Economics of disasters and climate change最新文献_第9页

Does Stringency of Lockdown Affect Air Quality? Evidence from Indian Cities. 封锁的严格程度会影响空气质量吗？印度城市的证据

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-08-15 DOI: 10.1007/s41885-020-00072-1

Surender Kumar, Shunsuke Managi

引用次数: 0

Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty. COVID-19 对家庭消费和贫困的社会经济影响。

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-07-23 DOI: 10.1007/s41885-020-00070-3

Amory Martin, Maryia Markhvida, Stéphane Hallegatte, Brian Walsh

{"title":"Socio-Economic Impacts of COVID-19 on Household Consumption and Poverty.","authors":"Amory Martin, Maryia Markhvida, Stéphane Hallegatte, Brian Walsh","doi":"10.1007/s41885-020-00070-3","DOIUrl":"10.1007/s41885-020-00070-3","url":null,"abstract":"The COVID-19 pandemic has caused a massive economic shock across the world due to business interruptions and shutdowns from social-distancing measures. To evaluate the socio-economic impact of COVID-19 on individuals, a micro-economic model is developed to estimate the direct impact of distancing on household income, savings, consumption, and poverty. The model assumes two periods: a crisis period during which some individuals experience a drop in income and can use their savings to maintain consumption; and a recovery period, when households save to replenish their depleted savings to pre-crisis level. The San Francisco Bay Area is used as a case study, and the impacts of a lockdown are quantified, accounting for the effects of unemployment insurance (UI) and the CARES Act federal stimulus. Assuming a shelter-in-place period of three months, the poverty rate would temporarily increase from 17.1% to 25.9% in the Bay Area in the absence of social protection, and the lowest income earners would suffer the most in relative terms. If fully implemented, the combination of UI and CARES could keep the increase in poverty close to zero, and reduce the average recovery time, for individuals who suffer an income loss, from 11.8 to 6.7 months. However, the severity of the economic impact is spatially heterogeneous, and certain communities are more affected than the average and could take more than a year to recover. Overall, this model is a first step in quantifying the household-level impacts of COVID-19 at a regional scale. This study can be extended to explore the impact of indirect macroeconomic effects, the role of uncertainty in households' decision-making and the potential effect of simultaneous exogenous shocks (e.g., natural disasters).","PeriodicalId":72868,"journal":{"name":"Economics of disasters and climate change","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376321/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38303310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accounting for Global COVID-19 Diffusion Patterns, January-April 2020. 2020 年 1-4 月全球 COVID-19 传播模式的核算。

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-09-04 DOI: 10.1007/s41885-020-00071-2

Yothin Jinjarak, Rashad Ahmed, Sameer Nair-Desai, Weining Xin, Joshua Aizenman

{"title":"Accounting for Global COVID-19 Diffusion Patterns, January-April 2020.","authors":"Yothin Jinjarak, Rashad Ahmed, Sameer Nair-Desai, Weining Xin, Joshua Aizenman","doi":"10.1007/s41885-020-00071-2","DOIUrl":"10.1007/s41885-020-00071-2","url":null,"abstract":"Key factors in modeling a pandemic and guiding policy-making include mortality rates associated with infections; the ability of government policies, medical systems, and society to adapt to the changing dynamics of a pandemic; and institutional and demographic characteristics affecting citizens' perceptions and behavioral responses to stringent policies. This paper traces the cross-country associations between COVID-19 mortality, policy interventions aimed at limiting social contact, and their interactions with institutional and demographic characteristics. We document that, with a lag, more stringent pandemic policies were associated with lower mortality growth rates. The association between stricter pandemic policies and lower future mortality growth is more pronounced in countries with a greater proportion of the elderly population and urban population, greater democratic freedoms, and larger international travel flows. Countries with greater policy stringency in place prior to the first death realized lower peak mortality rates and exhibited lower durations to the first mortality peak. In contrast, countries with higher initial mobility saw higher peak mortality rates in the first phase of the pandemic, and countries with a larger elderly population, a greater share of employees in vulnerable occupations, and a higher level of democracy took longer to reach their peak mortalities. Our results suggest that policy interventions are effective at slowing the geometric pattern of mortality growth, reducing the peak mortality, and shortening the duration to the first peak. We also shed light on the importance of institutional and demographic characteristics in guiding policy-making for future waves of the pandemic.","PeriodicalId":72868,"journal":{"name":"Economics of disasters and climate change","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38356321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

It's Awful, Why Did Nobody See it Coming? 太可怕了，为什么没人预见到?

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-09-01 DOI: 10.1007/s41885-020-00075-y

Ilan Noy, Shunsuke Managi

引用次数: 7

Impact of COVID-19 on the Economic Output of the US Outbreak's Epicenter. 新冠肺炎疫情对美国疫情中心经济产出的影响

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-07-21 DOI: 10.1007/s41885-020-00069-w

Orkideh Gharehgozli, Peyman Nayebvali, Amir Gharehgozli, Zaman Zamanian

{"title":"Impact of COVID-19 on the Economic Output of the US Outbreak's Epicenter.","authors":"Orkideh Gharehgozli, Peyman Nayebvali, Amir Gharehgozli, Zaman Zamanian","doi":"10.1007/s41885-020-00069-w","DOIUrl":"https://doi.org/10.1007/s41885-020-00069-w","url":null,"abstract":"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.","PeriodicalId":72868,"journal":{"name":"Economics of disasters and climate change","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41885-020-00069-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38303309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 46

Drivers of COVID-19 Stay at Home Orders: Epidemiologic, Economic, or Political Concerns? COVID-19居家令的驱动因素:流行病学、经济还是政治问题?

Economics of disasters and climate change Pub Date : 2020-01-01 Epub Date: 2020-08-17 DOI: 10.1007/s41885-020-00073-0

Lea-Rachel Kosnik, Allen Bellas

引用次数: 12

Oasis of Resilience? An Empirical Investigation of Rain Water Harvesting Systems in a High Poverty, Peripheral Community 弹性绿洲?高贫困边缘社区雨水收集系统的实证研究

Economics of disasters and climate change Pub Date : 2019-12-10 DOI: 10.1007/s41885-019-00050-2

Daniel P. Aldrich, Courtney Page-Tan

引用次数: 2

Extreme Weather and Poverty Risk: Evidence from Multiple Shocks in Mozambique 极端天气与贫困风险:来自莫桑比克多重冲击的证据

Economics of disasters and climate change Pub Date : 2019-12-07 DOI: 10.1007/s41885-019-00049-9

J. Baez, G. Caruso, Chiyu Niu

引用次数: 22

Distributional Impacts of Weather and Climate in Rural India 印度农村地区天气和气候对分布的影响

Economics of disasters and climate change Pub Date : 2019-12-05 DOI: 10.1007/s41885-019-00051-1

Barbora Šedová, M. Kalkuhl, R. Mendelsohn

引用次数: 0

An Overview of the Technological Environmental Hazards over the Last Century 上个世纪技术环境危害综述

Economics of disasters and climate change Pub Date : 2019-11-30 DOI: 10.1007/s41885-019-00053-z

G. Halkos, Argyro Zisiadou

引用次数: 8