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Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Comment

Author

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  • Bonaccolto, Giovanni
  • Caporin, Massimiliano
  • Iacopini, Matteo

Abstract

In this article, we provide a comment on the work of Dai et al. (2023), who introduced the Time-Varying Parameters Quantile Vector Auto Regressive model (TVP-QVAR) to analyze the spillovers between high carbon emission stocks, green bonds, and crude oil. We argue that some peculiar results provided in the study cited above are due to a mismatch between the methodology presented by the authors and the code used to conduct the empirical analysis. We empirically support our claims by applying an approximate methodology to the data shared by Dai et al. (2023).

Suggested Citation

  • Bonaccolto, Giovanni & Caporin, Massimiliano & Iacopini, Matteo, 2024. "Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Comment," Energy Economics, Elsevier, vol. 132(C).
    • Handle: RePEc:eee:eneeco:v:132:y:2024:i:c:s0140988324001774
    DOI: 10.1016/j.eneco.2024.107469
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    More about this item

    Keywords

    Quantile VAR; Time-varying parameters; Kalman filter; Starting values;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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