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Robust Two-Stage Estimation in General Spatial Dynamic Panel Data Models

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Abstract

This paper proposes a robust two-stage estimation procedure for a general spatial dynamic panel data model in light of the two-stage estimation procedure in Jin, et al. (2020). The authors replace the least squares estimation in the first stage of Jin, et al. (2020) by M-estimation. The authors also provide the justification for not making any change in its second stage when the number of time periods is large enough. The proposed methodology is robust and efficient, and it can be easily implemented. In addition, the authors study the limiting behavior of the parameter estimators, which are shown to be consistent and asymptotic normally distributed under some conditions. Extensive simulation studies are carried out to assess the proposed procedure and a COVID-19 data example is conducted for illustration.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, York University, Toronto, Ontario, M3J 1P3, Canada

    Hao Ding & Yuehua Wu

  2. Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, 230026, China

    Baisuo Jin

Authors
  1. Hao Ding
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  2. Baisuo Jin
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  3. Yuehua Wu
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Corresponding author

Correspondence to Hao Ding.

Ethics declarations

JIN Baisuo is an editorial board member for Journal of Systems Science & Complexity and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

Additional information

This research was supported by the Natural Sciences and Engineering Research Council of Canada under Grant No. RGPIN-2017-05720, the National Natural Science Foundation under Grant Nos. 12201601, 71873128, 11571337, 71631006, and 71921001, the Anhui Provincial Natural Science Foundation under Grant No. 2208085QA06.

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Ding, H., Jin, B. & Wu, Y. Robust Two-Stage Estimation in General Spatial Dynamic Panel Data Models. J Syst Sci Complex 36, 2580–2604 (2023). https://doi.org/10.1007/s11424-023-2172-2

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  • DOI: https://doi.org/10.1007/s11424-023-2172-2

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