• Medientyp: E-Book
  • Titel: How biased are U.S. government forecasts of the federal debt?
  • Werktitel: Detecting and quantifying biases in government forecasts of the U.S. gross federal debt
  • Beteiligte: Ericsson, Neil R. [VerfasserIn]
  • Erschienen: [Washington, DC]: Board of Governors of the Federal Reserve System, January 6, 2017
  • Erschienen in: International finance discussion papers ; 118900
  • Umfang: 1 Online-Ressource (circa Seiten); Illustrationen
  • Sprache: Englisch
  • Schlagwörter: 1984-2012 ; Haushaltsdefizit ; Prognoseverfahren ; Systematischer Fehler ; Wirtschaftsindikator ; Heteroskedastizität ; USA ; Arbeitspapier ; Graue Literatur
  • Entstehung:
  • Anmerkungen: "Forthcoming in the International Journal of Forecasting as the articles "How Biased Are U.S. Government Forecasts of the Federal Debt?" (Sections 1-7 below) and "Interpreting Estimates of Forecast Bias" (Appendix A below). Appendix B below lists the data and forecasts analyzed. An earlier version of this paper was titled "Detecting and Quantifying Biases in Government Forecasts of the U.S. Gross Federal Debt"." - Aus der Publikation
  • Beschreibung: Government debt and forecasts thereof attracted considerable attention during the recent financial crisis. The current paper analyzes potential biases in different U.S. government agencies' one-year-ahead forecasts of U.S. gross federal debt over 1984-2012. Standard tests typically fail to detect biases in these forecasts. However, impulse indicator saturation (IIS) detects economically large and highly significant time-varying biases, particularly at turning points in the business cycle. These biases do not appear to be politically related. IIS defines a generic procedure for examining forecast properties; it explains why standard tests fail to detect bias; and it provides a mechanism for potentially improving forecasts
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