This paper studies formal business registrations after the 2023 Türkiye earthquakes using a newly assembled province-month panel from official administrative registry statistics. The data cover all 81 provinces from January 2020 through March 2026 and record newly established companies, cooperatives and real-person commercial enterprises, liquidations, registered closures, total entry and exit, and the registered capital of newly established companies. A difference-in-differences design compares the 11 earthquake-affected provinces with the rest of Türkiye, while an event-study specification separates the immediate disruption from subsequent registration dynamics. New company registrations in affected provinces fell by approximately 59
This article examines the role of remittances on the relationship between flooding and household expenditure using data from the fourth Cameroonian household survey conducted by the National Institute of Statistics in 2014. The two-stage least squares method (2SLS) with instrumental variables (IV) shows that flooding is positively associate with total expenditure, food expenditure and non-food expenditure. Furthermore, remittances are positively associated with total expenditure, food expenditure and non-food expenditure. We also find that the interaction coefficient between remittances and flooding is negatively and significantly associate with each category of household expenditure. Finaly, flooding is not significantly associate with all household expenditure in urban areas but is positively and significantly associate with household expenditure in rural area. These results suggest that remittances should be considered an essential tool for adaptation and social protection policies for households.
Climate-related disasters generate uneven reported loss burdens across countries, and these burdens may vary with national adaptation readiness and financial development. Using a global country-year panel for 2004–2022, this study examines whether adaptation readiness and financial development condition the association between recorded climate-disaster frequency and reported climate-disaster loss burden. Two-way fixed-effects models are estimated with country and year effects and country-clustered standard errors. Additional analyses examine the availability of monetary-damage reporting, readiness dimensions, vulnerability-related components, peril-specific losses, financial-development channels, nonlinear readiness, and country-group heterogeneity. Recorded disaster frequency is positively associated with reported loss burden in both core and supplementary models. Financial development consistently weakens this association, especially through financial markets and financial-institution depth. Adaptation readiness does not show a uniform buffering effect; its moderation varies across specifications, dimensions, development groups, and functional forms. The findings indicate that financial development is a more stable moderator of reported disaster-loss burden than adaptation readiness, while readiness-related effects are more conditional and context-dependent.
Over the past two decades, the South of France has been increasingly exposed to climate-related hazards, experiencing several severe meteorological and hydrological disasters. Among these, the 2015 flash flood and the 2020 Storm Alex stand out as the two most devastating events, causing catastrophic economic and human losses. However, the transmission of these risks to banking institutions is not necessarily direct, particularly due to how credit is granted in France and the presence of risk-pooling mechanisms. Using data from 213 French regional banks over the period from 2000 to 2021, this article aims to analyze how bank customers and regional banks have responded to these extreme events, given the specificities of the French system. Using the Difference-in-Differences method, we observe that following a disaster, customers located in the affected regions withdraw cash to cover the costs associated with the extreme physical event. Similarly, banks come to the aid of customers by providing additional liquidity through loans. Despite the challenges posed by the advent of disasters (notably credit risk), French regional banks have managed to maintain a relatively stable level of profitability. Accordingly, this study sheds new light on the macro-financial transmission channels of physical climate risks, and thus on the need to implement policies to strengthen the resilience of banking systems to such climatic events.
Climate change is currently causing serious problems with food security in countries around the world, especially in developing countries, where large populations rely mainly on agriculture. Thus, the aim of the study examines whether the adoption of adaptation strategies to climate change improves household food security in the Abe Dongoro district, Ethiopia. A multistage sampling technique was employed to get 334 samples, and data were collected through interviews with household members, key informant interviews, focus group discussions, and previous document reviews. Propensity score matching and descriptive statistical methods were utilized to examine the data. The investigation outcome stated that educational level, farm income, land size, livestock ownership, access to climate information, extension contact, and credit services of households displayed statistically significant mean differences between non-adopters and adopters of adaptation strategies for climate change. Propensity score matching (PSM) model results revealed that adopting at least one strategy for adapting to climate change increased rural households’ food security. The average treatment effect for those who adopted adaptation strategies for climate change was 568.18 Kcal/AE/day more than non-adopted households. As a result, adopting adaptation strategies for climate change is vital for ensuring household food security. Therefore, the government should be enhancing farmer awareness of these techniques and implementing existing adaptation strategies more aggressively, accompanied by policy interventions, empowering institutions, and financial support. The adaptation strategies have critical possible roles in driving government efforts to enhance the food security of rural communities.
