IDEAS home Printed from https://ideas.repec.org/p/cir/cirwor/95s-08.html
   My bibliography  Save this paper

An Empirical Analysis of the Canadian Budget Process

Author

Listed:
  • Bryan Campbell
  • Eric Ghysels

Abstract

This paper provides a statistical analysis of the forecasts of a 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 the authors describe an easily applied non-parametric testing methodology that is more appropriate than the usual regression-based approach in small samples. The reliability and relative power of the various non-parametric tests are illustrated in a series of simulations. Applying these tests to the fiscal forecasts, they find that there is little cause to be concerned with the forecast performance of the Department of Finance over the last seventeen years.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Bryan Campbell & Eric Ghysels, 1995. "An Empirical Analysis of the Canadian Budget Process," CIRANO Working Papers 95s-08, CIRANO.
    • Handle: RePEc:cir:cirwor:95s-08
    as

    Download full text from publisher

    File URL: https://cirano.qc.ca/files/publications/95s-08.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jean‐Marie Dufour, 1981. "Rank Tests For Serial Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(3), pages 117-128, May.
    2. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    3. Plesko, George A., 1988. "The Accuracy of Government Forecasts and Budget Projections," National Tax Journal, National Tax Association, vol. 41(4), pages 483-501, December.
    4. Feenberg, Daniel R, et al, 1989. "Testing the Rationality of State Revenue Forecasts," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 300-308, May.
    5. Cassidy, Glenn & Kamlet, Mark S. & Nagin, Daniel S., 1989. "An empirical examination of bias in revenue forecasts by state governments," International Journal of Forecasting, Elsevier, vol. 5(3), pages 321-331.
    6. Gregory Mankiw, N. & Shapiro, Matthew D., 1986. "Do we reject too often? : Small sample properties of tests of rational expectations models," Economics Letters, Elsevier, vol. 20(2), pages 139-145.
    7. Dufour, J.M., 1988. "Non-Uniform Bounds for Nonparametric T Tests," Cahiers de recherche 8820, Universite de Montreal, Departement de sciences economiques.
    8. Benjamin M. Friedman, 1980. "Survey Evidence on The Rationality of Interest Rate Expectations," NBER Working Papers 0261, National Bureau of Economic Research, Inc.
    9. Mark S. Kamlet & David C. Mowery & Tsai-Tsu Su, 1987. "Whom do you trust? An analysis of executive and congressional economic forecasts," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 6(3), pages 365-384.
    10. Plesko, George A., 1988. "The Accuracy of Government Forecasts and Budget Projections," National Tax Journal, National Tax Association;National Tax Journal, vol. 41(4), pages 483-501, December.
    11. Dufour, J.M., 1979. "Rank Tests for Serial Dependence," Cahiers de recherche 7815, Universite de Montreal, Departement de sciences economiques.
    12. Friedman, Benjamin M., 1980. "Survey evidence on the `rationality' of interest rate expectations," Journal of Monetary Economics, Elsevier, vol. 6(4), pages 453-465, October.
    13. Campbell, Bryan & Dufour, Jean-Marie, 1991. "Over-rejections in rational expectations models : A non-parametric approach to the Mankiw-Shapiro problem," Economics Letters, Elsevier, vol. 35(3), pages 285-290, March.
    14. Gentry, William M., 1989. "Do State Revenue Forecasters Utilize Available Information," National Tax Journal, National Tax Association;National Tax Journal, vol. 42(4), pages 429-439, December.
    15. McNees, Stephen K, 1978. "The "Rationality" of Economic Forecasts," American Economic Review, American Economic Association, vol. 68(2), pages 301-305, May.
    16. Gentry, William M., 1989. "Do State Revenue Forecasters Utilize Available Information," National Tax Journal, National Tax Association, vol. 42(4), pages 429-39, December.
    17. Dufour, Jean-Marie & Hallin, Marc, 1991. "Nonuniform Bounds for Nonparametric t-Tests," Econometric Theory, Cambridge University Press, vol. 7(2), pages 253-263, June.
    18. repec:cup:etheor:v:7:y:1991:i:2:p:253-63 is not listed on IDEAS
    19. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    20. Campbell, Bryan & Ghysels, Eric, 1995. "Federal Budget Projections: A Nonparametric Assessment of Bias and Efficiency," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 17-31, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Mr. Mikhail Golosov & Mr. John R King, 2002. "Tax Revenue Forecasts in IMF-Supported Programs," IMF Working Papers 2002/236, International Monetary Fund.
