• Yu Xuewen

    Associate Profe

    Applied Economi

    Add: Guoshun Road Siyuan Building Room 330, Siyuan Building

    Tel: 25011110(TEL)

    E-mail: xuewenyu@fudan.edu.cn

    Research Field: Econometrics, Empirical Macroeconomics and Finance, Financial Technology (DeFi)

    Website:

    Teacher information
    Achievements in scientific research
    Academic activities and community service

    Journal Papers


    1.Joshua C. C. Chan, Gary Koop, and Xuewen Yu2024Large order-invariant Bayesian VARs with stochastic volatilityJournal of Business & Economic Statistics 42(2) 825-837.  



    2.Mohitosh Kejriwal, Linh Nguyen, and Xuewen Yu2023Multistep forecast averaging with stochastic and deterministic trendsEconometrics 11(4) 1-43.  



    3.Yong Bao and Xuewen Yu2023Indirect inference estimation of dynamic panel data modelsJournal of Econometrics 235(2) 1027-1053.  



    4.Joshua C.C. Chan and Xuewen Yu2022Fast and accurate variational inference for large bayesian VARs with stochastic volatilityJournal of Economic Dynamics and Control 143 1-19.  



    5.Mohitosh Kejriwal, Pierre Perron, and Xuewen Yu2022A two-step procedure for testing partial parameter stability in cointegrated regression modelsJournal of Time Series Analysis 43(2) 219–237.  



    6.Mohitosh Kejriwal and Xuewen Yu2021Generalized forecast averaging in autoregressions with a near unit rootThe Econometrics Journal 24(1) 83-102.  



    7.Mohitosh Kejriwal, Xuewen Yu, and Pierre Perron2020Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time seriesJournal of Time Series Analysis 41(5) 676-690.  


    Research Projects

    2025.01—2028.12MemberDecision Tree-based Asset Heterogeneity, Regime Switching, and Uncommon Factor StructuresNational Natural Science Foundation of China

    2024.01—2026.12Principal InvestigatorThe Econometric Testing of Asset Price Bubbles: Theory and MethodsNational Natural Science Foundation of China

    2023.04—2026.03Principal InvestigatorBayesian Identification and Estimation of Large Vector Autoregression ModelsShanghai Municipal Commission of Science and Technology