In 2020, the COVID-19 pandemic caused by far the largest shock to European economies since World War II. Yet, astonishingly, the EU unemployment rate had already declined to its pre-crisis level by 2021Q3, and in some countries the labor force participation rate is at a record high. This paper documents that the widespread use of job retention schemes has played an essential role in mitigating the pandemic’s impact on labor markets and thereby facilitating the restart of European economies after the initial lockdowns.
The COVID-19 pandemic had posed a dramatic impact on labor markets across Europe. Forceful fiscal responses have prevented an otherwise sharper contraction. Many countries introduced or expanded job-retention schemes to preserve jobs and support households. This paper uses a microsimulation approach (EUROMOD) and household data to assess the effectiveness of those schemes in stabilizing household income during the pandemic across European countries. Empirical evidence shows that job-retention schemes were effective in stabilizing income and, along with other measures, absorbed nearly 80 percent of market income shocks—almost doubling the extent of the automatic stabilization of the pre-pandemic tax and benefit systems. The large effects are related to the widespread use and scaling up of those schemes and a deep but short-lived disruption to labor markets during the pandemic. Along with other fiscal support measures, job-retention schemes helped mitigate the rise in the unemployment rate, by about 3 percentage points, and income inequality during the pandemic. Our results show that job-retention schemes were largely targeted, in which households more vulnerable to income losses, such as lower-income families, youth, and low-skilled workers, are able to stabilize their income.
This book focuses on the impact of the COVID-19 pandemic on changing labour markets and accelerating digitalisation of the workplace in Central and Eastern Europe. The COVID-19 pandemic disrupted workplaces substantially. As the lockdowns or stay-at-home measures entered into force, a large proportion of the workforce was instructed to stay home and continue to work remotely if their functions made it possible. This policy accelerated the introduction of many digital solutions, requiring the establishment of new patterns of work, and new institutional logic guiding daily activity for both organisations and individuals. In a relatively short time, remote working has become a kind of commonly accepted new institution with its own new logic, structures, rules, and behaviours (Jacks, 2021). The trends contributing to a shift towards more flexible, digital working patterns were emerging before the pandemic (over the last decade) in response to societal developments, the increasing participation of women, and greater global competition. In 2020, the combined health and economic shocks have only deepened the concerns about technology-driven displacement of jobs, growing income inequality, and rising societal discord towards globalisation.
Child poverty increased dramatically during the COVID-19 pandemic. In 2020 alone, the number of children suffering from poverty in the EU increased by 19 percent, or close to 1 million. Left unaddressed, this would not only affect individuals’ life prospects and well-being but also have long-term economic implications. This paper argues that, to limit this potential scarring effect of the pandemic, policies should be deployed to reduce rapidly the number of children affected by poverty and mitigate the long-term impact of poverty. Reducing the number of children affected by poverty can be achieved by (i) labor policies and reforms that increase parental work and the labor income of poor parents and (ii) fiscal spending on family and children that can have a powerful and immediate impact. These policies need to be complemented by public investment in education and childcare, health, and housing to mitigate the long-term impact of child poverty.
We develop a bottom-up model of inflation in the euro area based on a set of augmented Phillips curves for seven subcomponents of core inflation and auxiliary regressions for non-core items. We use the model’s disaggregated structure to explore which factors drove the deterioration in forecasting performance during the pandemic period and use these insights to improve on the ability to forecast inflation. In the baseline, the projection for core inflation is centered above 3 percent at end-2023, while headline inflation is expected to drop quite sharply over 2023, with energy base effects pulling inflation down from the currently very elevated levels to below 3 percent by 2023q4. The confidence intervals around these projections are wide given elevated uncertainty. We argue that the bottom-up approach offers a useful complement to the forecasters toolbox – even in the current uncertain environment - by improving forecast accuracy, shedding additional light on the drivers of inflation and providing a framework in which to apply ex post judgement in a structured way.
Reducing transport sector emissions is an important pillar of the green transition. However, the transition to electric vehicles (EV) portends major changes in vehicle manufacturing activity, on which many livelihoods in Europe depend. Using the heterogeneity across European countries in the speed of transition to EV production and variation in sectoral and regional exposure to the automotive sector, this paper offers early evidence of the labor market implications of the EV transition. Our results suggest that the transformation of the auto sector is already having an adverse impact on employment in the affected sectors and regions, which can be expected to grow at least in the near term. Many of the affected workers will be able to retire and our analysis suggests that those who will have to transition to new “greener” jobs have a fair chance to do so when compared to other workers in the manufacturing sector. Furthermore, we find evidence that active labor market policies, specifically training, can help to reduce the adjustment costs for the affected workers.