    3. Chatagny, Florian, 2015. "Incentive effects of fiscal rules on the finance minister's behavior: Evidence from revenue projections in Swiss Cantons," European Journal of Political Economy, Elsevier, vol. 39(C), pages 184-200.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    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. 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.
    10. 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.
    11. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Teresa Leal & Javier J. Pérez & Mika Tujula & Jean-Pierre Vidal, 2008. "Fiscal Forecasting: Lessons from the Literature and Challenges," Fiscal Studies, Institute for Fiscal Studies, vol. 29(3), pages 347-386, September.
    2. Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(2), pages 367-391, June.
    3. Merola, Rossana & Pérez, Javier J., 2013. "Fiscal forecast errors: Governments versus independent agencies?," European Journal of Political Economy, Elsevier, vol. 32(C), pages 285-299.
    4. de Mendonça, Helder Ferreira & Baca, Adriana Cabrera, 2022. "Fiscal opacity and reduction of income inequality through taxation: Effects on economic growth," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 69-82.
    5. Vasconcelos de Deus, Joseph David Barroso & de Mendonça, Helder Ferreira, 2017. "Fiscal forecasting performance in an emerging economy: An empirical assessment of Brazil," Economic Systems, Elsevier, vol. 41(3), pages 408-419.
    6. Björn Kauder & Niklas Potrafke & Christoph Schinke, 2017. "Manipulating Fiscal Forecasts: Evidence from the German States," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 73(2), pages 213-236, June.
    7. repec:rre:publsh:v:33:y:2003:i:1:p:85-103 is not listed on IDEAS
    8. Dean Croushore & Simon van Norden, 2018. "Fiscal Forecasts at the FOMC: Evidence from the Greenbooks," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 933-945, December.
    9. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Exact optimal inference in regression models under heteroskedasticity and non-normality of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2532-2553, November.
    10. Boum-Jong Choe, 1990. "Rational expectations and commodity price forecasts," Policy Research Working Paper Series 435, The World Bank.
    11. Dufour, Jean-Marie & Farhat, Abdeljelil & Hallin, Marc, 2006. "Distribution-free bounds for serial correlation coefficients in heteroskedastic symmetric time series," Journal of Econometrics, Elsevier, vol. 130(1), pages 123-142, January.
    12. Krol, Robert, 2013. "Evaluating state revenue forecasting under a flexible loss function," International Journal of Forecasting, Elsevier, vol. 29(2), pages 282-289.
    13. Croushore, Dean & van Norden, Simon, 2019. "Fiscal Surprises at the FOMC," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1583-1595.
    14. Luger, Richard, 2003. "Exact non-parametric tests for a random walk with unknown drift under conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 115(2), pages 259-276, August.
    15. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    16. George A. Krause, 2006. "Beyond the Norm," Rationality and Society, , vol. 18(2), pages 157-191, May.
    17. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    18. Mocan, H. Naci & Azad, Sam, 1995. "Accuracy and rationality of state General Fund Revenue forecasts: Evidence from panel data," International Journal of Forecasting, Elsevier, vol. 11(3), pages 417-427, September.
    19. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    20. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    21. Kiviet, Jan F. & Dufour, Jean-Marie, 1997. "Exact tests in single equation autoregressive distributed lag models," Journal of Econometrics, Elsevier, vol. 80(2), pages 325-353, October.

    More about this item

    Keywords

    Budget forecast; Nonparametric methods; Prévisions budgétaires ; Méthodes non-paramétriques;
    All these keywords.

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cir:cirwor:95s-08. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Webmaster (email available below). General contact details of provider: https://edirc.repec.org/data/ciranca.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.