This open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.
The coronavirus pandemic has upended local, national, and global food systems, and put the Sustainable Development Goals further out of reach. But lessons from the world’s response to the pandemic can help address future shocks and contribute to food system change. In the 2021 Global Food Policy Report, IFPRI researchers and other food policy experts explore the impacts of the pandemic and government policy responses, particularly for the poor and disadvantaged, and consider what this means for transforming our food systems to be healthy, resilient, efficient, sustainable, and inclusive. Chapters in the report look at balancing health and economic policies, promoting healthy diets and nutrition, strengthening social protection policies and inclusion, integrating natural resource protection into food sector policies, and enhancing the contribution of the private sector. Regional sections look at the diverse experiences around the world, and a special section on finance looks at innovative ways of funding food system transformation. Critical questions addressed include: - Who felt the greatest impact from falling incomes and food system disruptions caused by the pandemic? - How can countries find an effective balance among health, economic, and social policies in the face of crisis? - How did lockdowns affect diet quality and quantity in rural and urban areas? - Do national social protection systems such as cash transfers have the capacity to protect poor and vulnerable groups in a global crisis? - Can better integration of agricultural and ecosystem polices help prevent the next pandemic? - How did companies accelerate ongoing trends in digitalization and integration to keep food supply chains moving? - What different challenges did the pandemic spark in Asia, Africa, and Latin America and how did these regions respond?
COVID-19 is the most significant global crisis of any of our lifetimes. The numbers have been stupefying, whether of infection and mortality, the scale of public health measures, or the economic consequences of shutdown. Coronavirus Politics identifies key threads in the global comparative discussion that continue to shed light on COVID-19 and shape debates about what it means for scholarship in health and comparative politics. Editors Scott L. Greer, Elizabeth J. King, Elize Massard da Fonseca, and André Peralta-Santos bring together over 30 authors versed in politics and the health issues in order to understand the health policy decisions, the public health interventions, the social policy decisions, their interactions, and the reasons. The book’s coverage is global, with a wide range of key and exemplary countries, and contains a mixture of comparative, thematic, and templated country studies. All go beyond reporting and monitoring to develop explanations that draw on the authors' expertise while engaging in structured conversations across the book.
The Second Autumn Course on Mathematical Ecology was held at the Intern ational Centre for Theoretical Physics in Trieste, Italy in November and December of 1986. During the four year period that had elapsed since the First Autumn Course on Mathematical Ecology, sufficient progress had been made in applied mathemat ical ecology to merit tilting the balance maintained between theoretical aspects and applications in the 1982 Course toward applications. The course format, while similar to that of the first Autumn Course on Mathematical Ecology, consequently focused upon applications of mathematical ecology. Current areas of application are almost as diverse as the spectrum covered by ecology. The topiys of this book reflect this diversity and were chosen because of perceived interest and utility to developing countries. Topical lectures began with foundational material mostly derived from Math ematical Ecology: An Introduction (a compilation of the lectures of the 1982 course published by Springer-Verlag in this series, Volume 17) and, when possible, progressed to the frontiers of research. In addition to the course lectures, workshops were arranged for small groups to supplement and enhance the learning experience. Other perspectives were provided through presentations by course participants and speakers at the associated Research Conference. Many of the research papers are in a companion volume, Mathematical Ecology: Proceedings Trieste 1986, published by World Scientific Press in 1988. This book is structured primarily by application area. Part II provides an introduction to mathematical and statistical applications in resource management.
The global health and economic threats from the COVID-19 pandemic are not yet behind us. While the development of multiple safe and highly effective vaccines in less than a year is cause for hope, several significant dangers to recovery of global health and income are still clear and present: New concerning variants of SARS-CoV-2, the virus that causes COVID-19, continue to emerge at an alarming rate in different parts of the world; at the same time, vaccine rollouts have been shockingly inefficient even in some rich countries, while much of the developing world waits in line behind them for vaccines to arrive. The Briefing covers several policy areas in which cooperative forward-looking policy action will materially improve our chances of truly escaping today's pandemic and making future pandemics less costly.
Utilizing extensive research in economics, psychology, political science, neuroscience and evolutionary theory, Ananish Chaudhuri provides a critical perspective on the role of cognitive biases in decision-making during the Covid-19 pandemic. The extensive use of, and support for, stringent social distancing measures in particular is explored in depth.
