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Who on Earth Can Work from Home? This paper reviews the emerging literature on which jobs can be performed from home and presents new estimates of the prevalence of such jobs based on the task content of occupations, their technology requirements and the availability of internet access by country and income groupings Globally, one of every five jobs can be performed from home In lowincome countries, this ratio drops to one of every 26 jobs Failing to account for internet access yields upward biased estimates of the resilience of poor countries, lagging regions, and poor workers Since better paid workers are more likely to be able to work from home, COVID19 is likely to exacerbate inequality, especially in richer countries where better paid and educated workers are insulated from the shock The overall labor market burden of COVID-19 is bound to be larger in poor countries, where only a small share of workers can work from home and social protection systems are weaker Across the globe, young, poorly educated workers and those on temporary contracts are least likely to be able to work from home and more vulnerable to the labor market shocks from COVID-19 JEL Codes: J17, J21, J28, J48 Keywords: COVID-19, working from home, telecommuting, internet access As the COVID-19 pandemic ravages labor markets across the globe, questions on the changing nature of jobs have moved to the center of academic and policy debates The ability to work from home is a key determinant of employment outcomes given widespread shutdowns, mobility restrictions, and social distancing policies Workers in occupations more amenable to working from home (WFH) are more likely to retain their jobs and experience a smaller decline in earnings, as evidence from surveys conducted during the early stages of the pandemic has shown (Adams-Prassl et al 2020a; Bottan, Hoffman, and Vera 2020; Guven, Sotirakopoulos, and Ulker 2020; and Liu and Mai 2020; Montenovo et al 2020) According to estimates of the International Labor Organization (ILO 2020), half of the workforce in high-income regions of the world, like North America and Western Europe, has been able to work from home throughout the pandemic The World Bank Research Observer © The Author(s) 2021 Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK All rights reserved For permissions, please e-mail: journals.permissions@oup.com doi: 10.1093/wbro/lkab002 36:67–100 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Daniel Garrote Sanchez, Nicolas Gomez Parra, Caglar Ozden, Bob Rijkers, Mariana Viollaz, and Hernan Winkler Task Content of Jobs The vast majority of studies of the labor market impacts of COVID-19 have focused on the type and nature of tasks performed in different jobs in order to determine their 68 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 The widespread availability of home-based work in high-income countries is in part due to changes in the nature and task content of jobs that have accompanied advances in communication and information technologies (ICT) over the last decades The ICT revolution has fueled an expansion of high-skilled jobs that are intensive in tasks requiring cognitive skills and can feasibly be performed at home (World Bank 2019) By contrast, the demand for relatively lower-skilled workers executing routine tasks has fallen, resulting in widening labor market inequality Since workers in jobs with routine tasks are less likely to be able to WFH, the COVID-19 pandemic will most likely reinforce longer-term trends towards job polarization and increased income inequality This paper reviews the rapidly growing literature on the share and type of jobs that can be performed from home, various constraints on home-based work as well as their implications for the labor market and income inequality across the globe While the academic and policy literature on this topic is expanding as rapidly as the pandemic itself with new papers being circulated each week, the ability to work from home will continue to occupy economists and policymakers long after the pandemic is over The type and distribution of jobs which can be performed at home will stay as crucial determinants of the spatial division of economic activity, labor market competition, and income distribution in all countries regardless of their level of economic development The remainder of this paper proceeds as follows The next section discusses the evolving task content of jobs and how it varies across countries The third section reviews the recent literature on the vulnerability of the COVID-19 shock across occupations depending on their task content, particularly focusing on measures of homebased work and face-to-face interactions In the fourth section, we provide an original analysis of the importance of accounting for internet access to assess the feasibility of working from home, in particular in developing countries It presents estimates of the prevalence of jobs amenable to working from home across countries and shows that poorer countries have more jobs at risk The following section expands the analysis using different measures and sources of data The sixth section explores implications of COVID-19 for inequality within countries and the seventh demonstrates that labor market risk is inversely correlated with age, job tenure, and, crucially, education levels The subsequent section describes recent labor market developments across the globe and assesses the predictive capacity of different ex-ante measures of job vulnerability in explaining recent employment trends and the next highlights the main gaps in the literature as well as current data constraints A final section concludes Garrote Sanchez et al 69 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 holders’ ability to work from home Before delving into the literature on WFH under COVID-19, we briefly discuss its genesis—the literature on the analysis of the task content of jobs The strong correlation between expanding use of computers and demand for high-skilled labor was the main empirical observation that motivated the task content literature Emergence of this correlation, interpreted as evidence of skill-biased technical change, can be traced back to the 1960s in the United States Autor, Levy, and Murnane (2003)—ALM2003 from now on—argue that computers substitute for workers “carrying out a limited and well-defined set of cognitive and manual activities that can be accomplished by following explicit rules.” They refer to these as “routine tasks.” In contrast, computers complement workers who are “carrying out problem-solving and complex communication activities” which they label as “nonroutine tasks.” They hypothesize that occupations where routine tasks are more prevalent would experience replacement by computers at a faster rate and to a greater degree as well as a parallel decline in their employment levels The outcome is a steady increase in the relative demand for highly educated workers who have comparative advantage in nonroutine tasks ALM2003 use data on the task requirements of jobs from the Dictionary of Occupational Titles (DOT) to characterize the occupations of workers in the Census and the Current Population Survey (CPS).1 They find that the share of workers