By Katja Möhring, Elias Naumann, Maximiliane Reifenscheid, Annelies G. Blom, Alexander Wenz, Tobias Rettig, Roni Lehrer, Ulrich Krieger, Sebastian Juhl, Sabine Friedel, Marina Fikel, and Carina Cornesse
The Coronavirus crisis and the related lockdown measures had a devastating impact on the economies and labour markets of the affected countries. In Germany, lockdown measures were initiated in mid-March and included immediate closure of public facilities, restaurants, shops, theatres etc. on March, 22nd the latest. Due to the following collapse of domestic demand and exports, more sectors than hospitality and retail were affected.
Thus, many companies of the strongly export-oriented German economy either faced an immediate demise of revenues or a continuous decline of orders. How does this affect employment? How many employees have changed to short-time work (Kurzarbeit), are on leave or have lost their job since the onset of the lockdown? How many people continue working at their workplace on-site as before, and how many have changed to remote work from home?
The data of the Mannheim Corona Study consists of weekly interviews of the population-representative sample of the German Internet Panel (GIP), and therefore, offers the unique possibility to track changes in employment over the period of the lockdown in real-time. We use this data not only to track changes in employment during the lockdown, but also to shed light on the social inequality related to these.
Germany is a regulated market economy characterized by a pronounced ‘insider-outsider’ divide. In the 2000s, an expansion of marginal employment has been initiated, resulting in considerable amounts of low wage and fixed-term employment, while the core work force in standard employment is well protected by labour regulations. Immediate lay-offs, for example, are not possible for those in regular employment as the legal notice period is at least one month and increases with tenure. Furthermore, labour market measures and subsidies to stabilize the economy and buffer the negative crisis consequences for employees and companies are mostly targeted at the core work force. The state allowance for short-time work (Kurzarbeitergeld) is a governmental earnings replacement to compensate for the wage loss due to cuts in working hours: 60% (67% for those with children) of the previous net income is granted. The goal of the short-time work subsidy is to prevent lay-offs by enabling employers to reduce the working hours of their employees in case of a temporary loss of orders or an economic downturn. Short-time work, however, is restricted to employees in regular employment.
In the following analysis, we include only people who were employed in January 2020 (including self-employment and marginal employment) to focus on work related changes during the Coronavirus lockdown. We classify the employment situation into five categories: working on-site, remote working from home, short-time work, furlough with continued pay, furlough without pay, and unemployment.
Overall, the majority of those in employment before the Coronavirus pandemic continued working on-site on a regular basis over the lockdown period (close to 60 percent and increasing, Figure 1). About a fifth to a quarter of the employed persons is working remotely. From May 8th on, we applied a more detailed measure for the employment situation in the Mannheim Corona Study, allowing us to identify those who combine remote and on-site work. In fact, in May around 20% of employees work partly on-site and partly remotely, whereas a smaller and declining percentage works only at home.
At the beginning of our observation period in late March only a small share of employees had already been sent on short-time work (3.4 percent in the first week) and it was more common to be in furlough with or without pay. Already three weeks later, in early April, short-time work has become the most common response of employers to address the economic consequences of the Coronavirus crisis (see Figure 1). The share of employees on short-time work was around 10 percent at the beginning of April and then further increased to 15 percent in May and June. While during these first weeks, some of the employed persons were sent on unpaid leave (10 percent) or paid leave (4.2 percent), this share has dropped to below 2 percent May and June. The share of people who have lost their job since January 2020 has been comparable small and remained at a stable level of below 2 percent over the whole period of the lockdown. These results suggest that short-time work has been able to cushion the negative consequences for both employees and employers and prevented sharp increases in unemployment numbers.
Figure 1: Employment situation during lockdown, weekly information since March 20
However, these aggregate trends might hide social inequalities. Negative economic consequences of the Coronavirus pandemic might not affect all employees equally. If negative consequences are distributed along already existing inequality patterns, social inequality could increase leading to further social problems. In the following figures, we explore how the employment situation of different social groups has changed.
First, we examine gender differences in the employment situation. Before the Corona crisis, according to GIP data of January 2020, more men than women were at least occasionally working from home (22.5 percent of men, 15.5 percent of women). Furthermore, among those who did not work remotely, more women than men (39.0 percent compared to 31.4 percent) said that they would like to work from home. During the Corona lockdown, the differences between men and women in using remote work were vanishing. The share of men working from home is only around 3 percentage points higher than the share of women (Figure 2). This suggests that before the Corona lockdown, attitudes of superiors and employees’ fear of discrimination rather than technical obstacles hindered the use of remote work among female employees. While there are no gender differences in unemployment, women and men are differently affected by short-time work and furlough. Especially in the first weeks of the lockdown, women were much more likely to be send to furlough than men. This is due to the fact that in Germany a lot more women than men are in marginal employment working on call – for them furlough is mostly without pay. Furthermore, more women than men work in the educational sector where furlough is typically with continued pay. Short-time work is slightly more common among men (around 3 percentage points difference, see Figure 2), however, this difference is not significant. To sum up, the Corona crisis has the potential to intensify, but also to attenuate gender inequalities on the labour market. Women are more often working in marginal employment in which they have no access to short-time or unemployment benefits – this applies especially to the hard-hit hospitality and catering industry and household-related services. On the other hand, if firms and employers make positive experiences with remote work at home and allow more (male and female) employees with care responsibilities to work from home, this could contribute to lessen gender inequality.
