No abstract

Pandemic influenza represents a serious threat not only to the population of the United States, but also to its economy. In this study, we analyze the total economic consequences of potential influenza outbreaks in the United States for four cases based on the distinctions between disease severity and the presence/absence of vaccinations. The analysis is based on data and parameters on influenza obtained from the Centers for Disease Control and the general literature. A state-of-the-art economic impact modeling approach, computable general equilibrium, is applied to analyze a wide range of potential impacts stemming from the outbreaks. This study examines the economic impacts from changes in medical expenditures and workforce participation, and also takes into consideration different types of avoidance behavior and resilience actions not previously fully studied. Our results indicate that, in the absence of avoidance and resilience effects, a pandemic influenza outbreak could result in a loss in U.S. GDP of $25.4 billion, but that vaccination could reduce the losses to $19.9 billion. When behavioral and resilience factors are taken into account, a pandemic influenza outbreak could result in GDP losses of $45.3 billion without vaccination and $34.4 billion with vaccination. These results indicate the importance of including a broader set of causal factors to achieve more accurate estimates of the total economic impacts of not just pandemic influenza but biothreats in general. The results also highlight a number of actionable items that government policymakers and public health officials can use to help reduce potential economic losses from the outbreaks.

We examine the reduction in London Underground passenger journeys in response to the July 2005 bombings. Using entrance data for London Underground stations between 2001 and 2007, we incorporate demand and supply factors in a multivariate time-series regression model to estimate changes in passenger journeys between different Underground lines. We find that passenger journeys fell by an average of 8.3% for the 4 months following the attacks. This amounts to an overall reduction of 22.5 million passenger journeys for that period. Passenger journeys returned to predicted levels during September 2005, yet we find evidence of reduced travel until June 2006. Our estimates controlled for other factors, including reduced Underground service provision due to damage from the attacks, economic conditions, and weather, yet substantial reductions in passenger journeys remained. Around 82% of passenger journey reductions following the 2005 attacks cannot be attributed to supply-side factors or demand-side factors such as economic conditions, weather, or the summer school-break alone. We suggest that this reduction may partially be due to an increased perception of the risk of Underground travel after the attacks.

While extensive risk perception research has focused on emotions, cognitions, and behavior at static points in time, less attention has been paid to how these variables might change over time. This study assesses how negative affect, threat beliefs, perceived risk, and intended avoidance behavior change over the course of an escalating biological disaster. A scenario simulation methodology was used that presents respondents with a video simulation of a 15-day series of local news reports to immerse respondents in the developing details of the disaster. Systemic manipulation of the virus's causal origin (terrorist attack, medical lab accident, unknown) and the respondent's proximity to the virus (local vs. opposite coast) allowed us to investigate the dynamics of public response. The unfolding scenario was presented in discrete episodes, allowing responses to be tracked over the episodes. The sample includes 600 respondents equally split by sex and by location, with half in the Washington, DC area, and half in the Los Angeles area. The results showed respondents' reactions to the flu epidemic increased as the disaster escalated. More importantly, there was considerable consistency across respondents' emotional, cognitive, and behavioral responses to the epidemic over the episodes. In addition, the reactions of respondents proximally closer to the epidemic increased more rapidly and with greater intensity than their distant counterparts. Finally, as the flu epidemic escalated, both terrorist and accidental flu releases were perceived as being less risky and were less likely to lead to avoidance behavior compared to the unknown flu release.

No abstract

Cap and trade remains attractive to many state governments because it provides a much-needed source of additional revenue when greenhouse gas emission allowances are auctioned to the highest bidder. We analyze the income distribution impacts of the California Global Warming Solutions Act under alternative policy designs. These include the free allocation of emission allowances versus recycling of auction revenues through proportional income tax relief and a per capita dividend. The analysis is undertaken under conditions where significant economic gains, rather than losses, are projected for the policy, and in the context of the new electricity pricing regulatory environment in which passing along the opportunity costs of using free allowances may not be approved. We adapt and enhance the Regional Economic Models, Inc. Policy Insight Plus Model and apply it for the first time to estimate the income distribution impacts of cap and trade. The analysis illustrates the importance of considering macroeconomic impacts and identifies important efficiencyequity tradeoffs. The method and results are generalizable to the dozens of states and regions still formulating or revising climate action plans in the United States and to many regions and nations around the world. (JEL D31, R11, Q54) , and three Next 10 referees, as well as a reviewer and the editor of this journal. We are indebted to David Kennedy of the California Air Resources Board for providing us with simulations of direct economic impact we used as a major input to our scenarios. We also wish to thank Steve Miller for reconciling the CA REMI Model with the economic and energy consumption forecast included in the ENERGY 2020 model.

No abstract

the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.