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Economic Scenario Generator And Parameter Uncertainty: A Bayesian Approach

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  • Bégin, Jean-François

Abstract

In this article, we study parameter uncertainty and its actuarial implications in the context of economic scenario generators. To account for this additional source of uncertainty in a consistent manner, we cast Wilkie’s four-factor framework into a Bayesian model. The posterior distribution of the model parameters is estimated using Markov chain Monte Carlo methods and is used to perform Bayesian predictions on the future values of the inflation rate, the dividend yield, the dividend index return and the long-term interest rate. According to the US data, parameter uncertainty has a significant impact on the dispersion of the four economic variables of Wilkie’s framework. The impact of such parameter uncertainty is then assessed for a portfolio of annuities: the right tail of the loss distribution is significantly heavier when parameters are assumed random and when this uncertainty is estimated in a consistent manner. The risk measures on the loss variable computed with parameter uncertainty are at least 12% larger than their deterministic counterparts.

Suggested Citation

  • Bégin, Jean-François, 2019. "Economic Scenario Generator And Parameter Uncertainty: A Bayesian Approach," ASTIN Bulletin, Cambridge University Press, vol. 49(2), pages 335-372, May.
  • Handle: RePEc:cup:astinb:v:49:y:2019:i:02:p:335-372_00
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