An Evaluation of the Efficiency of Tertiary Education in the Explanation of the Performance of GDP per Capita Applying Data Envelopment Analysis (DEA)

Marco Marto (), João Lourenço Marques and Mara Madaleno
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Marco Marto: Department of Social, Political and Territorial Sciences, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
João Lourenço Marques: Department of Social, Political and Territorial Sciences, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Mara Madaleno: Research Unit in Governance, Competitiveness and Public Policies (GOVCOPP), University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal

Sustainability, 2022, vol. 14, issue 23, 1-20

Abstract: The scientific literature and decision makers debate and explore education’s influence on regional development. However, differences among EU regions remain to be explained. The present article proposes to measure these disparites in terms of the gross domestic product (GDP) per capita and understand how tertiary education can explain that performance. A data envelopment analysis (DEA) optimization technique was applied along with spatial econometric models for all EU NUTS 2 regions (as defined by Eurostat for regional policies application), using the year 2020 as reference. The case of Portugal as a particular set of (seven) NUTS 2 regions included in the EU is detailed and analyzed in-depth. The two-stage least squares regression seems to explain well the differences in GDP per capita with the independent (and instrumental) variables which include the percentage of tertiary education and the spatial lags of this variable. The DEA optimization can support and help to explain most of the spatial regression results. The study identifies the NUTS 2 regions with the best favorable relationships among GDP per capita and percentages of tertiary education, predominantly located in the central and northern European countries and some in Ireland. The south EU regions, as expected, were identified as the regions with the poorest performances for GDP per capita and percentage of tertiary education, as well as some regions in eastern Europe. The positive and significant impact of the percentage of people with tertiary education on the values of GDP per capita given by the spatial econometric model suggests that special priority must be given to education and science in public policies agenda and government budget.

Keywords: GDP per capita; tertiary education; EU NUTS 2; DEA optimization; spatial econometrics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:23:p:15524-:d:980509

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