14 July 2020. In response to the outbreak of COVID19, 114 countries have implemented policies that require closing or work from home for all but essential workplaces. In sectors required to shutter workplaces, work can only be conducted from workers’ homes. Cross-country differences in the ability to execute work from home are therefore crucial in evaluating the economic implications of lockdown policies. At the same time, countries differ substantially in their sectoral composition, implying that lockdowns targeting the same set of sectors may produce unequal outcomes in different economies.
A recent research paper by Charles Gottlieb (University of St.Gallen), Jan Grobovšek (University of Edinburgh), Markus Poschke (McGill University) and Fernando Saltiel (Duke University) measures the ability to work from home and the effect of realistic lockdown policies on employment and GDP for a broad cross-section of countries, ranging in income per capita from Niger to Luxembourg.
Who can work from home?
This research measures the ability to work from home using information on the task content of jobs. Using datasets on workers in urban areas of ten lower and upper-middle-income countries in 2012-2013, ranging in income per capita (ppp) from USD 3,700 (Kenya) to 15,000 (Macedonia), they show that the ability to work from home varies strongly with a worker’s occupation and demographics. While about 60% of jobs in managerial and professional occupations and in clerical support (groups 1-4) can be carried out from home, only about about 30% jobs in elementary occupations, crafts, or occupations involving plant or machine operation (groups 6-9) can be done remotely (see Figure 1a). The ability to work from home also differences strongly across demographic groups. It is 20 percentage points lower for high school dropouts compared to graduates, and 15 percentage points lower for the self-employed compared to wage employees. Women have a far higher ability to work from home (51.5%) than men (37.4%), as can be seen in Figure 1b.
Figure 1. Work from home ability by occupation and demographic groups
Working from home across countries
These measures are then used to measure the work from home ability of 57 countries ranging from Ethiopia to Luxembourg. Figure 2 shows that the work from home ability in urban areas is substantially lower in poor countries. It ranges from roughly 35% in the poorest countries to about 53% in the richest.
Much of this variation is due to differences in the occupational structure of countries, which differs systematically with development. Poor countries have low employment shares in high work from home ability occupations, such as managers and professionals, and high employment shares in low work from home ability occupations, as shown in Figure 3. In addition, they have larger shares of high-school dropouts and self-employed workers. All of these factors reduce their work from home ability.
Figure 2. Aggregate work from home ability in urban areas across countries
Figure 3. Urban occupation composition by country income group
The effects of sectoral lockdown policies
In practice, lockdown policies do not shutter the entire economy but focus on non-essential sectors. Workplaces in essential sectors can still operate, even if workers cannot work from home (e.g. the health sector, groceries, agricultural activities). As a result, the effect of lockdown policies on aggregate employment and output depends not only on a country’s work from home ability, but also on its sectoral structure.
Using data on value-added and employment for 20 sectors in 85 countries, they simulate a “hard” lockdown, that mimics lockdowns implemented in Italy, Spain, and Germany, as well as a “soft” lockdown, which is designed to capture the situation as shutdowns are eased.
Figure 4. Employment and GDP by lockdown scenario, relative to pre-trend
Figure 4 presents the drop in employment and GDP that results from lockdown policies for many countries ranked by income level. The upper (lower) pane portrays the hard (soft) lockdown. Across countries, the hard (soft) lockdown generates an average employment drop of 25.5% (9.8%). GDP declines on average by 28.9% (8.9%) on an annualized basis.
Under both scenarios, employment and GDP are U-shaped in income per capita. High-income countries have a substantially higher work from home ability, which mitigates declines in employment and GDP due to the lockdown of non-essential sectors. In contrast, low-income countries concentrate employment and value-added in essential sectors that are not shut down. Middle-income countries see the largest declines as they feature relatively large employment shares in non-essential sectors and relatively low work from home ability.
Lockdown policies have large disruptive effects on economies across the globe. This new piece of research documents that the employment structure of economies across the income per capita spectrum is such that the potential employment and GDP effects of lockdown policies are of a similar magnitude for low and high income countries, and strongest for middle-income countries. Also, the authors provide an online lockdown simulator that allows users to simulate user-defined sectoral lockdown policies, and foster the policy debate on the design of lockdown policies in low-, middle- and high-income countries.
Image: photocase / PolaRocket