Open AccessCurrent Development in Microsimulation and Experimental Innovation method in JUTTA Model
Author(s) -
Meng Zhou,
Yuting Men,
Xuwen Qing
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1865/4/042136
Subject(s) - microsimulation , ordinary least squares , computer science , econometrics , linear regression , regression analysis , linear model , industrial engineering , operations research , machine learning , economics , engineering , transport engineering
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, we will concentrate on microsimulation method used in Social Science by firstly explaining two main streams in microsimulation world, Static approach and Dynamic approach. In the following section, the uncertainty of a Finnish static microsimulation model JUTTA is assessed and Toimtuki model, one of the sub-models in JUTTA is detected to have space to be more accurate. In order to do so, two experimental statistical models-Linear Regression model and Two-Stage Least Squares(2SLS) model are applied to it. From the results, we could conclude that both the Linear Regression and 2SLS successfully improves the accuracy of TOIMTUKI to some extent.