employed in occupations with high levels of nonroutine analytical and interpersonal tasks increased substantially between 1960 and 2000 In contrast, the share of workers in occupations with lower levels of routine cognitive and manual tasks declined.2 Qualitatively similar trends have been documented in Europe (Goos, Manning, and Salomon 2009, Gorka et al 2017), and in several developing economies (World Bank 2016).3 This labor market polarization, in conjunction with offshoring and the rapid adoption of labor-displacing technologies stoked concerns about the future of jobs with high levels of routine tasks and the economic welfare of relatively low-skilled workers who hold these jobs The roll-out of broadband internet access induced firms to substitute workers performing routine tasks in Norway (Akerman, Gaarder, and Mogstad, 2015) Similarly, the adoption of industrial robots led to a significant decline in the employment of especially lower-skilled workers in several OECD countries as well as Mexico and China (Artuc, Christiaensen, and Winkler 2019; Giuntella and Wang 2019; Graetz and Michaels 2018; Acemoglu and Restrepo 2020).4 Autor (2015, 2019) argues that the technological progress “pushed the demand for skilled labor over many decades and will continue to so.” Analysis of the task content of jobs also attests to differential labor market trends in developed and developing countries as the pace of change seems to be correlated with income levels Jobs with high levels of cognitively demanding tasks are more common in countries with higher levels of GDP per capita and technology use (Lo Bello, Sanchez-Puerta, and Winkler 2019; Lewandowski, Park, and Schotte 2020) Measures of Job Vulnerability to COVID-19 The COVID-19 pandemic has accelerated long-term trends in the task content of jobs, their relationship with communication technologies as well as their social and economic impacts As soon as lockdown measures were in place, especially in highincome countries, workers with jobs involving high levels of nonroutine analytical and interpersonal tasks could make arrangements to work from home and thereby to keep their jobs Their jobs can be carried out almost anywhere if there is reliable internet access This is the case even for people with managerial responsibilities that require intensive interpersonal interactions, since most of their tasks can be carried out via online communication In contrast, those with jobs involving intensively routine and manual tasks requiring low or mid-leves of skill were not able to work remotely As a result, they were more likely to face income and possibly job losses In most cases, their jobs require them to be present at a specific location or interact with clients and/or co-workers in person Measures of Home-based Work Following the work of Dingel and Neiman (2020)—DN2020 from now on—most recent studies start by identifying the types and nature of tasks required by different occupations in order to assess workers’ ability to work from home To assess the feasibility to telework, DN2020 use information from 17 characteristics of more than 900 occupations based on two surveys from the US Department of Labor, Employment and Training Administration’s Occupational Information Network (O* NET) They categorize jobs as “not amenable to telework” if an occupation requires daily work outdoors, physical activity, frequent contact with the public, or operating vehicles, mechanized devices, or equipment, or if its holders use email less than once a month, interact with violent people on a weekly basis, spend the majority of their time walking or running, sustain minor burns or cuts each week, or have to routinely wear specialized protective equipment They assume that a job cannot be performed 70 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 In contrast, routine tasks are more prevalent in jobs in developing countries Despite the secular decline in the price of digital technologies and computing power, ALM2003’s prediction—i.e., that labor performing routine tasks would be replaced by computers—has not materialized at the same pace in developing countries Lower labor costs and barriers to the adoption of new technologies seem to have prevented poorer countries from experiencing a more rapid de-routinization of labor and increases in labor productivity (World Bank 2016; Artuc, Bastos, and Rijkers 2018) These patterns help us to explain why the fraction of jobs amenable to WFH is lower in the developing world and why its workers may be more vulnerable to COVID-19 induced job losses Garrote Sanchez et al 71 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 entirely from home if it meets at least one of these conditions The DN2020 results are highly correlated with the share of time working at home according to the American Time Use Survey DN2020 expand the task content analysis in the United States to 85 countries across the globe using ILO 2-digit ISCO occupations data They show that there is a strong positive correlation between the GDP per capita level of a country and the share of jobs that are amenable to working from home One key assumption of this analysis is that the task content of each occupation is the same across countries as they are all based on the O* NET data Several articles have implemented different adaptations of DN2020 Mongey, Pilossoph, and Weingerg (2020) use O* NET questions to estimate which jobs can be done from home but by constructing a continuous index of home-based work instead of categorizing jobs as either fully “teleworkable” or not Gottlieb, Grobovsek, and Poschke (2020) use labor force surveys from 57 countries and point out that low-income countries have a very high share of self-employed agricultural workers Their ability to work from home impacts the overall labor market effect of COVID-19 in lower-income countries The DN2020 measure is based on data from the United States, where farms are typically large and more reliant on hired labor As a result, DN2020 assumes that only 8.3 percent of all agricultural workers can work from home In poor countries farms are much smaller and a large share of agricultural workers is self-employed, which could imply that farming may be possible from home if plots are located very close to home (or perhaps, more relevant, may be feasible while respecting social distancing guidelines) Assuming that all these self-employed agricultural workers can their jobs from home leads to a negative association between home-based work and GDP per capita (See the analysis in the appendix based on alternative assumptions, especially on agricultural workers’ ability to work from home.) Several articles use skills surveys from different countries to test if US-based measures such as O* NET lead to biased results Saltiel (2020) follows an approach similar to DN2020 but uses worker-level data from the Skills Toward Employability and Productivity survey (STEP) from ten developing countries Hatayama, Viollaz, and Winkler (2020) use skills surveys from 53 countries at varying levels of economic development to identify the share of jobs that can be done at home.5 They find that there is variation in the task content for each occupation across countries, mostly due to differences in technology adoption and organization of production