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An Empirical Analysis of the Canadian Budget Process

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  • Campbell, B.
  • Ghysels, E.

Abstract

This paper provides a statistical analysis of the forecasts of significant number of expenditure and revenue components of the Federal budget provided each year by the Department of Finance. The sample available for such an investigation is limited and we describe an easily-applied nonparametric testing methodology which is more appropriate than the usual regression-based approach in small samples. The reliability and relative power of the various nonparametric tests are illustrated in a series of simulations. Applying these tests to the fiscal forecasts, we find that there is little cause to be concerned with the forecast performance of the Department of Finance over the last seventeen years. Dans cette étude nous examinons les erreurs de prévisions pour les comptes de dépenses et recettes du budget canadien. Nous appliquons des méthodes non-paramétriques à cause des petites tailles d'échantillons. Nous trouvons peu d'erreurs systématiques dans les prévisions budgétaires.
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Suggested Citation

  • Campbell, B. & Ghysels, E., 1995. "An Empirical Analysis of the Canadian Budget Process," Cahiers de recherche 9523, Universite de Montreal, Departement de sciences economiques.
    • Handle: RePEc:mtl:montde:9523
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    References listed on IDEAS

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    Cited by:

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    2. Friedrich Heinemann, 2006. "Planning or Propaganda? An Evaluation of Germany's Medium-term Budgetary Planning," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 62(4), pages 551-578, December.
    3. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    4. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    5. Artur Tarassow & Sven Schreiber, 2018. "FEP - the forecast evaluation package for gretl," IMK Working Paper 190-2018, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    6. Chatagny, Florian & Siliverstovs, Boriss, 2015. "Evaluating rationality of level and growth rate forecasts of direct tax revenues under flexible loss function: Evidence from Swiss cantons," Economics Letters, Elsevier, vol. 134(C), pages 65-68.
    7. Amigues, Jean-Pierre & Favard, Pascal & Gaudet, Gerard & Moreaux, Michel, 1998. "On the Optimal Order of Natural Resource Use When the Capacity of the Inexhaustible Substitute Is Limited," Journal of Economic Theory, Elsevier, vol. 80(1), pages 153-170, May.
    8. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
    9. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, University of Hamburg, Department of Socioeconomics.
    10. Mr. Mikhail Golosov & Mr. John R King, 2002. "Tax Revenue Forecasts in IMF-Supported Programs," IMF Working Papers 2002/236, International Monetary Fund.
    11. Touhami, A. & Martens, A., 1996. "Macroemesures in Computable General Equilibrium Models: a Probabilistic Treatment with an Application to Morocco," Cahiers de recherche 9621, Universite de Montreal, Departement de sciences economiques.

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    JEL classification:

    • H61 - Public Economics - - National Budget, Deficit, and Debt - - - Budget; Budget Systems

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