The Costs of Firm Exit and Labour Market Policies: New Evidence from Europe

Dan Andrews; Irene Ferrari; Alessandro Saia

doi:10.1515/bejeap-2017-0211

Article

The Costs of Firm Exit and Labour Market Policies: New Evidence from Europe

Dan Andrews , Irene Ferrari and Alessandro Saia

Published/Copyright: October 11, 2018

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From the journal The B.E. Journal of Economic Analysis & Policy Volume 19 Issue 1

Abstract

The churning of firms is an inherent process of industrialized economies, which entails a high rate of job destruction. Thus, a key question is: what are the policies that minimize the costs of worker displacement due to business closure? Accordingly, this paper exploits a retrospective panel of workers in 13 European countries over the period 1985–2008 to explore the factors which shape the reemployment prospects of workers displaced due to business closure. The results suggest that higher spending on active labour market policies increases the reemployment prospects of the unemployed workers displaced by business closure, both in terms of unemployment duration and in terms of stability of reemployment. On the contrary, there is evidence of a negative and sizable impact of passive labour market policies on unemployment duration.

Keywords: worker displacement; business closure; labour market programmes

JEL Classification: J63; J68; O40

A Appendix

Table 9:

Data sources.

Variable	Definition	Source
ALMP	Placement and Administration, Training, Employment Incentives, Direct Job Creation and Start-up Incentives, (public expenditure as a percentage of GDP)	OECD Labour Market Programmes Database
PLMP	Out-of-work income support and Early retirement, (public expenditure as a percentage of GDP)	OECD Labour Marketr Programmes Database
Out of income Support	Corresponds to public expenditure in unemployment benefits, redundancy compensation, and bankruptcy compensation	OECD Labour Market Programmes Database
Average Replacement rate	Proportion of income in work that is maintained after job loss	Bassanini and Duval (2009)
Entry barriers	Regulation in energy, transport, and communications	OECD.stat

B Appendix

Table 10:

Heterogeneous effects of labour market policies according to worker’s age.

	(1)
ALMP (% of GDP)	0.166***
	(0.0505)
PLMP (% of GDP)	$-$ $−$ 0.137***
	(0.0257)
Age	$-$ $−$ 0.0132***
	(0.00189)
ALMP $\times$ $×$ Age	0.00323
	(0.00454)
PLMP $\times$ $×$ Age	$-$ $−$ 0.00462**
	(0.00193)

Demographic controls	YES
Country-fixed effects	YES
Year-fixed effects	YES
Observations	1,348
$R^{2}$ $R2$	0.142

Notes: The estimates are based on a sample of displaced workers in 13 European countries over the period 1985 to 2008. Changes in the sample size are due to different coverage of the explanatory variables. The dependent variable is a dummy that takes value 1 if an individual who lost her job due to business closure in a given year found a new job within the next year. Demographic controls include gender, age, previous job tenure, relationship status, and number of children. Robust standard errors clustered at the country 5-year period level in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10%, respectively.

Table 11:

Robustness to the inclusion of additional controls.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)
ALMP (% of GDP)	0.171***	0.170***	0.172***	0.155***	0.121**	0.117*	0.128*
	(0.0525)	(0.0534)	(0.0541)	(0.0565)	(0.0591)	(0.0645)	(0.0672)
PLMP (% of GDP)	$-$ $−$ 0.0967***	$-$ $−$ 0.0953***	$-$ $−$ 0.0979***	$-$ $−$ 0.103***	$-$ $−$ 0.141***	$-$ $−$ 0.149***	$-$ $−$ 0.152***
	(0.0243)	(0.0255)	(0.0256)	(0.0261)	(0.0305)	(0.0296)	(0.0302)

Demographic controls	YES	YES	YES	YES	YES	YES	YES
Country-fixed effects	YES	YES	YES	YES	YES	YES	YES
Year-fixed effects	YES	YES	YES	YES	YES	YES	YES
Education	NO	YES	YES	YES	YES	YES	YES
Industry-fixed effects	NO	NO	YES	YES	YES	YES	YES
Total tenure and Total tenure $\times$ $×$ Education	NO	NO	NO	YES	YES	YES	YES
Output gap	NO	NO	NO	NO	YES	YES	YES
ETCR & EPL	NO	NO	NO	NO	NO	YES	YES
Labour tax wedge	NO	NO	NO	NO	NO	NO	YES
Observations	951	951	951	951	951	951	951
$R^{2}$ $R2$	0.173	0.179	0.191	0.250	0.253	0.254	0.255

Notes: The estimates are based on a sample of displaced workers in 13 European countries over the period 1985 to 2008. Changes in the sample size are due to different coverage of the explanatory variables. The dependent variable is a dummy that takes value 1 if an individual who lost her job due to business closure in a given year found a new job within the next year. Demographic controls include gender, age, previous job tenure, relationship status, and number of children. Robust standard errors clustered at the country 5-year period level in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10%, respectively.