Still, both papers’ measures of working-from-home amenability are positively correlated with those of DN2020 and both document that the ability to telework is higher in richer countries and among more educated and formal workers When deciding which data sources to use to assess the ability to work from home, there is a trade-off between capturing country-specific variation in task content of otherwise similar occupations and the breadth of countries for which data are available Expanding the Requirements for Effectively Working from Home The possibility of working remotely does not always translate into efficiently working from home Bloom et al (2014) provided the first causal evidence on the impact of working from home on workers’ productivity in a randomized control trial of workers of the Chinese company Ctrip Workers who worked from home experienced a 13 percent increase in performance due to longer effective working hours and more efficiency given the quieter work environment However, the current setting during the COVID pandemic is different, where several family members might need to work from home alongside children (Bloom 2020a) In a recent survey, Barreo et al, (2020) highlights the importance of having a private space to work at home, as was the case for all the workers in the Bloom et al (2014) study However, less than half of respondents in the United States currently report being able to work privately in a room other than their bedroom, which can negatively affect workers’ productivity Another important precondition for being able to work from home is internet access Barreo et al (2020) shows that in the United States, only two-thirds of respondents had an internet connection that was strong enough to sustain video 72 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Other papers have followed a different approach to DN2020 to identify the jobs that can be done at home, relying either on actual measures of home-based work or answers to questions in surveys about the ability to work from home Using the American Time Use Survey (ATUS), Hensvik, Le Barbanchon, and Rathelot (2020) show that approximately 15 percent of working hours were performed from home between 2011 and 2018 in the United States They argue that this is a likely to be a lower bound on the share of jobs that can be supplied from home Alipour, Falck, and Schüller (2020) use data from a 2018 employment survey for Germany that includes a question on whether the worker would accept an offer from his or her employer to work from home temporarily Adams-Prassl et al (2020b) collected new data from late March to early April 2020 in the United States and the United Kingdom, including a question about the share of tasks that they could at home in their current (or last) job They demonstrate that workers who are least able to work from home are most likely to lose their jobs Bonacini, Gallo, and Scicchitano (2021) use data from the Italian Survey of Professions (ICP), which is the Italian equivalent of O* NET, to construct an indicator of attitudes toward working from home In general, all these articles find that amenability to work from home increases with workers’ earnings and education levels Their indices are positively correlated with those from DN2020, but since they are based on developed countries the extent to which their findings generalize to developing countries remains unspecified, given that the task content of jobs may vary with development (Lo Bello, Sanchez Puerta, and Winkler 2019) calls while the other third had poor or no internet connectivity that hindered their ability to work from home Measures of Face-to-face Interactions and Physical Proximity Garrote Sanchez et al 73 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Beyond the feasibility of working from home, a number of studies have used other characteristics of jobs that shield them from the COVID-19 supply shock, in particular the physical proximity to other people and face-to-face interactions Even if a job cannot be performed from home, the worker may still have low exposure to health risks and can satisfy social distancing requirements if the role does not entail frequent close interactions with coworkers, customers, or suppliers Avdiu and Nayyar (2020), following Blinder (2009) and using O* NET surveys for the United States, create an index of face-to-face interactions based on the intensity of particular tasks that involve: (1) establishing and maintaining personal relationships; (2) assisting and caring for others; (3) performing for or working directly with the public; and/or (4) selling to or influencing others Similarly, Leibovici, Santacreu, and Famiglietti (2020) construct an index of contact-intensity for the United States, based on an O* NET question that asks about the extent to which the job requires the worker to perform tasks in close physical proximity to others Overall, measures of home-based work and close face-to-face interactions are negatively correlated This is true partly by design, as the DN2020 measure includes “performing for or working directly with the public is very important” as one of the reasons for a job not being amenable to telework For example, information, communication, and technology (ICT) and professional and scientific jobs can more easily be performed at home and require little face-to-face interaction On the other hand, most jobs in hospitality, food services, and health and social services are not amenable to home-based work and require extensive face-to-face interactions Measures of physical proximity and working from home may, however, diverge for other occupations The majority of manufacturing jobs require a physical presence in the place of work but are not always associated with extensive face-to-face interaction, thus allowing social distancing On the other end of the spectrum, education requires significant face-to-face interaction, but those occupations are still amenable to working from home when internet access is available When mobility restrictions are imposed, all non-WFH jobs are vulnerable to disruptions However, once mobility is restored, activities that require more face-to-face interactions can demonstrate a slower recovery and be more affected by new norms of social distancing and attendant changes in consumer demand(s) (Avdiu and Nayyar 2020) Therefore, jobs that require tasks that involve physical proximity are still more likely to be hit in the medium term even if mobility restrictions are removed, particularly if they cannot be carried out from home (Leibovici, Santacreu, and Famiglietti 2020) Government Mandated Essential Occupations 74 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Another aspect of job vulnerability does not relate to the type of tasks required in an occupation but on government mandates on mobility The vast majority of governments have introduced restrictive measures in order to contain the spread of COVID-19—affecting the ability to commute to work Although restrictions were temporarily eased in many countries during the summer of 2020, the increase in the number of COVID-19 cases pushed government officials to reintroduce these measures in many parts of the world during the subsequent fall and winter At the same time, governments have deemed