研究者
J-GLOBAL ID:201901008131004490
更新日: 2025年01月18日
山形 孝志
Yamagata Takashi
所属機関・部署:
職名:
特任教授
競争的資金等の研究課題 (5件):
- 2021 - 2025 不完全情報の行動マクロ経済学
- 2020 - 2025 経済停滞と格差拡大:世界経済の危機と統一マクロ理論の構築
- 2021 - 2024 反実仮想実験による炭素価格付加政策の排出削減効果と世界経済への影響の分析
- 2020 - 2023 ファクターモデルと罰則化法を用いた時系列・パネルデータの計量分析:理論と応用
- 2018 - 2022 時空間相関した動学パネルデータモデル統計的推計手法開発とその応用
論文 (24件):
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Yoshimasa Uematsu, Takashi Yamagata. Discovering the Network Granger Causality in Large Vector Autoregressive Models. Journal of the American Statistical Association. 2025. 1-23
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M Hashem Pesaran, Takashi Yamagata. Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities. Journal of Financial Econometrics. 2023. 22. 2. 407-460
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Yoshimasa Uematsu, Takashi Yamagata. Inference in Sparsity-Induced Weak Factor Models. Journal of Business & Economic Statistics. 2023. 41. 1. 126-139
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Yoshimasa Uematsu, Takashi Yamagata. Estimation of Sparsity-Induced Weak Factor Models. Journal of Business & Economic Statistics. 2023. 41. 1. 213-227
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Guowei Cui, Vasilis Sarafidis, Takashi Yamagata. IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude Toward Risk. Econometrics Journal. 2022. 26. 2. 124-146
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講演・口頭発表等 (7件):
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Discovering the network Granger causality in large vector autoregressive models
(Maastricht-York econometrics workshop 2022)
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Discovering the network Granger causality in large VAR models
(Recent Developments in Spatial Econometrics 2022)
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Discovering the Network Granger Causality in Large Vector Autoregressive Models
(応用統計ワークショップ 2022)
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Linear Panel Regression Models with Non-Classical Measurement Errors: An Application to Investment Equations
(Data Science Workshop 2022)
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A robust approach to slope heterogeneity in linear models with interactive effects for large panel data
(International Conference on Econometrics and Statistics 2022)
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