International Finance Discussion Papers (IFDP)
February 2017
How Biased Are U.S. Government Forecasts of the Federal Debt?
Supplemental materials (.zip): This file includes the data, code, and output for the empirical and analytical results in this paper.
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, heteroscedasticity, projections, United States.
DOI: https://doi.org/10.17016/IFDP.2017.1189
PDF: Full Paper