Digital Library of the European Council for Modelling and Simulation

Title:	Supporting Pension Pre-Calculation With Dynamic Microsimulation Technologies
Authors:	David Burka, Laszlo Mohacsi, Jozsef Csicsman, Benjamin Soos
Published in:	(2017).ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi:10.7148/2017 ISBN: 978-0-9932440-4-9/ ISBN: 978-0-9932440-5-6 (CD) 31st European Conference on Modelling and Simulation, Budapest, Hungary, May 23^rd – May 26^th, 2017
Citation format:	David Burka, Laszlo Mohacsi, Jozsef Csicsman, Benjamin Soos (2017). Supporting Pension Pre-Calculation With Dynamic Microsimulation Technologies, ECMS 2017 Proceedings Edited by: Zita Zoltay Paprika, Péter Horák, Kata Váradi, Péter Tamás Zwierczyk, Ágnes Vidovics-Dancs, János Péter Rádics European Council for Modeling and Simulation. doi: 10.7148/2017-0562
DOI:	https://doi.org/10.7148/2017-0562
Abstract:	Population ageing induces many challenges in the pension system of developed countries. It is necessary to support the decision-making processes regarding these challenges by forecasting different future scenarios. Long-term forecasts are required to understand the development process of the population and the pension system. The microsimulation approach has many benefits over other forecasting methods, though it requires high level of programing skills and significant computing capacity. Moreover, a long-term demographic microsimulation must be dynamic and it should preferably also include the relations between individuals. In this paper, we will introduce two different microsimulation based solutions for the above-mentioned forecasting tasks. The first one is a complex model – aiming to forecast the Hungarian population – built in SAS, that can highlight the advantages of the microsimulation approach. The second solution is a Simulation Framework (written in C#), that aims to drastically reduce the difficulties regarding microsimulation using the findings of the SAS model. Our goal is to introduce our systems in the hope of future collaboration with economists and demographers.
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