ALTERNATIVE APPROACHES TO EFFICIENCY EVALUATION OF HIGHER EDUCATION INSTITUTIONS

Evaluation of efficiency and ranking of higher education institutions is very popular and important topic of public policy. The assessment of the quality of higher education institutions can stimulate positive changes in higher education. In this study we focus on assessment and ranking of Slovak economic faculties. We try to apply two different quantitative approaches for evaluation Slovak economic faculties - Stochastic Frontier Analysis (SFA) as an econometric approach and PROMETHEE II as multicriteria decision making method. Via SFA we examine faculties’ success from scientific point of view, i.e. their success in area of publications and citations. Next part of analysis deals with assessing of Slovak economic sciences faculties from overall point of view through the multicriteria decision making method. In the analysis we employ panel data covering 11 economic faculties observed over the period of 5 years. Our main aim is to point out other quantitative approaches to efficiency estimation of higher education institutions

Income disparities and convergence across regions of Central Europe

This paper deals with the analysis of regional income disparities of the net disposable income of households (in Euro per inhabitant) across the regions of Central Europe (Austria, Czech Republic, Slovakia, Poland, Hungary and Germany) during the period 2000-2013. The analysis deals with the 82 NUTS 2 (Nomenclature of Territorial Units for Statistics) regions and is based on the concept of sigma-convergence, beta-convergence and growth-volatility relationship. Preliminary analysis concentrating on mapping of the analysed indicators is followed by consideration of the region’s location supported by the results of spatial autocorrelation testing. The sigma-convergence analysis reveals the persistence of disparities in the net disposable income of households in the period 2000-2013 both at the national and subnational level. Although the results of spatial analysis have proved the existence of spatial dependence, following the classical approach, the beta-convergence concept is tested with the use of both non-spatial and spatial models. The potentially different convergence characteristics of Visegrad 4 countries’ (Czech Republic, Slovakia, Poland, Hungary) regions and regions of Austria and Germany as well as the examination of the possible relationship between the regional growth and volatility are also taken into account in the econometric convergence modelling

Spatial Heterogeneity and Spillovers of Employment in the EU Regions

This paper focuses on the employment problem in the context of EU regions. Two main hypotheses were verified. The first hypothesis was related to the spatial heterogeneity problem, i.e., we hypothesised that relationship between the employment rate and the explanatory variables (GDP per inhabitant, educational attainment level and compensation of employees) may vary spatially. The second hypothesis dealt with the spatial autocorrelation, i.e., we assumed that the regional employment process is not isolated and that the neighbourhood of the regions also plays a significant role. As the main methodological tool the spatial regime models were applied. Spatial analysis of employment rate data indicated two spatial regimes. The results revealed the spatial instability of estimated parameters across the two regimes. Also, the spatial regional interconnections within both regimes were confirmed. Statistical significance of spillover effects of considered employment factors outlines the high importance of spatial spillovers

Multiple selections of alternatives under constraints : case study of european countries in area of research and development

This paper is given over to a multicriteria evaluation approach to the issue of international comparison of research and development indicators. The policy activities in R&D (Research & Development) area are significant parts of many national programs of many EU member states. There are several reasons for governments to take active role in stimulation investment in R&D. R&D are generally considered to be the main engine of long-run economic growth. Also The European Commission pays more attention to R&D activities and provides more and more resources to these activities through Community Framework Programs. We decided to exploit multi-attribute decision-making to evaluate R&D indicators of European countries. As multi-attribute decision-making method Topsis method was applied. Topis method has provided us complete ranking of the countries taking into account indicators such as patent applications, total intramural R&D expenditure, human resources in science and technology, employment in knowledge-intensive activities and business enterprise R&D expenditure. Having these results in a hand; we proceed to making multiple selections of countries under constraints. Our main goal was to suggest an optimization model for resources distribution - subsides for R&D encouragement, i.e. to find an optimal selection of several alternatives given a set of constraints. To make a decision concerning proper countries selection we employed optimization model inspired by Promethee V, which enables us to take into account the results of previous empirical part and, at the same time, to take into account defined constraints. Formulated binary linear programming model could be useful support decision making tool in the process of resources distribution - subsides for R&D encouragement

Regional Disparities in Education Attainment Level in the European Union: A Spatial Approach

This article deals with the analysis of education attainment level across the 252 NUTS 2 regions of the European Union (EU) with consideration of the spatial aspect. Since the individual EU regions cannot be seen as isolated, the main aim of this article is to assess the impact of location on the education attainment level (percentage of population aged 25–64 with at least upper secondary education) during the period 2007–2015, as well as to investigate the impact of regional growth 2014/2007 on the education attainment level in 2015. The spatial analysis proved the existence of positive spatial autocorrelation and persistence of disparities in education attainment level across EU regions during the analysed period. The results of econometric analysis confirmed the expected positive impact of economic growth on education attainment level as well as the necessity to incorporate the spatial dimension into the model

