Econometric Analysis of Modal Regression Models and Their Applications

• Project/Area Number: 18K01553
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 07030:Economic statistics-related
• Research Institution: Kwansei Gakuin University
• Principal Investigator: KOZUMI Hideo 関西学院大学, 経済学部, 教授 (10261273)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Project Status: Completed (Fiscal Year 2020)
• Budget Amount: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000); Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
• Keywords: ベイズ統計学 / マルコフ連鎖モンテカルロ法 / モード回帰モデル / モード回帰 / ベイズ統計 / 計量経済学

Outline of Final Research Achievements

Modal regression has gained increasing attention in recent years since it offers an important alternative to classical mean regression. Unlike mean regression, modal regression aims to explore the relationship between a response variable and its covariates. In this research project, we have developed new modal regression models and efficient simulation-based methods for analyzing economic data. The proposed methods were examined in comparison with some other existing methods, and their effectiveness were clarified via both simulated and real data sets.

Academic Significance and Societal Importance of the Research Achievements

本研究によって有用かつ実用的な計量モデルや推定方法が開発されたことにより、経済学におけるモード回帰モデルの利用が進むことが期待される。また、モード回帰分析の適用範囲は経済学だけでなく、生物学、医学、工学、天文学など多岐にわたるため、本研究の学術的波及効果は大きいと考えられる。