Governments worldwide are facing tough decisions on how to ease lockdown restrictions. Given the trade-off between the spread of the virus and the economic cost, the overall success of the COVID response will be determined as much by the reopening phase as it was by the initial response.
A new paper from the CEPR provides a framework for easing restrictions on working from home and uses data from Germany to estimate the optimal approach in output per worker. But the takeaways apply globally: firstly, the need to lift restrictions initially only for those who cannot work from home so as to keep infection rates low; secondly, undertaking a phased easing of restrictions by region that balances output losses per worker with the risk of rising infection rates. Systemic industries or those with very high value added should also be prioritised.
These findings will be useful for policymakers around the world as they search for the optimal way to reopen economies.
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Governments worldwide are facing tough decisions on how to ease lockdown restrictions. Given the trade-off between the spread of the virus and the economic cost, the overall success of the COVID response will be determined as much by the reopening phase as it was by the initial response.
A new paper from the CEPR provides a framework for easing restrictions on working from home and uses data from Germany to estimate the optimal approach in output per worker. But the takeaways apply globally: firstly, the need to lift restrictions initially only for those who cannot work from home so as to keep infection rates low; secondly, undertaking a phased easing of restrictions by region that balances output losses per worker with the risk of rising infection rates. Systemic industries or those with very high value added should also be prioritised.
These findings will be useful for policymakers around the world as they search for the optimal way to reopen economies.
The Relationship Between WFH and Infections and Deaths
Working from home (WFH) has become the new normal for many of us. Yet this social distancing measure is generally discussed in terms of the beneficial flattening of the infection curve rather than the economic cost from each lost worker. The CEPR study covering Germany fills an important gap in this regard, particularly as the approach can be easily extended to other countries.
Germany’s WFH share is estimated at 42%, which is not too far from the 37% estimated in an earlier study on the US. And in general, any country that has a large share of employment in finance and insurance, information and communication services and education will also have a high WFH share. By contrast, economies more reliant on agriculture, construction and accommodation and food services will fare worse on WFH shares.
Findings from the study show that for every additional 1pp share of WFH results in 20 less COVID infections and 0.9 less fatalities per 100,000 people. As a result, regions of Germany where the WFH share is lower (such as Lower Bavaria) have been significantly more affected by the virus than in Berlin where WFH is higher.
This analysis is extended to determine how WFH impacts infection rates. The authors find that every 1pp increase in WFH results in 1/3 pp reduction in the contact rate (defined as the average number of contacts per infective per day). Translating this for Germany shows that moving from a WHF share of 38% in Lower Bavaria to Berlin’s WFH share of 45% reduces the contact rate by 2.3pp, with a correspondingly large impact on the infection rate. This highlights the importance of a low contact rate to reduce the spread of the virus. And an increase in the WFH share is an effective way to achieve this.
A Framework for Phasing Out Lockdowns
With an estimated 1.6% of GDP loss for every week the German lockdown continues (assuming those employees who cannot WFH are simply removed from the labour force), lifting the restrictions is imperative. The authors take an industry- and region-based approach to find a solution that will minimize the amount of people in the workplace while maximising economic output.
Industry approach: To determine the impact on GDP of each 1% of industry workforce returning to work, the authors construct industry value added multiples from sectoral accounts. And to account for the differences in size of each sector, this is also calculated as a share of nominal GDP, giving an absolute euro amount for each worker returning to work.
In Chart 1 below all sectors shown have an individual worker contribution of over €2000/week to the economy with business services, supply industries (utilities) and manufacturing all scoring highly. This approach highlights that prioritizing the most economically important industries can help to minimize economic losses.
Chart 1: GDP Impact of Employees Returning to Work by Industry
Source: “The costs and benefits of home office during the Covid-19 pandemic:
Evidence from infections and an input-output model for Germany” (Page 120)
Regional approach: A second approach is to ease the lockdown on a regional basis, which is closer to that witnessed in China and now Italy. The authors calculate value added for each industry by region to show that cities like Belin, Hamburg and Dusseldorf would see the biggest impact on nominal GDP from reopening, with an overall range of €2,000-6,000/worker across regions.
The WHF shares are applied across the regions to determine the cost of normal (full) activity versus only those able to WFH. Tubingen in southern Germany is one of the regions most affected from WFH restrictions, with a weekly GDP loss of 1.77%, and Berlin the least affected, with a loss of 1.36%, with the industry structure the determining factor.
As expected, a strong negative correlation is found between regional WFH shares and regional losses from lockdown (Chart 2). This is quantified as a 10pp higher WFH share translating to a 0.4% lower weekly GDP loss.
Chart 2: Regions With the Lowest WFH Share Have the Most to Gain from Lifting Lockdowns
Source: “The costs and benefits of home office during the Covid-19 pandemic:
Evidence from infections and an input-output model for Germany” (Page 123)
To conclude: by identifying the sectors and regions where lifting restrictions would have the largest economic impact, policymakers globally can gradually ease restrictions while limiting the rate of new infections. Economic structure and geography are unique in every country but the principle of maximising economic gain while minimising risk to life is the same worldwide.
(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)