On March 12th 2020, World Health Organization (WHO) declared the spreading of the new virus, 2019-nCoV, a pandemic. In Asia, the virus, more commonly referred to as COVID-19, has been spreading since the end of December. To contain the public health threat, almost all countries enforced a variety of measures, including lockdowns, to minimize face-to-face human interactions between the infected and the susceptible.While these vigilant measures save lives, they also generate a substantial negative economic shock that immediately halts demand and significantly disrupts supply, global production value chain and trade. The consequences are dire — considerable decline in output, massive surge in unemployment, countless bankruptcy cases, and unrelentless worries over financial stability. The result, a worldwide economic setback, is more severe than that experienced during the Great Financial Crisis of 2008-2009.Asia's experiences with COVID-19 precede that in the West. This fortuitous timing allows Asia to share its learnings drawn from experiences to benefit the world.The Asian Bureau of Finance and Economic Research's (ABFER) community has gathered a collection of insights to inform the public. Besides providing access to research on the pandemic conducted in Asia, these commentaries offer comprehensive information on the effects of the pandemic, the effectiveness of measures employed to contain it and the subsequent economic impacts from such implementation. With granular analyses of government policies and their associated economic rescue packages, these commentaries elucidate the hard trade-offs between public health protection and economic security. Finally, the commentaries address the broader impact of the pandemic on international trade, global value chains and society.
This edited volume discusses digital transformation in the context of the COVID-19 pandemic. In the wake of the COVID-19 pandemic and the widespread lockdown policies that followed, digital technologies were touted as an effective means towards ensuring continuity and minimal interruption of day-to-day operations for businesses and other institutions. Digital transformation, however, is an inherently complex process and the pressure of short adoption times may further increase complexities for organizations looking to foster digital technologies. This volume comprises original research contributions on theoretical foundations and empirical studies of digital transformations in the pandemic era. Written by academics and practitioners from diverse disciplines and industries, the chapters cover topics such as psychological and technical implications of pandemic situations, the economic, organizational, social, and legal implications of digital adoption, and case studies for digital transformation in different industries. This book will be useful for academics, technology professionals, business policy makers, NGO managers, and governments looking to optimize their digital transformation processes to better prepare their organizations in the presence of pandemic situations.
The Office for Budget Responsibility was established to provide independent and authoritative analysis of the UK's public finances. Part of this role includes producing the official economic and fiscal forecasts. This report sets out forecasts for the period to 2015-16. The report also assesses whether the Government is on course to meet the medium-term fiscal objectives and presents preliminary observations on the long-run sustainability of the public finances. Since the June forecast, the UK economy has recovered more strongly than initially expected. The GDP growth was greater than expected in both the 2nd and 3rd quarters, but that unemployment levels have risen to levels that the June forecast did not anticipate until the middle of 2012. In general the world economy has also grown more strongly. CPI inflation has remained slightly higher than expected in June, whilst public finances have performed as forecast. The interest rates on UK debt are lower than in June. The OBR forecasts that the economy will continue to recover from the recession, but at a slower pace than the recoveries of the 1970s, 1980s and 1990s. The publication is divided into 5 chapters with two annexes.
This paper considers different approaches to modelling the economic impact of the Covid-19 pandemic/lockdown shocks. We review different modelling strategies and argue that, given the nature of the bottom-up recession caused by the pandemic/lockdowns, simulation models of the shocks should be based on a social accounting matrix (SAM) that includes both disaggregated sectoral data and the national accounts in a unified framework. SAM-based models have been widely used to analyze the impact of natural disasters, which are comparable to pandemic/lockdown shocks. The pandemic/lockdown shocks occurred rapidly, in weeks or months, not gradually over a year or more. In such a short period, adjustments through smooth changes in wages, prices and production methods are not plausible. Rather, initial adjustments occur through changes in quantities, altering demand and supply of commodities and employment in affected sectors. In this environment, we use a linear SAM-multiplier model that specifies a fixed-coefficient production technology, linear demand system, fixed savings rates, and fixed prices. There are three different kinds of sectoral shocks that are included in the model: (1) changes in demand due to household lockdown, (2) changes in supply due to industry lockdown, and (3) changes in demand due to induced macro shocks. At the detailed industry level, data are provided for all three shocks and the model imposes the largest of the three. We applied the model on a monthly time step for the period March to June 2020 for four countries: US, UK, Mexico, and South Africa. The models closely replicate observed macro results (GDP and employment) for the period. The results provide detailed structural information on the evolution of the different economies month-by-month and provide a framework for forward-looking scenario analysis. We also use the SAM-multiplier model to estimate the macro stimulus impacts of policies to support affected households. The model focuses attention on the structural features of the economy that define the multiplier process (who gets the additional income and what do they do with it) and provides a more nuanced analysis of the stimulus impact of income support programs than can be done with aggregated macro models.
