Statistics seminar 2016: "New Distribution Theory for the Estimation of Structural Break Point in Mean"

Si comunica che il seminario è stato annullato

  • Data: 26 ottobre 2016 dalle 14:30 alle 16:30

  • Luogo: Dipartimento di Scienze Statistiche "P. Fortunati" - Via Belle Arti 41 - Aula Seminari 1° piano

Prof. Jun Yu
(Singapore Management University)

Based on the Girsanov theorem, this paper first obtains the exact distribution of the maximum likelihood estimator of structural break point in a continuous time model. The exact distribution is asymmetric and trimodal, indicating that the estimator is seriously biased. These two properties are also found in the finite sample distribution of the least squares estimator of structural break point in the discrete time model. The paper then builds a continuous time approximation to the discrete time model and develops an infill asymptotic theory for the least squares estimator. The obtained infill asymptotic distribution is asymmetric and trimodal and delivers good approximations to the infinite sample distribution. In order to reduce the bias in the estimation of both the continuous time model and the discrete time model, a simulation-based method based on the indirect estimation approach is proposed. Monte Carlo studies show that the indirect estimation method achieves substantial bias reductions. However, since the binding function has a slope less than one, the variance of the indirect estimator is larger than that of the original estimator.

(joint with Liang Jiang and Xiaohu Wang)

Contact person
Giuseppe Cavaliere