| Project/Area Number |
20K01701
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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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| Review Section |
Basic Section 07040:Economic policy-related
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| Research Institution | Hiroshima Shudo University |
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Principal Investigator |
張 南 広島修道大学, 経済科学部, 教授 (20279061)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Project Status |
Granted (Fiscal Year 2022)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2022: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2021: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | Globla flow of funds / Financial network / Statistical matrix / Who-to-whom model / Financial crisis / Datasets / Shock Dynamics / Data sources / Global flow of funds / Who-to-whom matrices / Financial inflow outflow / global flow of funds / Who-to-Whom martrices / inverse of Leontief / cross-border exposures / financial networks / financial stability / データベースの整備 / 分析手法の開発 / 国際資金循環 |
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| Outline of Research at the Start |
国際的な統計整備の動きに対応し、GFF統計の理論的な枠組みと作成方法を提示する。
金融安定性の計測のため、GFF統計のストックデータとフローデータを整備する。
GFFMとFIOMという新しい統計作成手法で、「国家×国家」形式のGFFMを「部門×部門」形式のFIOMにリンクし、金融ネットワーク分析という新しい分析手法でGFF分析の視野を広げる。GFFの視座から独創的な分析手法で日米中における対外資金循環の同質性と異質性を定量的に解明する。
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| Outline of Annual Research Achievements |
This study presents a new statistical approach to measure the GFF and establishes a new statistical model based on the economic theory of the GFF. It also discusses the data sources needed to establish the GFFM and the integration of the dataset. A G20 statistical matrix based on W-t-W is established through empirical analysis; the analysis method of GFFM is discussed; and the influence and sensitivity of the G20 countries in GFF are measured. To observe the relationship between the GFFM and the sectors of the target countries, the sectoral FFSM of the G-3 economies is established using their FA and sectoral data. GFFM and FFSM are regarded as financial networks, and the network analysis method is introduced into GFF analysis.
The Statistical Template of Global Flow of Funds for a Country, which builds on prior theoretical constructs and is the core of this study, is an innovation because of its provision of an operational statistical system framework. Thus, the data contained in Table 2 make GFF a reality, connect useful metrics in Table 10, and integrate a system analysis of the GFFM and FFSM. Thus, other financial instrument matrices can be constructed to meet the needs of policymaking authorities.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
As a whole, the research on this subject has achieved the expected progress. Through my own research, as well as domestic and foreign society reports (mainly network conferences), the research results have been published in some authoritative academic journals.
However, there are still some problems. Due to the influence of the COVID-19 pandemic,I have not visited overseas research cooperation institutions during the research period, and we have not heard the opinions of relevant international institutions such as IMF on the compilation method of relevant data. Therefore, in this year, I will try to visit relevant cooperation units and international professional institutions and listen to the opinions of statistical practice expert.
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| Strategy for Future Research Activity |
This study has some limitations, which can be addressed in future studies. The accuracy of the GFF table, especially in processing reserve data, needs to be improved upon. The data of reserves are not included in the GFFM because of the mismatch of data sources. CPIS, CDIS, and LBS have their own information system, all of which can be carried out on the basis of the W-t-W matrix. However, the data of reserves are from IIP and cannot be carried out on the basis of the W-t-W matrix. Therefore, the integration and matching of data systems, that is, IIP with CPIS, CDIS, and LBS should be strengthened.
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