Dr. L. (Lina) Zhang
Lina Zhang is an Assistant Professor in the Quantitative Economics Section at University of Amsterdam, The Netherlands. My primary research interests include the identification and inference problems in studying treatment effects and program evaluation.
Faculty of Economics and Business
Section Quantitative Economics
Visiting address
- Roetersstraat 11
Postal address
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Postbus 15867
1001 NJ Amsterdam
Contact details
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Publications
2024
- Tommasi, D., & Zhang, L. (2024). Bounding Program Benefits When Participation Is Misreported. Journal of Econometrics, 238(1).
2017
- Chu, CSJ., Liu, N., & Zhang, L. (2017). Significance test in nonstationary logit panel model with serially correlated dependent variable. Economics Letters. https://www.sciencedirect.com/science/article/pii/S0165176517302835
2016
- Chu, CSJ., Liu, N., & Zhang, L. (2016). Significance test in nonstationary multinomial logit model. Economics Letters. https://www.sciencedirect.com/science/article/pii/S0165176517302835
2021
- Frazier, D. T., Renault, E., Zhang, L., & Zhao, X. (2021). Weak Identification in Discrete Choice Models. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2011.06753
- Lin, A. (Author), Tommasi, D. (Author), & Zhang, L. (Author). (2021). Bounding Program Benefits When Participation is Misreported with Stata. Manuscript submitted for publication. Web publication or website https://drive.google.com/file/d/1omTo4XifzO9HpzSc0um4bMXhNgg1N5vI/view
Zhang, L., Frazier, D. T., Poskitt, D. S., & Zhao, X. (2021). Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2009.02642 [details]
2020
- Zhang, L. (2020). Spillovers of Program Benefits with Mismeasured Networks: Job Market Paper. https://drive.google.com/file/d/1g4dxO_r4FkIF4GuXsd3obQZI5ix0Y9Yr/view
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Ancillary activities
No ancillary activities
Zhang, L., Frazier, D. T., Poskitt, D. S., & Zhao, X. (2021). Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects. (v2 ed.) ArXiv.