WYKORZYSTANIE DATA ENVELOPMENT ANALYSIS DO PORÓWNANIA POLITYKI WIEKOWEJ W KRAJACH UNII EUROPEJSKIEJ

• Authors: Andrzej Szuwarzyński

Title variants

EN

USE OF DATA ENVELOPMENT ANALYSIS TO COMPARE AGE POLICIES IN THE EUROPEAN UNION COUNTRIES

• Languages of publication: PL

Abstracts

PL

Celem artykułu jest zbudowanie modelu, bazującego na Data Envelopment Analysis (DEA), pozwalającego na porównanie działań związanych z polityką wiekową w krajach Unii Europejskiej. Zastosowano model z ograniczeniami na wagi, pozwalający na stworzenie rankingu i określenie kierunków kształtowania polityki wiekowej. Wykorzystano dane pochodzące z bazy danych Global AgeWatch Index 2013.

EN

The aim of this paper is to build a model, based on Data Envelopment Analysis (DEA), allowing the comparison of activities related to the age policy in the European Union countries. A model with bounded weights was adopted to create a ranking and determine the direction of age policy-making. Data from AgeWatch Global Index 2013 database were used.

Keywords

PL

DEA; efektywność; polityka wiekowa

EN

DEA; efficiency; ageing policy

• Publisher: Katedra Ekonometrii i Statystyki, Szkoła Główna Gospodarstwa Wiejskiego w Warszawie
• Journal: Metody Ilościowe w Badaniach Ekonomicznych
• Year: 2014
• Volume: 15
• Issue: 4
• Pages: 195-204

Dates

published

2014

Contributors

author

Andrzej Szuwarzyński

• Wydział Zarządzania i Ekonomii, Politechnika Gdańska

References

• Angulo-Meza L., Lins M.P.E. (2002) Review of Methods for Increasing Discrimination in Data Envelopment Analysis, Annals of Operations Research, 116, s. 225-242.
• Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. European Journal of Operational Research, 2, s. 429-444.
• Cherchye L., Moesen W., Rogge N., Van Puyenbroeck T. (2007) An introduction to ‘benefit of the doubt’ composite indicators, Social Indicators Research, 82, s. 111–145.
• Cherchye L., Moesen W., Rogge N., Van Puyenbroeck T. (2009) Constructing a Knowledge Economy Composite Indicator with Imprecise Data, Hub Research Paper – Economics & Management, 2009/16, Katholieke Universiteit Leuven.
• Cook W.D., Tone K., Zhu J. (2014) Data envelopment analysis: Prior to choosing a model. Omega-International Journal of Management Science, 44, s. 1-4.
• Cooper W.W., Seiford L.M., Tone K. (2007) Data Envelopment Analysis, A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Springer, New York.
• Cooper W.W., Ruiz J.L., Sirvent I. (2009) Selecting non-zero weights to evaluate effectiveness of basketball players with DEA, European Journal of Operational Research, 195, s 563-574.
• Cooper W.W., Seiford L.M., Zhu, J. (2011) Handbook on Data Envelopment Analysis, Springer, New York.
• Despotis D.K. (2005) Measuring human development via Data Envelopment Analysis: the case of Asia and the Pacific, Omega-International Journal of Management Science, 33, s. 385-390.
• Guzik B. (2009) Podstawowe modele DEA w badaniu efektywności gospodarczej i społecznej, Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu, Poznań.
• HelpAge (2013) Global AgeWatch Index 2013. Purpose, methodology and results, HelpAge International, London, www.globalagewatch.org
• Hoffman A., Giovanni E., Nardo M., Saisana M., Saltelli A., Tarantola S. (2008) Handbook on Constructing Composite Indicators. Methodology and User Guide, OECD Publishing, Paris.
• Koopmans T.C. (1951) Analysis of production as an efficient combination of activities, in: T.C. Koopmans (Ed.), Activity Analysis of Production and Allocation, Wiley, New York.
• Lovell K.C.A. (1995) Measuring the macroeconomic performance of the Taiwanese economy, Int. J. Production Economics, 39, s. 165-178.
• Lovell K.C.A., Pastor J.T., Turner J.A. (1995) Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries, European Journal of Operational Research, 87 s. 507-518.
• Marginson S. (2014) University Rankings and Social Science. European Journal of Education, 49 (1), s. 45-59.
• Murias, P., de Miguel, J.C. i Rodriguez D. (2008) A Composite Indicator for University Quality Assesment: The Case of Spanish Higher Education System, Social Indicators Research, 89, s. 129-146.
• Paruolo P, Saisana M., Saltelli, A. (2013). Ratings and rankings: voodoo or science?, Journal of the Royal Statistical Society. Series A, Statistics in Society, 176 (3), 609-634.
• Ramanathan R. (2006) Evaluating the comparative performance of countries of the Middle East and North Africa: A DEA application, Socio-Economic Planning Sciences, 40, s. 156-167.
• Ramón N., Ruiz J.L., Sirvent I. (2010) A multiplier bound approach to assess relative efficiency in DEA without slacks, European Journal of Operational Research, 203, s. 261-269.
• Roll Y., Golany B. (1993) Alternate Methods of Treating Factor Weights in DEA, Omega-International Journal of Management Science, vol. 21, no. 1, s. 99-109.
• Saisana M., d’Hombres B., Saltelli A. (2011) Rickety numbers: Volatility of university rankings and policy implications. Research Policy, 40, s. 165-177.
• UN (2013) World Population Ageing 2013, Department of Economic and Social Affairs, Population Division, United Nations, New York.
• UNFPA (2012) Ageing in the Twenty-First Century: A Celebration and A Challenge, United Nations Population Fund, New York and HelpAge International, London.
• Zaidi A., Gasior K., Hofmarcher M.M., Lelkes O., Marin B., Rodrigues R., Schmidt A., Vanhuysse P., Zolyomi E. (2013) Active Ageing Index 2012. Concept, Methodology and Final Results, Project: ‘Active Ageing Index (AAI)’ UNECE Grant No: ECE/GC/2012/003, United Nations Economic Commission for Europe (UNECE), Geneva.
• Zhu J., Cook W.D. (2007) Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, Springer, New York