Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The educational expansion in many advanced economies in the past few decades has triggered a debate on overeducation. The aim of the study is to provide an empirical evaluation of the wage effects of overeducation in different occupational groups. We also analyse whether these effects differ between genders. In order to achieve this, we use individual data from the Structure of Wages and Salaries by Occupations database of firms with 10 or more employees in Poland. We use data from the 2006-2014 waves of the survey. We calculate the impact of overeducation on wages using a Mincer-type wage regression model. We show that on average workers are rewarded for being overeducated, but the size of wage effects of overeducation differs among particular occupational groups. We show also that the choice of the method of measurement of overeducation affects the results.
Go to article

Bibliography

[1] Alba-Ramirez A., (1993), Mismatch in the Spanish labour market: Overeducation?, Journal of Human Resources 28, 259–278.
[2] Allen J., van der Velden R., (2001), Educational Mismatches Versus Skill Mismatches: Effects on Wages, Job satisfaction and On-the-Job Search, Oxford Economic Papers 53(3), 434–452.
[3] Attanasio O. P., Kaufmann K., (2017), Education choices and returns on the labor and marriage markets: Evidence from data on subjective expectations, Journal of Economic Behavior & Organization 140(C), 35–55.
[4] Baran J., (2016), A side effect of a university boom: rising incidence of overeducation among tertiary-educated workers in Poland, University of Warsaw Faculty of Economic Sciences Working Papers 22/2016 (213).
[5] Battu H., Belfield C. R., Sloane P., (2000), How Well Can We Measure Graduate Over Education and Its Effects?, National Institute Economic Review 171(1), 82–93.
[6] Bauer T., (2002), Educational mismatch and wages: a panel analysis, Economics of Education Review 21, 221–229.
[7] Becker G. S., (1964), Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education, University of Chicago Press, Chicago.
[8] Boll Ch., Leppin J., Rossen A., Wolf A., (2016), Overeducation – New Evidence for 25 European Countries, Research Paper no. 173.
[9] Caroleo F. E., Pastore F., (2013), Overeducation at a Glance: Determinants and Wage Effects of the Educational Mismatch, Looking at the AlmaLaurea Data, IZA Discussion Papers 7788, Institute of Labor Economics (IZA).
[10] Chevalier A., (2000), Graduate Over-Education in the UK, Centre for the Economics of Education Discussion Paper 07.
[11] Chevalier A., Lindley J., (2009), Over-education and the Skills of UK Graduates, Journal of the Royal Statistical Society 172(2), 307–337.
[12] Chiappori P., Iyigun M., Weiss Y., (2009), Inverstment in Schooling and the Marriage Market, American Economic Review 99(5), 1689–1713.
[13] Chłon-Dominczak A., Zurawski A., (2017), Measuring Skills Mismatches Revisited – Introducing Sectoral Approach, IBS Working Paper 03/2017.
[14] Daly M. C., Buchel F., Duncan G. J., (2000), Premiums and Penalties for Surplus and Deficit Education: Evidence from the United States and Germany, Economics of Education Review 19, 169–178.
[15] Di Pietro G., Urwin P., (2006), Education and skills mismatch in the Italian graduate labour market, Applied Economics 38(1), 79–93.
[16] Dolton P., Vignoles A., (2000), The incidence and effects of mismatch in the UK graduate labour market, Economics of Education Review 19, 179–198.
[17] Duncan G., Hoffman S. D., (1981), The Incidence and Wage Effects of Overeducation, Economics of Education Review 1(1), 75–86.
[18] Freeman R. B., (1976), The overeducated American, Academic Press.
[19] Goraus K., Tyrowicz J., (2014), Gender wage gap in Poland – can it be explained by differences in observable characteristics?, Ekonomia 36, 125–148.
[20] Green F., McIntosh S., (2007), Is There a Genuine Under-utilisation of Skills Amongst the Overqualified?, Applied Economics 39 (4), 427–439.
[21] Groot W., (1996), The incidence of, and returns to overeducation in the UK, Applied Economics 28(10), 1345–1350.
[22] Groot W., Maaseen van den Brink H., (2000), Overeducation in the labor market: a meta-analysis, Economics of Education Review 19(2), 149–158.
[23] Hartog J., Oosterbeek H., (1988), Education, allocation and earnings in the Netherlands: Overschooling?, Economics of Education Review 7, 185–194.
