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This study investigates the impact of hurricane-induced discharges from Superfund sites on residents’ risk perception and housing values in Harris County, Texas. Employing a difference-in-differences hedonic approach with property sales data from 2013 to 2019, we analyze how residents adjust their risk perception based on environmental hazard information and whether this affects the real estate market. Examining proximity to Superfund sites, we find a 27% reduction in price for houses located within half a mile of impacted sites, diminishing with distance. The findings provide valuable insights for enhancing hazardous waste management through targeted interventions, risk assessments, and response plans. 

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. 

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. 

We examined whether floods and cyclones, the shocks that are transient in nature, affect interregional migration differently compared to riverbank erosion that causes loss of lands and thus generates permanent shocks. We tracked Household Income and Expenditure Survey 2000 participants in nine coastal districts of Bangladesh and collected further information in 2015. Our analyses suggest that both transient and permanent shocks induce households to migrate, but the effect is higher for the latter category. Using a difference-in-differences setting, we find that migrants’ income and expenditure increase relative to their counterparts, indicating that facilitating migration may improve welfare in disaster-prone countries. 

Abstract Critical infrastructures are ubiquitous and their interdependencies have become more complex leading to their uncertain behaviors in the aftermath of disasters. The article develops an integrated economic input–output model that incorporates household‐level survey data from Hurricane Sandy, which made its landfall in 2012. In this survey, 427 respondents who were living in the state of New Jersey during Hurricane Sandy were used in the study. The integration of their responses allowed us to show the probability and duration of various types of critical infrastructure failures due to a catastrophic hurricane event and estimate the economic losses across different sectors. The percentage of disruption and recovery period for various infrastructure systems were extracted from the survey, which were then utilized in the economic input–output model comprising of 71 economic sectors. Sectors were then ranked according to: (i) inoperability, the percentage in which a sector is disrupted relative to its ideal level, and (ii) economic loss, the monetary worth of business interruption caused by the disaster. With the combined infrastructure disruptions in the state of New Jersey, the model estimated an economic loss of $36 billion, which is consistent with published estimates. Results from this article can provide insights for future disaster preparedness and resilience planning.