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Panel Interval-Valued Data Nonlinear Regression Models and Applications

Author

Listed:
  • Ai-bing Ji

    (Hebei University)

  • Qing-qing Li

    (Hebei University)

  • Jin-jin Zhang

    (Hebei University)

Abstract

Panel data models have become increasingly popular in economic research and data analysis. Considering the uncertainty and variability of panel data, based on support vector regression, we propose robust estimations of some fixed effects panel interval-valued data models: nonlinear model, a special case of nonlinear model and nonlinear model with mathematical coherence. Monte Carlo simulations are used to evaluate the performance and robustness of our proposed models. The proposed models are applied to real datasets for stock price prediction, and experimental results demonstrate the excellent fitting and forecasting performance of our proposed models.

Suggested Citation

  • Ai-bing Ji & Qing-qing Li & Jin-jin Zhang, 2024. "Panel Interval-Valued Data Nonlinear Regression Models and Applications," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2413-2435, October.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:4:d:10.1007_s10614-023-10519-8
    DOI: 10.1007/s10614-023-10519-8
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