Model Checks for Marginal Effects in Proportional Hazard Models


10:00 AM - 11:00 AM



  • Time: 10:00-11:00AM
  • Date: Wednesday, December 6, 2023
  • Venue: MB341


Proportional hazard models have wide applications in finance and economics. They are semiparametric models that include two parts: the unspecified nonparametric baseline hazard is flexible and the parametric part allows regression analysis of lifetime variables. The article considers a specification test of the parametric part of proportional hazard models, which determines the covariate effects. The test is based on a CUSUM process of the martingale residuals. We develop Principal Component Decomposition of the process, where the components, which are asymptotically independent standard normal variables, provide a basis for different types of tests that specialized in certain directions. The omnibus Cramer-von Mises test, which is the squared L2-norm of the CUSUM process, turns out to have an orthogonal representation as a weighted sum of chi-square variables asymptotically. Smooth tests that based on a few components are also constructed to improve the efficiency. Finite sample performance of the proposed tests is illustrated through Monte Carlo experiments.


Dr. Rui Cui earned a Bachelor's degree in Mathematics from Sun Yat-sen University in 2010 and a Master’s degree in Economics from Xiamen University in 2013. She then received a Doctorate in Economics from Universidad Carlos III de Madrid in 2019, under the guidance of Professor Miguel A. Delgado. Since 2019, she has served as an Assistant Professor at the Faculty of Economics and Management at East China Normal University. Her primary research areas include theoretical and applied econometrics, survival analysis, and semi- and non-parametric models.

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