Philip Hans Franses Henk Kranendonk () Debby Lanser ()
Abstract
Official forecasts of international institutions are never purely model-based. Preliminary results of models are adjusted with expert opinions. What is the impact of these adjustments for the forecasts? Are they necessary to get ‘optimal’ forecasts? When model-based forecasts are adjusted by experts, the loss function of these forecasts is not a mean squared error loss function. In fact, the overall loss function is unknown. To examine the quality of these forecasts, one can rely on the tests for forecast optimality under unknown loss function as developed in Patton and Timmermann (2007). We apply one of these tests to ten variables for which we have model-based forecasts and expert-adjusted forecasts, all generated by the Netherlands Bureau for Economic Policy Analysis (CPB). For almost all variables the added expertise yields better forecasts in terms of fit. In terms of optimality, the effect of adjustments for the forecasts is limited, because for most variables the assumption that the forecast are not optimal can be rejected for both the model-based and the expert-adjusted forecasts.
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Publisher Info
Paper provided by CPB Netherlands Bureau for Economic Policy Analysis in its series CPB Discussion Papers with number
92.
Find related papers by JEL classification: C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Christoffersen, Peter F, 1998.
"Evaluating Interval Forecasts,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
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