Microsimulation. Statistical methodology and assessment of uncertainty

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dc.contributor.author Zhou, M
dc.coverage.spatial Helsinki fi
dc.date.accessioned 2013-04-15T09:38:46Z
dc.date.available 2013-04-15T09:38:46Z
dc.date.issued 2013
dc.identifier.issn 2323-9239
dc.identifier.uri http://hdl.handle.net/10138/38871
dc.description 57 pages fi
dc.description.abstract Nowadays, microsimulation method has been introduced to different fields, such as Social Science, Medicine research and Economic study. This method evaluates the effects of the proposed interventions or policies before they are implemented in the real world. In this article, I concentrate on microsimulation method used in Social Science by firstly explaining two main streams in microsimulation world, Static approach and Dynamic approach, in them, how statistical models are used are carefully explained by giving examples in Dynamic approach. In the following section, a Norwegian case is studied, this case gives the typical example of how the dynamic microsimulation used in the labor force and child care research, the effects of four different reform options are measured in this study. In the last section, the empirical study of a Finnish static microsimulation model (JUTTA) is carried out. The uncertainty of JUTTA is assessed and one of its sub model called Toimtuki (income-related supplementary benefit) is detected to have space to be more accurate. In order to do so, two statistical models - Linear Regression model and Two-Stage Least Squares (2SLS) model - are applied to it. From their results and diagnostics, we could conclude that both the Linear Regression and 2SLS successfully improves the accuracy of TOIMTUKI to some extent. fi
dc.language.iso Englanti fi
dc.publisher Kela fi
dc.relation.ispartofseries Working papers 44 fi
dc.title Microsimulation. Statistical methodology and assessment of uncertainty fi
dc.type Nettityöpapereita ja nettiartikkeleita fi

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