The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach

Abstract

Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.Download this ZEW Discussion Paper from our ftp server:ftp://ftp.zew.de/pub/zew-docs/dp/dp07058.pdf Non-technical summaryThe last decade has seen marked economic fluctuations in the major industrial countries, which regularly present business cycle forecasters with a challenge. In this paper we are interested in how professional forecasters managed to predict GDP and price developments during the last decade. To this end, we explore the accuracy and evolution of the Consensus Forecast for twelve industrial countries for the years 1996 to 2006. This pooled forecast has the main advantage that it offers monthly publications of revised forecasts for the current and the next year, so that an explicit revision process of 24 forecasts for every target year can be observed.The theoretical and econometric analysis is based on the framework of Davies and Lahiri (1995) and Clements et al. (2006). The latter employ a pooling procedure which permits the evaluation of all forecasts for each target variable over 24 horizons simultaneously. Adopting this methodology allows us to draw conclusions on evaluating systematic forecast bias and, by applying a test on the predictability of forecast revisions, on the efficient use of new information for all forecast horizons jointly. It is shown how the pooled approach needs to be adjusted in order to accommodate the forecasting scheme of the Consensus Forecasts.Furthermore, the pooled approach is extended by a sequential test with the purpose of detecting the critical horizon beyond which the forecast should be regarded as biased.Moreover, we show how the pooled tests for the predictability of forecast revisions can be improved by taking heteroscedasticity in the form of target year-specific variances of macroeconomic shocks into account.In the empirical part we first present results in the form of analytical confidence intervals surrounding the horizon-specific bias estimates which allow intuitive and meaningful interpretations. The test for common bias reveals that several countries show biased forecasts, especially with forecasts covering more than 12 months. These results partially confirm the presumption that the macroeconomic forecasts for the past 10 years were severely affected by the pronounced shocks in that period. The fact that for individual countries systematic biases can be observed by applying the Consensus Forecasts reveals that in these countries the forecasting industry on the whole was not able to cope with the shoc...

Central bank transparency and the consensus forecast: What does The Economist poll of forecasters tell us?

“…Apparently, the forecast inefficiency is more pronounced during years with a pernicious financial crisis because forecastsers fail to adjust their predictions in a consistent manner in response to incoming information. This is 12 almost in accordnance with previous studies that rejected efficiency for a wide range of countries based both on consensus forecasts (Loungani, 2001;Isiklar et al, 2006;Ager et al, 2009) and on individual forecasts (Davies and Lahiri, 1995;Lahiri and Sheng, 2008).…”

High-Frequency Credit Spread Information and Macroeconomic Forecast Revision

“…19) This result indicates that, although 18) Our estimate of the rigidity parameter () is larger than those from previous studies with different sample periods. For example, Ager et al (2009)'s estimated rigidity coefficient is 0.28 based on the data from 1996 to 2006, andDovern et al (2015) report a coefficient of 0.33 using a sample from 1989 to 2010. 19) The survey deadlines do not necessarily match the dates when surveys are actually submitted or the dates when the respondents form their predictions.…”

“…Nordhaus (1987) demonstrated the failure of forecast efficiency by showing forecast errors and revisions are correlated with past forecast revisions. Forecast efficiency has been tested in numerous studies, most of which have rejected weak-form efficiency in consensus forecasts (see, for example, Isiklar et al 2006;Ager et al 2009;Capistrán and López-Moctezuma 2014) and also in individual forecasts (Gallo et al 2002;Dovern and Weisser 2011;Deschamps and Ioannidis 2013;Andrade and Le Bihan 2013). With only a few exceptions such as Clements (1997), most studies have found positive coefficients on lagged revisions, implying that forecasts are not sufficiently updated when new information is received.…”

The accuracy of alternative GDP growth forecasts: Do they represent a credible alternative to the official ones?

“…Batchelor, 2001;Novotný & Raková, 2010) indicate that they are less biased and more accurate than their official counterparts, other studies point to no significant differences between the two (e.g. Artis, 1996;Hawkins, 2002;Juhn & Loungani, 2002;or Timmermann, 2007) or even to an inferior performance of alternative predictions (Ager et al, 2009). This naturally puts the frequent hypothesis of "greater independence means higher flexibility and accuracy in volatile times" at stake.…”

“…While such interconnection might provide a degree of stability, it naturally undermines the ability of these institutions to produce dissenting and significantly dissimilar views on the country´s future development. This rigidity gradually raises interest in the alternative (private) predictions, often aggregated into a consensus forecast, particularly when the official ones sustain large forecasting errors, as evinced by papers Ager et al (2009) or Novotný & Raková (2010).…”