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Determinants of Cognitive Skills and Competencies: Preliminary Statistical Analysis of PIAAC Data

Author

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  • Maxym Bruhanov
  • Sergiy Polyachenko

Abstract

Maxim Bruhanov - Candidate of Sciences in Economics, Junior Researcher, International Research Laboratory for Institutional Analysis, National Research University-Higher School of Economics. Email: mbryukhanov@gmail.comSergiy Polyachenko - M. Sc. in Economics, Junior Researcher, International Research Laboratory for Institutional Analysis, National Research University-Higher School of Economics. Email: sergiy.polyachenko@gmail.comAddress: 20 Myasnitskaya str., 101000, Moscow, Russian Federation.The paper presents results of factor and regression analysis of determinants affecting cognitive skills assessed with PIAAC tests. Comparative analysis of competencies by occupation categories and by specializations shows that results of the Russian sample fall remarkably behind the average OECD scores in literacy and numeracy. The difference is especially perceptible between lawmakers, high-level public officials, top- and middle-level managers, most highly skilled professionals, and respondents from humanities, social sciences, business, law, mathematics, or computer sciences. However, respondents with low education levels (8 years of school or less) and unqualified workers scored better than their average European counterparts. OECD graduates from natural sciences, mathematics and computer sciences had higher points in numeracy in the PIAAC sample. Russia demonstrated almost no difference between the numeracy points obtained by people who majored in humanities, languages and art, natural sciences, mathematics and computer sciences, engineering sciences, production and construction, health are, or services. We believe that graduates from natural sciences, mathematics and computer sciences cannot enjoy a competitive advantage in numeracy due to no rigid selection of school students, to the low-level requirements to university graduates, and to no efficient labor markets available.DOI: 10.17323/1814-9545-2015-1-214-233

Suggested Citation

  • Maxym Bruhanov & Sergiy Polyachenko, 2015. "Determinants of Cognitive Skills and Competencies: Preliminary Statistical Analysis of PIAAC Data," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 1, pages 214-233.
    • Handle: RePEc:nos:voprob:2015:i:1:p:214-233
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    1. Hansen, Karsten T. & Heckman, James J. & Mullen, K.J.Kathleen J., 2004. "The effect of schooling and ability on achievement test scores," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 39-98.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    3. Elizabeth U. Cascio & Ethan G. Lewis, 2006. "Schooling and the Armed Forces Qualifying Test: Evidence from School-Entry Laws," Journal of Human Resources, University of Wisconsin Press, vol. 41(2).
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