Table 12:

Robustness to alternative definitions of labour market policies.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
ALMP spending per unemployed	0.00251***	0.00295***			0.00285***	0.00328***
divided by GDP p.c. (%)	(0.000728)	(0.000722)			(0.000727)	(0.000701)
PLMP spending per unemployed			$-$ $−$ 0.00320*	$-$ $−$ 0.00362*	$-$ $−$ 0.00400***	$-$ $−$ 0.00436***
divided by GDP p.c. (%)			(0.00181)	(0.00181)	(0.00145)	(0.00150)
Average unemployment benefit							$-$ $−$ 0.00569**	$-$ $−$ 0.00714***
replacement rate (%)							(0.00258)	(0.00229)
Demographic controls	YES	YES	YES	YES	YES	YES	YES	YES
Country-fixed effects	YES	YES	YES	YES	YES	YES	YES	YES
Year-fixed effects	YES	YES	YES	YES	YES	YES	YES	YES
Education	NO	YES	NO	YES	NO	YES	NO	YES
Industry-fixed effects	NO	YES	NO	YES	NO	YES	NO	YES
Total tenure and Total tenure $\times$ $×$ Education	NO	YES	NO	YES	NO	YES	NO	YES
Output gap	NO	YES	NO	YES	NO	YES	NO	YES
ETCR & EPL	NO	YES	NO	YES	NO	YES	NO	YES
Labour tax wedge	NO	YES	NO	YES	NO	YES	NO	YES
Observations	972	972	972	972	972	972	1,021	1,021
$R^{2}$ $R2$	0.165	0.245	0.162	0.241	0.170	0.250	0.156	0.246

Notes: The estimates are based on a sample of displaced workers in 13 European countries over the period 1985 to 2008. Changes in the sample size are due to different coverage of the explanatory variables. The dependent variable is a dummy that takes value 1 if an individual who lost her job due to business closure in a given year found a new job within the next year. Demographic controls include gender, age, previous job tenure, relationship status, and number of children. Robust standard errors clustered at the country 5-year period level in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10%, respectively.

Table 13:

Robustness to the adoption of an alternative model: probit model.

	(1)	(2)	(3)
ALMP (% of GDP)	0.463**		0.472***
	(0.202)		(0.151)
PLMP (% of GDP)		$-$ $−$ 0.361***	$-$ $−$ 0.366***
		(0.0798)	(0.0792)
Demographic controls	YES	YES	YES
Country-fixed effects	YES	YES	YES
Year-fixed effects	YES	YES	YES
Observations	1,304	1,367	1,304

Notes: The estimates are based on a sample of displaced workers in 13 European countries over the period 1985 to 2008. Changes in the sample size are due to different coverage of the explanatory variables. The dependent variable is a dummy that takes value 1 if an individual who lost her job due to business closure in a given year found a new job within the next year. Demographic controls include gender, age, previous job tenure, relationship status, and number of children. Robust standard errors clustered at the country 5-year period level in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10%, respectively.

Table 14:

Robustness to alternative clustering: country-year level.

	(1)	(2)	(3)
ALMP (% of GDP)	0.165**		0.164**
	(0.0817)		(0.0771)
PLMP (% of GDP)		$-$ $−$ 0.123***	$-$ $−$ 0.122***
		(0.0275)	(0.0282)
Demographic controls	YES	YES	YES
Country-fixed effects	YES	YES	YES
Year-fixed effects	YES	YES	YES
Observations	1,304	1,367	1,304
$R^{2}$ $R2$	0.126	0.134	0.136

Notes: The estimates are based on a sample of displaced workers in 13 European countries over the period 1985 to 2008. Changes in the sample size are due to different coverage of the explanatory variables. The dependent variable is a dummy that takes value 1 if an individual who lost her job due to business closure in a given year found a new job within the next year. Demographic controls include gender, age, previous job tenure, relationship status, and number of children. Robust standard errors clustered at the country year-level in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10%, respectively.

Figure 5:

Percentage of workers aged 20–64 displaced from one year to the next, 1985–2008.

Notes: this graph shows the percentage of workers aged 20 to 64 who lose their job each year due to business closure, by country. Years 1985 to 2008.

Acknowledgements

We thank the Co-Editor Frans de Vries and one anonymous referee for their helpful comments and suggestions. The authors would also like to thank Catherine L. Mann, Giuseppe Nicoletti, Jean-Luc Schneider, Lilas Demmou, Oliver Denk, Paula Garda, Valentine Millot, Andrea Bassanini, Axel Börsch-Supan, Tabea Bucher-Koenen, and seminar participants at the OECD and Munich Center for the Economics of Aging for their valuable comments; Catherine Chapuis and Sarah Michelson for statistical and editorial support. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: N211909, SHARE-LEAP: N227822, SHARE M4: N261982). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging and from various national funding sources is gratefully acknowledged (see www.share-project.org).

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Published Online: 2018-10-11

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DOI: doi.org/10.1515/bejeap-2017-0211

Keywords for this article

worker displacement; business closure; labour market programmes