Figure 2: Employment situation by gender
Education and income are the most important dimensions of social inequality. Does the Coronavirus crisis increase the existing social inequality and are lower education and income groups particularly affected by the negative economic consequences? Our results do suggest this. We show the employment situation depending on the level of school education and distinguish between low (without or with basic school-leaving qualification, Hauptschulabschluss), middle (intermediate school-leaving qualification, Mittlere Reife), and high (higher education entrance qualification, (Fach-)Hochschulreife).
The lower the level of education, the higher the proportion of people who change to short-time work, to furlough with or without pay or are laid off (Figure 3). Job loss for someone with a low or middle education is twice as likely as for someone with a high level of education. Among those who kept their jobs and were able to work about the same hours as in January 2020, employees with a high level of school education are more often working remotely (more than 40 percent in March and April) than employees with a lower level of education. The majority of those with a low or medium school education works on-site in the employer’s company (about 62 percent and 64 percent in march). In summary, high education reduces the risk of job loss and at the same time provides the privilege to work remotely. The negative consequences of the coronavirus lockdown hence increase existing social inequalities along two dimensions. The lower educated either loose their job or experience partial income loss in on short-time work or if they are able to keep their jobs, they have to work on-site facing higher infection risks.
Figure 3: Employment situation by school degree
Figure 4: Employment situation by income
A similar pattern can be observed when looking at the employment situation by income (Figure 4). Here, we refer to the personal income before the onset of the Coronavirus lockdown. Among persons with a net income of more than 2,500 Euro (and thereby belonging to the top 25% income earners in Germany), about 40 percent worked from home in March, somewhat more than 45 percent worked on-site at their employer’s company and only between 12 and 15 percent were affected by short-time work, furlough or layoff. The majority of those with a medium income (1,000 – 2,500 Euro) as well as of those with a low income of less than 1,000 Euro per month was working on-site even during the first weeks of the lockdown. Particularly low-income groups are hit by short-time work, suspensions and layoffs. This means that low-income groups are either exposed to a higher infection risk because of continued work on-site or they have to experience the negative economic implications of the Coronavirus pandemic much earlier than the higher income groups.
So far, we have focused on the immediate consequences of the lockdown. Although some groups were more affected by the negative crisis consequences than others, overall, transitions into unemployment were not common in Germany during the first phase of the lockdown. Therefore, we take a look at the respondents’ subjective assessment of their future job security to derive conclusions on the possible long-term impact of the crisis.
Figure 5: Perceived risk of unemployment in the next 12 months
Figure 5 displays average concerns about job loss within the next 12 months divided into three categories: no/low likelihood, moderate likelihood, high/very high likelihood of job loss. Among those who continue working at usual hours—either on-site or remotely from home— concerns about job loss are low, while those in short-time work and especially those suspended without pay assess their future job security low. Overall, despite a massive slump in production in March/April, the working population as a whole shows only moderately increased worries about future job loss. The growing concerns about future job security among those in short-time work signal, however, that the long-term consequences of the crisis might be more severe for some groups. Especially employees who were employed under precarious conditions before the Coronavirus pandemic are more exposed to the effects of the crisis. They already had a much higher risk of becoming unemployed or suspended without pay during the first weeks of the lockdown and now estimate their future unemployment risk as comparatively high. Consequently, the immediate and mid-term consequences of the Coronavirus crisis in Germany resemble and will possibly intensify the pre-existing structures of social inequality in the German labour market.
About the Authors:
Katja Möhring is Assistant Professor for Sociology of the Welfare State at the School of Social Sciences, University of Mannheim
Elias Naumann is Post-Doctoral Researcher at Collaborative Research Center SFB 884, University of Mannheim
Maximiliane Reifenscheid is Doctoral Researcher at Collaborative Research Center SFB 884, University of Mannheim
Annelies G. Blom is Professor for Data Science at the School of Social Sciences, University of Mannheim
Alexander Wenz is Post-Doctoral Researcher at Chair for Data Science, University of Mannheim
Tobias Rettig is Doctoral Researcher at Chair for Data Science, University of Mannheim
Roni Lehrer is Post-Doctoral fellow at the Mannheim Centre for European Social Research
Ulrich Krieger is Post-Doctoral Researcher at Chair for Data Science, University of Mannheim
Sebastian Juhl is Doctoral Researcher at Collaborative Research Center SFB 884, University of Mannheim
Sabine Friedel is Doctoral Researcher at Chair for Data Science, University of Mannheim
Marina Fikel is Doctoral Researcher at Chair for Data Science, University of Mannheim
Carina Cornesse is Post-Doctoral Researcher at Chair for Data Science, University of Mannheim