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Does inequality help in forecasting equity premium in a panel of G7 countries?

Author

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  • Christina Christou
  • Rangan Gupta
  • Fredj Jawadi

    (LUMEN - Lille University Management Lab - ULR 4999 - Université de Lille)

Abstract
This paper investigates whether the post-tax and transfer growth rate in the Gini index can help in forecasting the equity premium in the G7 countries (Canada, France, Germany, Italy, Japan, United Kingdom (UK), and United States (US)). To this end, we use a panel data-based predictive framework, which controls for heterogeneity, cross-sectional dependence, persistence and endogeneity. When we analyze the annual out-of-sample period of 1990–2011, given an in-sample period of 1967–1989, our results show that: (a) Time series based predictive regression models fail to beat the benchmark of historical average, except for Italy; and, (b) the panel data models beat the benchmark in a statistically significant fashion for all the seven countries. Further, our results highlight the importance of pooling information when trying to forecast excess stock returns based on a measure of inequality.
(This abstract was borrowed from another version of this item.)

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  • Christina Christou & Rangan Gupta & Fredj Jawadi, 2021. "Does inequality help in forecasting equity premium in a panel of G7 countries?," Post-Print hal-04478772, HAL.
    • Handle: RePEc:hal:journl:hal-04478772
    DOI: 10.1016/j.najef.2021.101456
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    Cited by:

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    3. Sergey Dianov & Lyudmila Koroleva & Natalia Pokrovskaia & Natalia Victorova & Andrey Zaytsev, 2022. "The Influence of Taxation on Income Inequality: Analysis of the Practice in the EU Countries," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    4. Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
    5. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
    6. Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
    7. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta & Riza Demirer, 2022. "Forecasting stock market (realized) volatility in the United Kingdom: Is there a role of inequality?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2146-2152, April.
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    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G1 - Financial Economics - - General Financial Markets

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