[24] Hartog J., (2000), Overeducation and earnings: where are we, where should we go?, Economics of Education Review 19(2), 131–147.
[25] Kiker B. F., Santos M. C., Mendes De Oliveira M., (1997), Overeducation and Undereducation: Evidence for Portugal, Economics of Education Review 16(2), 111–125.
[26] Kucel A., Vilalta-Bufi M., (2012), Graduate Labour Mismatch in Poland, Polish Sociological Review 3(179), 413–429.
[27] Leuven E., Oosterbeek H., (2011), Overeducation and Mismatch in the Labour Market, IZA Discussion Paper, no. 5523.
[28] Li I., Simonson R., Malvin M., (2014), Over-education and Employment Mismatch: Wage Penalties for College Degrees in Business, The Journal of Education for Business 90(3), 119–125.
[29] Majchrowska A., Strawinski P., (2018), Impact of minimum wage increase on gener wage gap: Case of Poland, Economic Modelling 70, 174–185.
[30] Mavromaras K., McGuinness S., O’Leary N., Sloane P., Wei Z., (2013), Job Mismatches and Labour Market Outcomes: Panel Evidence on University Graduates, Economic Record 89, 382–395.
[31] McGuiness S., Wooden M., (2009), Overskilling, Job Insecurity and Career Mobility, Industrial Relations: A Journal of Economy and Society 48(2), 265-286.
[32] McGuinness S., Sloane P., (2011), Labour market mismatch among UK graduates: An analysis using REFLEX data, Economics of Education Review 30(1), 130–145.
[33] McGuinness S., Bergin A., Whelan A., (2017), Overeducation in Europe: Trends, Convergence and Drivers, IZA Discussion Paper No. 10678.
[34] McGuiness S., (2006), Overeducation in the Labour Market, Journal of Economic Surveys 20(3), 387–418.
[35] Mincer J., (1974), Schooling, Experience and Earnings, National Bureau of Economic Research, Cambridge.
[36] Mysikova M., (2016), Has Personal Earnings Inequality Become Polarized? The Czech Republic in a Comparative Perspective, Journal of Income Distribution 24(3-4), 3-24.
[37] OECD, (2019), OECD Skills Strategy Poland: Assessment and Recommendations, OECD Skills Studies, OECD Publishing, Paris, https://doi.org/10.1787/b377fbcc-en.
[38] Ortiz L., Kucel A., (2008), Do Fields of Study Matter for Over-education? The Cases of Spain and Germany, International Journal of Comparative Sociology 49, 305–327, DOI: 10.1177/0020715208093079.
[39] Robst J., (2008), Overeducation and College Major: Expanding the Definition of Mismatch Between Schooling and Jobs, The Manchester School 76(4), 349–368.
[40] Rossen A., Boll Ch., Wolf A., (2019), Patterns of Overeducation in Europe: The Role of Field of Study, IZA Journal of Labor Policy 9(1).
[41] Rubb S., (2003), Overeducation in the Labor Market: A Comment and Re- Analysis of a Meta-analysis, Economics of Education Review 22(6), 621–629.
[42] Sánchez-Sánchez N., McGuinness S., (2013), Decomposing the impacts of overeducation and overskilling on earnings and job satisfaction: an analysis using REFLEX data, Education Economics, in press, http://dx.doi.org/10.1080/ 09645292.2013.846297.
[43] Sattinger M., (1993), Assignment Models of the Distribution of Earnings, Journal of Economic Literature 31, 831–880.
[44] Sloane P., (2003), Much Ado about Nothing? What Does the Over-education Literature Really Tell Us?, International Conference on Over-education in Europe: What Do We Know?.
[45] Sloane P. J., (2014), Overeducation, Skill Mismatches, and Labor Market Outcomes for College Graduates, IZA World of Labor 88, 1–10.
[46] Strawinski P., Broniatowska P., Majchrowska A., (2016), Returns to vocational education evidence from Poland, WNE Working Papers No. 16/2016 (207).
[47] Strawinski P., (2015), Krzyzowe porównanie danych o wynagrodzeniach z polskich badan przekrojowych, Bank i Kredyt 46 (5), 433–462.
[48] Vahey S., (2000), The great Canadian training robbery: evidence on the returns to educational mismatch, Economics of Education Review 19, 219–227.
[49] Verdugo R., Verdugo N., (1989), The Impact of Surplus Schooling on Earnings: Some Additional Findings, Economics of Education Review 22(4), 690–695.
[50] Verhaest D., Omey E., (2006), The impact of overeducation and its measurement, Social Indicators Research, 77(3), 419–448.
[51] Wincenciak L., (2016), Educational mismatches and earnings in Poland: are graduates penalised for being overeducated?, Ekonomia 46, 145–167.
Go to article

