A MULTIFACTORIAL EXPLANATION OF YOUTH UNEMPLOYMENT AND THE SPECIAL CASE OF AUSTRIA

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1 A MULTIFACTORIAL EXPLANATION OF YOUTH UNEMPLOYMENT AND THE SPECIAL CASE OF AUSTRIA The Future of Capitalism Vienna, 24 th September 2014 Dennis Tamesberger Department for Economic, Welfare and Social policy.

2 The agenda: Which problems in comparing youth unemployment exist? Which factors influence youth unemployment? Can these factors explain the relatively low youth unemployment in Austria? Our perplexity really begins at the point when we ask why young people are so much more disadvantaged than older age groups in some regions of Europe and not in others (Bertram 1994, 293).

3 To the problem of measurement youth unemployment Labor-Force-Concept: employed (e), unemployed (u) and out-of-labor-force (OLF) Unemployed (u) not working available for work proactive steps to find a job Urate=u/(u+e) Difficulties by international comparisons the number of employed youth depends on different qualification and education schemes the demarcation between unemployed and out-of-labor-force is for young people difficult young people, who are in training, are not counted as unemployed

4 To the problem of measurement youth unemployment The Urate underestimates the extent of the problem, in particular for youth, and the explanatory power for international comparisons is limited. For cross-country analyses, it is useful to use more indicators Uratio=u/(u+e+OLF) NEETratio=(u+OLFnet)/pop OLF rate=olf/pop

5 80 Youth labour market indicators in the EU 27, between 15 and 24 years, Urate% Uratio% NEETratio% OLFratio% DE AT NL DK MT LU FI CZ BE SI EE UK RO SE FR LT PL ZY BG HU LV IE SK IT PT ES EL

6 Correlation matrix of youth labour market indicators Urate Rank-Correlation (Spearman s rho) Urate Uratio Neetratio OLFratio Uratio 0.747*** Neetratio 0.843*** 0.573** OLFratio 0.515** * *=p<0.10; **=p<0.05; ***=p<0.01. Sources: Eurostat (2013); own calculations.

7 Factors influencing youth unemployment Business cycle and the aggregated Urate: aggregated Urate 1% youth Urate 1,3% (Gangl 2002); adult Urate 1% youth Urate 1,79% (Bell/Blanchflower 2011) Labour market regulation: No clear picture: EPL keeps young employees from losing their jobs and can hamper school leavers labour market integration (Breen 2005; Russell/O Connell 2001; Boeri 2011; O Higgins 2012 ) Strength of the union: Influence on labour market regulation, on vocational systems, job security for high internal flexibility (Quintini et al. 2007; Cahuc et al. 2013; O Higgins 2010; Sturn 2013) Vocational systems: Apprenticeship: positive employment effects but selective access (Ryan 2000; O Higgins 2012; Kohlrausch 2012 ) Active labour market policy: Significant influence of ALMP on youth employment (Russell/O'Connell 2001)

8 Data source and Method Member states of the EU and 2012 (N=135 country year observations). After Exclusion of the missing values (71 country-year observations) International databases Eurostat, OECD, ICTWSS database version 4 General Linear Model, time-fixed effects with robust stand errors

9 Independent variables Label Description of variable Source EPT Vocational ALMP coordn Regulation of temporary forms of employment Share of students in apprenticeships Expenditure for ALMP as a ratio from GDP divided through the average unemployment rate Degree of coordination in collective bargaining GDP Real GDP growth rate Percentage change on previous year Urate_25_74 Adult unemployment rate aged OECD Datenbank (2013a) OECD (2011; 2012; 2013b) Operationalization according to Database Breen (2005) Eurostat (2013) Nickel (1997) Visser (2013) Crouch (2013) Eurostat (2013) Eurostat (2013) Database Database Crisis Year 2009 and 2010 Eurostat (2013) own calculations aut_almpexp Interaction term of ALMP expenditure and Austria Eurostat (2013) own calculations

10 Change of adult unemploymentrate %points, DE AT NL DK MT LU FI CZ BE SI EE UK RO SE FR LT PL ZY BG HU LV IE SK IT PT ES EL -4

11 Labour market regulation 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0 DE AT NL DK MT* LU FI CZ BE SI EE UK RO* SE FR LT* PL ZY* BG* HU LV IE SK IT PT ES EL Protection of permanent workers against individual and collective dismissals *No data available Regulation on temporary forms of employment

12 Vocational systems DE AT NL DK MT* LU FI CZ BE SI** EE UK* RO* SE** FR LT* PL ZY* BG* HU LV* IE SK IT** PT* ES EL* *No data available; **Magnitude is either negligible or zero. Vocational of which combined school- and work-based in % 2008

13 Active labour market policy

14 Results Urate Uratio *=p<0.10; **=p<0.05; ***=p<0.01. Time-fixed-effects models with robust standard errors. Sources: Eurostat (2013); OECD (2011; 2012; 2013a); Visser (2013); own calculations. 1 regression coefficient B 2 = with interaction term 1 2 = with interaction term EPT.715*.775* -.489* -.501* Vocational -.156*** -.148*** -.059*** -.061*** ALMP *** *** Coordn GDP Urate_25_ *** 1.777***.846***.850*** Crisis aut_almpexp ***

15 Results NEET ratio OLF ratio regression coefficient B 1 2 = with interaction term 1 2 = with interaction term EPT *** 5.126*** Vocational -.066*** -.073*** -.121* ALMP ** *** *** *** coordn GDP -.141* *.373*.404* Urate_25_74.696***.720*** -.801** -.934*** crisis aut_almpexp *** *** *=p<0.10; **=p<0.05; ***=p<0.01. Time-fixed-effects models with robust standard errors. Sources: Eurostat (2013); OECD (2011; 2012; 2013a); Visser (2013); own calculations.

16 Can these factors explain the relatively low youth unemployment in Austria? 1 Urate Uratio NEET ratio OLF ratio 2 = with interaction term 1 2 = with interaction term 1 2 = with interactio n term 1 2 = with interaction term 2008 Yes Yes Yes Yes No Yes No Yes 2009 Yes Yes Yes Yes No Yes No Yes 2010 No Yes Yes Yes No Yes No Yes 2011 No Yes Yes Yes Yes Yes No Yes

17 Conclusions For cross-country analyses one indicator is not enough The adult unemployment rate - as an indicator for the labour market tightness and the size of the apprenticeship system are the main influencing factors on youth unemployment ALMP especially helps young people to escape from an outof-labour status The influencing factors are only relevant for Austria with an ALMP interaction term: Austrians ALMP is more effective for the typical unemployed and less successful for the NEET group

18 Conclusions Economic policy measures to stimulate demand and to lower the general unemployment rate Social consensus for full employment Austrians youth safety net Institutional background: such institutions can flourish only in societies in which concern for the integration of youth into socio-economic life is widely shared and deeply felt, and that therein lies the fundamental source of their resilience and effectiveness (Ryan, 2001, 83). Photo 2011 J. Ronald Lee