Grouped Change-Points Detection and Estimation in Panel Data

Haoran Lu and Dianpeng Wang ()
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Haoran Lu: The School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China
Dianpeng Wang: The School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China

Mathematics, 2024, vol. 12, issue 5, 1-20

Abstract: The change-points in panel data can be obstacles for fitting models; thus, detecting change-points accurately before modeling is crucial. Extant methods often either assume that all panels share the common change-points or that grouped panels have the same unknown parameters. However, the problem of different change-points and model parameters between panels has not been solved. To deal with this problem, a novel approach is proposed here to simultaneously detect and estimate the grouped change-points precisely by employing an iterative algorithm and the penalty cost function. Some numerical experiments and case studies are utilized to demonstrate the superior performance of the proposed method in grouping the panels, and estimating the number and positions of change-points.

Keywords: grouped change-point; integer programming; penalty cost function; panel data (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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