Accessible Unlicensed Requires Authentication Published by De Gruyter January 24, 2019

Voluntary Mobility of Employees for Better Job Opportunities Given a Temporary Contract: Insights Regarding an Age-Varying Association Between the Two Events

Chiara Mussida and Luca Zanin

Abstract

What mechanisms govern the mobility of employees who voluntarily switch employers for better opportunities, given a temporary contract (TC)? We attempt to answer this question by exploring this issue in Southern and Central European countries. We use cross-sectional data from the European Union Statistics on Income and Living Conditions survey for the 2005–2016 period. We estimate a flexible simultaneous equation model for binary responses by assuming the presence of an age-varying association between voluntary mobility and having a TC. After accounting for several socio-demographic and economic variables, we find a nonlinear decreasing relation between age and the outcomes, while we detect heterogeneous nonlinear patterns in the association between voluntary mobility and having a TC across countries. These insights can support policy-makers aiming to promote initiatives that facilitate the professional mobility of employees given a TC for an efficient allocation of human capital in the production system.

JEL Classification: C14; C3; J01; J6

Acknowledgements

We thank the two anonymous reviewers for their useful suggestions, which helped improve the clarity and quality of the article. The opinions expressed herein are those of the authors and do not reflect those of the institutions of affiliation.

Compliance with Ethical Standards

  1. Funding: This research has not received funding.

  2. Conflict of Interest: The authors declare that they have no conflict of interest.

Appendix

Table 5:

Kendall’s τˆ coefficient and the associated confidence interval. The values of the estimated τ are not statistically significant and indicate absence of sample selection bias. Please refer to Marra et al. (2017) for further methodological details.

CountryKendall’s τˆConfidence intervals
France0.0812(-0.096,0.247)
Italy0.0346(-0.167,0.257)
Spain0.0411(-0.153,0.208)
Austria0.0205(-0.163,0.268)
Germany0.0944(-0.160,0.364)
Czech Republic0.0333(-0.111,0.222)
Poland-0.1680(-0.337,0.031)
Table 6:

The Akaike information criterion obtained after estimation of the system of two binary equations without including a third equation to model the copula association parameter as a function of employee age. We have estimated 15 models for each country (3 combinations of link functions × 5 copulae) and selected (in bold) the model with the best support in terms of the Akaike information criterion.

Southern European countriesCentral European countries
Link function and copulaFranceItalySpainAustriaGermanyCzech RepublicPoland
Eq.1:Probit; Eq.2:Probit
Gaussian49,33085,33877,26325,41755,91454,95699,236
Clayton49,31185,31877,27525,41155,90154,94199,218
Gumbel49,33785,34877,27325,42055,92554,96599,254
Joe49,36685,43077,38325,44256,01155,02899,415
Frank49,35385,39477,31625,43655,97355,01099,306
Eq.1:Probit; Eq.2:Cloglog
Gaussian49,34985,34077,25625,42855,94754,95799,243
Clayton49,33185,31977,27025,42255,93454,94399,225
Gumbel49,35685,35077,26525,43155,95854,96699,262
Joe49,38685,43277,37325,45256,04555,02999,424
Frank49,37285,39677,30725,44656,00755,01199,314
Eq.1:Cloglog; Eq.2:Cloglog
Gaussian49,48785,65877,83625,37855,85054,98399,603
Clayton49,46885,63677,84725,37255,83754,96899,579
Gumbel49,49385,66977,84525,38155,86154,99299,622
Joe49,52285,75477,95425,40355,95255,05599,787
Frank49,50885,71377,88425,39655,90755,03699,672
Sample period2005–2005–2005–2005–2007–2006–2006–
2016201520162016201620162016
Table 7:

The Akaike information criterion obtained after estimation of the system of two binary equations and including a third equation to model the copula association parameter as a function of employee age (see Section 3). We have estimated 15 models for each country (3 combinations of link functions × 5 copulae) and selected (in bold) the model with the best support in terms of the Akaike information criterion.

