Since the onset of the Covid-19 pandemic, working from home (WFH) has been increasingly implemented in major advanced countries. Before the crisis, the percentage of workers participating working from home was approximately 10% in major advanced countries. The number of workers who conduct their jobs at home increased suddenly in March 2020. But productivity at home compared to the usual workplace – which is a key parameter in assessing the impact of WFH on the economy – has not been well understood.
Working from home in the epidemiology models
Epidemiological models that incorporate the economic behaviour of individuals have been developed, and simulation analyses of the effects of social distancing measures (such as a shelter-in-place orders and mandatory shutdowns of service industries) have been conducted in many countries (Avery et al. 2020). These studies indicate that stringent social distancing policies are effective in mitigating the spread of the pandemic, but have large negative impacts on economic activity. This means that there is a trade-off, at least in the short run, between public health and the severity of the recession.
Some of the simulation models explicitly take into account people working from home (e.g. Akbarpour et al. 2020, Aum et al. 2020, Bodenstein et al. 2020, Brotherhood et al. 2020, Jones et al. 2020, Fujii and Nakata 2021), because the feasibility of working from home practices can mitigate the trade-off between health and economic activity arising from social distancing policies.1 However, in addition to the feasibility of home working, its productivity relative to working at the usual workplace also affects how well WFH mitigates the negative impacts of social distancing policies on the economy. In the simulation studies, the percentage of jobs that can be performed at home is often taken from task-based estimates such as Dingel and Neiman (2020). By contrast, because estimates of working from home productivity have been scarce, simulation studies have assumed arbitrary figures for home productivity, such as 50% or 70% relative to working at the workplace.
How productive is working from home during the Covid-19 pandemic?
A small number of studies have presented evidence on productivity when working from home based on individual or firm surveys during the Covid-19 pandemic. Etheridge et al. (2020), using data from a survey of individuals in the UK, show that, on average, productivity at home is not significantly different from that in the workplace. Barrero et al. (2020), based on a survey of individuals in the US, indicate that the majority of respondents who have adopted home working practices report higher productivity than their expectation before the start of the pandemic. Using data from a survey of individuals in Japan, in Morikawa (2020) I show that the productivity of employees adopting the home working arrangement during the Covid-19 pandemic is, on average, 30–40% lower than that in the office. Bartik et al. (2020), using data from a survey of small and medium-sized firms in the US, report a decrease in productivity of about 20% on average.
However, despite its importance, quantitative evidence on WFH productivity during the pandemic has still been limited and inconclusive. In this respect, I designed an original survey of Japanese firms in order to deepen our knowledge (Morikawa 2021). The Survey of Corporate Management and Economic Policy (SCMEP) was conducted from August to September 2020. The survey questionnaire was sent to 2,498 firms, and 1,579 firms (approximately 63%) responded.2
The main topics of inquiry in the survey regarding home working were (1) whether the home working practice has been implemented; (2) the percentage of employees who have used this workstyle; (3) the mean working from home frequency of teleworkers); (4) the mean productivity of working from home relative to the workplace; and (5) factors that affect the adoption of the home working system and productivity of employees using this workstyle. Many of the questions are aligned with the employee survey (Morikawa 2020). Hence, the two surveys can be compared.
Working from home intensity: Contribution to total labour input
The percentage of firms that adopted the home working system is 49.6% (Column 1 of Table 1). Across industries, the information and communications industry is the highest (96.4%), and the retail industry is the lowest (29.8%). However, even for firms that have adopted a home working system, not all employees exploited this workstyle. In this regard, the survey asks: “What percentage of your employees used the WFH practice after the spread of COVID-19?” The result is presented in Column 2 of the table. The mean percentage of firms adopting home working is 30.7%. Across industries, the information and communications industry (59.6%) is the highest, and the manufacturing industry (18.8%) is the lowest.
Table 1 Adoption and intensity of WFH
Note: Columns (2) and (3) indicate figures for firms adopting WFH practice.
Even for employees who exploited this workstyle, they were not necessarily full-time teleworkers (i.e. working at home on all working days). As a result, the survey asks: “What was the average number of WFH days per week for employees who implemented the WFH practice?” The results are summarised in Column 3 of Table 1. The mean frequency of home working implementation is 3.67 days per week. Assuming that the normal number of working days is five days a week, teleworkers have spent more than 70% of their work hours at home during the pandemic.
Next, I calculate the intensity of working from home at the firm level as the share of employees using home working multiplied by the frequency of working from home per week (converted into percentages). This measure indicates the contribution of hours spent working from home to the total labour input. Column 4 of Table 1 shows the weighted average of the working from home intensity, using the number of employees of a firm as weight and including the home working non-adopters (whose intensity is regarded as zero). The average working from home intensity across all industries is 10.9%. The contribution of working from home to labour input is surprisingly small, even during the period when home working peaked. Even if a firm adopted this workstyle, many employees did not exploit it; and even those who used home working did not necessarily work at home throughout the week. Hence, the macroeconomic contribution of working from home to total labour input was limited. Across industries, the information and telecommunications industry is the highest at 44.6%, while the retail industry is extremely low at 3.9%. This is an unsurprising result, as more than 70% of firms in the retail industry did not adopt home working.
