Covid-19: Industry Level Origins of Fluctuations in Growth Rates and Economic Welfare

Covid-19：增长率和经济福利波动的行业层面根源

• 批准号: ES/V015664/1
• 负责人: Harjoat Bhamra
• 金额: $ 24.91万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FV015664%2F1
• 关键词: Covid; 19; Industry; Level; Origins

The impact of the COVID-19 shock on the UK economy has been heterogeneous across sectors, suggestive of significant reallocation as the economy recovers. Government support for the economy will therefore need to be targeted at specific sectors in order to be effective.We can observe sector-level stock prices and dividends, and estimate wages, but cannot observe directly how expectations of their long-run growth rates and sector sizes have shifted in response to the COVID-19 shock. However, using an asset pricing theory model (based on an extension of work by one of the applicants [Bhamra, Kuehn and Strebulaev (2011)] we can use sector-level stock prices and dividends and wages to derive equations linking these variables to expected longrun growth rates of dividends and wages across sectors. We can hence estimate sector-level expected long-run growth rates and show how they have changed in response to the COVID-19 shock. We can also estimate the contribution of each sector to aggregate welfare in terms of labour income and consumption and show how these contributions have changed over time.By basing our analysis on asset prices, we can update our estimates of sector-level growth rates in real time. This is important, because sector-level macroeconomic data often lags events (e.g., UK sector-level data on output for February 2020 was released by the ONS on 9th April 2020). Existingwork has exploited asset prices to estimate aggregate growth rates for the US [see Gormsen & Koijen (2020)], but no such work exists at the sectoral level.

“新冠肺炎”冲击对英国经济的影响在不同行业表现不一，表明随着经济复苏，英国经济将出现显著的再配置。因此，政府对经济的支持将需要针对特定行业才能有效。我们可以观察行业层面的股票价格和股息，并估计工资，但无法直接观察对它们的长期增长率和行业规模的预期如何随着新冠肺炎的冲击而发生变化。然而，使用资产定价理论模型(基于其中一位申请者[Bhamra，Kuehn and StreBulaev(2011)]的扩展工作)，我们可以使用行业层面的股票价格、股息和工资来推导出将这些变量与各行业股息和工资的预期长期增长率联系起来的方程式。因此，我们可以估计行业层面的预期长期增长率，并展示它们在应对“新冠肺炎”冲击时发生了怎样的变化。我们还可以估计每个部门在劳动收入和消费方面对总福利的贡献，并显示这些贡献是如何随着时间的推移而变化的。通过基于资产价格的分析，我们可以实时更新对部门层面增长率的估计。这一点很重要，因为部门层面的宏观经济数据往往滞后于事件(例如，英国国家统计局于2020年4月9日发布了2020年2月英国部门层面的产出数据)。现有的工作利用资产价格来估计美国的总增长率[见Gormsen&Koijen(2020)]，但在部门层面上没有这样的工作。