certain occupations as essential, excluding them from mobility restrictions A number of studies have quantified what jobs are essential Fasani and Mazza (2020b) use the European Commission’s guidelines concerning the exercise of the free movement of workers during COVID-19 outbreak6 and supplement it with the Dutch government’s definition of key workers Based on these guidelines they identify essential workers based on ISCO-08 occupations at three digits and find that about 33 percent of the working-age population in the EU have jobs that are deemed essential Garrote-Sanchez et al (2020) use different lists of “essential sectors” based on the decisions of Italy (EU) and the US states of Delaware, Minnesota, and Oklahoma, and mapped them to broad NACE 1-digit sectors of activity Their results show that slightly more than half of jobs in the EU are deemed essential One of the challenges for researchers is that the definition of essential workers varies from country to country—and even across regions within countries—(Garrote-Sanchez et al 2020) However, these lists overlap considerably and typically include the delivery of critical healthcare services (such as medical professionals) and the provision of basic goods and services (e.g., food, utilities, security, ICT) Overall, occupations most affected by the COVID-19 supply shock in the short term are those that are not categorized as essential by authorities and cannot be effectively performed from home That is, it is not just that jobs have to be amenable to telework but workers in practice need the appropriate environment and resources to work from home In the medium-term, after mobility restrictions are removed, the intensity of face-to-face interactions can determine the extent of job vulnerability in the context of changing social norms on social distancing and the subsequent sectoral shifts in demand Even in the case of occupations that require frequent face-to-face interactions, new technologies can reduce physical exposure For example, education services, which traditionally involve face-to-face interactions, have shifted in many contexts to online platforms after COVID-19 Technology and internet access have, thus, a central role in shielding workers’ employment from the COVID-19 pandemic, which is analyzed in more depth in the following section Working from Home and Internet Access Garrote Sanchez et al 75 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 This section presents new estimates of the share of jobs that can be done from home across the globe comparing various approaches discussed in the previous section, with special attention paid to the constraints imposed by internet availability As mentioned earlier, there are several different approaches used in the literature DN2020 use information from characteristics of more than 900 occupations based on two surveys from O* NET, US Department of Labor/Employment and Training Administration’s Occupational Information Network When answers reveal that an occupation requires daily activities such as “working outdoors” or “operating vehicles, mechanized devices,” or “contact with the public,” they determine that the occupation cannot be performed entirely from home DN2020’s measure, which is based on the Standard Occupational Classification (SOC) system used in the United States, needs to be concorded to the International Standard Classification of Occupations (ISCO-08) that is widely used globally at the 2- (or 3)-digit level of granularity (depending on the country) As DN2020 acknowledge, their Home-Based Work (HBW) index is likely to present an “upper bound” on the number of jobs that could feasibly be performed entirely from home, as it “neglects many characteristics that would make working from home difficult.”7 For many jobs, one of the principal constraints on performing them from home is internet access Even when a job is in principle suitable for working from home (teleworking), that option may not be available in practice if the worker does not have internet access at home To properly measure this constraint and account for the importance of ICT, we first need to split the telework jobs identified by the DN2020 index into two categories—jobs that require internet and those that not require it Then, for those telework jobs that require internet, we must identify which workers actually have access to the internet and for which workers a lack of access constitutes a constraint Our final objective is to classify jobs as amenable to being performed from home only if they not require internet or if they require internet and are held by workers who have internet access Our first step is identifying telecommutable jobs that require internet access using detailed information on occupation characteristics from the O* NET surveys We use two specific questions on the importance and frequency of computer and email use in the performance of the tasks The answers to these questions are scored on a 5-point scale with higher numbers indicating greater dependence on computers and email use We consider an occupation as requiring internet access if the combined average score exceeds (of a total of 10) This leads to 55 percent of all SOC 8-digit occupations in O* NET being classified as requiring internet By combining this measure with the DN2020 index, we can now distinguish four different types of occupations: (a) those that can be performed from home and require internet; (b) those that can be performed from home without the use of internet; (c) those that cannot be performed Figure Home Based Work across Countries (a) (b) Source: Authors’ elaboration based on income and employment data from International Labour Organization (ILO), internet requirement from O* NET surveys, internet access from the 2019 Gallup World Poll (GWP) and GDP per capita from the World Development Indicators of the World Bank Note: The country groups are aggregated by income level following the World Bank classification from home and not require internet; and (d) those that cannot be performed from home but require internet In the United States, 33.3 percent of all jobs can be done from home and require internet—e.g., fall into group (a), while a further 3.3 percent can be performed from home without internet usage—e.g., fall into group (b) To apply our occupation-level measures to other countries, we aggregate our 76 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Source: Authors’ elaboration based on income and employment data from International Labour Organization (ILO), internet requirement from O* NET surveys, internet access from the 2019 Gallup World Poll (GWP) and GDP per capita from the World Development Indicators of the World Bank Note: The GDP per capita is PPP-adjusted using 2017 international dollars Figure Home-based Work by level of income in Turkey, Mexico, Brazil, and India internet access constraints, there is very little change in the income distribution, hence smaller changes in the Gini coefficients Vulnerability to Labor Market Outcome: Which Workers are Most at Risk? Our analysis up to this point captured averages across countries by occupation groups, income deciles, or sub-national geographic areas The data indicate that labor market shocks associated with the COVID-19 pandemic impact poor