Southern European countriesCentral European countries
Link function and copulaFranceItalySpainAustriaGermanyCzech RepublicPoland
Eq.1:Probit; Eq.2:Probit
Gaussian49,29085,34077,24525,40455,87154,93799,189
Clayton49,29785,31177,25325,40755,88254,93199,191
Gumbel49,29985,34977,24925,41055,87654,94199,193
Joe49,30985,42177,31425,41855,90954,96699,252
Frank49,29685,39077,27525,40955,89254,96199,219
Eq.1:Probit; Eq.2:Cloglog
Gaussian49,30985,66077,23825,41555,90354,93999,198
Clayton49,31685,63177,24825,41855,91454,93399,199
Gumbel49,31885,66977,24125,42055,90854,94299,203
Joe49,32885,74477,30525,42955,94254,96799,262
Frank49,31585,70977,26725,42055,92454,96299,229
Eq.1:Cloglog; Eq.2:Cloglog
Gaussian49,44585,66077,81725,36555,80954,96499,557
Clayton49,45185,63177,82825,36755,82054,95999,554
Gumbel49,45485,66977,82025,37055,81454,96899,561
Joe49,46385,74477,88225,38055,84854,99599,620
Frank49,45085,70977,84225,37055,82954,98799,586
Sample period2005–2005–2005–2005–2007–2006–2006–
2016201520162016201620162016

References

Addabbo, T., R. García-Fernández, C. Llorca-Rodríguez. and A. Maccagnan. 2012. Poverty and Unemployment: The Cases of Italy and Spain, AIEL Series in Labour Economics,in: Parodi, G. and Sciulli, D. (ed. s), Social Exclusion. Short and Long Term Causes and Consequences, chapter 10: 199–219. Search in Google Scholar

Amabile T., and Kramer S. 2011.” The Progress Principle: Using Small Wins to Ignite Joy, Engagement, and Creativity at Work. Boston, Massachusetts: Harvard Business Review Press. Search in Google Scholar

Baranowska, A., M. Gebel, and I. E. Kotowska. 2011. “The Role of Fixed-Term Contracts at Labour Market Entry in Poland: Stepping Stones, Screening Devices, Traps or Search Subsidies?” Work, Employment and Society 25: 777–93. Search in Google Scholar

Bentolila, S., P. Cahuc, J. J. Dolado, and T. Le Barbanchon. 2012. “Two Tier Labour Markets in the Great Recession: France Versus Spain.” Economic Journal, Royal Economic Society 122: F155–87. Search in Google Scholar

Berger, M., and S. Schaffner. 2015. “A Note on How to Realize the Full Potential of the EU-SILC data.” Discussion Paper No. 15-005, Centre for European Economic Research, ZEW. Search in Google Scholar

Berton, F., F. Devicienti, and L. Pacelli. 2011. “Are Temporary Jobs a Port of Entry into Permanent Employment? Evidence from Matched Employer-Employee Data.” International Journal of Manpower 32 (8): 879–99.10.1108/01437721111181651 Search in Google Scholar

Bjelland, M., B. Fallick, J. Haltiwanger, and E. McEntarfer. 2012. Employer-to-Employer Flows in the United States: Estimates Using Linked Employer-Employee Data.” Journal of Business & Economic Statistics 29: 493–505. Search in Google Scholar

Baslevent, C., and H. Kirmanoglu. 2014. “The Impact of Deviations from Desired Hours of Work on the Life Satisfaction of Employees.” Social Indicators Research 118: 433–43. Search in Google Scholar

Bertola, G. and P. Garibaldi. 2003. “The Structure and History of Italian Unemployment.” CESifo Working Paper Series 907, CESifo Group Munich. Search in Google Scholar

Brechmann, E. C., and U. Schepsmeier. 2013. “Modeling Dependence with c- and d-vine Copulas: The R package CDVine.” Journal of Statistical Software 52: 1–27. Search in Google Scholar

Boeri, T. and P. Garibaldi. 2007. “Two Tier Reforms of Employment Protection: a Honeymoon Effect?” The Economic Journal 117 (521): 357–85.10.1111/j.1468-0297.2007.02060.x Search in Google Scholar

