| Project/Area Number |
16K03640
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Economic policy
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| Research Institution | Ritsumeikan University (2018-2019)
Nara Prefectual University (2016-2017) |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 労働力率 / 女性 / 地域差 / 就業時間 / 空間的自己相関 / 地域労働 / 女性就業 / パネルデータ / 経済政策 |
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| Outline of Final Research Achievements |
The purpose of this study is to investigate the causes of regional differences in female labor force participation rates (FLP) in Japan and their recent changes. The Japanese FLP by age show an “M-shaped” curve with a clear dip aged 30-39, around childbearing ages. This study analyzed the determinants of regional labor market inequalities for women using Japanese and US regional data and showed policy implications for alleviating work-life balance problems for married women with young children. The study also performed an exploratory spatial data analysis by using GIS and the data of the Japanese municipalities for different years. The findings show that regions with low FLP are spatially concentrated in large metropolitan areas with high population density. The results suggest that regional policies for increasing the FLP in large metropolitan areas are crucial for correcting the regional inequality and raising the nationwide value of FLP.
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| Academic Significance and Societal Importance of the Research Achievements |
日本の女性の年齢別労働力率はM字型を示しており、政策的にもその改善が重要な課題とされてきた。M字型労働力率カーブの底が生じる主な要因は、結婚や出産が多くなる年齢層の有配偶女性の労働力率の低さにある。そして、生産年齢人口の女性の労働力率には、地域間で大きな差があるが、地域差についての研究は現状ではまだ不十分である。女性労働力率に地域差が生じる要因がわかれば、特に労働力率の低い地域に対して、改善のための政策的な提言が可能となる。
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