countries, poor regions, and poor people more negatively We now assess whether there are personal characteristics of workers that can explain these patterns More specifically, we assess which workers are most at risk by running individual-level regressions in which the dependent variable is having a job that can be performed from home We estimate separate regressions for European Union Countries based on the EU Labor Force Survey of 2018 We control for age, gender, and education, first separately and then jointly The results for the European Union countries are reported 86 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Sources: Authors’ elaboration based on data from the Brazil 2017 Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC)—SEDLAC; the India 2011–12 National Sample Survey (NSS); the Mexico 2018 Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH)—SEDLAC; and the Turkey Labor Force Survey 2017–18 Figure Simulated Impact of COVID-19 on Income Inequality in table Next, we perform the same analysis for Brazil, India, Mexico, and Turkey Table presents the results for these countries Several common patterns emerge as seen in tables and Young workers (i.e., those between 15 and 24 years of age), who comprise the omitted age category in our regressions, are significantly less likely to have a job suitable for home-based work than older people across all countries Unlike the health risks of COVID-19, which are disproportionately borne by the elderly, the economic risk is thus concentrated among the youth Second, and most important, labor market vulnerability is inversely correlated with educational attainment Workers with tertiary education are much more likely to be able to work from home in all countries and regions Education is the strongest predictor of who has a relatively safe job among the set of explanatory variables we consider here While education offers protection in all countries, the probability of having a job suitable for working from home increases least with additional education in India, which is not surprising given that India has fewer jobs that can be performed from home to start with Interestingly, when using the DN2020 telework variable instead of our home-based work measure, the coefficient of education level Garrote Sanchez et al 87 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Source: Authors’ elaboration based on income and employment data from International Labour Organization (ILO), internet requirement from O* NET surveys, internet access, and usage from the 2019 Gallup World Poll (GWP) and GDP per capita from the World Development Indicators of the World Bank Table Determinants of Having a Job that Can Be Performed from Home—European Union Dependent Variable: Home-Based Work (O* NET) Country/Region Age 25–34 Age 45–54 Age 55–64 EU EU EU (2) (3) (4) 0.117*** (0.006) 0.128*** (0.007) 0.109*** (0.006) 0.109*** (0.007) 0.097*** (0.008) Female 0.132*** (0.006) 0.443*** (0.009) Secondary Tertiary Temporary Constant Observations R-squared Region FE 0.214*** (0.009) 1,244,093 0.008 NO 0.273*** (0.008) 1,244,093 0.017 NO 0.104*** (0.004) 1,242,384 0.213 NO 0.015*** (0.005) 0.040*** (0.005) 0.050*** (0.005) 0.060*** (0.006) 0.069*** (0.007) 0.140*** (0.006) 0.438*** (0.009) −0.030*** (0.003) 0.070 (0.064) 1,205,261 0.257 YES Source: Analysis based on individual data from the EU 2018 Labor Force Survey Note: Standard errors are clustered at the region and occupation (ISCO 2-digit) level and presented in parentheses *** , ** , * denote significance at the 10 percent, percent, and percent significance level respectively The omitted category comprises 15–24 year old workers who completed primary education in India becomes similar to the one in the other studied countries, which attests to a lack of internet access being a binding constraint on highly educated Indians’ ability to work from home Third, workers in temporary jobs are less likely to have jobs that can be performed from home This is worrisome, as they are more susceptible to losing their jobs, and reinforces the conclusion that COVID-19 is likely to exacerbate labor market inequality and will disproportionately impact those least protected Including all the explanatory variables, together with the regional fixed effects, does not change the significance of specific variables Education level, age, and job security are still highly important for the ability to perform a job from home even when regional heterogeneity is taken into account in each country 88 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Age 35–44 EU (1) Table Determinants of Having Jobs that Can Be Performed from Home (Dingel and Neiman 2020) Dependent Variable: Telework Index (Dingel and Neiman 2020) Country/Region Age 25–34 Age 45–54 Age 55–64 Female Secondary Tertiary Temporary Observations R-squared Turkey Brazil Mexico India (2) (3) (4) (5) −0.017 (0.012) 0.008 (0.017) 0.029 (0.020) 0.054*** (0.018) 0.104*** (0.021) 0.240*** (0.020) 0.562*** (0.028) −0.040*** (0.010) 88,320 0.286 0.007 (0.005) 0.016*** (0.006) 0.029*** (0.007) 0.015* (0.009) 0.061*** (0.009) 0.168*** (0.014) 0.512*** (0.022) −0.107*** (0.008) 75,337 0.406 0.009 (0.005) 0.024*** (0.006) 0.041*** (0.008) 0.041*** (0.009) 0.018* (0.008) 0.097*** (0.017) 0.453*** (0.028) −0.123*** (0.017) 63045 0.440 *** 0.014 (0.005) 0.040*** (0.005) 0.051*** (0.006) 0.062*** (0.006) 0.078*** (0.008) 0.154*** (0.007) 0.496*** (0.010) −0.034*** (0.004) 1,205,261 0.252 *** 0.058 (0.008) 0.098*** (0.010) 0.110*** (0.011) 0.160*** (0.014) -0.088*** (0.014) 0.133*** (0.014) 0.526*** (0.029) −0.024* (0.010) 104191 0.374 Source: Analysis based on data from the Brazil 2017 Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC)—SEDLAC; the India 2011–12 National Sample Survey (NSS); the Mexico 2018 Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH)—SEDLAC; and the Turkey Labor Force Survey 2017–18 Note: Standard errors are clustered at the region and 2-digit occupation (isco2d level) and presented in parentheses *** , ** , * denote significance at the 10 percent, percent, and percent significance level respectively Region fixed effects are included in all the estimations The omitted category comprises 15–24 year-old workers who completed primary education For India, the “Temporary” variable is based on an indicator of informality indicator instead of the type of contract due to data availability These findings dovetail with evidence from Latin America (Bottan, Hoffman, and Vera 2020), South Asia (ILO 2020b; World Bank 2020), and sub-Saharan Africa (Balde, Boly, and Avenyo 2020) that workers in informal jobs are more likely to have lost their jobs and income, in part because informal jobs tend to be more contactintensive Evidence for Italy shows that workers on a temporary contact are at higher risk of losing their job due to the pandemic (Casarico and Lattanzio 2020) In the same vein, employment in large firms has been more resilient to the COVID-19 pandemic than employment in small firms (IMF 2020) In the United States, Campello, Kankanhalli, and Muthukrishnan (2020) find a steeper decline in job postings by firms of smaller size, with higher levels of unionization, and in non-tradable sectors Garrote Sanchez et al 89 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Age 35–44 