Foundations and applications of statistics for nonlinear nonstationary stochastic processes

2017 Fiscal Year Final Research Report

• Project/Area Number: 16H06836
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Single-year Grants
• Research Field: Economic statistics
• Research Institution: Shinshu University
• Principal Investigator: Yabe Ryota 信州大学, 学術研究院社会科学系, 講師 (60779164)
• Project Period (FY): 2016-08-26 – 2018-03-31
• Keywords: 時系列解析 / 非定常 / ノンパラメトリック統計学 / セミパラメトリック統計学

Outline of Final Research Achievements

Macroeconomic data such as GDP and interest rate has been considered to have stochastic trend, which is represented by a nonstationary process such as unit root and long memory process in Econometrics. To analyze nonlinear relationship between multiple economic data, the non/semi parametric nonstationary regression model is often applied. To study various nonstationary semiparametric model, we have provided asymptotic theory about a kernel function such as its uniform convergence rate and asymptotic distribution.

Free Research Field

経済統計