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In this comment on ‘‘How Biased are US Government Forecasts of the Federal Debt?’’ by Neil R. Ericsson, we investigate the sensitivity of the ‘‘bare-bones’’ application of the impulse indicator saturation technique. We offer an alternative but complementary interpretation of Ericsson’s findings of bias in government debt forecasts. Our findings reinforce his interpretation of the role of the IIS technique as a general diagnostic tool for detecting model misspecification. © 2014 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Ex-post analyses of forecast errors are important for both model builders and policymakers. Neil Ericsson’s paper explores the biases in the debt forecasts produced by the OMB and the CBO. We (and Ericsson and others) interpret the IIS technique to include a more general method for detecting model misspecification. In our analysis of the debt data, we find a violation of the assumption of homoskedastic errors. In other applications, the IIS technique has the potential to detect a wide variety of model misspecifications.