EU (1) From Vulnerability to Outcomes: A Bird’s Eye View of COVID-19 How well these vulnerability measures predict actual outcomes? The aggregate labor market impact of COVID-19 is unprecedented; workplace closures, working hour losses, and labor income losses have been higher than in any previous recession or crisis according to the ILO (2020) Between the fourth quarter of 2019 and the second quarter of 2020, global working hours declined by the equivalent of 495 million full-time jobs Global labor income is projected to decline by 10.7 percent in 2020 Consistent with the cross-country patterns of vulnerability identified using measures of home-based work, the labor market burden of COVID-19 is negatively correlated with GDP Lower-middle-income countries suffered a loss in working hours of 15.6 percent in the third quarter of 2020 with respect to the last quarter of 2019, compared to an estimated reduction of 9.4 percent in high-income countries for the same period (ILO 2020) The vulnerability metrics also predict differences in labor market outcomes across different groups where disadvantaged socio-economic groups within countries seem to be impacted more negatively Based on this comparison of the labor market 90 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 One group that is particularly vulnerable to the economic consequences of the COVID shock are immigrants Migrant workers systematically differ from the native labor force on a number of socio-economic characteristics and they are disproportionately concentrated in certain occupations and sectors where they have comparative advantage While natives specialize in occupations requiring more intensive communication and language skills, immigrants pursue jobs needing manual or quantitative skills (Peri and Sparber 2009, 2011) The self-selection of migrants into occupations has led to an asymmetric effect of COVID, with migrants concentrated in more vulnerable jobs Yasenov (2020) follows DN2020 and finds that only one in three migrants in the United States have jobs suitable for telework, compared to 45 percent of natives Fasani and Mazza (2020b) find similar results for migrants in the European Union, in particular those coming from extra-EU developing countries Given that migrants were more likely to have more vulnerable working conditions, with lower income and less job security, the COVID shock exacerbates pre-existing inequalities vis-à-vis natives Borjas and Cassidy (2020) analyze employment trends since the COVID outbreak and find that migrant males had higher rates of losing employment Migrants out of work at the onset of the crisis were also less likely to find new employment The authors attribute the larger impact on employment to the higher concentration of migrants in jobs with lower potential to being performed remotely On the other hand, the presence of migrant workers pushes natives, in particular those with higher education, towards occupations that are more suitable for working from home, thus, partially shielding them from the COVID shock (Bossavie et al 2020) Garrote Sanchez et al 91 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 outcomes of the second quarters of 2019 and 2020, workers with low incomes, with low levels of education, younger adults, ethnic minorities, and immigrants are concentrated in occupations that are more likely to be affected by the lockdowns The employment levels of women, of younger people, and of less educated workers have declined the fastest For example, while the number of employed college-educated workers declined by only 0.7 percent year on year, the employment levels of noncollege educated people decreased by over 10 percent People between 15–24 years of age lost 22 percent of their jobs while the same number is only 5.6 percent for 55–64-year-olds Employment in various services (trade, transportation, accommodation) declined by almost 10 percent whereas manufacturing employment increased marginally, and construction employment decreased only slightly Differences in employment vulnerability by education levels are similar across sectors While highly-skilled occupations that can be performed from home (such as for managers and professionals) experienced employment declines of between 3–6 percent, lower-skilled workers (such as those in sales) lost over 15 percent of their jobs To assess which of the different ex-ante measures of job vulnerability has the most predictive power we conduct a validation exercise using data from the European Union Specifically, table reports their correlations with actual employment losses in the 2nd quarter of 2020 (vis-à-vis employment in the 2nd quarter of 2019) for a given 1-digit occupation in a given 1-digit sector in every EU country for which Eurostat data is available As shown in the table, measures of ability to work from home (DN2020), face-to-face jobs (Avdiu and Nayyar 2020), or essential jobs (Fasani and Mazza 2020a) are strongly correlated with actual COVID-induced job losses Among them the DN2020 measure adjusted for internet access has the highest predictive power A 10 percentage point increase in the share of workers who can work from home reduces initial COVID-induced employment losses by 1.1 percentage points When splitting the DN2020 measure into (i) teleworkable jobs that not require internet, (ii) jobs that require internet and have access, and (iii) those that require internet but not have access, we find that only the shares of jobs in the former two categories are correlated with employment outcomes Jobs for which internet constraints are binding thus seem to be spuriously included in the original DN2020 measure Put differently, taking internet constraints into consideration helps to predict who is most at risk The results presented in table are consistent with other very recent papers Montenovo et al (2020) and Liu and Mai (2020) use CPS monthly employment data in the United States up to May and April 2020 respectively and show that job losses were greater in occupations that required more physical proximity and those that were less suitable for teleworking Using weekly administrative payroll data from the largest US payroll processing company up to June 2020, Cajner et al (2020) also observe a strong positive correlation between changes in employment and measures of feasibility to work from home per 3-digit industry In the EU, Fasani and Mazza (2020b) categorize occupations by level of ex-ante vulnerability based among other Table Predictive Power of Different Measures of Employment Vulnerability—European Union Data Dependent Variable: ࢞employment rate (2020, Q2 vs 2019, Q2) (at the ISCO occupation (1-digit)*NACE sector (1-digit) * country level) (1) (2) (3) (4) (5) (6) (7) Telework jobs (Dingel and Neiman 2020) 0.095*** (0.012) 0.067** (0.032) 0.114*** (0.015) −0.036 (0.057) Teleworkable without internet 0.046 0.048 (0.042) (0.043) Teleworkable with internet, have access 0.110*** 0.125*** (0.015) (0.020) Teleworkable with internet, no access −0.023 −0.119 (0.060) (0.098) 0.030*** Essential jobs (Avdiu and Nayyar 2020 in listing.) 