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The Implications of Parameter Uncertainty for Medium-Term Fiscal Planning

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  • Douglas Hostland
  • David Dupuis

Abstract

Most existing studies on medium-term fiscal planning focus on a single source of uncertainty, which is captured by including additive random error terms in stochastic simulation models. The fiscal authority in these models plans its budget with complete knowledge of the structure of the economy, including the parameters. Abstracting from parameter uncertainty greatly simplifies stochastic simulation experiments, but could lead to misleading policy conclusions for reasons given by Brainard (1967). This paper investigates how parameter uncertainty influences the results obtained from stochastic simulation studies on medium-term fiscal planning. We compare simulation results obtained from two kinds of stochastic simulation experiments. In the conventional stochastic simulation framework, the fiscal authority faces uncertainty from a single source - additive error terms. In the other stochastic simulation framework, the fiscal authority also involves uncertainty about the parameters of the model. Our results indicate that parameter uncertainty leads to larger forecast errors and thereby makes fiscal planning more difficult. However, we find that one can obtain much the same results by increasing the magnitude of the additive shocks in the model. This implies that the non-linear (multiplicative as opposed to additive) nature of the stochastic parameters plays a relatively minor role in our analysis of fiscal planning. The additive error terms in the stochastic simulation model can therefore be interpreted to capture parameter uncertainty, as well as other sources of uncertainty. La plupart des études qui ont été menées sur la planification financière à moyen terme développent une seule source d’incertitude, qui est définie par l’intégration de termes d’erreur aléatoire additif dans des modèles de simulation stochastique. Dans ces modèles, le responsable de la planification financière qui travaille à établir le budget connaît à fond la structure de l’économie, notamment les paramètres. Or, si l’on simplifie grandement les expériences en simulation stochastique en faisant abstraction du paramètre incertitude, les conclusions dont on pourrait retirer de ces expériences et qui serviraient de fondements à l’élaboration des directives risquent de s’avérer trompeuses, pour les raisons décrites par Brainard (1967). La présente étude examine les effets du paramètre incertitude sur les résultats obtenus lors d’études de simulation stochastique ayant pour cadre la planification financière à moyen terme. Les auteurs comparent les résultats concernant la simulation que donnent de deux différents genres d’expériences de simulation stochastique. En employant la simulation stochastique conventionnelle, le responsable de la planification financière est aux prises avec une incertitude découlant d’une seule source, soit les termes d’erreur additive, tandis que la seconde simulation stochastique comporte en plus l’incertitude à l’égard des paramètres du modèle. Selon les conclusions de l’étude, le paramètre incertitude produit des erreurs plus grandes en matière de prévisions, ce qui complique la planification financière. Toutefois, il est possible d’arriver à des résultats assez similaires en augmentant la valeur absolue des erreurs additives sur les équations dans le modèle. Par conséquent, la nature non linéaire (multiplicative, contrairement à additive) des paramètres stochastiques joue un rôle relativement mineur dans la présente analyse sur la planification financière. Il est ainsi possible d’interpréter les termes d’erreur additive dans le modèle de simulation stochastique pour définir le paramètre incertitude de même que d’autres sources d’incertitude.

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Bibliographic Info

Paper provided by Department of Finance Canada in its series Working Papers-Department of Finance Canada with number 2001-21.

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Handle: RePEc:fca:wpfnca:2001-21

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Cited by:
  1. Giovanni Di Bartolomeo & Francesco Giuli & Marco manzo, 2005. "Policy Uncertainty, Symbiosis, and the Optimal Fiscal and Monetary Conservativeness," Macroeconomics 0508005, EconWPA.
  2. Giovanni Di Bartolomeo & Marco Manzo, 2010. "Fiscal Policy Under Balanced Budget And Indeterminacy: A New Keynesian Perspective," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(4), pages 455-472, 09.
  3. Isabell Koske & Nigel Pain, 2008. "The Usefulness of Output Gaps for Policy Analysis," OECD Economics Department Working Papers 621, OECD Publishing.

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