ANALYSIS OF ELDERLY FINANCIAL STABILITY IN CENTRAL AND EASTERN EUROPEAN COUNTRIES – CLASSIFICATION APPROACH
The purpose of the paper is to analyze and compare the financial situation of elderly people in Central and Eastern European (CEE) countries. The above countries have gone through similar transformation path to market economy in their socio-economic development and they have been faced similar demographic and economic problems. The financial situation of elderly people in CEE region has been strongly influenced by demographic trends, changes in macroeconomic situation and reforms of existing pension systems. Increasing lifetime, low replacement rate from the public pension systems and little pension savings or even a lack of them cause that increasing number of elderly people can be exposed to financial instability or even poverty risk. Consequently, the examination of the financial standing of the elderly in CEE region seems to be an important scientific and practical issue.
In the analysis, six variables measuring the level of income and expenses, exposure to poverty risk as well as gender differences in disposable income for age group of 65 years or over were included. The data characterizing the financial situation of elderly people in eleven CEE countries was acquired from Eurostat database. The authors applied Ward’s method and the k-means method in order to classify the examined countries according to the financial standing of elderly people. The obtained results allow to indicate countries with similar financial situation of elderly people in 2007, 2010 and 2014 as well as changes in clusters over the analyzed period. Moreover, the variance analysis was applied to indicate the influence of particular variables on the clustering results. The main findings show that the financial situation of the elderly in CEE countries is very differentiated and changeable, however over the analyzed period financial standing of the elderly seems to be the most similar in Hungary, Poland and Slovenia.
Alemayehu, B. & Warner, K.E. (2004). The Life Distribution of Health Care Costs. Health Services Research, 39(3), 627–642, doi: 10.1111/j.1475-6773.2004.00248.x
Anioła, P. & Gołaś, Z. (2013). Zachowania oszczędnościowe gospodarstw domowych w Polsce [Savings behaviour of households in Poland]. Poznań: Poznań University of Life Sciences Publishing House.
Ćwiek, M. & Wałęga, A. (2014). Financial situation of households of elderly people in Poland. Proceedings of IAC-EMM 2014: International Academic Conference on Economics, Management and Marketing in Prague.
De Nardi, M., French, E., & Jones, J. B. (2010). Why do the elderly save? The role of medical expenses. Journal of Political Economy, 118, 39–75. Retrieved from http://www.jstor.org/stable/10.1086/651674
European Commission. (2015). The 2015 Ageing Report. European Economy, 3, 1–424.
Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis. Chichester: John Wiley & Sons Ltd.
Fatuła, D. (2010). Zachowania polskich gospodarstw domowych na rynku finansowym [Behaviour of the Polish households in the financial market]. Cracow: Cracow University of Economics Publishing House.
Hartigan, J. A. (1975). Clustering Algorithms. New York: John Wiley & Sons Ltd.
Income and living condition Database Eurostat, Retrieved February 20, 2017, from http://ec.europa.eu/eurostat/web/income-and-living-conditions/data/database
Johnson, S. C. (1967). Hierarchical clustering schemes. Psychometrika, 32, 241–254. doi: 10.1007/BF02289588
Kolasa, A., & Liberda, B. (2014). Determinants of saving in Poland: Are they different than in other OECD countries. University of Warsaw Working Papers, No. 13/2014 (130). Retrieved from http://126.96.36.199/inf/wyd/WP/WNE_WP130.pdf
Kośny, M. (2013). Determinanty bezpieczeństwa ekonomicznego rodzin [Determinants of economic security of families]. Wroclaw: Wroclaw University of Economics Publishing House.
Lance, G. N., & Williams, W. T. (1967a). A general theory of classificatory sorting strategies I. Hierarchical system. The Computer Journal, 9, 373–380. Retrieved from http://biocomparison.ucoz.ru/_ld/0/50_Lance_Willams_1.pdf
Lance, G. N., & Williams, W. T. (1967b). A general theory of classificatory sorting strategies II. Hierarchical system. The Computer Journal, 10, 271–277. doi: https://doi.org/10.1093/comjnl/10.3.271
Milligan, G. W., & Cooper, M. C. (1987). Methodology review: clustering methods. Applied Psychological Measurement, 11(4), 329–354. doi: https://doi.org/10.1177/014662168701100401
Mooi, E., & Sarstedt, M. (2011). A concise guide to market research. Berlin Heidelberg: Springer-Verlag. doi: 10.1007/978-3-642-12541-6_9
Palumbo, M. G. (1999). Uncertain medical expenses and precautionary savings near the end of the life cycle. Review of Economic Studies, 66(2), 395–421. doi: https://doi.org/10.1111/1467-937X.00092
Piekut, M. (2014). Konsumpcja w polskich gospodarstwach domowych na tle krajów europejskich [Household consumption in Poland in comparison to other European countries]. Problemy Zarządzania, 11(40), 23–39.
Punj, G., & Steward, D. W. (1983). Cluster analysis in marketing research: review and suggestions for application. Journal of Marketing Research, XX, 134–148. doi: 10.2307/3151680
Rencher, A. C. (2002). Methods of multivariate analysis. Chichester: John Wiley & Sons Ltd.
Świecka, B. (2009). Niewypłacalność gospodarstw domowych. Przyczyny – skutki – przeciwdziałanie [Insolvency of households. Causes – effects – prevention]. Warsaw: Difin.
Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58, 236–244. Retrieved from https://pdfs.semanticscholar.org/8ece/d091ab3e3fd0b1747896cff082711c510d4a.pdf
Zivadinovic, N. K., Dumicic, K., & Casni, A. C. (2009). Cluster and factor analysis of structural economic indicators for selected European countries. WSEAS Transactions on Business and Economics, 6(7), 331–341. Retrieved from http://www.wseas.us/e-library/transactions/economics/2009/29-469.pdf
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