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Climate- and weather-related disasters have become increasingly frequent and costly, resulting in substantial government spending on disaster assistance. Yet less is known about the effectiveness of disaster aid in enhancing community resilience to future disaster risks. This study examines multiple post-disaster aid programs implemented by the US federal government to support state and local governments as well as households and private businesses. Specifically, we estimate the risk-mitigating effects of these disaster-related programs by linking program spending with reported economic losses from flooding. Our empirical analysis utilizing panel data at the county level finds that low-interest disaster loans lead to the largest reduction in subsequent flooding damage, and grants targeting public infrastructure restoration and flood control measures also reduce future flooding losses. Results suggest a limited loss-mitigating effect of disaster cash aid given to private individuals. These findings provide important implications for federal disaster policy design and suggest that more efficiency gains could be realized by redistributing funds and streamlining processes across programs and agencies.

In this paper, we empirically examine whether the Federal Emergency Management Agency’s Public Assistance (PA) program, which targets postdisaster cleanup and infrastructure rehabilitation, affects household purchases of flood insurance. Using the fixed-effects model with instrumental variables to address the endogeneity of disaster aid, we find that increased PA grants reduce a county’s flood insurance take-up rates, thereby driving down its total insurance coverage and premiums paid. Our findings provide empirical evidence on the crowding-out effect of public disaster programs, and shed light on their implicit social costs and increased federal financial exposure to natural disasters and climate change.

Understanding socioeconomic consequences of natural disasters both locally and nationally is critical in assessing and informing mitigation strategies to combat future catastrophic threats. We develop a state-level computable general equilibrium model and assess the vulnerability of state and US national economies to surge events affecting coastal communities and strategic industrial assets including petroleum and chemical manufacturing in the south-eastern region of Texas. In addition to enumerating these impacts, our model also assesses loss avoidance associated with one kind of adaptation strategy, a storm surge suppression system, that has been proposed for the region to address growing concerns over storm surge inundation. Our results indicate persistent and adverse long-term impacts of storm surge events on the economies of Texas and the USA without the surge suppression system. Importantly, while neighboring states may temporarily benefit from substitution effects and reallocation of resources, the majority of states will suffer welfare losses as a result of surge-induced impacts in Texas. Adjusting impacts by storms’ return probabilities, the average annualized decline in Texas Gross State Product is approximately 0.05% in 2066, corresponding to $5 billion, while welfare and personal income will decline by 0.05% and 0.04%, respectively. Model simulations with the storm suppression system indicate moderation in negative impacts. Our research provides a modeling framework for assessing economic impacts of disasters and further contributes to estimating ripple effects on national and regional economies.

Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly USD 30 billion in damage after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the relationship between eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model and National Flood Insurance Program (NFIP) insurance damage data. The NFIP insurance database contains a large amount of building damage data, building stories, and elevation, as well as other information from the Ike event. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories. We also found that the resulting damage functions are steeper than those developed for residential structures in many other locations.

Numerous studies have evaluated the impact of Extension on farm productivity and related outcomes. Here we use annual data from 1983 to 2010 covering the 50 U.S. states to examine the impact of Extension on net changes in the number of farmers. The historical transition of farmers out of U.S. agriculture raises the question of whether Cooperative Extension and underlying Hatch-funded research spending keeps farmers in agriculture or accelerates their exit. On balance, nearly 500,00 more farmers left than entered agriculture over the period studied. We estimate that without Extension, as many as 137,700 (or 28%) additional farmers would have disappeared on net. Overall, Extension programs are a remarkably cost effective way of keeping farmers in agriculture. Alternatively, shifting just 1.5% of federal farm program payments to Extension would have reduced net exits over this period by an estimated 11%, or 55,000 farmers.

