A Microanalytical Simulation Model to Predict the Long-Term Evolution of Employment Biographies in Austria: The Demographics Module

Authors

  • Marcus Wurzer Vienna University of Economics and Business
  • Reinhold Hatzinger Vienna University of Economics and Business

DOI:

https://doi.org/10.17713/ajs.v38i4.277

Abstract

The well-known problems of decreasing birth rates and population ageing represent a major challenge for the Austrian pension system. It is expected that the group of pensioners will grow steadily in the future, while the proportion of people that support them – the taxpayers – will shrink. In this regard, microsimulation provides a valuable tool to identify the impact of various policy measures. With microsimulation, it is not only possible
to predict cross-sectional data (e.g., the distribution of age groups in 2050), but also to simulate lifecourses of people, providing longitudinal outcomes. The demographics module is the first in a series of modules that are part of a microsimulation prototype. This prototype is being developed in order to predict the long-term evolution of Employment Biographies in Austria.

References

Cassells, R., Harding, A., and Kelly, S. (2006). Problems and prospects for dynamic microsimulation: A review and lessons for APPSIM (Tech. Rep.). Canberra: National Centre for Social and Economic Modelling. (Discussion Paper no. 63 December

; Online: http://www.canberra.edu.au/centres/natsem/)

Cheesbrough, S., and Scott, A. (2003). Simulating demographic events in the SAGE model (Tech. Rep.). London School of Economics, UK: ESRC SAGE Research Group. (SAGE Technical note no. 4 December 2003; Online: http://www.lse.ac.uk/collections/SAGE/)

Flood, L. (2008). SESIM: A Swedish micro-simulation model.

Harding, A. (1996). Microsimulation and Public Policy. Amsterdam: North-Holland, Elsevier Science B.V.

Hosmer, D. W., and Lemeshow, S. (2000). Applied Logistic Regression (2nd ed.). Hoboken, NJ: Wiley.

Keegan, M. (2007). Modelling the workers of tomorrow: the APPSIM dynamic microsimulation model (Tech. Rep.). Canberra.

(HILDA Survey Research Conference 2007 19-20 July 2007; Online: http://www.melbourneinstitute.com/conf/hildaconf2007/)

Kelly, S. (2007). APPSIM: Selection of the main source data file for the base data (Tech. Rep.). Canberra: National Centre for Social and Economic Modelling. (Working Paper No. 2 April 2007; Online: http://www.canberra.edu.au/centres/natsem/)

King, A., Bækgaard, H., and Robinson, M. (1999). DYNAMOD-2: AN

OVERVIEW (Tech. Rep.). Canberra: National Centre for Social and

Economic Modelling. (Technical Paper no. 19 December 1999; Online: http://www.canberra.edu.au/centres/natsem/)

Klotz, J. (2007). Soziale Unterschiede in der Sterblichkeit; Bildungsspezifische Sterbetafeln 2001/2002. In Statistische Nachrichten April 2007. Vienna: Statistik Austria.

Orcutt, G. H. (1957). A new type of socio-economic system. Review of Economics and Statistics, 58, 773-797.

R Development Core Team. (2009). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Available from http://www.R-project.org

Statistik Austria. (2001). Familienstrukturen und Familienbildung – Ergebnisse des Mikrozensus September 2001. Vienna: Statistik Austria.

Statistik Austria. (2008). Demographisches Jahrbuch 2007. Vienna: Statistik Austria.

Zaidi, A., and Scott, A. (2001). Base dataset for the SAGE model (Tech. Rep.). London School of Economics, UK: ESRC SAGE Research Group. (SAGE Technical note no. 1 September 2001; Online: http://www.lse.ac.uk/collections/SAGE/)

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Published

2016-04-03

How to Cite

Wurzer, M., & Hatzinger, R. (2016). A Microanalytical Simulation Model to Predict the Long-Term Evolution of Employment Biographies in Austria: The Demographics Module. Austrian Journal of Statistics, 38(4), 241–254. https://doi.org/10.17713/ajs.v38i4.277

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