摘要翻译：
我开发了一个基于Agent的新的宏观经济流行病学模型来研究新冠肺炎疫情在不同政策情景下的影响。代理人的职业、家庭地位和年龄各不相同，在家庭、工作或休闲活动中与其他代理人互动。该模型允许实施和测试实际使用的或反事实的政策，如在模型中明确关闭学校或休闲行业，以探索它们对病毒传播的影响及其经济后果。该模型是用德国关于时间使用、人口统计、家庭、企业人口统计、就业、公司利润和工资的统计数据校准的。我根据德国的遏制政策建立了一个基线假设，并将模拟的流行病学参数与观察到的德国死亡曲线和第一波新冠肺炎疫情的估计感染曲线进行了拟合。我的模型表明，如果在一周后采取行动，德国第一波浪潮的死亡人数将会高出180%，而如果政策在一周前颁布，死亡人数将会低60%。最后，我讨论了两种程式化的财政政策情景：顺周期（零赤字）和反周期财政政策。在零赤字的情况下，出现了一个恶性循环，经济衰退从高互动的休闲行业蔓延到其他经济领域。即使在消除病毒和解除限制后，经济复苏也不完整。另一方面，反周期的财政政策限制了经济损失，允许V型复苏，但不会增加死亡人数。这些结果表明，对这一流行病的最佳反应旨在遏制或坚持接种疫苗，将及早采取遏制措施以保持低感染人数与扩张性财政政策相结合，以保持低风险部门的高产出。
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英文标题：
《COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model》
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作者：
Patrick Mellacher
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最新提交年份：
2020
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分类信息：

一级分类：Economics 经济学
二级分类：Theoretical Economics 理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
I develop a novel macroeconomic epidemiological agent-based model to study the impact of the COVID-19 pandemic under varying policy scenarios. Agents differ with regard to their profession, family status and age and interact with other agents at home, work or during leisure activities. The model allows to implement and test actually used or counterfactual policies such as closing schools or the leisure industry explicitly in the model in order to explore their impact on the spread of the virus, and their economic consequences. The model is calibrated with German statistical data on time use, demography, households, firm demography, employment, company profits and wages. I set up a baseline scenario based on the German containment policies and fit the epidemiological parameters of the simulation to the observed German death curve and an estimated infection curve of the first COVID-19 wave. My model suggests that by acting one week later, the death toll of the first wave in Germany would have been 180% higher, whereas it would have been 60% lower, if the policies had been enacted a week earlier. I finally discuss two stylized fiscal policy scenarios: procyclical (zero-deficit) and anticyclical fiscal policy. In the zero-deficit scenario a vicious circle emerges, in which the economic recession spreads from the high-interaction leisure industry to the rest of the economy. Even after eliminating the virus and lifting the restrictions, the economic recovery is incomplete. Anticyclical fiscal policy on the other hand limits the economic losses and allows for a V-shaped recovery, but does not increase the number of deaths. These results suggest that an optimal response to the pandemic aiming at containment or holding out for a vaccine combines early introduction of containment measures to keep the number of infected low with expansionary fiscal policy to keep output in lower risk sectors high.
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