The unequal cost of job loss across countries

Antoine Bertheau, Edoardo Maria Acabbi, Cristina Barceló, Andreas Gulyas, Stefano Lombardi, Raffaele Saggio 11 March 2022

a

A

Imagine one Italian and one Danish worker who have similar skills and work in a similar industry. Imagine they suddenly lose their jobs because of a collective dismissal or a firm closure. Are the consequences of job loss different for the two workers? Do they share similar income and employment recovery paths?  And if these consequences are different, what are the underlying reasons?

Studying the consequences of job loss can help us understand the extent to which labour markets efficiently reallocate unemployed workers to new jobs (Jacobson et al. 1993). The literature on the consequences of job loss is vast and has shown that different groups of workers experience wildly different long-run recovery paths (Gulyas and Pytka 2020, Carrington and Fallick 2017).1 Nonetheless, the existing empirical evidence does not provide an answer to the questions posed above. Comparing the cost of job loss across different countries can shed light on which labour markets function better than others and why. However, it remains difficult to make meaningful cross-country comparisons of the consequences of job loss from existing studies due to differences in sample selection and methodology.

In a recent paper (Bertheau et al. 2022), we overcome these comparability issues by building a harmonized dataset that combines administrative records from the following seven countries that are characterized by diverse labour market institutions: Austria, Denmark, France, Italy, Portugal, Spain, and Sweden.2 We analyse the labour market outcomes of workers fired due to collective dismissals or firm closures (’mass layoffs’) for each country in our sample. We compare their labour market outcomes with those of workers who are similar along key observable dimensions but who don’t lose their jobs during a mass layoff in the same period. Mass layoffs allow us to capture actual involuntary job separations rather than voluntary quits or individual firings.

Figure 1 shows losses in earnings (excluding government transfers) due to mass layoffs. Each dot in the graph represents the average difference in labour earnings between the two groups of workers (those who were laid off during a mass layoff and those who were not), up to five years before and after the job loss event. To ensure the comparability of results across countries, Figure 1 reports quantities in the percentage change from the average pre-mass layoffs earnings in the sample. The main takeaway from Figure 1 is that losing a job has very different implications across Europe. Northern European workers (Danish and Swedish) experience by far the lowest earnings losses: five years after job loss, earnings are about 10% lower than before the mass layoffs. By contrast, the earnings drop of laid off workers from Southern Europe (Italy, Portugal, and Spain) is about 30%. Austrian workers experience earnings losses in between those of the Scandinavian and Southern European countries, while French workers experience losses similar to those of Scandinavian workers. 

Figure 1 Job loss effects on earnings 

To what extent are the differential earnings losses driven by differences in employment or in wages? On the one hand, Figure 2 shows that a large part of these cross-country differences in earnings losses is due to differences in the probability of finding a new job.  Around 20% of laid off workers from Spain, Portugal, and Italy are unable to find a job five years after losing their job. This number is only around 5% in Sweden and Denmark and around 10% in France and Austria. On the other hand, as we show in our paper, differences in wages are less dispersed and are clustered between 5% and 10% five years after job loss for most countries (see Bertheau et al. 2022 for details). Our analysis further shows that a considerable share of the wage declines after job loss is explained by transitions of laid off workers to worse-paying firms: this share ranges from around 40% for Spain to more than 95% for Portugal. 

Figure 2 Job loss effects on the probability of receiving positive yearly earnings

When trying to understand the sources of the large cross-country differences in income losses, a natural question is whether these are driven by differences in worker and employer characteristics across countries. In our recent paper, we show that the differential job loss effects observed across the European countries are not driven by cross-country differences in gender, job tenure, age, the unemployment rate, year of job loss, or other worker-level or previous employer characteristics. 

Given that neither wage losses nor differences in worker or employer characteristics appear to explain the large cross-country differences in earnings losses, we then focus on labour market institutions. As noted by Boeri (2011), institutional features – such as the strictness of employment protection, the generosity of unemployment benefits, and the scope of active labour market programmes – tend to vary substantially across the countries in our sample. 