Regional disparities in education attainment level in the European Union: a spatial approach

This article deals with the analysis of education attainment level across the 252 NUTS 2 regions of the European Union (EU) with consideration of the spatial aspect. Since the individual EU regions cannot be seen as isolated, the main aim of this article is to assess the impact of location on the education attainment level (percentage of population aged 25–64 with at least upper secondary education) during the period 2007–2015, as well as to investigate the impact of regional growth 2014/2007 on the education attainment level in 2015. The spatial analysis proved the existence of positive spatial autocorrelation and persistence of disparities in education attainment level across EU regions during the analysed period. The results of econometric analysis confirmed the expected positive impact of economic growth on education attainment level as well as the necessity to incorporate the spatial dimension into the model

Stochastic frontier analysis of regional competitiveness

The regional competitiveness is the source of national competitiveness and the efficiency measuring and relative regional efficiency comparison are crucial questions for analysts as well as for economic policy creators. Regional competitiveness becomes a subject of evaluation due to increasing significance of regions in concept of European Union. This paper deals with the application of parametric benchmarking method – Stochastic Frontier Analysis (SFA) for measuring technical efficiency of NUTS2 regions of V4 countries within the time period of 8 years

The analysis of employment rates in the context of spatial connectivity of the EU regions

Research background: The main objective of this paper is to analyse the employment rates in the context of spatial connectivity of the EU regions. Employment rate is declared as one of the important indicators of the strategic document Europe 2020. The achievement of high levels of employment in individual regions plays therefore an important role. Purpose of the article: The aim of the paper is to verify the possible spill-over effects within the EU regions and their territorial interconnection in the context of employment rates. Methods: Analysis is based on tools of the Exploratory Spatial Data Analysis (ESDA) to consider spatial connectivity of the EU regions. Findings & Value added: The results show that the statistically significant clusters of regions with high employment rates are situated mainly in the central, northern and north-western part of the EU while the clusters with low values are located mainly in Greece, Spain, Italy, Portugal, Bulgaria, Romania and some French regions

Interregional R and D spillovers and regional convergence: a spatial econometric evidence from the EU regions

Research background: Many contemporary empirical studies and also most of economic growth theories recognize the importance of innovation and knowledge for achieving an economic growth. A large part of empirical literature has treated the issue of beta convergence without the spatial aspect, i.e. the possible spatial dependence among regions or states in growth process was neglected. Purpose of the article: In this paper, we investigate the link between selected R&D (Research and Development) indicators as proxies for the regional innovation and knowledge and economic performance of the region. We also assume a significant role of regional R&D spillovers in the regional growth process determination. Methods: The main methodological basis for our analysis is beta convergence approach and the dataset under the consideration consists of 245 NUTS 2 (Nomenclature of Units for Territorial Statistics) EU (European Union) regions during the 2003–2014 period. Our analysis is made with respect to spatial interactions across the EU regions. Findings & Value added: The influence of R&D indicators on the economic growth has been confirmed, and spatial interconnection across the EU regions have been proven. Potential existence of geographical R&D spillovers across the EU regions was examined by formulation of additional beta convergence model with spatial lag variables. We have identified that the influence of R&D spillovers is not strictly restricted to the neighbouring regions, but they spread across a larger area. For the construction of spatial lags of R&D indicators different spatial weight matrices were considered

INTERREGIONAL R&D SPILLOVERS AND REGIONAL CONVERGENCE: A SPATIAL ECONOMETRIC EVIDENCE FROM THE EU REGIONS

Research background: Many contemporary empirical studies and also most of economic growth theories recognize the importance of innovation and knowledge for achieving an economic growth. A large part of empirical literature has treated the issue of beta convergence without the spatial aspect, i.e. the possible spatial dependence among regions or states in growth process was neglected. Purpose of the article: In this paper, we investigate the link between selected R&D (Research and Development) indicators as proxies for the regional innovation and knowledge and economic performance of the region. We also assume a significant role of regional R&D spillovers in the regional growth process determination. Methods: The main methodological basis for our analysis is beta convergence approach and the dataset under the consideration consists of 245 NUTS 2 (Nomenclature of Units for Territorial Statistics) EU (European Union) regions during the 2003–2014 period. Our analysis is made with respect to spatial interactions across the EU regions. Findings & Value added: The influence of R&D indicators on the economic growth has been confirmed, and spatial interconnection across the EU regions have been proven. Potential existence of geographical R&D spillovers across the EU regions was examined by formulation of additional beta convergence model with spatial lag variables. We have identified that the influence of R&D spillovers is not strictly restricted to the neighbouring regions, but they spread across a larger area. For the construction of spatial lags of R&D indicators different spatial weight matrices were considered