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The Growing Pains of Education: Exploring Educational Mismatch Trends

Martin Krejčí

Martin Krejčí

Faculty of Economics, VSB – Technical University of OstravaOstrava, Czech Republic
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Krejčí, Martin
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Jiří Balcar

Jiří Balcar

Faculty of Economics, VSB – Technical University of OstravaOstrava, Czech Republic
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Balcar, Jiří
  
Sep 08, 2025
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Published Online: Sep 08, 2025
Page range: 48 - 65
DOI: https://doi.org/10.2478/revecp-2025-0004
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© 2025 Martin Krejčí et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1:

Educational Mismatch by Sex
Educational Mismatch by Sex

Fig. 2:

Education Mismatch by Age Categories
Education Mismatch by Age Categories

Fig. 3:

Development of Educational Mismatch by Highest Degree of Education Notes: *) Upper secondary vocational education (with apprenticeship certificate); **) Upper secondary general/technical education (with Matura certificate).
Development of Educational Mismatch by Highest Degree of Education Notes: *) Upper secondary vocational education (with apprenticeship certificate); **) Upper secondary general/technical education (with Matura certificate).

Fig. 4:

Share of Education Mismatch by Study Field in 2022
Share of Education Mismatch by Study Field in 2022

Fig. 5:

Share of Different Types of Education Mismatches
Share of Different Types of Education Mismatches

Fig. 6:

Share of Workers by Education Mismatch and Field of Study in 2022
Share of Workers by Education Mismatch and Field of Study in 2022

Fig. 7:

Share of Education Mismatch by Study Field in 2011
Share of Education Mismatch by Study Field in 2011

Fig. 8:

Share of Workers by Education Mismatch and Field of Study in 2011
Share of Workers by Education Mismatch and Field of Study in 2011