Boeri, T. 2011. “Institutional Reforms and Dualism in European Labor Markets.” in Handbook of Labor Economics, chapter 13, edited O. Ashenfelter and D. Card, 1173–236. Elsevier. Search in Google Scholar

Booth, A., M. Francesconi, and J. Frank. 2002. “Temporary jobs: stepping stones or dead ends.” The Economic Journal 112 (480): 189–213.10.1111/1468-0297.00043 Search in Google Scholar

Bosler, C. and N. Petrosky-Nadeau. 2016. Job-to-Job Transitions in an Evolving Labor Market, FRBSF Economic Letter, 34, Federal Reserve Bank of San Francisco. Search in Google Scholar

Cahuc, P., and F. Postel-Vinay. 2002. “Temporary Jobs, Employment Protection and Labor Market Performance.” Labour Economics 9 (1): 63–91.10.1016/S0927-5371(01)00051-3 Search in Google Scholar

Comi, S., and M. Grasseni. 2012. “Are Temporary Workers Discriminated Against? Evidence from Europe.” The Manchester School 80: 28–50.10.1111/j.1467-9957.2011.02231.x Search in Google Scholar

Christensen, B. J., R. Lentz, D. T. Mortensen, G. R. Neuman, and A. Werwatz. 2005. “On-the-Job Search and the Wage Distribution.” Journal of Labor Economics 23: 31–58.10.1086/425432 Search in Google Scholar

Cracolici, M.F, M. Cuffaro, and P. Nijkamp. 2010. “The Measurement of Economic, Social and Environmental Performance of Countries: A Novel Approach.” Social Indicators Research 95: 339–56.10.1007/s11205-009-9464-3 Search in Google Scholar

De Pater, I. E., A. E. M. Van Vianen, and M. N. Bechtoldt. 2010. “Gender Differences in Job Challenge: A Matter of Task Allocation.” Gender, Work and Organization 17 (4): 433–53. Search in Google Scholar

Dolton, P. J., and M. P. Kidd. 1998. “Job Changes, Occupational Mobility and Human Capital Acquisition: An Empirical Analysis.” Bulletin of Economic Research 50: 265–95.10.1111/1467-8586.00065 Search in Google Scholar

Eurofound Austria: Latest working life developments Q4. 2017. Available at: https://www.eurofound.europa.eu/printpdf/observatories/eurwork/articles/austria-latest-working-life-developments-q4-2017. Search in Google Scholar

European Commission. 2014. “Eurostat. Employment and Unemployment (LFS).” Available at: http://ec.europa.eu/eurostat. Search in Google Scholar

Eurostat. 2010. “Description of Target Variables: Cross-Sectional and Longitudinal.” EU-SILC 065/2010. Search in Google Scholar

Farber, S. H. 1999. “Mobility and Stability: The Dynamics of Job Change in Labor Market.” in Handbook of Labor Economics, vol. 3, edited by O. Ashenfler and D. Card, 2439-83. Amsterdam: Elsevier Science. Search in Google Scholar

Farber, S. H. 2017. “Employment, Hours, and Earnings Consequences of Job Loss: US Evidence from the Displaced Workers Survey.” Journal of Labor Economics 35 (S1): S235–S272. Search in Google Scholar

Foster-McGregor, N. and J. Poschl. 2016. “Productivity Effects of Knowledge Transfers Through Labour Mobility.” Journal of Productivity Analysis 46: 169–84.10.1007/s11123-016-0478-y Search in Google Scholar

Gielen, A. C., and K. Tatsiramos. 2012. “Quit Behavior and the role of job protection.” Labour Economics 19: 624–32.10.1016/j.labeco.2012.05.002 Search in Google Scholar

Gielen, A. C., and J. C. van Our. 2006. “Age-Specific Cyclical Effects in Job Reallocation and Labor Mobility.” Labour Economics 13: 493–504.10.1016/j.labeco.2006.02.006 Search in Google Scholar

Givord, P. and W. Lionel. 2015. “When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions.” Journal of Applied Econometrics 30 (5): 787–805.10.1002/jae.2394 Search in Google Scholar

