Autor: Furková, Andrea - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Stochastic frontier analysis of regional competitiveness
Autorzy:: Furková, Andrea
Surmanová, Kvetoslava
Powiązania:: https://bibliotekanauki.pl/articles/453463.pdf
Data publikacji:: 2011
Wydawca:: Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:: Stochastic Frontier Analysis
Technical Efficiency
NUTS2 regions
Competitiveness
Opis:: 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.
Źródło:: Metody Ilościowe w Badaniach Ekonomicznych; 2011, 12, 1; 67-76
2082-792X
Pojawia się w:: Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The analysis of employment rates in the context of spatial connectivity of the EU regions
Autorzy:: Chocholatá, Michaela
Furková, Andrea
Powiązania:: https://bibliotekanauki.pl/articles/22446568.pdf
Data publikacji:: 2018
Wydawca:: Instytut Badań Gospodarczych
Tematy:: employment rate
exploratory spatial data analysis
EU NUTS 2 regions
Opis:: 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.
Źródło:: Equilibrium. Quarterly Journal of Economics and Economic Policy; 2018, 13, 2; 181-213
1689-765X
2353-3293
Pojawia się w:: Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: INTERREGIONAL R&D SPILLOVERS AND REGIONAL CONVERGENCE: A SPATIAL ECONOMETRIC EVIDENCE FROM THE EU REGIONS
Autorzy:: Chocholatá, Michaela
Furková, Andrea
Powiązania:: https://bibliotekanauki.pl/articles/517295.pdf
Data publikacji:: 2017
Wydawca:: Instytut Badań Gospodarczych
Tematy:: beta convergence modelling
spatial econometrics
R&D indicators
R&D spillovers effects
Opis:: 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.
Źródło:: Equilibrium. Quarterly Journal of Economics and Economic Policy; 2017, 12, 1; 9-24
1689-765X
2353-3293
Pojawia się w:: Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:: Biblioteka Nauki

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