Covid-19: Industry Level Origins of Fluctuations in Growth Rates and Economic Welfare
Lead Research Organisation:
Imperial College London
Department Name: Imperial College Business School
Abstract
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). Existing
work 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.
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). Existing
work 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.
| Description | The importance of different sectors of the economy changes over time, often in response to changes in technology. Not so long ago, firms such as Google and Apple did not exist. Shocks to the economy such as COVID-19 can also lead to changes in how economic activity is allocated. While we cannot peer directly into the future to see how different sectors of the economy will rise and fall in importance, asset prices are based on market participants' expectations of future cashflows, discounted to account for time and risk. We can therefore exploit asset prices to estimate how different sectors of the economy will grow. In the initial phase of our research, we have built a framework with connects changes in the price of shares in a particular sector, say technology, to expectations of how that sector will grow. We are now combining our framework with 25 years of UK stock price data to estimate the growth rates and long-run means of all the sectors which make up the UK economy. We have found that sector-specific shocks to asset returns can be used to predict sector-level shocks to consumption growth. This means that it is possible to use data on sector-level asset returns to predict how consumption is reallocated across sectors. |
| Exploitation Route | We have presented our work at the the National Institute Of Economic and Social Research, the UK's longest established independent research institute. We envision that our work will be useful to policymakers deciding on how to allocate government spending. Further work linking sectors of the economy to different regions of the UK will help understand the geography of sector-level economic growth. |
| Sectors | Communities and Social Services/Policy,Creative Economy,Financial Services, and Management Consultancy,Government, Democracy and Justice |
| Title | Dataset on Individual Consumption (based on UK Credit Card Spending) from Fable |
| Description | We have developed an algorithm for matching credit card spending to sectors of the economy (on the UK) |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2022 |
| Provided To Others? | No |
| Impact | This dataset and algorithm have allowed us to implement a VAR to assess the impact of sector-level shocks to asset returns on sector-level consumption growth. We find that for several sectors of the UK economy, shocks to sector-level asset returns predict how consumption is reallocated across different sectors of the economy. |
| Description | NIESR-Imperial |
| Organisation | National Institute of Economic and Social Research (NIESR) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | By working together with team members from NIESR, we have been able to present our work there and receive early feedback. This has helped us ensure that our research is relevant to UK policymakers. |
| Collaborator Contribution | NIESR have provided technical expertise in the form of econometric estimation techniques, which were fundamental to our empirical work. |
| Impact | The empirical methodology for show how sector-specific shocks to asset returns impact sector-level consumption growth, |
| Start Year | 2020 |