- 学术相关
- CCP estimation of dynamic discrete choice demand models with segment level data and continuous unobserved heterogeneity: rethinking EV subsidies vs. Infrastructure
- Scaling and network evolution of technology transfer in US cities
- Difference-in-differences designs: a practitioner’s guide
- VAR变体
- Anticipating critical transitions
学术相关
CCP estimation of dynamic discrete choice demand models with segment level data and continuous unobserved heterogeneity: rethinking EV subsidies vs. Infrastructure 1
Scaling and network evolution of technology transfer in US cities 2
Difference-in-differences designs: a practitioner’s guide 3
VAR变体
Anticipating critical transitions 4
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Chou, C., & Derdenger, T. (2025). CCP estimation of dynamic discrete choice demand models with segment level data and continuous unobserved heterogeneity: Rethinking EV subsidies vs. Infrastructure. Marketing Science, mksc.2024.860. https://doi.org/10.1287/mksc.2024.0860 ↩
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Li, Q., Du, D., & Yu, Y. (2025). Scaling and network evolution of technology transfer in US cities. Nature Cities, 2(4), 316–326. https://doi.org/10.1038/s44284-025-00209-x ↩
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Baker, A., Callaway, B., Cunningham, S., Goodman-Bacon, A., & Sant’Anna, P. H. C. (2025). Difference-in-differences designs: A practitioner’s guide (No. arXiv:2503.13323). arXiv. https://doi.org/10.48550/arXiv.2503.13323 ↩
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Scheffer, M., Carpenter, S. R., Lenton, T. M., Bascompte, J., Brock, W., Dakos, V., Van De Koppel, J., Van De Leemput, I. A., Levin, S. A., Van Nes, E. H., Pascual, M., & Vandermeer, J. (2012). Anticipating critical transitions. Science, 338(6105), 344–348. https://doi.org/10.1126/science.1225244 ↩