1992 …2024

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  • 2023

    Using machine learning methods to estimate the gender wage gap

    Forshaw, R. J., Iakovlev, V., Schaffer, M. E. & Tealdi, C., 1 Feb 2023, (Accepted/In press) 16th International Conference of Thailand Econometric Society. Springer, (Machine Learning for Econometrics and Related Topics).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 2022

    An Introduction to Stacking Regression for Economists

    Ahrens, A., Ersoy, E., Iakovlev, V., Li, H. & Schaffer, M. E., 30 Jul 2022, Credible Asset Allocation, Optimal Transport Methods, and Related Topics. TES 2022. Springer, p. 7-29 23 p. (Studies in Systems, Decision and Control; vol. 429).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    2 Citations (Scopus)
    263 Downloads (Pure)
  • Practical Steps to Improve Specification Testing

    Nichols, A. & Schaffer, M. E., 2022, Prediction and Causality in Econometrics and Related Topics. Ngoc Thach, N., Ha, D. T., Trung, N. D. & Kreinovich, V. (eds.). Springer, p. 75-88 14 p. (Studies in Computational Intelligence; vol. 983).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    1 Citation (Scopus)
    177 Downloads (Pure)
  • 2021

    Using Machine Learning Methods to Support Causal Inference in Econometrics

    Ahrens, A., Aitken, C. & Schaffer, M. E., 2021, Behavioral Predictive Modeling in Economics. Springer, p. 23-52 30 p. (Studies in Computational Intelligence; vol. 897).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
    2 Citations (Scopus)
    673 Downloads (Pure)