Estimation and inferences of structural changes in panel data models

2022 Fiscal Year Final Research Report

• Project/Area Number: 21K20121
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0107:Economics, business administration, and related fields
• Research Institution: Tokyo Metropolitan University (2022); Hitotsubashi University (2021)
• Principal Investigator: Jiang Peiyun 東京都立大学, 経営学研究科, 助教 (20906929)
• Project Period (FY): 2021-08-30 – 2023-03-31
• Keywords: structural change / panel data models / common break estimator / cross section dependence

Outline of Final Research Achievements

In this research project, I have developed new approaches for break points detection in panel data models. (1) I propose an approach to test whether the break in parameters in panels occurs at a common location across individuals. (2) I investigate the statistical properties of the change point estimators. (3) New tests for structural changes are introduced in a general and realistic panel data model, which allows for cross-sectional dependence in error terms. (4) The empirical analyses using financial and macroeconomic datasets strongly demonstrate the usefulness of the proposed methods.

Free Research Field

Econometrics

Academic Significance and Societal Importance of the Research Achievements

本研究では、パネルデータモデルにおける新たな構造変化の検定と推定手法を開発した。大規模な経済データを用いた経済政策分析に応用することで、重要な学術的意義と社会的意義を持つ。