Bayesian shape-restricted functional regression with application to economic data
| Project/Area Number |
18K12754
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 07030:Economic statistics-related
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| Research Institution | Chiba University |
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Principal Investigator |
Kobayashi Genya 千葉大学, 大学院社会科学研究院, 准教授 (00725103)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| 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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| Keywords | ベイズ統計学 / 状態空間モデル / 分位点回帰モデル / 空間統計 / 所得分布 / ロレンツ曲線 / ベイズ計量経済学 / 分位点 / 非線形回帰 |
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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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| Academic Significance and Societal Importance of the Research Achievements |
関数の形状に制約がある事前情報がある場合，それを適切にモデルに反映させることで柔軟性を保ちつつより効率的にモデルの推定を行うことができるようになった．本研究の意義は回帰モデルにおける非線形関数の推定にとどまらず，ロレンツ曲線やSIRモデルなどといった関数あるいは方程式の解に形状制約があるものに対して状態空間モデルを構築することで，現実のデータのばらつきを許容・捕捉キャプチャーできるようになり，また時点感・空間上で情報を借り合うことでモデルをより安定的に推定し，将来の予測を行えるようになった．
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Report
(4 results)
Research Products
(15 results)
