Managing Uncertainty: The Bias and Efficiency of Federal Macroeconomic Forecasts

Corder, J. Kevin

doi:10.1093/jopart/mui003

Cited by 16 publications

(15 citation statements)

References 15 publications

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“…(1) sum to 1, the first agency's forecast error cannot be explained by its deviations from 5 Similar approaches were used by Belongia (1988), Cohen and Follette (2003), Corder (2005), and Douglas and Krause (2005).…”

Section: Forecast-encompassing Testsmentioning

confidence: 92%

“…They find that the FRB unemployment forecasts perform better than those from either the CBO or the OMB, while the CBO taxrevenue forecasts perform worse than those of either the OMB or the FRB. Corder (2005) examines forecasts of GDP, inflation, unemployment, and interest rates from the Social Security Administration (SSA), the CBO, and the OMB between 1976 and 2003. Using two different tests to check for bias and efficiency, he finds that the CBO forecasts encompass the OMB forecasts for GDP, the OMB forecasts encompass the CBO forecasts for unemployment and inflation, and neither encompasses the other for interest rates.…”

Section: Literature Reviewmentioning

confidence: 99%

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How good are US government forecasts of the federal debt?

Martinez

2015

International Journal of Forecasting

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a b s t r a c tThis paper compares annual one-year-ahead and five-year-ahead forecasts from government agencies for the US gross federal debt and deficit from 1984 to 2013. Other studies have compared two of these agencies' forecasts, but not for debt. The current paper finds that the forecast from the Analysis of the President's Budget performs best across both horizons but does not encompass the other forecasts. Instead, each of the forecasts lacks information included by the other agencies and therefore a combination of all three outperforms all individual forecasts.

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Section: Forecast-encompassing Testsmentioning

confidence: 92%

Section: Literature Reviewmentioning

confidence: 99%

How good are US government forecasts of the federal debt?

Martinez

2015

International Journal of Forecasting

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“…This broader usage of the term "forecast" is also in line with Clements and Hendry (2002b, p. 2): "A forecast is any statement about the future". For some previous analyses of these and other governmental and institutional forecasts, see Corder (2005), Engstrom and Kernell (1999), Frankel (2011), Joutz and Stekler (2000), Nunes (2013), Sinclair, Joutz, and Stekler (2010), Romer and Romer (2008), and Tsuchiya (2013). Finally, many prior studies have compared forecasts whose assumptions differ from each other.…”

Section: The Data and The Forecastsmentioning

confidence: 99%

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

Ericsson

2017

internationalfinance

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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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“…3 Conversely, high quality forecasts refer to random forecasting errors consistent with a failure to reject the UFR hypothesis. Interestingly enough, a scholarly consensus has emerged that finds government agencies' current year macroeconomic forecasts to be consistent with the UFR hypothesis (Blackley and DeBoer 1993;Corder 2005;Kamlet, Mowery, and Su 1987;McNees 1995;but see Frendeis and Tatalovich 2000;Howard 1987;Plesko 1988 for mixed evidence). 4 These existing studies, however, are limited to the forecasting of normal macroeconomic conditions, and thus fail to uncover the inherent heterogeneity that underlies policy decisions.…”

Section: Cognitive Bias and The Quality Of Us Federal Agency Macroecomentioning

confidence: 99%

Beyond the Norm

Krause

2006

Rationality and Society

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US federal agency macroeconomic forecasts are generally made in a manner consistent with the unbiasedness-forecast rationality (UFR) hypothesis. While this inference may be valid under normal policy conditions, cognitive biases can make ex ante policy analysis more difficult when macroeconomic circumstances deviate from the norm. I test whether policy forecasting under abnormal macroeconomic conditions generates predictions that exhibit cognitive biases (uncertainty-induced bias). Moreover, I investigate whether government agencies will either overstate (availability bias) or understate (mean anchoring bias) true conditions during both good and bad times. These three behavioral hypotheses are examined by performing simultaneous quantile regression analysis on a pooled dataset on US macroeconomic forecasts by the Office of Management and Budget (OMB), Congressional Budget Office (CBO), and Social Security Administration (SSA) for the 1976-2002 period. The statistical evidence provides unequivocal support for the uncertainty bias hypothesis as well as strong support for the availability bias hypothesis. Specifically, deviations from frequently occurring (normal) policy conditions are positively related to cognitive bias involving ex ante policy decisions, and such biases tend to overstate abnormal policy conditions. These empirical findings highlight the power of cognitive psychology for explaining departures from classical rationality with respect to government agency forecasting under atypical macroeconomic conditions. How deeply do cognitive anomalies infect economic market behavior and economic data, and how much of the edifice of economic analysis, particularly demand forecasting and project evaluation, can be preserved? The answer will depend crucially on how rationality fails. It is possible that the standard model of rationality works well in some circumstances, where repetition and the experience of market rewards train consumers to adopt behavior rules that are consistent with rationality. It is also possible that consumers conform to the rational model at some points in the decision process, but not in others. (McFadden 1999: 83-4)

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Managing Uncertainty: The Bias and Efficiency of Federal Macroeconomic Forecasts

Cited by 16 publications

References 15 publications

How good are US government forecasts of the federal debt?

How good are US government forecasts of the federal debt?

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

Beyond the Norm

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