Rate My Professor Wei Wei
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Makes even hard topics easy to grasp.
Encourages creative and innovative thinking.
Makes even hard topics easy to grasp.
Always patient and encouraging to students.
Inspires curiosity and a thirst for knowledge.
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About Wei
Dr. Wei Wei is a Senior Lecturer in the Department of Econometrics and Business Statistics at Monash Business School, Monash University. His research specializations encompass financial econometrics, Bayesian econometrics, and energy economics. This work relates to United Nations Sustainable Development Goals such as SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), SDG 8 (Decent Work and Economic Growth), and SDG 13 (Climate Action).
Wei Wei is Chief Investigator and Primary Chief Investigator on the project 'New methods for modelling complex trends in climate and energy time series,' from 3 August 2020 to 30 June 2026, in collaboration with Heather M. Anderson, Jiti Gao, Farshid Vahid-Araghi, Peter C. B. Phillips, Oliver B. Linton, and Anders Lunde. His major publications include 'Does climate sensitivity differ across regions? A varying–coefficient approach' (with H. M. Anderson, J. Gao, F. Vahid, Y. Yang; 2025; Journal of Business and Economic Statistics); 'Energy transition and climate policy selection with stochastic demand: evidence from Australian electricity generation expansion planning' (with X. Sun, H. M. Anderson, X. Zhang; 2025; Energy Economics, 146); 'A stochastic price duration model for estimating high-frequency volatility' (with D. Pelletier; 2024; Journal of Financial Econometrics, 22(5), 1372-1396); 'Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach' (with H. M. Anderson, J. Gao, G. Turnip, F. Vahid; 2023; Energy Economics, 125); and 'Identifying risk factors and their premia: a study on electricity prices' (with A. Lunde; 2023; Journal of Financial Econometrics, 21(5), 1647-1679). These contributions demonstrate impact in econometrics and energy economics through advanced modeling for policy and market analysis.