0.031*** 0.032*** (0.006) (0.008) (0.008) Face-to-face (F2F) jobs (AN 2020) −0.070***−0.059***−0.057*** (0.021) (0.020) (0.020) Constant −6.046***−6.093***−5.965***−3.670*** 0.545 −4.481*** (0.574) (0.563) (0.544) (0.391) (0.949) (0.924) Observations Country Fixed Effects R-squared 1,892 No 0.066 1,892 No 0.068 1,892 No 0.068 1,892 No 0.007 1,892 No 0.008 1,892 No 0.081 1,892 Yes 0.093 Data Source: EULFS (2018), Eurostat (2020) Note: Standard errors clustered at the country level are presented in parentheses *** , ** , * denote significance at the 10 percent, percent, and percent significance level respectively Each observation represents one ISCO occupation (1-digit) * NACE sector (1-digit) * country The dependent variable is year to year change in employment between the 2nd quarter of 2019 and 2020 Telework jobs are jobs that are suitable for working from home according to Dingel and Neiman (2020, DN 2020) Home-Based Work (HBW) jobs are suitable working from home taking into consideration internet access constraints as explained in the article’s fourth section “Working from Home and Internet Access” They can be divided into three groups: (i) Teleworkable without internet: teleworkable jobs that not require internet, (ii) Teleworkable with internet, have access: jobs that require internet and have access, and (iii) Teleworkable with internet, no access: those that require internet but not have access Essential jobs are jobs classified as essential based on guidelines from the EU and the Dutch government by Fasani and Mazza (2020b, FM 2020b) Face-to-face jobs are ones that require extensive in-person interaction as measured by the index constructed by Avdiu and Nayyar (2020, AN 2020) factors on the contractual protection workers enjoy and the potential to telework, and they find that these measures are closely correlated with actual employment losses in European countries after COVID with data up to the second trimester of 2020 Nonetheless, these measures only capture one dimension of labor market vulnerability, as a preliminary review of the differential impact of COVID-19 by gender reveals Even though women are more likely to hold jobs that can be performed from home in many countries, they appear more likely to have lost their jobs during the COVID-19 crisis (Adams-Prassl et al 2020a,b; Alon et al 2020; Andrew et al 2020; Bèland et al 2020; Farré et al 2020; Mongey, Pilossoph, and Weingerg 92 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 0.109*** (0.013) Home-Based Work (HBW) jobs Garrote Sanchez et al 93 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 2020; Montenovo et al 2020; Qian and Fuller 2020; Sevilla and Smith 2020) Their hours of work have declined more (Andrew et al 2020; Collins et al 2020), and, in the United States, the partial recovery in employment over the last months has benefited men more than women (Bick, Baldwin, and Mertens 2020) The available evidence also points to a positive correlation between spouses’ home-based work opportunities, suggesting that the COVID-19 crisis is likely to impose a constraint on intra-household insurance through adjustments in spouses’ (typically female) labor supply (Malkov 2020; Peluffo and Viollaz forthcoming) The larger impact of COVID-19 on female unemployment exhibits a sharp contrast to the patterns from the previous recessions, in which men were harder hit (Alon et al 2020) Two main reasons can explain this difference First, in regular recessions, sectors with higher shares of male employment, such as construction and manufacturing, suffer larger employment reductions In the current recession, the sectors more affected have been the contact-intensive service sectors, such as travel, hospitality, and retail which also employ larger shares of women (Albanesi et al 2020; Alon et al 2020; Hupkau and Petrongolo 2020; Mongey, Pilossoph, and Weingerg 2020; Queisser, Adema, and Clarke 2020) The second reason is related to the increased housework and childcare responsibilities resulting from the closing of schools and nurseries The evidence shows that, in general, both women and men increased the amount of time allocated to childcare and housework, but the extra time was greater among women (Adams-Prassl et al 2020b; Del Boca et al 2020; Lyttelton, Zang, and Musick 2020; Sevilla and Smith 2020) These findings are consistent with existing studies documenting that women are more likely to miss work to shoulder caregiving responsibilities resulting from illness shocks to family members (Heath, Mansuri, and Rijkers forthcoming) This result is observed even when comparing women and men in the same employment situation (Adams-Prassl et al 2020b) More generally, how vulnerable workers are to crises induced by labor market strain also depends critically on both (i) the quality of pre-existing social protection systems (Paci, Revenga, and Rijkers 2012), which tend to be weaker in developing countries, and (ii) remedial policy responses Countries that acted swiftly and spent more have experienced smaller economic losses during the COVID-19 pandemic (Deb et al 2020; Demirgỹỗ-Kunt, Lokshin, and Torre 2020) Simulation evidence for Latin America shows that losses may be greatest in the middle of the ex-ante income distribution rather than among the poorest, because social assistance policies put a “floor” on the incomes of the poorest (Lustig et al 2020) Similarly Clark, D’Ambrosio, and Lepinteur (2020) argue that policy responses to COVID-19 may have offset its disequalizing impact in Europe By September, relative income inequality in France, Germany, Italy, Spain and Sweden had fallen compared to its pre-pandemic levels, despite an initial increase in income inequality in the early stages of the pandemic Additional data requirements 94 The World Bank Research Observer, vol 36, no (2021) Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 In the previous sections we have discussed the data used in other papers as well in our analysis Naturally, more detailed data can only improve the quality of the analysis and this section lists several suggestions that would enhance future analysis First, the ability to work-from-home depends on other infrastructure characteristics of the dwelling where a worker lives, such as space restrictions For instance, an office worker might lack adequate physical space to use as a home office or the proper equipment required to work from home Space restrictions interact with family size and composition, hindering productivity Similarly, data on family composition would be crucial to identify the constraints that care for dependants (children and the elderly) may impose on the potential to work from home As the previous section points out, these family care constraints are among the reasons why women are more likely to be negatively impacted even though they are more likely to hold jobs that can be performed from home The reason for not including these determinants in our HBW index is the absence of microdata for a large number of countries Second, data on internet access at the worker (or household) level is necessary to obtain a more precise HBW index Internet quality may impose a restriction on HBW possibilities as well, but comparable micro data on internet access and internet quality for a wide range of countries are not available Third, using skills surveys to determine the precise task content of each country’s jobs (as in Hatayama, Viollaz, and Winkler 2020) will improve the accuracy of HBW measures, particularly