Household Preferences for Managing Coastal Vulnerability: State vs. Federal Adaptation Fund

Pavel, Tanvir; Mozumder, Pallab

doi:10.1007/s41885-019-00046-y

Cited by 5 publications

(2 citation statements)

References 51 publications

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“…The US federal government (and governments around the globe) has (have) been continuously working on strategies such as stimulus packages and employment of different monetary policy tools to control and reduce the magnitude of the economic downfall, but the long term effects (including costs and benefits) of such policies remain to be studied in the future work. This experience will also renew our attention toward fields of studies focusing on disasters aggregate management and preparedness, demographic dynamics, and private preparedness and responses to the disasters (Kellenberg and Mobarak 2008 ; Maruta et al 2020 ; Goeschl and Managi 2019 ; Pavel and Mozumder 2019 ; Owen and Noy 2019 ). Moreover, for the US specifically, we believe this can be the time to participate in (and pay specific attention to) the threads of studies focusing on the relationship between individual and household characteristics such as income and wealth percentile, gender, race, education and so on; and the unbalanced negative impacts of the economic downfall.…”

Section: -Step Var Modelmentioning

confidence: 90%

Impact of COVID-19 on the Economic Output of the US Outbreak’s Epicenter

et al. 2020

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Coronavirus disease of 2019 (COVID-19) started in December 2019 in Wuhan, China. In a few months, it has become a pandemic with devastating consequences for the global economy. By the end of June, with almost 2.6 million confirmed COVID-19 cases, United States is above other countries in the rankings. Furthermore, New York with more than 416 thousand cases is the epicenter of outbreak in the US and had more cases than any other countries in the world until first half of June. In this paper, we use a two-step Vector Auto Regressive (VAR) model to forecast the effect of the virus outbreak on the economic output of the New York state. In our model, we forecast the effect of the shutdown on New York's Gross Domestic Product (GDP) working with Unemployment Insurance Claim series representing a workforce factor, as well as the Metropolitan Transportation Authority (MTA) ridership data indicating the economic activity. We predict annualized quarterly growth rate of real GDP to be between-3.99 to-4.299% for the first quarter and between-19.79 to-21.67% for the second quarter of 2020.

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Section: -Step Var Modelmentioning

confidence: 90%

Impact of COVID-19 on the Economic Output of the US Outbreak’s Epicenter

et al. 2020

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“…A number of studies underline the role of the human population in climate change adaptation, referring both to the size of households [43] and, more importantly, the density [44] and proximity to dangerous inevitable natural events [45]. Higher population density, especially in urban areas, may provide enabling conditions that increase adaptation [44] together with external interventions [46], but there is still conflicting evidence as to whether higher density in large conurbations does actually increase vulnerability [47][48][49][50].…”

Section: Introduction-rationale For the Studymentioning

confidence: 99%

A Hierarchical Multilevel Approach in Assessing Factors Explaining Country-Level Climate Change Vulnerability

et al. 2020

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Assessing vulnerability is key in the planning of climate change adaptation policies and, more importantly, in determining actions increasing resilience across different locations. This study presents the results of a hierarchical linear multilevel modeling approach that utilizes as dependent variable the Notre Dame Global Adaptation Initiative (ND-GAIN) Climate Change Vulnerability Index and explores the relative impact of a number of macro-level characteristics on vulnerability, including GDP, public debt, population, agricultural coverage and sociopolitical and institutional conditions. A 1995–2016 annual time series that yields a panel dataset of 192 countries is employed. Findings suggest that country-level climate change vulnerability is responding (strongly) to the majority of the explanatory variables considered. Findings also confirm that less-developed countries demonstrate increased vulnerability compared to the developed ones and those in transition stages. While these results indeed warrant further attention, they provide a background for a more nuanced understanding of aspects defining country-level patterns of climate vulnerability.

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