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Modeling the Diffusion of Private Pension Provision

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  • Larysa Yakymova

Abstract

The purpose of this paper is threefold: to adapt the innovation diffusion models to describe and predict the diffusion of private pension provision; to evaluate the suitability of diffusion models based on the historical data from the Romanian and Ukrainian voluntary pension systems; and to compare the diffusion parameters of private pension provision in these countries. The study proven that diffusion models, such as the Rogers model and the Bass model, can reproduce the diffusion of innovations in the field of pensions. The Rogers diffusion parameters for Romania and Ukraine are almost identical; this gives grounds for a conclusion about the similar behavioral patterns in post-socialist countries. However, some limitations on models use are noted. During the crisis and when using the nudge mechanism, models are not always well-fitting, but when new pension schemes are introduced or new pension funds are opened, models can be used in “guessing by analogy†. JEL Codes - C51; G53

Suggested Citation

  • Larysa Yakymova, 2018. "Modeling the Diffusion of Private Pension Provision," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(4), pages 385-405, December.
  • Handle: RePEc:aic:saebjn:v:65:y:2018:i:4:p:385-405:n:122
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    File URL: http://saeb.feaa.uaic.ro/index.php/saeb/article/view/1106
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    References listed on IDEAS

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    1. Christoph Freudenberg & Tamás Berki & Ádám Reiff, 2016. "A Long-Term Evaluation of Recent Hungarian Pension Reforms," MNB Working Papers 2016/2, Magyar Nemzeti Bank (Central Bank of Hungary).
    2. Andreea Gabriela BALTAC & Zoica DINCA (NICOLA), 2013. "Companies' Role in the Evolution of the Romanian Economy in the Period 2011-2013," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 61(4), pages 113-117, December.
    3. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    4. Alexandra Hennessy & Martin C. Steinwand, 2014. "The Sources of Pension Reforms in Western Europe: Domestic Factors, Policy Diffusion, or Common Shock?," International Interactions, Taylor & Francis Journals, vol. 40(4), pages 477-505, August.
    5. Robert Holzmann & Mitchell Orenstein & Michal Rutkowski, 2003. "Pension Reform in Europe : Process and Progress," World Bank Publications - Books, The World Bank Group, number 15132, December.
    6. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
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    More about this item

    Keywords

    voluntary pension system; diffusion mechanism; Rogers model; Bass model; CEE countries;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G53 - Financial Economics - - Household Finance - - - Financial Literacy

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