This study investigates the asymmetric impacts of climate extremes on the Italian agricultural sector. Utilizing annual time-series data from 1961 to 2023, the research employs a Nonlinear Autoregressive Distributed Lag (NARDL) framework. This methodological approach effectively captures the complex dynamics of environmental shocks that traditional linear models frequently overlook. The findings confirm a stable long-run relationship between agricultural production value, temperature, rainfall, and carbon emissions. Notably, the agricultural sector demonstrates a robust short-term adaptive capacity, recovering approximately 61
Communities in typhoon-prone regions may underestimate rainfall-driven flood risks from non-landfalling tropical cyclones because they often rely on traditional storm cues such as landfall location and wind intensity. In the Philippines, particularly in the Bicol Region widely regarded as the country’s typhoon landfall belt, repeated exposure to tropical cyclones has shaped local perceptions and behavioral responses toward storm hazards. This study examines flood risk perception, exposure, preparedness behavior, and trust in disaster risk communication, including artificial intelligence (AI)-based weather forecasting, during Tropical Storm Ada (Nokaen), the first tropical cyclone of the 2026 season and a rare early-season, non-landfalling storm. Using survey data from 640 residents in the Partido District of Camarines Sur, the study employed behavioral econometric analysis to analyze factors influencing disaster-related decision-making. Results showed moderate overall risk perception (WM = 3.71) but high preparedness behavior (WM = 4.20). Respondents strongly relied on traditional storm indicators such as landfall and wind intensity (WM = 3.69), contributing to a perception–reality gap (WM = 3.92). Although most respondents reported no flooding, 28.12
This paper improves climate-impact assessment for Europe by integrating NUTS-2 level damage functions from the ICES computable general equilibrium model into the spatially explicit CLIMRISK integrated assessment model. The framework combines market damages, spatial GDP projections, temperature change, and urban heat island (UHI) effects under multiple probabilistic climate and socioeconomic scenarios. Results show that aggregate European damages are broadly consistent with the RICE model, but the ICES damage functions help highlight the sub-national impact heterogeneity. The largest relative losses are expected to ocur in regions of southern Europe (Spain, Italy, Greece), particularly in urban areas. UHI effects account for about 40
The literature on wildfires and residential property prices is limited and primarily focuses on events in North America. There is a lack of studies examining this relationship in Europe. With the largest forest area in the entire EU, understanding this impact is particularly relevant in a Swedish context. In this paper, we investigate how the largest wildfire in Sweden’s recent history, the 2014 wildfire in Västmanland County, affected nearby housing prices and time-on-market. Using a difference-in-differences method, we find a significant negative effect on housing prices. Our most conservative estimate indicates an approximate 2.7
Disasters’ adverse impacts on human health are not limited to physical health but extend to mental health and well-being. Multiple causal mechanisms can impact mental health, including direct physical injury and disability, psychological trauma, the loss of loved ones, displacement, or socioeconomic stressors associated with the disaster recovery process. Here, we review the literature that focuses on the economic quantifications of the mental health consequences of disasters, including both how economic circumstances can contribute to or ameliorate the mental health impacts, and how these mental health impacts can shape people’s economic trajectories. We review several methods that can be used to quantify these costs. This literature also includes several cost-effectiveness studies of interventions that have been evaluated with quality-adjusted life years (QALY) metrics. We evaluate the strengths and weaknesses of each approach and describe their quantifications. Since these quantifications conclude that these mental health costs can be high, their exclusion from standard disaster risk assessments can lead to the underestimation of disasters’ total social costs, and consequently to an underinvestment in disaster risk-reduction measures. Quantifying these mental health costs may hence yield a more comprehensive understanding of disaster losses and help inform decisions about the appropriate levels of investments in prevention and mitigation.
