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Zhan Gao

Personal Details

First Name:Zhan
Middle Name:
Last Name:Gao
Suffix:
RePEc Short-ID:pga1364
https://zhan-gao.github.io/
Terminal Degree:2025 Department of Economics; University of Southern California (from RePEc Genealogy)

Affiliation

Department of Economics
Southern Methodist University

Dallas, Texas (United States)
http://www.smu.edu/economics/
RePEc:edi:desmuus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Zhan Gao & Hyungsik Roger Moon, 2024. "Robust Estimation of Regression Models with Potentially Endogenous Outliers via a Modern Optimization Lens," Papers 2408.03930, arXiv.org.
  2. Zhan Gao & Ji Hyung Lee & Ziwei Mei & Zhentao Shi, 2024. "Econometric Inference for High Dimensional Predictive Regressions," Papers 2409.10030, arXiv.org, revised Nov 2024.
  3. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and Estimation of Categorical Random Coefficient Models," Papers 2302.14380, arXiv.org.
  4. Ji Hyung Lee & Zhentao Shi & Zhan Gao, 2018. "On LASSO for Predictive Regression," Papers 1810.03140, arXiv.org, revised Feb 2021.
  5. Zhan Gao & Zhentao Shi, 2018. "Implementing Convex Optimization in R: Two Econometric Examples," Papers 1806.10423, arXiv.org, revised Aug 2019.

Articles

  1. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
  2. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
  3. Zhan Gao & Zhentao Shi, 2021. "Implementing Convex Optimization in R: Two Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1127-1135, December.

Chapters

  1. Zhan Gao & M. Hashem Pesaran, 2024. "Identification and estimation of categorical random coefficient models," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 79-124, Springer.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and Estimation of Categorical Random Coefficient Models," Papers 2302.14380, arXiv.org.

    Cited by:

    1. Pablo Rodriguez & Mauricio Sarrias, 2025. "Instrumental variable estimation with observed and unobserved heterogeneity of the treatment and instrument effect: a latent class approach," Empirical Economics, Springer, vol. 68(2), pages 879-914, February.

  2. Ji Hyung Lee & Zhentao Shi & Zhan Gao, 2018. "On LASSO for Predictive Regression," Papers 1810.03140, arXiv.org, revised Feb 2021.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    2. Marie Levakova & Susanne Ditlevsen, 2024. "Penalisation Methods in Fitting High‐Dimensional Cointegrated Vector Autoregressive Models: A Review," International Statistical Review, International Statistical Institute, vol. 92(2), pages 160-193, August.
    3. Campeanu Emilia Mioara & Boitan Iustina Alina & Anghel Dan Gabriel, 2023. "Student engagement and academic performance in pandemic-driven online teaching: An exploratory and machine learning approach," Management & Marketing, Sciendo, vol. 18(s1), pages 315-339, December.
    4. Shaobo Li & Ben Sherwood, 2025. "Quantile Predictions for Equity Premium using Penalized Quantile Regression with Consistent Variable Selection across Multiple Quantiles," Papers 2505.16019, arXiv.org.
    5. Mei, Ziwei & Shi, Zhentao, 2024. "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, vol. 242(2).
    6. Fan, Rui & Lee, Ji Hyung & Shin, Youngki, 2023. "Predictive quantile regression with mixed roots and increasing dimensions: The ALQR approach," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Ziwei Mei & Zhentao Shi, 2022. "On LASSO for High Dimensional Predictive Regression," Papers 2212.07052, arXiv.org, revised Jan 2024.
    8. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    9. Etienne Wijler, 2022. "A restricted eigenvalue condition for unit-root non-stationary data," Papers 2208.12990, arXiv.org.
    10. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    11. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    12. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    13. Yanqing Yang & Nan Zhang & Jinfeng Ge & Yan Xu, 2025. "Sino-US S and T Frictions and Transnational Knowledge Flows: Evidence from machine learning and cross-national patent data," Papers 2503.21822, arXiv.org.
    14. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de Economía.
    15. Ben Jabeur, Sami & Bakkar, Yassine & Cepni, Oguzhan, 2025. "Do global COVOL and geopolitical risks affect clean energy prices? Evidence from explainable artificial intelligence models," Energy Economics, Elsevier, vol. 141(C).
    16. David Neto, 2023. "Penalized leads-and-lags cointegrating regression: a simulation study and two empirical applications," Empirical Economics, Springer, vol. 65(2), pages 949-971, August.
    17. Julien Hambuckers & Li Sun & Luca Trapin, 2023. "Measuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors," Papers 2301.01362, arXiv.org.
    18. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.

Articles

  1. Zhan Gao & M. Hashem Pesaran, 2023. "Identification and estimation of categorical random coefficient models," Empirical Economics, Springer, vol. 64(6), pages 2543-2588, June.
    See citations under working paper version above.
  2. Lee, Ji Hyung & Shi, Zhentao & Gao, Zhan, 2022. "On LASSO for predictive regression," Journal of Econometrics, Elsevier, vol. 229(2), pages 322-349.
    See citations under working paper version above.Sorry, no citations of articles recorded.

Chapters

  1. Zhan Gao & M. Hashem Pesaran, 2024. "Identification and estimation of categorical random coefficient models," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 79-124, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (6) 2018-07-16 2018-11-05 2022-04-25 2022-06-13 2024-09-16 2024-10-14. Author is listed
  2. NEP-DCM: Discrete Choice Models (3) 2022-04-25 2022-06-13 2023-03-20. Author is listed
  3. NEP-ETS: Econometric Time Series (2) 2018-11-05 2024-10-14. Author is listed
  4. NEP-BIG: Big Data (1) 2018-07-16
  5. NEP-IPR: Intellectual Property Rights (1) 2024-10-14
  6. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2022-06-13
  7. NEP-ORE: Operations Research (1) 2022-04-25

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