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PhD Defense Mr. B. Zhou, MSc

Title: Semiparametric Inference for non-LAN Models
Supervisor: Prof. B.J.M. Werker
Co-supervisor: Dr. I.G. Becheri

This thesis consists of three essays in theory of econometrics and statistics, focusing on the issue of semiparametric efficiency in non-LAN (Locally Asymptotically Normality) models. The first essay starts with a univariate case of the unit root testing problem, of which the limit experiment is of the LABF (Locally Asymptotically Brownian Functional) model. A novel approach is designed for developing the semiparametric power envelope and a family of rank-based tests that are semiparametrically efficient is proposed. The second essay generalizes the approach to all LAQ (Locally Asymptotically Quadratic) models. Moreover, it expands the rank statistics in a unique way from the univariate case to the multivariate case. Using these results, in the third essay, the semiparametric power envelop of all invariant tests for stock return predictability is developed. And subsequently, a new family of tests that are more efficient than the existing ones is proposed.

Bo Zhou (Hebei, China, 1989) graduated from Shanghai Jiao Tong University (Shanghai, China) in 2011, with a Bachelor degree in Physics. He then pursued graduate studies in Tilburg University and obtained a Research Master degree in Economics in 2013. Afterward, he joined the Department of Econometric as a Ph.D. student, from 2013 to 2017.

Location: Cobbenhagen building, Auditorium (access via Koopmans building)

Order the PhD thesis

When: 06 December 2017 10:00

Where: Route description Tilburg University campus