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Trending Time Series Models with Endogeneity

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thesis
posted on 19.02.2020 by LI CHEN
The thesis explores the endogeneity problem in the trending regression models. I propose a nonparametric control function method and a bias-correction method to deal with this problem in the weak and strong trending time series regression models respectively. I have proved that the proposed estimators for the coefficients are unbiased and consistent so that the economists are able to obtain accurate estimates and reliable inferences for the trending time series regression models.

History

Campus location

Australia

Principal supervisor

Jiti Gao

Additional supervisor 1

Farshid Vahid

Additional supervisor 2

David Harris

Year of Award

2017

Department, School or Centre

Econometrics and Business Statistics

Course

Doctor of Philosophy

Degree Type

Doctorate

Faculty

Faculty of Business and Economics

Exports

Exports