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The demand for flood insurance is low when the frequency and severity of flood disasters are increasing due to climate change. We show that beliefs about climate change influence homeowners' choice and level of flood insurance coverage. The demand for voluntary flood insurance coverage for homes and contents is higher in areas with more people who are worried about global warming. Property‐level analysis shows that individuals are more likely to terminate flood insurance after unanticipated premium increases if they do not perceive climate change as a risk. We use the heterogeneous impact of widening partisan polarization on climate change beliefs to rule out alternative explanations. [ABSTRACT FROM AUTHOR]

We use a unique feature of California's property tax system to empirically identify the causal effect of selling homeowners' past property tax payments on their choice of listing price. Although past property taxes are sunk costs, we find that they have a significant positive effect on the sellers' choice of listing price, which is inconsistent with rational models of decision making. This effect is stronger when sellers expect to sell at a loss relative to their purchase price and for properties whose value is harder to assess. The effect of property taxes on listing price is mostly transmitted to the selling price, which is consistent with the idea that buyers use listing prices as anchors to assess property values. Overall, our results suggest that sunk costs affect prices in the housing market. This paper was accepted by Tomasz Piskorski, finance. Supplemental Material: Data files are available at https://doi.org/10.1287/mnsc.2021.4285. [ABSTRACT FROM AUTHOR]

Does salient information on social media influence individuals' economic decisions and beliefs? Using aggregated data from Facebook and a difference-in-differences strategy, I show that individuals who are socially connected to someone affected by Hurricane Harvey are more likely to purchase flood insurance policies after the event. This effect is stronger in areas at higher risk of flooding. Being socially connected to someone affected by Hurricane Harvey also influences individuals' perceptions of global warming. [ABSTRACT FROM AUTHOR]

Social distancing, a non-pharmaceutical tactic aimed at reducing the spread of COVID-19, can arise because individuals voluntarily distance from others to avoid contracting the disease. Alternatively, it can arise because of jurisdictional restrictions imposed by local authorities. We run reduced form models of social distancing as a function of county-level exogenous demographic variables and jurisdictional fixed effects for 49 states to assess the relative contributions of demographic and jurisdictional effects in explaining social distancing behavior. To allow for possible spatial aspects of a contagious disease, we also model the spillovers associated with demographic variables in surrounding counties as well as allow for disturbances that depend upon those in surrounding counties. We run our models weekly and examine the evolution of the estimated coefficients over time since the onset of the COVID-19 pandemic in the United States. These estimated coefficients express the revealed preferences of individuals who were able to and chose to stay at home to avoid the disease. Stay-at-home behavior measured using cell phone tracking data exhibits considerable cross-sectional variation, increasing over nine-fold from the end of January 2020 to the end of March 2020, and then decreasing by about 50% through mid-June 2020. Our estimation results show that demographic exogenous variables explain substantially more of this variation than predictions from jurisdictional fixed effects. Moreover, the explanations from demographic exogenous variables and jurisdictional fixed effects show an evolving correlation over the sample period, initially partially offsetting, and eventually reinforcing each other. Furthermore, the predicted social distance from demographic exogenous variables shows substantial spatial autoregressive dependence, indicating clustering in social distancing behavior. The increased variance of stay-at-home behavior coupled with the high level of spatial dependence can result in relatively intense hotspots and coldspots of social distance, which has implications for disease spread and mitigation. [ABSTRACT FROM AUTHOR]

The National Flood Insurance Program (NFIP) was created in 1968 and allows homeowners, renters, and businesses to purchase flood insurance from the federal government. During the summer of 2019, without compromising privacy, the Federal Emergency Management Agency (FEMA) released two datasets containing roughly 50 million flood insurance policy observations (beginning in 2009) and 2.5 million flood insurance claims (beginning in 1970). Researchers can now download and evaluate the entire policies and claims datasets in machine-readable format, bypassing the complex request procedures of the past. We explore what is included in this policy and claims data and how they might be used to examine flood insurance related topics. We provide real estate academics and industry professionals with the details of the 44 usable policy data variables and the 37 usable claims data variables, which we group into seven categories: Locational, Structural, Occupancy, Policy Terms, Zone/Elevation/Rating, Premiums, and Claims. In an effort to aid researchers with the initial complexities of working with the data, we provide sample R-code that can be altered to analyze NFIP data. Finally, for illustration, we demonstrate how the NFIP data can be merged with data from both the American Community Survey and Zillow to study the determinants of flood insurance take-up. [ABSTRACT FROM AUTHOR]

In this paper, we show that areas affected by major flood disasters attract less affluent and less creditworthy homebuyers. House prices drop after a flood disaster. The households that purchased homes after a major flood disaster had 2–7% lower annual income and were 8.5% more likely to be seriously delinquent on their mortgages. We find the effects are stronger after repeated flooding incidents. Demand by minority homebuyers does not increase after the disasters. Lenders charge a higher interest rate and are more likely to securitize post-flood mortgages, which is consistent with the idea that lenders infer that the post-flood loans they originate are of lower credit quality ex-ante. Overall our results imply that more affordable house prices in flood-prone areas attract less affluent and more economically vulnerable households. [ABSTRACT FROM AUTHOR]

Although some have proposed eliminating the National Flood Insurance Program (NFIP) to reduce government expenditures, other alternatives exist that could reduce the cost of the program and increase its viability, such as increasing deductibles, which may increase participation and revenue. The​ recently released FIMA NFIP Redacted Policies Data Set provides unprecedented opportunities to examine homeowner deductible choices for flood insurance policies using policy-level data. The menu of deductibles currently ranges from $1,000 to $10,000 in Special Flood Hazard Areas (SFHAs), but until April 1, 2015, the maximum deductible was $5,000. Using a matched sample of 252,280 SFHA policies that were active for the 2013–2019 time period, we provide insight regarding characteristics of homeowners who chose the maximum deductible as well as those who switched from the $5,000 to the new $10,000 deductible. Consistent with nudge theory and stickiness, we show that the majority of the homeowners accept the default deductible option. Individuals in high-income and high-premium areas were more likely to select the maximum dedu​ctible. Level of education and past flood events do not impact whether people decide to select the maximum deductible option. [ABSTRACT FROM AUTHOR]

This article attempts to quantitatively measure the various influences on mobile phone adoption at the bottom of the pyramid (BoP) in Bangladesh, Pakistan, India, Sri Lanka, the Philippines, and Thailand. Based on an existing theoretical framework, adoption is modeled by fitting a logit model to a large six country dataset. The study finds evidence for the importance of social influence in mobile adoption in two modes: one that exerts pressure on individuals to adopt, and another that helps to generate benefits via social networks that are tied in with economic and business networks. The article elaborates on the resulting social policy implications for using mobile telephone services to fight poverty at the BoP in these and similar countries. [ABSTRACT FROM AUTHOR]

Mobile phone access is widespread in Asia; voice connectivity has been achieved for the most part through intense competition, with prices being driven down to almost unsustainable levels. Against the backdrop of intense competition, new services and applications, such as price information alerts, news alerts, mobile money applications, and mobile Internet services, may provide new revenue sources, allowing operators to expand services. More important, from a development perspective, they also offer a way to get information and services with lower transaction costs to customers at the "bottom of the pyramid." This article examines the use of such "more-than-voice" services among telecom users at the bottom of the pyramid in emerging Asia. Through a logistical regression model, it attempts to understand what factors can predict their use in order to inform operators on how they can better serve these markets, and to educate policymakers on how they can assist with policies that will favor greater access. [ABSTRACT FROM AUTHOR]