原田が共著の論文「Income allocation to each worker in synthetic populations using basic survey on wage structure」が2017 IEEE Symposium Series on Computational Intelligence (SSCI)で出版されました．
Published in 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017
Recommended citation: Tadahiko Murata, Sho Sugiura, Takuya Harada: Income allocation to each worker in synthetic populations using basic survey on wage structure, 2017 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1-6 (2017)
原田が共著の論文「Income allocation to each worker in synthetic populations using basic survey on wage structure」が2017 IEEE Symposium Series on Computational Intelligence (SSCI)で出版されました．
In this paper, we propose a simulated-annealing based method to allocate an income attribute to each worker in synthetic populations. An income attribute is one of important attributes when microsimulations or agent-based simulations are conducted for making or examining some policy of government, enterprises or firms. We add an income attribute to workers in individual households using Basic Survey on Wage Structure in Japan. In order to add that attribute, we first prepare the synthetic populations of households with members where their sex, age, family type, role and kinship that are already determined by our previously proposed synthetic population generation method (SPGM). Then we add a working status (working or not working) and an industry type if the working status of a household member is working according to three statistics that show the relation between sex, family type, and age in a prefecture or a city using a simulated annealing based SPGM. After determining the working status and their industry, we add average monthly income to each worker in the synthesized population. To see the validity of allocated monthly income, we compare the average income of each industry in the synthesized population with the statistics of the average income of each industry that is not used in the synthesizing procedure.