Literature DB >> 35707494

Do German economic research institutes publish efficient growth and inflation forecasts? A Bayesian analysis.

Christoph Behrens1, Christian Pierdzioch1, Marian Risse1.   

Abstract

We use Bayesian additive regression trees to reexamine the efficiency of growth and inflation forecasts for Germany. To this end, we use forecasts of four leading German economic research institutes for the sample period from 1970 to 2016. We reject the strong form of forecast efficiency and find evidence against the weak form of forecast efficiency for longer-term growth and longer-term inflation forecasts. We cannot reject weak efficiency of short-term growth and inflation forecasts and of forecasts disaggregated at the institute level. We find that Bayesian additive regression trees perform significantly better than a standard linear efficiency-regression model in terms of forecast accuracy.
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Entities:  

Keywords:  Bayesian modeling; C53; E31; E32; E37; Forecast efficiency; regression trees

Year:  2019        PMID: 35707494      PMCID: PMC9041732          DOI: 10.1080/02664763.2019.1652253

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.416


  2 in total

1.  Commentary: practical advantages of Bayesian analysis of epidemiologic data.

Authors:  D B Dunson
Journal:  Am J Epidemiol       Date:  2001-06-15       Impact factor: 4.897

2.  Bayesian Additive Regression Trees using Bayesian Model Averaging.

Authors:  Belinda Hernández; Adrian E Raftery; Stephen R Pennington; Andrew C Parnell
Journal:  Stat Comput       Date:  2017-07-27       Impact factor: 2.559

  2 in total

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