Monitaring of parameter chamge in economic time series model

2016 Fiscal Year Final Research Report

• Project/Area Number: 26380279
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Economic statistics
• Research Institution: Hiroshima University of Economics
• Principal Investigator: MAEKAWA Koichi 広島経済大学, 経済学研究科(研究院), 教授 (20033748)
• Research Collaborator: LEE Sangyeol National university of Seoul(ソウル国立大学), 統計学部, 教授 ; Kusdhianto Setiawan ガジャマダ大学, 経済学部, 講師 ; Amirullah Setya Hardi ガジャマダ大学, 経済学部, 講師 ; Alessio Moneta Scuola superiore, Institute of Economics, 准教授
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 独立成分分析 / 因果序列 / 非正規性 / 構造変化 / ボラティリティ / 非定常時系列 / バブル / ジャンプ過程

Outline of Final Research Achievements

The Main results of our study are as follows :　(1)Causal inference of economic variables is studied through the independent component analysis(ICA). As a result we could assign an appropriate order of variables in the structural vector autoregression (SVAR) model. This can be used to evaluate economic policy such as quantitative easing policy by Bank of Japan. (2) Statistical methods of analyzing high frequency time series data is developed. Those methods are useful for risk analysis of financial investment. (3) Financial bubble model is developed. It seems to mimic the real bubble phenomenon in Japanese Bubble period very well.

Free Research Field

計量経済学