IDEAS home Printed from https://ideas.repec.org/p/gwc/wpaper/2011-002.html
   My bibliography  Save this paper

Comparing Government Forecasts of the United States’ Gross Federal Debt

Author

Listed:
  • Andrew B. Martinez

    (George Washington University)

Abstract

This paper compares annual one-step-ahead forecasts from the Congressional Budget Office (CBO) and the Office of Management and Budget (OMB) of the United States‟ gross federal debt from 1984 to 2010. While comparisons of these agencies‟ forecasts have been done before, they have not focused on the debt. The paper finds that both agencies do a good job forecasting the debt except during recessions. Each agency‟s forecast lacks something that the other accounts for and an average of both out performs either individually. However, the Analysis of the President‟s Budget (APB), which includes information from both agencies, performs best.

Suggested Citation

  • 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.
  • Handle: RePEc:gwc:wpaper:2011-002
    as

    Download full text from publisher

    File URL: https://www2.gwu.edu/~forcpgm/2011-002.pdf
    File Function: First version, 2011
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Darrel Cohen & Glenn Follette, 2003. "Forecasting exogenous fiscal variables in the United States," Finance and Economics Discussion Series 2003-59, Board of Governors of the Federal Reserve System (U.S.).
    2. 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.
    3. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 671-690.
    4. Bollerslev, Tim & Russell, Jeffrey & Watson, Mark (ed.), 2010. "Volatility and Time Series Econometrics: Essays in Honor of Robert Engle," OUP Catalogue, Oxford University Press, number 9780199549498.
    5. David F. Hendry & Carlos Santos, 2005. "Regression Models with Data‐based Indicator Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 571-595, October.
    6. Stephen K. McNees, 1995. "Assessment of the \"official\" economic forecasts," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 13-23.
    7. Carlos Santos & David Hendry & Soren Johansen, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 317-335, April.
    8. Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
    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. J. D. Foster & James C. Miller, 2000. "The Tyranny of Budget Forecasts," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 205-215, Summer.
    12. Ericsson, Neil R., 1992. "Parameter constancy, mean square forecast errors, and measuring forecast performance: An exposition, extensions, and illustration," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 465-495, August.
    13. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
    14. Jurgen A. Doornik, 2008. "Encompassing and Automatic Model Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 915-925, December.
    15. Michael T. Belongia, 1988. "Are economic forecasts by government agencies biased? Accurate?," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 15-23.
    16. Søren Johansen & Bent Nielsen, 2008. "An analysis of the indicator saturation estimator as a robust regression," Discussion Papers 08-03, University of Copenhagen. Department of Economics.
    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. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
    2. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.
    3. Gamber, Edward N. & Liebner, Jeffrey P., 2017. "Comment on “How Biased are US Government Forecasts of the Federal Debt?”," International Journal of Forecasting, Elsevier, vol. 33(2), pages 560-562.
    4. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

    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. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.
    2. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
    3. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
    4. Hendry, David F. & Johansen, Søren, 2015. "Model Discovery And Trygve Haavelmo’S Legacy," Econometric Theory, Cambridge University Press, vol. 31(1), pages 93-114, February.
    5. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    6. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    7. Neil R. Ericsson, 2008. "The Fragility of Sensitivity Analysis: An Encompassing Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 895-914, December.
    8. David Hendry & Grayham E. Mizon, 2012. "Forecasting from Structural Econometric Models," Economics Series Working Papers 597, University of Oxford, Department of Economics.
    9. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Ragnar Nymoen, 2014. "Misspecification Testing: Non-Invariance of Expectations Models of Inflation," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 553-574, August.
    10. David F. Hendry & Felix Pretis, 2013. "Anthropogenic influences on atmospheric CO2," Chapters, in: Roger Fouquet (ed.), Handbook on Energy and Climate Change, chapter 12, pages 287-326, Edward Elgar Publishing.
    11. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    12. 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.
    13. Hendry David F & Mizon Grayham E, 2011. "Econometric Modelling of Time Series with Outlying Observations," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-26, February.
    14. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
    15. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    16. Neil Ericsson & Erica Reisman, 2012. "Evaluating a Global Vector Autoregression for Forecasting," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 18(3), pages 247-258, August.
    17. Jurgen A. Doornik & David F. Hendry & Steve Cook, 2015. "Statistical model selection with “Big Data”," Cogent Economics & Finance, Taylor & Francis Journals, vol. 3(1), pages 1045216-104, December.
    18. David F. Hendry & Grayham E. Mizon, 2016. "Improving the teaching of econometrics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170096-117, December.
    19. Søren Johansen & Lukasz Gatarek, 2014. "Optimal hedging with the cointegrated vector autoregressive model," CREATES Research Papers 2014-40, Department of Economics and Business Economics, Aarhus University.
    20. White, Halbert & Pettenuzzo, Davide, 2014. "Granger causality, exogeneity, cointegration, and economic policy analysis," Journal of Econometrics, Elsevier, vol. 178(P2), pages 316-330.

    More about this item

    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:gwc:wpaper:2011-002. 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: GW Economics Department (email available below). General contact details of provider: https://edirc.repec.org/data/pfgwuus.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.