Authors and Affiliations

Paulina Broniatowska
1
ORCID: ORCID

  1. University of Warsaw
Download PDF Download RIS Download Bibtex

Abstract

In this paper we investigate the quantitative importance of efficiency wages of no-shirking type in explaining business cycle fluctuations in Bulgarian labor markets. This is done by augmenting a relatively standard real business cycle model with unobservable workers effort by employers and efficiency wage contracts, as well as through the inclusion of a detailed government sector. This imperfection in labor markets introduces a strong internal transmission mechanism that allows the model framework to capture the business cycles in Bulgarian data better than earlier models, and setups assuming perfectly-competitive labor markets in particular.

Go to article

Authors and Affiliations

Aleksandar Vasilev
Download PDF Download RIS Download Bibtex

Abstract

The studies using Mincer equations are generally applied to cross-sectional data at the micro-level. There are however limited studies conducted with macro or panel data for wage equations. Pseudo panel data methods can be applied to empirical studies by creating cohorts from repeated cross-sectional data in the absence of genuine panel data. Difference in both the human and labour resources according to the spatial positions may also affect the prediction of the wage equations. We aim to introduce the application of spatial pseudo panel models by creating cohorts according to the birth years of employees and regions in which they live from the Turkish household labour survey for the period 2010-2015. As a result, we find that the spatial autocorrelation model is appropriate for wage equations of Turkey. We also find that return of education on wages is 11% while return of experience on wages is 4%.
Go to article

Authors and Affiliations

Selahattin Güris
1
Gizem Kaya Aydin
2

  1. Marmara University, Department of Econometrics, Istanbul, Turkey
  2. Istanbul Technical University, Department of Management Engineering, Istanbul, Turkey
Download PDF Download RIS Download Bibtex

Abstract

This article investigates two interesting phenomena which exist within the framework of the European Union (EU) integration process, i.e. “social dumping” and “letterbox companies”. Taking into account recent EU legislative changes and commentaries in the available legal literature, it contends that the EU’s institutions and its Member States are aware of some negative effects that these phenomena may have for attaining one of the EU’s basic aims, that of a “highly competitive social market economy”, as provided in Article 3(3) (ex 2, as amended) of the Treaty on the European Union. The EU should be understood as being not only focused on the implementation of the Internal Market freedoms, but also the protection of social rights. “Social dumping”, and to a certain extent also “letterbox companies”, reduce the level of this protection. Posting of workers is a good example of an EU integration area where “social dumping” and “letterbox companies” occur on a quite large scale and create some real practical problems. If we can clearly understand the concepts underlying these phenomena and their possible relationships, it would be easier to find a solution to reduce their negative effect on the protection of social rights. This article researches these issues and presents possible solutions to problems they give rise to.
Go to article

Authors and Affiliations

Joanna Ryszka
Download PDF Download RIS Download Bibtex

Abstract

Recently, in most developed economies, the average age of the workforce has been growing rapidly. Therefore, the questions arise how will it affect the level of wages and the shape of age-productivity and age-wage profiles. The aim of the paper is to analyse the relationship between changes in the age structure of the employment and wages of individuals in minor occupational groups. Using individual data from the Structure of Earnings Survey in Poland in 2006-2014 we created an unique database of individual wages and the characteristics of employed in occupational groups at 3-digit level of classification. In our analysis we used an extended version of Mincerian wage model where both the characteristics of employees (education, work tenure, age, gender, and type of employment contract) and employers (size and ownership sector) were taken into account. The results for the whole sample indicate a significant and negative relationship between the proportion of older workers in employment in a given occupational group and individual wages. However, when the analyses were performed separately for each of the 1-digit occupational groups, the results varied significantly. In those groups where knowledge and qualifications of employees are more important than physical strength had to be updated permanently, an increase in the number of the older workers raises the average wages.

Go to article

Authors and Affiliations

Paulina Broniatowska
Aleksandra Majchrowska
Maciej Nasiński

This page uses 'cookies'. Learn more