-28
DOI: 10.1007/s41885-024-00146-4
- Hurricane-Induced Power Disruptions: Household Preferences for Improving
Infrastructure Resilience-
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Abstract: Abstract In recent years, the increase in the frequency and intensity of hurricanes has posed a significant threat to coastal infrastructures, particularly the electricity supply system. In response to these challenges, several policies have been proposed to improve the resilience of electricity systems, specifically focusing on expediting the restoration of disrupted utilities. However, implementing these resilience plans comes with considerable costs, which must be balanced against the potential benefits experienced by households. This study examines the willingness of Florida residents to financially support the improvement of the electricity infrastructure resilience in response to hurricanes in Florida. We conduct a Discrete Choice Experiment involving 1138 Floridians to assess their willingness to pay for different scenarios aimed at improving electricity system resilience. Three panel mixed logit models are estimated, accounting for preference heterogeneity. Results indicate that the annual welfare estimates per individual range from $525.51 to $604.70 across the restoration scenarios. The findings offer compelling evidence, indicating strong support for minimizing hurricane-induced power disruptions by implementing the proposed resilience programs in Florida.
PubDate: 2024-03-27
DOI: 10.1007/s41885-024-00145-5
- Adapting to Climate Risk' Local Population Dynamics in the United
States-
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Abstract: Abstract Using a new composite climate-risk index, we show that population in high-risk counties has grown disproportionately over the last few decades, even relative to the corresponding commuting zone. We also find that the agglomeration is largely driven by increases in the (white) working-age population. In addition, we show that high-risk tracts have typically grown more than low-risk tracts within the same county, suggesting the presence of highly localized amenities. We also document heterogeneous population dynamics by degree of urbanization, region and type of natural hazard. Specifically, population has been retreating from high-risk, low-urbanization locations, but continues to grow in high-risk areas with high residential capital. Net migration flows have contributed to the higher growth of high-risk counties in the South and Northeast of the country, but the opposite has happened in the West and Midwest. Last, we provide evidence of microretreat in the case of coastal flooding: tracts with high levels of this risk have grown significantly less than other tracts in the same county, suggesting that residents are willing to relocate within short distances to avoid predictably risky locations.
PubDate: 2024-02-19
DOI: 10.1007/s41885-024-00141-9
- Wish You Were Here' The Economic Impact of the Tourism Shutdown from
Australia’s 2019-20 ‘Black Summer’ Bushfires-
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Abstract: Abstract Tourism, including education-related travel, is one of Australia’s top exports and generates substantial economic stimulus from Australians travelling in their own country, attracting visitors to diverse areas including World Heritage rainforests, picturesque beachside villages, winery townships and endemic wildlife. The globally unprecedented 2019-20 bushfires burned worst in some of these pristine tourist areas. The fires resulted in tourism shutting down in many parts of the country over the peak tourist season leading up to Christmas and into the New Year, and tourism dropped in many areas not physically affected by the fires. Our research quantified the cost of the short-term shock from tourism losses across the entire supply chain using input-output (IO) analysis, which is the most common method for disaster analysis; to this end, we also developed a framework for disaggregating the direct fire damages in different tourism sectors from which to quantify the impacts, because after the fires, the economy was affected by COVID-19. We calculated losses of AU$2.8 billion in total output, $1.56 billion in final demand, $810 million in income and 7300 jobs. Our estimates suggest aviation shouldered the most losses in both consumption and wages/salaries, but that accommodation suffered the most employment losses. The comprehensive analysis highlighted impacts throughout the nation, which could be used for budgeting and rebuilding in community-and-industry hotspots that may be far from the burn scar.
PubDate: 2024-01-30
DOI: 10.1007/s41885-024-00142-8
- Extreme Weather Events and the Performance of Critical Utility
Infrastructures: A Case Study of Hurricane Harvey-
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Abstract: Abstract Extreme weather events have significant economic and social impacts, disrupting essential public services like electricity, phone communication, and transportation. This study seeks to understand the performance and resilience of critical infrastructure systems in Houston, Texas, using Hurricane Harvey (2017) as a case study. We surveyed 500 Houston Metropolitan Statistical Area residents after Hurricane Harvey’s landfall about disruption experience in electricity, water, phone/cellphone, internet, public transportation, workplace, and grocery stores. Our household survey data revealed the proportion and duration of disruption in each system. Approximately 70% of respondents reported experiencing electricity outages, while half (51%) had no access to water for up to six days. Two-thirds of surveyed households lacked internet access, and 50% had their phone services disconnected. Additionally, around 71% of respondents were unable to commute to work, and 73% were unable to purchase groceries for their families during this period. We incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses across interconnected sectors. The projected economic loss was estimated to be in the range of $6.7- $9.7 billion when sensitivity analysis is performed with respect to the number of working days. Understanding the resilience of each sector and the inherent interdependencies among them can provide beneficial insight to policymakers for disaster risk management, notably preparedness and recovery planning for future events.
PubDate: 2023-12-20
DOI: 10.1007/s41885-023-00139-9
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