Session Information
22 SES 01 C, Employability and Transition to Work of Higher Education Graduates
Paper Session
Contribution
Unemployment rates among Portuguese Higher Education (HE) graduates have been rising, as was the case before the present labor market crisis. This trend becomes quite obvious when we compare Portugal and other European Member States whose labor markets have been facing similar difficulties. In fact, Portuguese graduates are not only more prone to facing unemployment but they are also enduring long term unemployment as a result of the current unemployment crisis.
Among the main reasons for this situation is the mismatch between the supply and demand for qualifications due to the inability of the Portuguese labor market to absorb higher skills (chimney effect). This outcome can be clearly understood by observing indicators of the GDP breakdown throughout different knowledge intensity services and industries and compare them between Portugal and other European Countries.
Nevertheless, competition in demand and the need to overcome labor productivity’s weaknesses compel (education and training policies and labor market interventions) to improve the match between supply and demand for HE qualifications in order to prevent social disinvestment and to foster inclusion and economic development. In the short and medium term, given the economic and social development strategy, adjustments will consider the need to redefine the HE graduates’ skills and profiles throughout education and training. In this paper we are concerned with the effects exerted by additional education programs compared to informal and non formal additional learning activities on HE unemployed graduates’ reemployment. We place our research in the framework of life cycle theories and take Willis (1986) as our main theoretical reference:
dK/dt= K0 h ∑ Ki - δ ∑ Kj
where dk/dt denotes individual learning accumulation and skills acquisition through time, K0 initial schooling outcomes (in this case, HE graduation skills), ∑ Ki eventual occupational experience powered by h (0 ≤ h ≤ 1) during i employment periods, ∑ Kj the “human capital” depreciation during unemployment and/or inactivity spells j, and δ the rate of obsolescence. As δ depends on “refreshment” activities for a given unemployment/inactivity spell, any adequate vocational training program, further schooling aiming at skills reshaping or even non formal learning activities can theoretically contribute to shorten δ and therefore to foster reemployment, given labor market conditions. In this paper, we let δ be positively affected by any of the following learning activities: further education, informal learning and non formal activities. Then, we will assess the outcomes of the joint effect displayed by these activities and different levels of K0 on reemployment. Although the Willis model has usually been adjusted to evaluate the incremental effect displayed by public labor market policies on reemployment throughout the reduction in δ, in the present work we allow for different forms of learning activity funding: public financing, share funding between individuals/families and government or employers or self financing.
Method
Expected Outcomes
References
• Albrecht, J. et al, (1991), “Career interruptions and subsequent earnings: a reexamination using Swedish data”, Journal of Human Resources 34, 249-311; • Ammermüller, A. (2005), “Educational Opportunities and the Role of Institutions”, Research Memoranda 004, Maastricht, ROA; • Barry & Beckman (2007), “Innovation as a Learning Process: embedding design thinking”, California Management Review, vol. 50, nº1, Fall 2007. • Bidart, C. & Lavenu, D. (2005), “Evolutions of personal networks and life events”, LEST, Université Aix-en-Provence, SN Working Papers, 27; • Chagas Lopes, M. & Medeiros, J. (2004), “School Failure and Intergenerational “Human Capital” Transmission in Portugal” (http://mpra.ub.uni-muenchen.de/26764/) • Crick, Ruth Deakin (2008): «Key Competencies for Education in a European Context: narratives of accountability or care», European Education Research Journal, vol. 7, n.º 3, (http://www.wwwords.co.uk/pdf/validate.asp?j=eerj&vol=7&issue=3&year=2008&article=5_Crick_EERJ_7_3_web) • EU (2009) Europe in Figures – Eurostat Yearbook 2009, Luxembourg: EUROSTAT • EU (2010), Population and Social Conditions – Education, EUROSTAT DATA BASE. • Heckman, J. & Macurdy, T. (1980), “A life cycle model of female labour supply”, The Review of Economic Studies, vol 47, nº1, 47-74; • Heijke, Hans & Muysken, Joan (2000), Education and Training in a Knowledge Based Economy, Palgrave, Mc.Millan. • Kachigan, S. (1986), Statistical Analysis – An Interdisciplinary Introduction to Univariate & Multivariate Methods, New York, Radius Press. • Lawless, J. (1982), Statistical Models and Methods for Lifetime Data, New York, Wiley & Sons; • Leâo Fernandes, G., Passos, J. & Chagas Lopes, M. (2004); “ Skill Development Patterns and their Impact on Re-employability: Evidence for Portugal”(http://mpra.ub.uni-muenchen.de/22075/) • OECD (2006), Thematic review of tertiary education – country background report:Portugal, http://www.oecd.org/dataoecd/23/1/37745972.pdf • OECD (2006), Bologna Process: National Report from Portugal – 2005/2007,http://www.ond.vlaanderen.be/hogeronderwijs/bologna/links/National-reports-2007/National_Report_Portugal2007.pdf • Willis, Richard (1986),“Wage Determinants: a Survey and Reinterpretation of Human Capital Earnings Function” In Handbook of Labour Economics, Ashenfelter&Layard (org), Amesterdam, North Holland.
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