| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Outline of Final Research Achievements |
This project considered Bayesian analysis for shape-restricted functional models, particularly, nonlinear quantile regression models, state space SIR model and Lorenz curves, and applied the proposed approaches to some important economic problems, such as female labour, income inequality, and urgent social and economic problem of the spread of COVID-19 and its prediction. Various approaches to introducing shape restriction were considered, for example, Gaussian process, differential equations, parametric families of functions. Centred on those shape-restricted functions, flexible models based on state space models, hierarchical models, nonparametric Bayes models were considered. As related studies, the model for spatial income distributions and mixture model with both flexibility and estimation stability were also considered.
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