Figure 3 reports the previously estimated job loss effects on earnings plotted against spending on active labour market policies (as a share of total spending on labour market programs). The figure highlights that active labour market policies, such as training programmes, are highly predictive of earnings losses. In countries that use more training policies, we find lower earnings losses three years after job loss. This result appears to be robust even when controlling for a wide range of worker-level demographic and labour market characteristics, employer features and calendar time trends. Furthermore, the results are robust across and within countries. By contrast, none of the other labour market institutions that we analyse in our paper (such as total spending in labour market policies, employment protection, and union coverage) appears to be robustly predictive of the persistent earnings drop that follows job loss. 

Figure 3 Earnings losses and spending on active labour market policies.

Note: Relationship between the estimated earnings losses three years after job loss and spending on active labour market policies. The regression coefficient obtained when controlling for country and year fixed effects, worker and employer characteristics, macroeconomic controls and labour market institutions is printed in pink, standard errors in parentheses (see Bertheau et al. 2022, for further details).

All in all, the considerably different earnings trajectories that follow job loss constitute a striking result that raises the question of what can be done to mitigate permanent earnings and employment losses. Our results reveal that labour markets function better in some countries than others and that labour market institutions have the potential to mitigate these differences.

Editors' note: An Italian version of this column is available on Lavoce.

References

Autor, D, D Dorn, G Hanson, and K Majlesi (2020). “Importing political polarization? The electoral consequences of rising trade exposure”, American Economic Review 110(10):3139-3183.

Bennett, P and A Ouazad (2016), “The relationship between job displacement and crime”, VoxEU.org, 29 October.

Bertheau, A, E Acabbi, C Barceló, A Gulyas, S Lombardi, and R Saggio (2022), “The unequal cost of job loss across countries”, NBER working paper 29727.

Boeri, T  (2011), “Institutional reforms and dualism in European labor markets”, Handbook of Labor Economics 4B: 1173-1236.

Carrington, J and B Fallick (2017), “Why do earnings fall with job displacement?”, Industrial Relations: A Journal of Economy and Society 56(4): 688-722.

Gulyas, A and K Pytka (2021), “Understanding the sources of earnings losses after job displacement: A machine-learning approach”, Working paper.

Jacobson, L S, R J LaLonde, and D G Sullivan (1993), "Earnings losses of displaced workers", The American Economic Review 83(4):685-709.

Kleven, H, C Landais, J Posch, A Steinhauer, and J Zweimüller (2019a), “Child penalties across countries: Evidence and explanations,” VoxEU.org, 14 May.

Kleven, H, C Landais, J Posch, A Steinhauer, and J Zweimüller (2019b), “Child penalties across countries: Evidence and explanations”, American Economic Association: Papers and Proceedings 109: 122-126.

Sullivan, D and T Von Wachter (2009), "Job displacement and mortality: An analysis using administrative data", The Quarterly Journal of Economics 124(3): 1265–1306.

Endnotes

1 A better understanding of the consequences of job loss has implications that go beyond the labour market outcomes. A large number of causal studies have found detrimental effects of job loss on workers’ health and likelihood of committing a crime, as well as on the rise of extreme political discourse (Sullivan and Von Watcher 2009, Bennett and Ouazad 2016, Autor et al. 2020).

2 This approach is analogous to the one employed in a different setting by Kleven et al. (2019a, 2019b). They study how men’s and women’s earnings are differently affected by the birth of a child and show that the magnitude of the child penalty for women differs widely across countries.

a

A

Topics:  Labour markets

Tags:  job loss, unemployment, Job market, labour market, employment

Postdoctoral researcher, University of Copenhagen

Assistant Professor of Finance, Universidad Carlos III de Madrid

Economist, Banco de España

Assistant Professor of Economics, University of Mannheim

Senior Researcher, VATT Institute for Economic Research

Assistant Professor, Vancouver School of Economics, University of British Columbia

Events

CEPR Policy Research