RAPID: Joint Epidemiological and Macroeconomic Outcomes from Non-Pharmaceutical Interventions in Response to the COVID-19 Pandemic

RAPID：应对 COVID-19 大流行的非药物干预措施的联合流行病学和宏观经济成果

• 批准号: 2032493
• 负责人: James Stock
• 金额: $ 19.66万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2032493&HistoricalAwards=false
• 关键词: RAPID; Joint; Epidemiological; Macroeconomic; Outcomes

AbstractThe initial shutdown of the US economy in March 2020 resulted in a peak and a slow decline in the death rate from COVID-19, but at a tremendous cost to the economy, with the April 2020 seeing the highest rate of unemployment since the Great Depression. Urgent questions now concern how to reopen the economy in a way that gets workers back to work while controlling the spread of the disease. While intuition might suggest general directions, ultimately a quantitative understanding of the effects of proposed reopening plans is needed to guide a safe and durable reopening. This project will provide a granular, integrated modeling system capable of providing internally consistent joint paths for epidemiological and economic outcomes. Doing so entails merging epidemiological models and sectoral economic models at a sufficient level of detail to provide quantitative assessments of detailed non-pharmaceutical interventions (NPIs), such as sectoral-level reopening strategies, testing and quarantine, school closings, and the use of masks and gloves at the workplace, which has immediate substantial broader impacts for the economy and the society. At a technical level, the research will merge an age-based epidemiological SEIRD (Susceptible, Exposed, Infectious, Recovered and Dead) model with a nonlinear input-output model of the US economy. Closure and reopening paths are specified at a granular sector level, where sectors are characterized by different age distributions of workers and different degrees of proximity and contacts at the workplace. NPIs affect infections, quarantine, and deaths, which, along with direct labor supply and other shocks from the NPIs, feed into the economic model. The age structure of the SEIRD model allows examination of detailed age-specific and activity-specific NPIs. The research will extend the existing nonlinear input-output structure to labor market frictions and to endogenous shifts in labor supply and consumption demand in response to the epidemic. The result will be a quantitative framework for assessing the joint path of the epidemic and the economy at a level of granularity currently not available.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

摘要：美国经济于 2020 年 3 月首次关闭，导致 COVID-19 死亡率达到峰值并缓慢下降，但给经济带来了巨大成本，2020 年 4 月出现了大萧条以来的最高失业率。现在紧迫的问题是如何重新开放经济，让工人重返工作岗位，同时控制疾病的传播。虽然直觉可能会提出总体方向，但最终需要对拟议的重新开放计划的影响进行定量了解，以指导安全和持久的重新开放。该项目将提供一个精细的集成建模系统，能够为流行病学和经济结果提供内部一致的联合路径。这样做需要足够详细地融合流行病学模型和部门经济模型，以对详细的非药物干预措施（NPI）进行定量评估，例如部门级重新开放策略、检测和隔离、学校停课以及在工作场所使用口罩和手套，这对经济和社会产生直接的、更广泛的影响。在技​​术层面上，该研究将基于年龄的流行病学SEIRD（易感、暴露、传染、康复和死亡）模型与美国经济的非线性投入产出模型相结合。关闭和重新开放路径是在细粒度的部门级别指定的，其中部门的特点是工人的年龄分布不同以及工作场所的接近和接触程度不同。 NPI 会影响感染、检疫和死亡，这些因素与 NPI 带来的直接劳动力供应和其他冲击一起影响经济模型。 SEIRD 模型的年龄结构允许检查详细的特定年龄和特定活动的 NPI。该研究将把现有的非线性投入产出结构延伸到劳动力市场摩擦以及应对疫情的劳动力供给和消费需求的内生变化。其结果将是一个定量框架，用于在目前无法达到的粒度水平上评估流行病与经济的共同路径。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Policies for a Second Wave

• DOI: 10.1353/eca.2020.0013
• 发表时间: 2020-06-01
• 期刊: BROOKINGS PAPERS ON ECONOMIC ACTIVITY
• 影响因子: 5.9
• 作者: Baqaee, David;Farhi, Emmanuel;Stock, James H.
• 通讯作者: Stock, James H.