February 2017

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

Neil R. Ericsson

Supplemental materials (.zip): This file includes the data, code, and output for the empirical and analytical results in this paper.


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, heteroscedasticity, projections, United States.

DOI: https://doi.org/10.17016/IFDP.2017.1189

PDF: Full Paper

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Last Update: January 09, 2020