among less developed countries For example, workers are more likely to use nonroutine skills and higher levels of technology to perform the same job in higher-income countries The rapid adoption of skills surveys in countries at different levels of income is an encouraging development for this research agenda In the absence of skills surveys, a possible approach would be to use questions such as “what fraction of the tasks in your current job can be done from home?” (as in Adams-Prassl et al 2020b) However, these types of questions are not available in most countries’ labor force surveys Fourth, and related to the previous point, existing data are silent regarding the suitability of jobs to WFH in the rural areas of low-income countries As mentioned above, while farmers in subsistence agriculture may be able to WFH, this is not necessarily the case if they sell part of their production outside the home Finally, while WFH has been a key factor in protecting jobs during the pandemic, it is still not clear to what extent it is an efficient organization of work in the longer term While Bloom et al (2014) find that WFH has positive impacts on productivity, it is not obvious if this would also be the case for workers who, for example, not have the right infrastructure at home or live in a crowded dwelling At the same time, more research is needed to understand for what types of workers, firms, or sectors, WFH provides an efficient solution For example, empirical evidence from the Business and Management literature suggests that physical proximity and face-toface interactions can have significant impacts on innovation (Choudhury 2017), but that physical distance between managers and employees can give rise to separation costs in certain situations (Bonet and Salvador 2017) At the same time, understanding the productivity implications of hybrid models where WFH is not a binary outcome but a continuous one (e.g., WFH on certain days of the week or hours of the day) could be an important area of future research The COVID-19 pandemic will continue to cause severe labor market pain across the globe in the foreseeable future After reviewing the literature, we create a new measure of which jobs can be performed from home by combining information on the task content of jobs with information on internet access by country and income groupings On average, one in five jobs across the globe can be performed from home, but this number masks enormous heterogeneity across countries because the ability to telework is correlated with income In high-income countries one in every three jobs is suitable for home-based work, while in low-income countries only one in every 26 jobs can be done at home Failing to account for internet access would cause one to overestimate the prevalence of jobs amthat can be home-based in low-income countries by a factor of 4, and hence cause one to underestimate the vulnerability of poor countries The latter suffer two disadvantages: they have fewer jobs that are theoretically telecommutable to start with, and limited internet access is a bigger handicap Telecommutable jobs are highly unequally distributed across space, not only across but also within countries They are less prevalent in lagging regions The COVID-19 pandemic is thus likely to exacerbate spatial inequality, especially when one considers that local governments in lagging regions may have less fiscal capacity to cushion the COVID-19 shock Across all countries, jobs that can be performed from home tend to be much better paid Absent remedial action, the COVID-19 pandemic is thus likely to exacerbate inequality, and especially so in relatively richer countries given the higher prevalence of jobs suitable for home-based work Yet, the bulk of the labor market pain will be shouldered by workers in developing countries given the very limited feasibility of working from home and their limited recourse to social safety nets Across the globe, young, poorly educated workers and those with temporary contracts are especially exposed to labor market pain induced y COVID-19, which is worrying since they are more vulnerable at the outset The COVID-19 crisis is therefore bound to exacerbate domestic as well as global labor market inequality Garrote Sanchez et al 95 Downloaded from https://academic.oup.com/wbro/article/36/1/67/6158069 by KIM Hohenheim user on 19 April 2022 Conclusion Notes Caglar Ozden (corresponding author) email address is cozden@worldbank.org CEDLAS-FCE-UNLP Development Research Group The World Bank1818 H Street, NW Washington DC 20433 The DOT was succeeded by the Occupational Information Network (O* NET), which is the source of information used by Dingel and Neiman (2020) to categorize occupations by their amenability to WFH This is supported by other studies such as Autor and Dorn (2013) and Autor, Dorn, and Hanson (2015), who find that local labor markets more exposed to computerization experienced job polarization Polarization is more muted in poorer countries Graetz and Michaels (2018) use data from 17 high-income countries and find that robots not affect total hours worked, but they reduce the hours of low- and mid-skilled workers They use the Survey of Adult Skills from the Programme for the International Assessment of Adult Competencies (PIAAC), surveys from the Skills Toward Employment and Productivity (STEP) and the Labor Market Panel Surveys for Middle East countries https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020XC0330(03) In addition, it is not clear how the tasks required to perform an occupation are the same across economies at different levels of development Using PIAAC (Programme for the International Assessment of Adult Competencies) data at the country level, Hatayama, Viollaz, and Winkler (2020) observe changes in the ranking of countries in terms of their jobs’ suitability to WFH when comparing the measure based on PIAAC with DN2020’s measure, which are highly correlated Since most of the lower income developing countries not have data on the task content of their jobs (the PIAAC survey covers mostly OECD countries), we apply the DN2020 index to all countries The results from PIAAC countries using the Hatayama, Viollaz, and Winkler’s (2020) methodology are very similar and available upon request Recall from an earlier discussion that the association between GDP per capita and the share of jobs amenable to working from home depends critically on what we assume about the ability of agricultural workers to their jobs from home; assuming that the agricultural self-employed can work from home would result in a negative association between GDP and the prevalence of work suitable for working from home (Gottlieb, Grobovsek, and Poschke 2020) In contrast, there is less spatial variability in the share of jobs amenable to telework in India (not shown here but available from the authors upon request), reflecting the severely limited internet penetration in the country at the residential level 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(PNADC)—SEDLAC; the India 201 1–1 2 National Sample Survey (NSS); the Mexico 2018 Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH)—SEDLAC; and the Turkey Labor Force Survey 201 7–1 8; and regional
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