Wildfires have been increasing in frequency and severity across the United States as climate change lengthens the wildfire season. California has endured a significant number of devastating wildfires in the past decade. Obtaining wildfire insurance in California is growing more and more difficult as the affordability and availability decrease. The objectives of this research are to explore the correlation between the number of wildfires per year in California with the number of insurance renewals by county in both the FAIR (Fair Access to Insurance Requirements) Plan and the voluntary market, and to identify where wildfires have most frequently been occurring through spatial analyses. Kernel density and Getis-Ord Gi Hot Spot analyses were conducted to visualize where wildfires happened most in California from 2014 to 2024. The results show that there is a significant positive correlation between the number of wildfires each year with insurance renewal rates in both the FAIR plan and the voluntary market. However, the voluntary market appears more responsive to changes in wildfire activity and premium conditions than the FAIR Plan. Los Angeles was found to be the county that suffers from the most wildfires each year. There is generally insignificant correlations between the sociodemographic indicators with the number of insurance renewals in both the FAIR Plan and the voluntary market. This research contributes to the understanding of wildfire risk and frequency patterns and may inform local governments and insurance companies of insurance demand and renewal rate predictions based on the previous wildfire season. Leverage spatial and statistical analysis and visualization to identify wildfire prevalence and relationship with insurance renewals in California at a county level. Given the increasing risk of wildfire exposure, insurance renewals are more influenced by wildfire frequency than sociodemographic factors, with the voluntary market showing greater responsiveness than the FAIR Plan.
This study models the behaviour of economic systems during pandemic events by extending Zellner’s Seemingly Unrelated Regressions (SUR) within a Generalised Method of Moments (GMM) framework. The proposed approach identifies systems of equations that remain stable when explaining one or more variables simultaneously. Applied to pandemic–economic dynamics across major economies (2020–2023), the results show interactions between epidemiological indicators (transmission, recovery, mortality) and macroeconomic variables (employment, trade, investment, inflation). The findings suggest that the pandemic negatively affected employment and trade, while higher recovery rates acted as stabilising forces, reducing inflationary pressures and supporting economic resilience. The framework captures how structural relationships evolve across risk phases including initial shock, early recovery and post-vaccination, identifying systemic vulnerabilities and resilience pathways during global disruptions.
Improved rice varieties play a critical role in enhancing food security, strengthening climate resilience, and achieving multiple Sustainable Development Goals (SDGs). Despite these benefits, their adoption remains limited in many rice-growing regions. This study examines the adoption likelihood and intensity of Hybrid (HV), High-Yielding (HYV), and Traditional (TV) rice varieties by analyzing data from 2,673 rice-farming households in Bangladesh, the world’s third-largest rice-producer. Descriptive results show that HYV is the most widely adopted variety (88.85
This study evaluates the predictive efficacy of conventional disaster risk index (DRI) modelling against empirical generalised linear model (GLM) analysis using data from 71 districts in Myanmar. While the standard DRI framework (Hazard × Exposure × Vulnerability) is widely used for risk ranking, its reliance on a composite vulnerability score can mask the underlying factors that shape disaster impacts. This study employed negative binomial regression to model the affected population count, comparing an initial model using a categorical vulnerability index with a subsequent model using disaggregated socioeconomic components. The analysis revealed that the composite index lacked statistical significance, while disaggregation was essential for policy relevance. The model identified four highly significant predictors, with flood risk emerging as the sole dominant hazard (IRR ≈ 1.44). Three socioeconomic factors were highly significant: districts with the highest secondary education (IRR ≈ −1.74) and the highest conflict index (IRR ≈ −0.71) were major contributing factors, while economic precarity, such as unpaid family workers, was an extreme exacerbating factor (IRR ≈ 1.52). These findings demonstrate that, compared to vulnerability indices, GLM offers a superior, evidence-based framework for identifying high-impact intervention areas. Shifting resource allocation towards flood mitigation and targeted resilience investments in education and economic stability is recommended.
