Sheng Dai

Postdoctoral researcher at University of Turku

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Sheng Dai | Postdoctoral researcher at University of Turku

Google Scholar: 499 Citations; h-index: 7; i10-index: 6.

Articles

  1. Liao, Z., Dai, S.*, & Kuosmanen T. 2023. Convex Support Vector Regression. European Journal of Operational Research, In Press.

  2. Dai, S., Kuosmanen, T. & Zhou, X. 2023. Generalized quantile and expectile properties for shape constrained nonparametric estimation. European Journal of Operational Research, 310, 914-927.

  3. Kuosmanen, T., Tan, Y. & Dai, S. 2023. Performance analysis of English hospitals during the first and second waves of the coronavirus pandemic. Health Care Management Science, In Press.

  4. Dai, S. 2023. Variable selection in convex quantile regression: L1-norm or L0-norm regularization? European Journal of Operational Research, 305, 338-355.

  5. Yi, J., Dai, S., Cheng, J., Wu, Q. & Liu, K. 2021. Production quota policy in China: Implications for sustainable supply capacity of critical minerals. Resources Policy, 72, 102046.

  6. Dai, S., Zhou, X. & Kuosmanen, T. 2020. Forward-looking assessment of the GHG abatement cost: Application to China. Energy Economics, 88, 104758.

  7. Kuosmanen, T., Zhou, X. & Dai, S. 2020. How much climate policy has cost for OECD countries? World Development, 125, 104681.

  8. Cheng, J., Yi, J., Dai, S. & Xiong, Y. 2019. Can low-carbon city construction facilitate green growth? Evidence from China’s pilot low-carbon city initiative. Journal of Cleaner Production, 231, 1158-1170. [ESI top 1%; Highly cited paper]

  9. Dai, Q., Ye, X., Wei, Y.D., Ning, Y. & Dai, S. 2018. Geography, ethnicity and regional inequality in Guangxi Zhuang autonomous region, China. Applied Spatial Analysis and Policy, 11, 557-580.

  10. Chen, J., Cheng, J. & Dai, S. 2017. Regional eco-innovation in China: An analysis of eco-innovation levels and influencing factors. Journal of Cleaner Production, 153, 1-14.

  11. Cheng, J., Dai, S.* & Ye, X. 2016. Spatiotemporal heterogeneity of industrial pollution in China. China Economic Review, 40, 179-191.

Preprints

  1. Dai, S., Kuosmanen, T., & Zhou, X. 2022. Non-crossing convex quantile regression. arXiv:2204.01371.

  2. Dai, S., Fang, Y.H., Lee, C.Y. & Kuosmanen, T. 2021. pyStoNED: A Python package for convex regression and frontier estimation. arXiv:2109.12962.

Technical reports

  1. Kuosmanen, T., Kuosmanen, N., & Dai, S. 2022. Kohtuullinen muuttuva kustannus sähkön jakeluverkkoyhtiöiden valvontamallissa: Ehdotus tehostamiskannustimen kehittämiseksi 6. ja 7. valvontajaksoilla vuosina 2024-2031. Energiavirasto, Finland.

  2. Dai, S., Kuosmanen, N., Kuusi, T., Kuosmanen, T. (Editor), Liesiö, J., & Maczulskij, T. 2022. Misallocation of labor and capital in Finland’s business sector. Prime Minister’s Office of Finland.

Thesis

  1. Dai, S. 2022. Essays on Convex Regression and Frontier Estimation. Aalto University publication series DOCTORAL THESES, 111/2022.