Is Remote Working? An Index of Teleworking Capacity by Country

The Fall/Winter 2020 issue looks at the economic effects of the COVID-19 Pandemic on society and the economy.


The Fall/Winter 2020 issue looks at the economic effects of the COVID-19 Pandemic on society and the economy.

Mariya Brussevich

Era Dabla-Norris

Salma Khalid

Will COVID-19 kill the traditional workplace? The impact of lockdowns and social distancing policies to contain the spread of the pandemic on labor markets has been unprecedented, especially for contact-intensive industries that require physical presence at the workplace or high levels of personal interaction. Workers in such industries are consequently at a higher risk of reduced hours or pay, temporary furloughs, or permanent layoffs. In contrast, occupations involving the use of information and communication technology (ICT) are less likely to experience disruption.

How is the risk of job disruption spread across different economic sectors? How does the level of “tele-workability” relate with worker characteristics (age, educational attainment, gender, employment status, and income level)? How does the ability to work remotely vary across advanced and emerging market economies? Answers to these questions can inform the policies needed to support workers both during and after the lockdown period.

Recent IMF research has estimated the distribution of tele-workability across sectors, occupations, age groups, gender, income, and education levels in 35 advanced and emerging market economies, including 30 OECD member countries and Cyprus, Ecuador, Kazakhstan, Peru, and Singapore. Worker-level microdata from the OECD Programme for the International Assessment of Adult Competencies (PIAAC) allows the authors to unpack differences in job task characteristics—and therefore tele-workability—among workers within the same occupation, as well as across different occupations, sectors, and countries. The existing literature on tele-workability uses aggregated data at the occupational level (Dingel and Neiman 2020; Hensvik and others 2020; Mongey and others 2020). This type of data cannot establish risk and exposure at the level of individual workers.

Tele-Workability Index

The study combines two sources of data to estimate the ability to telework. First, estimates of the ability to telework at the occupational level from Dingel and Neiman (2020) serve as a starting point in the estimation procedure. Second, these estimates are projected onto worker characteristics from the PIAAC database, including gender, age, education, income, and a rich set of task characteristics, such as flexibility in work hours and the use of ICT. The result is an index of tele-workability that pairs individual workers’ characteristics with their ability to telework.

Who are the Most Vulnerable?

Sectors that are the least tele-workable, and therefore at the highest risk of job loss, include accommodation and food services, construction, transportation, and wholesale and retail trade. Meanwhile, the financial services and ICT sectors are highly tele-workable, and therefore workers in these sectors are at lower risk of displacement. These trends are in line with high-frequency data on employment losses by sector in the United States. Data from the US Bureau of Labor Statistics show largest employment losses in the hospitality and services sectors and smallest in financial activities.

There is substantial variation in workers’ ability to work remotely by country, and emerging market economies have significantly lower tele-workability indices than advanced economies (Figure 1). These differences persist across all sectors. For instance, ICT in Turkey has lower tele-workability than wholesale and retail trade in Finland, highlighting important aggregate differences in tele-workability among economies at various levels of development.

Figure 1.
Figure 1.

Tele-workability Index by GDP per capita

Citation: IMF Research Perspectives 2020, 002; 10.5089/9781513564081.053.A003

Sources: Dingel and Neiman 2020; PIAAC survey; IMF, World Economic Outlook; and authors’ calculations. PPP – purchasing power parity. Data labels use International Organization for Standardization (ISO) country codes.

The ability to telework also varies by demographic characteristics (Figure 2). Workers younger than 30 are significantly less likely to be able to telework, while workers older than 60 tend to be employed in positions that are more amenable to teleworking. This difference is reflective of career progression over the life cycle as older workers are more likely to occupy managerial positions. However, there is significant cross-country variation with, for instance, older workers in Korea being less able to telework and younger workers being more able to telework. On average, men are less likely to be in telework-friendly jobs than women, although the difference between male and female workers is negligible in some countries, such as Japan and Korea.

Figure 2.
Figure 2.

Tele-workability Index by Worker Characteristics

Citation: IMF Research Perspectives 2020, 002; 10.5089/9781513564081.053.A003

Sources: Dingel and Neiman 2020; PIAAC survey; and authors’ calculations.Note: Dots in the figure represent estimates from cross-country regressions wherein the tele-workability index is regressed on one of the worker characteristics in the list. All coefficients are statistically significant at 1 percent significance level. End points represent the smallest and largest coefficients on worker characteristics from regressions. Data labels use International Organization for Standardization (ISO) country codes.

Firm size, contract type, skill, and pay levels also play significant roles in determining the ability to telework. Workers in smaller firms are less likely to be able to telework than workers in larger firms. Moreover, part-time workers are less likely than full-time workers to hold jobs that are tele-workable. Workers without a college education and workers with low wages are much more likely to face employment interruption because their jobs are less amenable to teleworking.

Tele-workability is likely to exacerbate inequality in the workforce, given that workers whose jobs are at highest risk from the pandemic are also the most vulnerable in terms of their existing socioeconomic status.

How many Jobs are at Risk?

To gauge the pandemic’s impact on job losses, the study uses data on the employment by sector in the United States during the lockdown period to estimate job losses for all economies in the sample. Using data from the Oxford Coronavirus Government Response Tracker, this approach accounts for differences in the stringency of lockdown measures among countries. The outcome: more than 97 million jobs are at high risk of layoff or furlough across the 35-country sample, with the United States alone contributing more than 21 million jobs to this total. The accommodation and food services sector is the worst hit, with more than 17 million workers at risk of job loss, equivalent to 47 percent of all jobs in that sector. Sectors including finance and utilities are more insulated with an estimated 10 percent of jobs at risk of disruption.

To support incomes and formal employment during the crisis, governments should broaden social protection, social insurance, and safety nets. Wage and hiring subsidies as well as public works programs should be the focus as activity resumes. To prepare the workforce for the jobs of the future, governments need to strengthen education and training.

This crisis has highlighted the importance of access to digital infrastructure in workers’ ability to continue to engage in the workplace. Policies should be geared toward closing the digital divide for firms and workers.