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MICSIM-4j - A General Microsimulation Model User Guide (Version 1.1)

Listed author(s):
  • Joachim Merz
  • Lars Rusch


    (LEUPHANA University Lüneburg,Department of Economic, Behaviour and Law Sciences, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)))

Microsimulation models allow targeted simulations to analyze the impacts of alternative policies, measures, scenarios based on microunits like persons, families, households, firms etc. Meanwhile it is out of question that microsimulation models are a helpful, successful and an imperative instrument for a wide range of policy analyses in the political administration, business area, private and university institutes and consulting groups in general. Though there is a multitude of microsimulation models nowadays developed and in use, however, in most cases they still need skilled handling and experience or another program system when applied. A general, generic stand-alone and platform independent microsimulation model which provides all necessary simulation tools under a common shield, and which is easy to use for non-expert scholars, is still required. The overall objective of this paper and of the new MICSIM-4J is to describe and offer such a userfriendly, non-technical and powerful general microsimulation model, to support impact microanalyses for applied research, teaching and consulting. Though the stand-alone MICSIM-4J as a general tool also allows dynamic model building, its focus is on static microsimulation with a powerful module for the adjustment of microdata.

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File Function: First version, 2015
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Paper provided by Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg in its series FFB-Discussionpaper with number 100.

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Length: 19 pages
Date of creation: 2015
Handle: RePEc:leu:wpaper:100
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  1. Joachim Merz & Tim Rathjen, 2010. "Sind Selbständige zeit- und einkommensarm? Eine Mikroanalyse der Dynamik interdependenter multidimensionaler Armut mit dem Sozio-ökonomischen Panel und den deutschen Zeitbudgeterhebungen," FFB-Discussionpaper 82, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
  2. Merz, Joachim, 1991. "Microsimulation -- A survey of principles, developments and applications," International Journal of Forecasting, Elsevier, vol. 7(1), pages 77-104, May.
  3. Robert Tanton, 2014. "A Review of Spatial Microsimulation Methods," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 4-25.
  4. Oliver Mannion & Roy Lay-Yee & Wendy Wrapson & Peter Davis & Janet Pearson, 2012. "JAMSIM: a Microsimulation Modelling Policy Tool," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-8.
  5. Merz, Joachim, 1993. "Microsimulation as an Instrument to Evaluate Economic and Social Programmes," MPRA Paper 7236, University Library of Munich, Germany.
  6. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
  7. Martin Spielauer, 2006. "The "LifeCourse" model, a competing risk cohort microsimulation model: source code and basic concepts of the generic microsimulation programming language Modgen," MPIDR Working Papers WP-2006-046, Max Planck Institute for Demographic Research, Rostock, Germany.
  8. Gaëtan de Menten & Gijs Dekkers & Geert Bryon & Philippe Liégeois & Cathal O'Donoghue, 2014. "LIAM2: a New Open Source Development Tool for Discrete-Time Dynamic Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(3), pages 1-9.
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