Cartographic display of cross-scale phenomena and user-centered design are considered through a discussion of the development of an interactive web map depicting local-to-national economic impacts of hurricane storm surge events in Galveston Bay, Texas. Map development and design (as informed by stakeholder focus groups) is described, including approaches to presenting complex, cross-scale impacts of surge events across multiple years and scenarios. Particular consideration is given to how designs may communicate complexity without overly taxing users' mental and perceptual resources (measured via NASA task-load index) or outstripping their mapping/domain expertise. The map produced uses linked map views to communicate multiple, cross-scale storm surge impacts. The production process and associated user testing highlighted the importance of matching tool complexity to users' needs and levels of expertise, including through the use of tiered interface design. Optimizing the design of such maps to meet users' needs is essential to fostering public hazard literacy.

The role of socio-demographic vulnerability to hazards is an increasingly important aspect for consideration in disaster mitigation and adaptation. This paper examines the spatial adjustments of populations to the 2008 Hurricane Ike by estimating the effects of damage on the changes of socially vulnerable populations pre- and post-Hurricane Ike. Multivariate regression models are used to understand household-level adjustments in different flood zones and inundation levels at the block-group level in Galveston county. In contrast to past literature that suggests that vulnerable populations remain or move into hazardous areas post-disaster, our results indicate that socially vulnerable populations have moved out of highly damaged areas. The tremendous investment opportunity post-disaster and the slow distribution of funds to recover public housing on Galveston Island provide potential explanation of the estimated adjustment patterns. Analyzing post disaster adjustments offers important insights into the “resilient” recovery of Galveston County post-Hurricane Ike. Our results also point to potential vulnerabilities that may arise in the future because of the change in community identity and the loss of social memory. Understanding disaster-driven changes in community make-up will help inform potential recovery trajectories from future catastrophes.

In this paper, we examine the impacts of floods on businesses and the efficacy of small business administration (SBA) disaster loans on mitigating disaster aftereffects. We find lack of business adaptation to extreme events in the short term, indicating their extreme vulnerability to flood disasters. Our results further indicate that subsidized disaster loans are important for businesses, with statistically significant effects estimated for businesses employing fewer than 50 people. At the margin, for every additional dollar spent on disaster loans per establishment in a county, four small businesses survive. Gloomy projections about increasing frequency and severity of disasters imply there will be significant loss in local economic activities because of increased vulnerability of small businesses to these incidents. Moreover, these effects will have implications nationwide, given the vital role small businesses play in creating jobs.

We develop a county-level recursive dynamic computable general equilibrium (CGE) model of Orleans Parish (OP) to examine local economic impacts of migration and brain drain after Hurricane Katrina. To incorporate hurricane-induced brain drain in the CGE model, we use a reduced-form model to estimate the change in the share of college graduates caused by hurricane-induced damages. Calibrating the model using pre-disaster social accounting matrices (SAMs) in 2004, we find that permanent loss in population and skilled labor results in 33.57% decline in county-level gross regional product (GRP) in 2012 relative to the 2012 business as usual scenario (BAU) that assumes steady annual growth without Hurricane Katrina. Interestingly, we find that skill loss causes larger decline in GRP than overall decline in population. After accounting for post-disaster public assistance by recalibrating model using 2012 SAMs, we find a lower declining rate of 6.36% in GRP.

This paper examines household adjustments to Hurricane Katrina by estimating the effects of Katrina-induced damages on changes in household demographics and income distributions in the Orleans Parish between 2000 and 2012. Adjustment patterns are found to be heterogeneous across ethno-racial segments, income classes, and educational attainment. Shares of middle-income and affluent households along with educated individuals decreased in severely damaged areas relative to less damaged ones. Also the share of individuals with lower educational levels and incomes below the poverty line increased in severely damaged block groups. Furthermore, the share of the white population decreased and the share of the black population increased in damaged areas for both home owners and renters. Overall adjustment patterns suggest that resource and financially constrained population adjust by moving into previously damaged areas, while economically capable households adjust by relocating to safer areas within or outside of the parish. Given estimated increases in vulnerable segments of the population in hazardous hotspots, public efforts should focus on either revitalizing poorer neighborhoods, by investing in long-term hazard mitigation measures and improving infrastructure, with segregated housing or assisting gradual population retreat to enhance community resilience and reduce vulnerability and exposure to future catastrophic events.