Productivity of working from home and its determinants
The question about working from home productivity evaluated from the employer’s viewpoint is: “Suppose that employees’ productivity at the workplace is 100, how do you evaluate their productivity at home? Please answer the mean productivity by considering all tasks covered by the WFH system”. The questionnaire also noted that, “[if] the WFH system is more productive than the workplace, please answer a figure over 100”. Respondents were thus given the chance to suggest that, in their experience, working from home is more productive than the workplace.
The simple average for firms adopting home working is 68.3% (Figure 1). According to a survey of employees, the mean subjective productivity of working from home is 60.6% (Morikawa 2020). As the firms surveyed in this study only included those with at least 50 employees, we should be careful in comparing the figures simply, but the figure is similar to employees’ subjective assessments of their productivity at home. Across industries, the mean productivity when working from home is highest in the information and telecommunications industry at 80.3%, with the figures for the rest of the industries ranging from 62.6% to 69.5%.
Figure 1 Mean productivity of WFH relative to the workplace
Note: I&C stands for the information and communications industry.
The survey asked multiple-choice questions about factors negatively affecting the adoption and productivity of home working. The specific question is: “Were there any obstacles or limitations in adopting or expanding the WFH practice or matters that negatively affected WFH productivity?”.
A large number of firms chose, in descending order (Table 2), “Some tasks cannot be conducted at home although these are not required by the rules and regulations” (76.1%), “Poor telecommunication environment at home relative to the workplace” (60.8%), “Rules and regulations that require some tasks to be conducted in the office” (57.7%), and “Loss of immediate communication that is only possible through face-to-face interactions with colleagues at the workplace” (46%). Although the percentages are different, these four reasons occupy the top positions in the employee survey reported in Morikawa (2020).
Table 2 Factors affecting adoption and productivity of WFH
Note: Multiple answers were allowed for this question.
In summary, the findings from a firm survey on the prevalence, intensity, and productivity of working from home are generally consistent with the results obtained from an employee survey. The results suggest that the feasibility of home working has room for improvement and that productivity at home can be enhanced by improving the ICT environment and by revising existing laws, regulations, and internal company rules that currently inhibit working at home. For the foreseeable future, however, the existence of types of work that must be performed at the workplace, together with the difficulty of efficient, face-to-face communication from home, are both likely to restrict the diffusion of working from home.
Editor’s note: The main research on which this column is based (Morikawa 2021) first appeared as a Discussion Paper of the Research Institute of Economy, Trade and Industry (RIETI) of Japan.
Akbarpour, M, C Cook, A Marzuoli, S Mongey, A Nagaraj, M Saccarola, P Tebaldi, S Vasserman and H Yang (2020), “Socioeconomic Network Heterogeneity and Pandemic Policy Response”, NBER Working Paper 27374.
Aum, S, S Y Lee and Y Shin (2020), “Inequality of Fear and Self-Quarantine: Is There a Trade-off between GDP and Public Health?”, NBER Working Paper 27100.
Avery, C, W Bossert, A Clark, G Ellison and S F Ellison (2020), “Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists”, NBER Working Paper 27007.
Barrero, J M, N Bloom and S J Davis (2020), “Why Working from Home will Stick”, University of Chicago, Becker Friedman Institute for Economics, Working Paper 174.
Bartik, A W, Z B Cullen, E L Glaeser, M Luca and C T Stanton (2020), “What Jobs are Being Done at Home During the Covid-19 Crisis? Evidence from Firm-Level Surveys”, NBER Working Paper 27422.
Behrens, K, S Kichko and J-F Thisse (2021), “Working from Home: Too Much of a Good Thing?”, CEPR Discussion Paper 15669.
Bodenstein, M, G Corsetti and L Guerrieri (2020), “Social Distancing and Supply Disruptions in a Pandemic”, CEPR Discussion Paper 14629.
Brotherhood, L, P Kircher, C Santos and M Tertilt (2020), “An Economic Model of the Covid-19 Epidemic: The Importance of Testing and Age-Specific Policies”, CEPR Discussion Paper 14695.
Dingel, J I and B Neiman (2020), “How Many Jobs Can be Done at Home?”, NBER Working Paper 26948 (see also the Vox column here).
Etheridge, B, L Tang and Y Wang (2020), “Worker Productivity during Lockdown and Working from Home: Evidence from Self‑reports”, Covid Economics 52: 118–151.
Fujii, D and T Nakata (2021), “COVID-19 and Output in Japan”, RIETI Discussion Paper 21-E-004.
Jones, C J, T Philippon and V Venkateswaran (2020), “Optimal Mitigation Policies in a Pandemic: Social Distancing and Working from Home”, NBER Working Paper 26984.
Morikawa, M (2020), “Productivity of Working from Home during the COVID-19 Pandemic: Evidence from an Employee Survey”, Covid Economics 49: 132–147.
Morikawa, M (2021), “Productivity of Working from Home during the COVID-19 Pandemic: Evidence from an Employee Survey”, RIETI Discussion Paper 21-E-002.
1 Behrens et al. (2021) develop a general equilibrium model to study the WFH intensity in the economy. They indicate that the relationship between WFH and productivity is ∩-shaped and the share of WFH that maximizes GDP is between 20% and 40%.
2 The SCMEP does not include small firms with fewer than 50 employees or capital of less than 30 million yen.