Gervais M, N. Jaimovich, HE Siu, and Y. Yedid-Levi. 2016. “What Should I Be When I Grow Up? Occupations and Unemployment over the Life-Cycle.” Journal of Monetary Economics 83: 54–70.10.1016/j.jmoneco.2016.08.003 Search in Google Scholar

Greene, W. H. 2012. Econometric Analysis. New York: Prentice Hall. Search in Google Scholar

Guell, M. and B. Petrongolo. 2007. “How binding are legal limits? Transitions from temporary to permanent work in Spain.” Labour Economics 14 (2): 153–83.10.1016/j.labeco.2005.09.001 Search in Google Scholar

Gunkel, M., E. J. Lusk, B. Wolff, and F. Li. 2007. “Gender-Specific Effects at Work: An Empirical Study of Four Countries.” Gender, Work and Organization 14 (1): 56–79.10.1111/j.1468-0432.2007.00332.x Search in Google Scholar

Hahn, J. K., H. R. Hyatt, H. P. Janicki, and S. R. Tibbets. 2017. “Job-to-Job Flows and Earnings Growth.” American Economic Review 107: 358–63.10.1257/aer.p20171077 Search in Google Scholar

Hyatt, H. R., and E. McEntarfer. 2012. “Job-to-Job Flows in the Great Recession.” American Economic Review 102: 580–83.10.1257/aer.102.3.580 Search in Google Scholar

Hyatt, H. R. 2015. “The Decline in Job-to-Job Flows.” IZA World of Labor 175: 1–10. Search in Google Scholar

Ingham, H. and M. Ingham. 2014. “Towards Eurosclerosis: Will Poland Escape?” The World Economy 37: 290–310.10.1111/twec.12106 Search in Google Scholar

Izquierdo, M., J. F. Jimeno, T. Kosma, A. Lamo, S. Millard, T. Room, E. Viviano. 2017. “Labour Market Adjustment in Europe During the Crisis: Microeconomic Evidence from the Wage Dynamics Network Survey.” The Occasional Paper Series. BANCO DE ESPANA. Search in Google Scholar

Jovanovic B. 1979. Job Matching and the Theory of Turnover. Journal of Political Economy 87 (5): 972–90.10.1086/260808 Search in Google Scholar

Judge, T. A. and J. D. Kammeyer-Mueller. 2012. “Job Attitudes.” Annual Review of Psychology 63: 341–67.10.1146/annurev-psych-120710-100511 Search in Google Scholar

Jurajda, S., K. Terrel. 2007. “Regional Unemployment and Human Capital in Transition Economies.” CEPR Discussion Paper No. 6569. Search in Google Scholar

Kahn, L. 2012. “Labour Market Policy: A Comparative View on the Costs and Benefits of Labour Market Flexibility.” Journal of Policy Analysis and Management 31 (1): 94–110.10.1002/pam.20602 Search in Google Scholar

Karahan, F., R. Michaels, B. Pugsley, A. Åžahin, and R. Schuh. 2017. “Do job-to-job transitions drive wage fluctuations over the business cycle?” American Economic Review 107: 353–57. Search in Google Scholar

King, G. and L. Zeng. 2001. “Logistic Regression in Rare Events Data.” Political Analysis 9: 137–63.10.1093/oxfordjournals.pan.a004868 Search in Google Scholar

Kirchmeyer, C. 2006. “The Different Effects of Family on Objective Career Success Across Gender: A Test of Alternative Explanations.” Journal of Vocational Behavior 68 (2): 323–46.10.1016/j.jvb.2005.05.002 Search in Google Scholar

Lasi, H., P. Fettke, H. G. Kemper, T. Feld, M. Hoffmann. 2014. “Industry 4.0.” Business & Information Systems Engineering 6: 239–42.10.1007/s12599-014-0334-4 Search in Google Scholar

Levitt, S. D. 2016. “Heads or Tails: The Impact of a Coin Toss on Major Life Decisions and Subsequent Happiness.” NBER Working Paper no. 22487. Cambridge: National Bureau of Economic Research. Search in Google Scholar

