How Biased Are U.S. Government Forecasts of the Federal Debt?

Neil Ericsson

No 1189, International Finance Discussion Papers from Board of Governors of the Federal Reserve System (U.S.)

Abstract: 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.

Keywords: Autometrics; Bias; Debt; Federal government; Forecasts; Impulse indicator saturation; heteroskedasticity; Projections; United States (search for similar items in EconPapers)
JEL-codes: C53 H68 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2017-01-06
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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https://www.federalreserve.gov/econresdata/ifdp/2017/files/ifdp1189.pdf (application/pdf)

Related works:
Journal Article: How biased are U.S. government forecasts of the federal debt? (2017)
Working Paper: How Biased Are U.S. Government Forecasts of the Federal Debt? (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgif:1189

DOI: 10.17016/IFDP.2017.1189

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