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Forecasting dividend growth: The role of adjusted earnings yield

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  • Yu, Deshui
  • Huang, Difang
  • Chen, Li
  • Li, Luyang

Abstract

This paper revisits the predictability of dividend growth. Motivated by the dividend partial adjustment model, we decompose the earnings yield into smoothing and residual components. The residual component reflects the variations in the forecast of dividend dynamics and thus forms a powerful predictor of dividend growth. Empirically, the proposed predictor shows significant in-sample predictive power for aggregate dividend growth at both monthly and annual frequencies over several forecast horizons. The regression results are robust to dividend reinvestment strategies and economic status. More importantly, the proposed predictor contains significant out-of-sample predictability, outperforming the historical mean benchmark and a list of popularly used financial and macroeconomic predictors in the literature.

Suggested Citation

  • Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
  • Handle: RePEc:eee:ecmode:v:120:y:2023:i:c:s0264999322004254
    DOI: 10.1016/j.econmod.2022.106188
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    Cited by:

    1. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
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    More about this item

    Keywords

    Cash flow; Dividend smoothing; Present-value model; Out-of-sample forecasting;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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