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Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model

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  • Pettenuzzo, Davide
  • Sabbatucci, Riccardo
  • Timmermann, Allan

Abstract

Firms suspended dividend payments in unprecedented numbers in response to the outbreak of the Covid-19 pandemic. We develop a multivariate dynamic econometric model that allows dividend suspensions to affect the conditional mean, volatility, and jump probability of growth in daily industry-level dividends and demonstrate how the parameters of this model can be estimated using Bayesian Gibbs sampling methods. We find considerable heterogeneity across industries in the dynamics of daily dividend growth and the impact of dividend suspensions.

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  • Pettenuzzo, Davide & Sabbatucci, Riccardo & Timmermann, Allan, 2023. "Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1522-1541.
    • Handle: RePEc:eee:econom:v:235:y:2023:i:2:p:1522-1541
    DOI: 10.1016/j.jeconom.2022.11.008
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    Cited by:

    1. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).

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