Hawai‘i’s economy, heavily specialized in tourism, is particularly vulnerable to shocks that disrupt tourism numbers. The Maui economy is even more dependent on tourists, and the extraordinary losses from the 2023 wildfires in Lahaina and Kula continue to dampen tourist numbers. To help understand the wider economic effects of the Maui wildfires, we quantify the statewide reduction in tourism spending in 2023 and 2024 and use the inter-county input output tables to construct a model to estimate the corresponding loss in its economic contribution. Our analysis reveals a steep contraction in Maui’s economy and traces negative spillovers from reduced spending on Maui to other counties in Hawai‘i, particularly Honolulu. Relative to the 12-month pre-wildfire baseline, the tourism expenditure shock implies an average employment impact of about 18,000 jobs in Maui County over September–December 2023, narrowing to just over half that magnitude, on average, throughout 2024. In late 2023, travel substitution toward Hawaiʻi Island and Kauaʻi was largely offset by declines on Oʻahu, leaving the total similar in magnitude to Maui alone. In 2024, statewide impacts amounted to approximately 23,100 full-time equivalent jobs and 2.3 billion in output, as the short-term substitution effects dissipate. Although the fires occurred on Maui, up to 28
The crisis caused by COVID-19 revealed the global unpreparedness to handle the impact of a pandemic. At the outbreak of a pandemic, time is the key variable that can save lives and reduce financial losses. In the present paper, we propose, as a risk transfer tool, a reinsurance product mainly for developing countries, based on a parametric insurance design, that can supplement a state’s social insurance during a pandemic. The key feature of the proposed social reinsurance is a conditional payout function: the trigger provides guaranteed and immediate financing at the onset of a pandemic, while the cap links further payments to infection dynamics and the effectiveness of government measures. This two-step structure offers a win–win outcome, by delivering unconditional early support consistent with insurance principles, while at the same time incentivising proactive risk management and addressing market concerns over moral hazard. We develop the cap-curve concept as a benchmark mechanism that can be constructed from pooled early-wave infection-speed profiles across comparable countries or regions, and used to assess whether subsequent payouts remain justified. We illustrate the approach by exploring different trigger candidates and by constructing anonymised benchmark and policyholder infection-speed curves calibrated on early COVID-19 dynamics. Any numerical illustrations are intended to demonstrate contract mechanics rather than provide implementable market pricing.
Coastal communities continue to face escalating flood risks due to changing climate patterns, yet conventional flood risk maps fail to communicate these dynamic threats effectively. This study examines the capitalization of baseline Federal Emergency Management Agency’s (FEMA) 100-year floodplains and continuous probability-based flood hazard information into property values following Hurricane Harvey in Harris County, Texas. Using a repeat-sales model, we analyze price changes within the same properties before and after Hurricane Harvey employing a quasi-experimental difference-in-difference estimation strategy. Our findings reveal that inundated properties within the 100-year floodplain experienced a price discount of approximately 10.8
Flooding is a recurrent disaster in the revirine areas of Bangladesh, yet its impacts on river-dependent livelihoods remain poorly understood at the local scale. During the 2024 nationwide floods, communities along the Halda River were severely affected, with riverbank households facing disruption of both subsistence and income-generating activities. This study examines livelihood vulnerability and coping mechanisms in three unions of Hathazari Upazila, using household surveys (n = 100), focus group discussions, key informant interviews, and participatory observations. Results show widespread losses, including income loss (85
East Africa remains heavily reliant on agriculture, making it particularly vulnerable to economic instability associated with climatic variability, especially fluctuations in precipitation and temperature. This study empirically examines the long-term relationship between climate change variability and food price inflation in East Africa, with a specific focus on temperature and precipitation anomalies. Using balanced panel data from five East African countries spanning the period from 1982 to 2023, the analysis employs a Pooled Mean Group (PMG) estimator within a dynamic panel ARDL framework, alongside Panel-Corrected Standard Errors (PCSE) and Feasible Generalized Least Squares (GLS) using the Prais-Winsten transformation, to address issues of serial autocorrelation, heteroskedasticity, and cross-sectional dependence. The findings reveal that below-average precipitation is significantly associated with rising food prices, as it disrupts agricultural output. At the same time, higher-than-normal temperatures are strongly associated with increased food price inflation due to heat stress on crops and reduced yields. These results underscore the structural vulnerability of East African food systems to climate shocks, highlighting the urgent need for climate-resilient agricultural and macroeconomic policies to safeguard food affordability and economic stability in the region.
The southwestern part of Bangladesh is highly vulnerable to frequent and severe meteorological events, which are exacerbated by rapid climate change. This study addresses the imperative for effective risk reduction in agriculture, given the escalating frequency and intensity of disasters in this region. As conventional markets for crop insurance are lacking, the research employs the Contingent Valuation Method (CVM) to estimate farmers’ Willingness to Pay (WTP) for weather-risk-induced crop insurance programs in three environmentally hazard-prone and geographically vulnerable districts: Khulna, Satkhira, and Bagerhat. A multistage sampling technique was used to select 360 farm households, predominantly involved in paddy production across six villages, comprising farmers of varying scales, though mostly smallholders. The study proposes a hypothetical crop insurance scheme, presenting two benefit packages (ISP1 and ISP2) alongside a status quo option to mitigate yield loss and weather-related risks. Despite ISP2 offering more comprehensive benefits, farmers overwhelmingly prefer ISP1 for its balance of effectiveness and affordability. Approximately 78
