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A '''dynamic microsimulation pension model''' is a type of a [[pension model]] projecting a pension system by means of a [[microsimulation]] and generating the complete history of each individual in a data set. The results of such model offer both the aggregate (e.g. total replacement ratio, implicit debt) and individual indicators (e.g. individual cash-flows) of the pension system. Thanks to complexity of results, there is a possibility to investigate the distribution of pensions, poverty of pensioners, impact of the changes of the pension formula, for more examples see e.g. (Deloitte, 2011).<ref name=Deloitte /> Detailed individual set of (administrative) data should serve as a model input.
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== Dynamic Microsimulation Pension Models ==
A dynamic microsimulation pension models (or a dynamic model with dynamic ageing) is a type of a [[pension model]] – see its [[pension model#Taxonomy of the Pension Models|taxonomy]] and also (Gál, Horváth, Orbán, & Dekkers, 2009).<ref name=GHOD2009>{{cite book|last1=Gál|first1=R. I.|last2=Horváth|first2=A.|last3=Orbán|first3=G.|last4=Dekkers|first4=G.|title=PENMICRO: Monitoring pension developments through micro socioeconomic instruments based on individual data sources: feasibility study|year=2009|publisher=TARKI Social Research Institute|pages=67|url=http://ec.europa.eu/social/main.jsp?langId=en&catId=89&newsId=490&furtherNews=yes}}</ref> There are two basic types of this kind of model - (i) deterministic, which is based on best estimates of input parameters and simultaneous modelling of all statuses; and (ii) stochastic, based on random simulation of one status path for the individual concerned.
=== Deterministic Models ===
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Transfers between statuses are modelled based on random parameters (generating a random number). At one moment in time, each model point corresponds with just one status. The transfer between defined statuses depends on a random number and its comparison with the transfer probability.
One model point has exactly one random career. As a result, the insurance period and other variables occurring in the pension formula are known exactly at the point of retirement, which makes it possible to perform exact modelling of pension formula non-linearities in extreme lines, see e.g. ("Pojistné rozpravy 28/2011").<ref name=PojistneRozpravy>{{cite journal|last=Bednařík|first=Petr|title=Mikrosimulační model českého důchodového systému se stochastickými kariérami|journal=Pojistné rozpravy|year=2011|volume=28}}</ref>
The data requirements are the same as with the deterministic model (probability of transfers). If more detailed data are available, it is easy to use them and adapt the structure of the model.
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To achieve stable results, it is necessary to have a large number of model points or simulations. The more parameters are generated stochastically, the higher is the number of simulations required to ensure convergence.
== Strengths and
Strengths
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* makes it possible to use all available information and individual data (exact calculation of pensions for individuals approaching the retirement age)
* makes it possible to reflect all legislative parameters (i.e. even non-linearities, etc.)
* comprehensive outputs (non-deviated aggregate results, individual results and pensions structure, poverty indicators, for more see e.g. see (Deloitte, 2011)
* evaluation of actuarial aspects of the pension system
* can be extended to cover other social benefit systems and used as a consistent tool in creating the social policy
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There are a number of dynamic microsimulation models in various countries:
* [[Dynamic Microsimulation Model of the Czech Republic]]
* [[Pensim2]] (British Department for Work and Pensions),
* Destinie (French National Statistical Institute),
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[[Category:Pensions]]
[[Category:Microsimulation]]
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