Adjusting for information content when comparing forecast performance

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The Working Paper series presents reports on matters in the sphere of activities of the Riksbank that are considered to be of interest to a wider public. Terms of use: Documents inThe papers are to be regarded as reports on ongoing studies and the authors will be pleased to receive comments.The opinions expressed in this article are the sole responsibility of the author(s) and should not be interpreted as reflecting the views of Sveriges Riksbank. Adjusting for Information Content when Comparing ForecastSveriges Riksbank Working Paper Series No. 328Abstract Cross institutional forecast evaluations may be severely distorted by the fact that forecasts are made at different points in time, and thus with different amount of information. This paper proposes a method to account for these differences. The method computes the timing effect and the forecaster's ability simultaneously. Monte Carlo simulation demonstrate that evaluations that do not adjust for the differences in information content may be misleading. In addition, the method is applied on a real-world data set of 10 Swedish forecasters for the period 1999-2015. The results show that the ranking of the forecasters is affected by the proposed adjustment.

Nowcasting Swedish GDP with a large and unbalanced data set

“…Various actors regularly publish forecasts for Swedish GDP, among others the Swedish central bank, the Riksbank, other government agencies and commercial banks. These published forecasts are regularly evaluated, thereby taking into account the publication timing and, hence, the differing amounts of available information (Andersson et al 2017). Typically, the average yearly growth rates of GDP are evaluated, that is, each year's four quarters average of year-on-year growth rates.…”

Electoral cycles in macroeconomic forecasts

“…Hence, the cost of releasing a biased forecast should be approaching infinity for period one, but not for period two. See, for example,Andersson et al (2017) for an analysis of the relationship between horizon and forecast error when forecasting annual growth rates.16 These assumptions about the voters' utility allow for an electorate that is not too polarized, so that at least some voters can be persuaded by the forecasts.…”