Li, Jin. 2013. “Job Mobility, Wage Dispersion, and Technological Changes: An Asymmetric Informal Perspective.” European Economic Review 60: 105–26.10.1016/j.euroecorev.2013.01.008 Search in Google Scholar

Lilla, M. and S. Staffolani. 2012. “Young Entrants, Temporary Jobs and Career Opportunities: Short-Term Perspectives of Young Italian Workers.” Rivista di Statistica Ufficiale 1: 49–60. Search in Google Scholar

Longhi, S. and M. Taylor. 2014. “Employed and Unemployed Job Seekers and the Business Cycle.” Oxford Bulletin of Economics and Statistics 76 (4): 463–83.10.1111/obes.12029 Search in Google Scholar

McGovern, P., D. Smeaton, and S. Hill. 2004. “Bad Jobs in Britain: Nonstandard Employment and Job Quality.” Work and Occupations 31: 225–249.10.1177/0730888404263900 Search in Google Scholar

Marino, M., P. Parrotta, and D. Pozzoli. 2016. “Educational Diversity and Knowledge Transfers via Inter-Firm Labor Mobility.” Journal of Economic Behavior & Organization 123: 168–83.10.1016/j.jebo.2015.10.019 Search in Google Scholar

Marra, G., R. Radice, T. Barnighausen, S. N. Wood, M. E. McGovern. 2017. “A Simultaneous Equation Approach to Estimating HIV Prevalence with Non Ignorable Missing Responses.” Journal of the American Statistical Association 112: 484–96.10.1080/01621459.2016.1224713 Search in Google Scholar

Marra, G., and R. Radice. 2017. “A Joint Regression Modeling Framework for Analyzing Bivariate Binary Data in R.” Dependence Modeling 5: 268–94.10.1515/demo-2017-0016 Search in Google Scholar

Marra, G., and R. Radice. 2018. GJRM: Generalised Joint Regression Modelling. R package version 0.1-4. Search in Google Scholar

Mukoyama, T. 2014. “The Cyclicality of Job-to-Job Transitions and its Implications for Aggregate Productivity.” Journal of Economic Dynamics and Control 39: 1–17.10.1016/j.jedc.2013.12.004 Search in Google Scholar

Montt, G. 2017. “Field-of-Study Mismatch and Overqualification: Labour Market Correlates and Their Wage Penalty.” IZA Journal of Labor Economics 6: 2.10.1186/s40172-016-0052-x Search in Google Scholar

Mosthaf, A., Schnabel, C., and Stephani, J. 2011. “Low-Wage Careers: Are There Dead-End Firms and Dead-End Jobs?” Journal for Labour Market Research 43: 231–49.10.1007/s12651-010-0036-4 Search in Google Scholar

Mussida, C., and L. Zanin. 2019. “I Found a Better Job Opportunity! Voluntary Job Mobility of Employees and Temporary Contracts Before and After the Great Recession in France, Italy and Spain.” Empirical Economics. https://doi.org/10.1007/s00181-019-01622-7. Search in Google Scholar

Neffke, F. M. H., A. Otto, and A. Weyh. 2017. “Inter-Industry Labor Flows.” Journal of Economic Behavior & Organization 142: 275–292.10.1016/j.jebo.2017.07.003 Search in Google Scholar

Newell, A. 2006. “Skill Mismatch and Regional Unemployment in Poland.” In The European Labour Market Regional Dimensions. AIEL Series in Labour Economics, chapter 8, edited by F. E. Caroleo, and S. Destefanis, 187–201. Heidelberg: Physica-Verlag. Search in Google Scholar

Nieuwenhuis, R., and L. C. Maldonado. 2018. The Triple Bind of Single-Parent Families: Resources, Employment and Policies to Improve Wellbeing. Bristol, UK: Policy Press, University of Bristol. Search in Google Scholar

