Cluster analysis of new EU member states' pension systems

Mira Krpan (), Ana Pavkovic and Berislav Zmuk
Additional contact information
Mira Krpan: University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia
Ana Pavkovic: University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia
Berislav Zmuk: University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia

Interdisciplinary Description of Complex Systems - scientific journal, 2020, vol. 18, issue 2B, 208-222

Abstract: The aging of European societies is reshaping their population pyramids. The increase in life expectancy and the decrease in the fertility rate lead to an increasing share of the elderly population. This leads to rising age-related expenditures, especially public pension expenditures to GDP. Consequently, economies are reforming their pension systems to make them more sustainable. Next to the aging-related challenges, the new EU members, eleven post-socialist economies: Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia share a similar history of restructuring of their pension systems and establishment of a multi-pillar system. The objective of this article is to examine the similarities and differences between the pension systems of the selected post-transition economies of the European Union to establish the basis for further research, simulations, and assumptions on the impact of future pension reforms. For that purpose, we apply Ward's clustering methodology on three variable groups in three selected years: 1996, 2006, and 2016. The idea of clustering economies in three years with a 10-year gap is relevant since it reveals how the cluster structure is changing over time. Additionally, three periods represent three different phases in the pension systems' development. Three groups of variables were used for cluster analysis. First, pension systems' characteristics include average effective retirement age, pension expenditure, and replacement rate. Second, demographics encompass fertility rate, life expectancy at the age of 65, net migration rate, and old-age dependency ratio. Third, the macroeconomics and labour market variables refer to the GDP growth rate, real labour productivity, labour force participation rate, and the unemployment rate. Results of cluster analysis show that the composition of the countries in the extracted clusters changes significantly, both throughout the observed period and when looking at different variable groups. Our results revealed that the pension systems of economies with later retirement proved to be more sustainable, during the three observed periods, due to lower pension expenditures that are in turn positively reflected in the favourable economic conditions and their labour market.

Keywords: pension sustainability; pension systems; hierarchical cluster analysis; New Member States; Ward's method (search for similar items in EconPapers)
JEL-codes: C38 H55 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://indecs.eu/2020/indecs2020-pp208-222.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zna:indecs:v:18:y:2020:i:2:p:208-222

Access Statistics for this article

More articles in Interdisciplinary Description of Complex Systems - scientific journal from Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu
Bibliographic data for series maintained by Josip Stepanic ().