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Job Polarization in Europe: Evidence from Central and Eastern European Countries
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Job Polarization in Europe: Evidence from Central and Eastern European Countries

By: Dennis Nchor and  Petr Rozmahel  
Open Access
|Apr 2020

Figures & Tables

Figure 1

Job polarization in USA and CEEC, 2000–2016Source: Generated by authors using data from the Bureau of Labour Statistics
Job polarization in USA and CEEC, 2000–2016Source: Generated by authors using data from the Bureau of Labour Statistics

Figure 2

Employment performance by occupations in CEEC, 2000–2016Source: Generated by authors using data from the Bureau of Labour Statistics
Employment performance by occupations in CEEC, 2000–2016Source: Generated by authors using data from the Bureau of Labour Statistics

Figure 3

Labour in skill groups by education, CEECSource: Generated by authors using data from Eurostat
Labour in skill groups by education, CEECSource: Generated by authors using data from Eurostat

Figure 4

Lowly educated labour in other skill occupations, CEECSource: Generated by authors using data from Eurostat
Lowly educated labour in other skill occupations, CEECSource: Generated by authors using data from Eurostat

Results of Hausman test of mean group and pooled mean group models

Low sill employment
Variable(b)(B)(bB)sqrt (diag (V_bV_B))
MGPMGdifferenceS.E.
Log GVA(L1.)0.9071.151−0.2440.469
Log TFP (L1.)−2.422−3.5691.1473.926
Chi2(2) = = (bB)′ [(V _ bV _ B) ˆ(−1)] (bB)P value
0.40.821
Middle skill employment
Variable(b)(B)(bB)sqrt diag (V _ bV _ B)
MGPMGdifferenceS.E.
Log GVA(L1.)0.2280.428−0.2000.090
Log TFP (L1.)−0.444−1.1490.7050.580
Chi2(2) = = (bB) ′ [(V _ bV _ B) ˆ(−1)] (bB)P value
4.940.085
High skill employment
Variable(b)(B)(bB)sqrt diag (V _ bV _ B)
MGPMGdifferenceS.E.
Log GVA(L1.)0.0090.205−0.1970.273
Log TFP (L1.)1.4701.1550.3152.923
Chi2(2) = = (bB) ′ [(V _ bV _ B) ˆ(−1)] (bB)P value
4.940.085

Impact of Technology on high skill labour

VARIABLESECTBulgariaCzech RHungaryPolandRomaniaSlovakia
ECT 0.100**(0.0145)−0.923***(0.138)−0.55***(0.034)−0.850***(0.180)−0.383***(0.060)−0.969***(0.268)
D.ln High skill −0.124**(0.048)−0.48**(0.020)−0.21**(0.020)−0.47(0.029)−0.50***(0.003)−0.70**(0.036)
D.ln GVA −0.551(0.429)1.053***(0.169)−0.301***(0.104)0.194(0.180)0.279***(0.029)−1.834***(0.550)
D2.ln GVA 1.585***(0.597)−2.725***(0.487)0.948***(0.302)−0.257(0.273)−0.196***(0.068)4.396***(1.443)
D3.ln GVA −2.030**(0.798)3.312***(0.693)−0.768**(0.385)0.416(0.283)0.617***(0.094)−3.966***(1.366)
D4.ln GVA 1.143*(0.592)−1.655***(0.420)0.163(0.222)−0.215(0.150)−0.804***(0.070)1.916***(0.691)
D5.ln GVA −0.237(0.189)0.311***(0.098)0.001(0.052)0.041(0.034)0.298***(0.021)−0.389***(0.142)
D.TFP −0.176(0.300)1.634***(0.356)0.010(0.185)1.100***(0.319)−0.440***(0.090)0.964**(0.442)
L.ln GVA0.213***(0.025)
L.TFP2.560***(0.181)
Constant −0.197(0.358)3.320***(0.484)0.201*(0.103)3.220***(0.679)1.290***(0.224)2.214***(0.606)
Observations72727272727272
Standard errors in parentheses*** p < 0.01, ** p < 0.05, * p < 0.1

Impact of Technology on employment of low skill labour

VARIABLESECTBulgariaCzech RHungaryPolandRomaniaSlovakia
ECT −0.559**(0.272)0.161**(0.090)−0.109**(0.043)−0.739***(0.135)−0.543***(0.157)−0.252**(0.109)
D.Ln low skill −0.68**(0.012)−0.198***(0.002)−0.56**(0.011)−0.39***(0.009)−0.18***(0.007)−0.80**(0.091)
D.ln GVA −0.050(0.246)−0.063(0.056)−0.038(0.080)0.002(0.042)0.055(0.070)0.167(0.183)
D.ln TFP −0.999(2.002)1.007***(0.390)4.704**(1.915)2.433***(0.706)1.600***(0.523)1.168(0.852)
D2.ln TFP −0.975(2.171)−0.521(0.539)−4.181***(1.531)−3.417***(0.918)−2.555***(0.796)−1.384(1.126)
D3.ln TFP 0.513(0.739)0.079(0.260)1.742***(0.676)0.831***(0.321)0.917***(0.352)−0.115(0.531)
L.ln GVA0.211***(0.068)
L.ln TFP−2.882***(0.219)
Constant 1.617*(0.869)−0.428(0.306)0.267*(0.142)2.515***(0.802)1.890**(0.837)0.280(0.280)
Observations72727272727272

Impact of Technology on middle skill labour

VARIABLESECTBulgariaCzech RHungaryPolandRomaniaSlovakia
ECT −1.060***(0.210)−0.209**(0.085)−0.387**(0.021)−0.372***(0.096)−0.163***(0.051)−0.195**(0.012)
D.ln Middle Skill −0.125**(0.055)−0.190***(0.018)−0.0170**(0.055)−0.390***(0.004)−0.220**(0.019)−0.160**(0.032)
D.ln GVA 1.441***(0.243)−0.292***(0.112)0.657*(0.350)0.492***(0.062)0.224***(0.057)0.470**(0.191)
D2.ln GVA −1.152***(0.286)0.446***(0.159)−0.525(0.339)−0.308***(0.072)−0.053(0.069)−0.051(0.230)
D3.ln GVA 0.473***(0.150)−0.486***(0.105)0.193(0.134)0.034(0.040)−0.066(0.041)−0.071(0.105)
D.ln TFP −0.006(0.011)−0.161***(0.034)0.014(0.050)−0.015(0.018)−0.038***(0.013)0.006(0.021)
L. ln GVA0.368***(0.065)
L.ln TFP−0.719***(0.187)
Constant 3.588***(0.736)0.613*(0.325)1.246(0.839)1.589***(0.464)0.607**(0.261)0.589(0.432)
Observations72727272727272
Standard errors in parentheses*** p < 0.01, ** p < 0.05, * p < 0.1
DOI: https://doi.org/10.2478/danb-2020-0004 | Journal eISSN: 1804-8285 | Journal ISSN: 1804-6746
Language: English
Page range: 52 - 74
Published on: Apr 21, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Dennis Nchor, Petr Rozmahel, published by European Association Comenius - EACO
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.