Pavlopoulos, D. 2009. “Starting Your Career with a Temporary Job: Stepping Stone or “Dead-End”?” SOEP papers on Multidisciplinary Panel Data Research, No 228, DIW Berlin, The German Socio-Economic Panel. Search in Google Scholar

Pellizzari, M., and A. Fichen. 2017. “A New Measure of Skill Mismatch: Theory and Evidence from PIAAC.” IZA Journal of Labor Economics 6: 1.10.1186/s40172-016-0051-y Search in Google Scholar

Perez, G. J. I., and Y. R. Sanz. 2005. “Wage Changes Through Job Mobility in Europe: A Multinomial Endogenous Switching Approach.” Labour Economics 12: 531–55.10.1016/j.labeco.2005.05.005 Search in Google Scholar

Picchio, M. 2008. “Temporary Contracts and Transitions to Stable Jobs in Italy.” LABOUR 22 (s1): 147–74.10.1111/j.1467-9914.2008.00415.x Search in Google Scholar

Pilc, M. 2017. “The Temporary Employed in Poland: Beneficiaries or Victims of the Liberal Labour Market?” Economic and Industrial Democracy 38 (3): 400–24.10.1177/0143831X15574113 Search in Google Scholar

R Core Team. 2018. “R: A language and environment for statistical computing.” R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org. Search in Google Scholar

Radice, R., G. Marra, and M. Wojtys. 2016. “Copula Regression Spline Models for Binary Outcomes.” Statistics and Computing 26: 981–99.10.1007/s11222-015-9581-6 Search in Google Scholar

Schnabel, C. 2016. “United, Yet Apart? A Note on Persistent Labour Market Differences between Western and Eastern Germany.” Journal of Economics and Statistics 236 (2): 157–79. Search in Google Scholar

Silva, A. D., and A. Turrini. 2015. “Precarious and less well-paid? Wage differences between permanent and fixed-term contracts across the EU countries.” Economic Papers 544, European Commission - Directorate-General for Economic and Financial Affairs. Search in Google Scholar

Van Lancker, W. 2012. “The European World of Temporary Employment: Gendered and Poor?” European Societies 14 (1): 83–111.10.1080/14616696.2011.638082 Search in Google Scholar

von Wachter, T, and S. Bender. 2006. “In the Right Place at the Wrong Time: The Role of Firms and Luck in Young Workers’ Careers.” American Economic Review 96: 1679–705.10.1257/aer.96.5.1679 Search in Google Scholar

Zanin, L., and G. Marra. 2012. “A Comparative Study of the use of Generalized Additive Models and Generalized Linear Models in Tourism Research.” International Journal of Tourism Research 14: 451–68.10.1002/jtr.872 Search in Google Scholar

Zanin L., R. Radice, and G. Marra. 2014. “A comparison of approaches for estimating the effect of women’s education on the probability of using modern contraceptive methods in Malawi.” The Social Science Journal 51 (3): 361–67.10.1016/j.soscij.2013.12.008 Search in Google Scholar

Zanin, L. 2015. “Determinants of Risk Attitudes Using Sample Surveys: The Implications of a High Rate of Nonresponse.” Journal of Behavioral and Experimental Finance 8: 44–53.10.1016/j.jbef.2015.08.001 Search in Google Scholar

Zanin, L., and R. Calabrese. 2017. “Interaction Effects of Region-Level GDP Per Capita and Age on Labour Market Transition Rates in Italy.” IZA Journal of Labor Economics 6: 4.10.1186/s40172-017-0054-3 Search in Google Scholar

Zanin, L. 2018. “Private Monetary Transfers Between Households: Who is Helped and by Whom?” Journal of Behavioral and Experimental Finance 17: 76–82.10.1016/j.jbef.2017.12.010 Search in Google Scholar

Wood, S. N. 2017.” Generalized Additive Models: An Introduction with R, 2nd ed., London: Chapman & Hall/CRC. Search in Google Scholar

Supplementary Material

The online version of this article offers supplementary material (DOI:https://doi.org/10.1515/bejeap-2018-0143).

Published Online: 2019-01-24

© 2019 Walter de Gruyter GmbH, Berlin/Boston