Estimates from Logistic Regression for Vertical and Horizontal Mismatch (average marginal effects reported)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
Yearly dummy variables Year 2011 Year 2022
Undereducation Matched Overeducation Horizontal mismatch Undereducation Matched Overeducation Horizontal mismatch Undereducation Matched Overeducation Horizontal mismatch
Women 0.004 (0.016) –0.051** (0.022) 0.047** (0.019) 0.085*** (0.020) 0.003 (0.022) –0.034 (0.029) 0.031 (0.026) 0.065** (0.027) –0.004 (0.022) –0.065** (0.031) 0.070** (0.028) 0.114*** (0.030)
Age
 25–34 years baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline
 35–44 years –0.023 (0.016) 0.033 (0.023) –0.010 (0.020) –0.006 (0.020) –0.021 (0.021) 0.035 (0.030) –0.013 (0.026) –0.026 (0.026) –0.025 (0.026) 0.032 (0.035) –0.007 (0.030) 0.020 (0.031)
 45–54 years –0.017 (0.017) 0.050** (0.024) –0.033 (0.020) 0.014 (0.021) –0.021 (0.022) 0.035 (0.031) –0.014 (0.026) 0.014 (0.026) –0.013 (0.027) 0.072** (0.036) –0.059* (0.031) 0.026 (0.034)
Years of education –0.069*** (0.005) –0.001 (0.006) 0.070*** (0.004) 0.005 (0.005) –0.074*** (0.006) 0.008 (0.007) 0.066*** (0.005) 0.007 (0.006) –0.061*** (0.007) –0.017** (0.008) 0.078*** (0.005) 0.006 (0.006)
ISCED
 00 – Generic programmes baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline baseline
 01 – Education 0.308*** (0.058) –0.006 (0.062) –0.302*** (0.032) –0.622*** (0.046) 0.335*** (0.066) –0.037 (0.073) –0.298*** (0.043) –0.706*** (0.054) 0.259** (0.106) 0.057 (0.109) –0.316*** (0.048) –11.516*** (0.075)
 02 – Arts & Humanities 0.221*** (0.086) –0.178** (0.081) –0.043 (0.059) 0.083** (0.035) 0.383** (0.151) –0.368*** (0.124) –0.015 (0.113) —— 0.168* (0.086) –0.108 (0.090) –0.059 (0.070) 0.129*** (0.046)
 03 – Social Sciences & Info 0.089* (0.046) 0.016 (0.056) –0.106** (0.042) –0.175*** (0.047) 0.099* (0.059) 0.024 (0.073) –0.123** (0.055) –0.300*** (0.060) 0.044 (0.069) 0.042 (0.083) –0.085 (0.064) –0.001 (0.057)
 041 – Business 0.006 (0.025) 0.016 (0.039) –0.022 (0.035) — 0 444*** (OT34) –0.015 (0.036) 0.026 (0.058) –0.011 (0.052) –0.350*** (0.046) 0.030 (0.034) 0.019 (0.051) –0.049 (0.047) –0.527*** (0.046)
 042 – Administration & Law 0.126*** (0.035) –0.019 (0.046) –0.106*** (0.038) –0.487*** (0.039) 0.150*** (0.045) –0.056 (0.059) –0.094* (0.048) –0.625*** (0.043) 0.070 (0.058) 0.108 (0.077) –0.178*** (0.061) –0.166** (0.067)
 05 – Natural Sciences & Math 0.034 (0.041) 0.100* (0.060) –0.134** (0.053) –0.034 (0.037) 0.038 (0.050) 0.110 (0.077) –0.149** (0.068) –0.093** (0.043) 0.028 (0.087) 0.107 (0.095) –0.134* (0.074) 0.009 (0.062)
 06 – ICTs 0.198*** (0.068) –0.113 (0.072) –0.085* (0.051) –0.332*** (0.071) 0.390** (0.183) –0.327** (0.162) –0.063 (0.102) –0.145 (0.185) 0.160** (0.067) –0.065 (0.078) –0.095 (0.062) –0.314*** (0.080)
 07 – Engin. & Manufacturing 0.017 (0.021) 0.009 (0.034) –0.026 (0.032) –0.465*** (0.028) 0.004 (0.031) 0.042 (0.048) –0.046 (0.044) –0.540*** (0.031) 0.025 (0.029) –0.012 (0.047) –0.013 (0.045) –0.389*** (0.045)
 08 – Agriculture & Vet. –0.033 (0.032) –0.040 (0.053) 0.072 (0.048) –0.035 (0.039) –0.018 (0.045) –0.111 (0.069) 0.129* (0.066) –0.106** (0.042) –0.055 (0.039) 0.071 (0.075) –0.016 (0.069) 0.043 (0.064)
 09 – Health & Welfare 0.374*** (0.040) –0.187*** (0.046) –0.187*** (0.038) –0.681*** (0.037) 0.427*** (0.052) –0.257*** (0.061) –0.170*** (0.056) –0.726*** (0.051) 0.292*** (0.062) –0.075 (0.070) –0.217*** (0.050) –0.665*** (0.050)
 10 – Services –0.042* (0.022) 0.053 (0.038) –0.011 (0.036) –0.287*** (0.033) –0.061* (0.031) 0.107** (0.054) –0.047 (0.049) –0.303*** (0.038) –0.014 (0.030) –0.018 (0.055) 0.032 (0.051) –0.274*** (0.055)
Region of residence YES YES YES YES YES YES YES YES YES YES YES YES
Year dummies (base 2011) –0.023 (0.015) –0.032 (0.020) 0.055*** (0.017) –0.017 (0.018)
Adj. McFadden R2 0.092 0.092 0.092 0.143 0.088 0.088 0.088 0.152 0.071 0.071 0.071 0.150
Observations 3,394 3,394 3,394 3,394 1,978 1,978 1,978 1,978 1,516 1,516 1,516 1,516

Share of overeducated university graduates (in %)

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
CR 8.3 12.7 12.5 13.4 13.3 13.4 13.7 14.5 14.6 15.1
EU average 20.3 19.6 20.7 21.0 21.7 21.8 21.7 22.1 22.1 21.9
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