A Bayesian Analysis of the Efficiency of Growth and Inflation Forecasts for Germany

38 Pages Posted: 19 Jul 2017 Last revised: 20 Apr 2018

See all articles by Christoph Behrens

Christoph Behrens

University of the German Federal Armed Forces - Department of Economics

Christian Pierdzioch

University of the German Federal Armed Forces - Department of Economics

Marian Risse

University of the German Federal Armed Forces - Helmut Schmidt Universit├Ąt

Date Written: March 7, 2018

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 forecasts 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. We find that Bayesian additive regression trees perform significantly better than a standard linear efficiency-regression model.

Keywords: Forecast Efficiency, Bayesian Modeling, Regression Trees

JEL Classification: C53, E31, E32, E37

Suggested Citation

Behrens, Christoph and Pierdzioch, Christian and Risse, Marian, A Bayesian Analysis of the Efficiency of Growth and Inflation Forecasts for Germany (March 7, 2018). Available at SSRN: https://ssrn.com/abstract=3002394 or http://dx.doi.org/10.2139/ssrn.3002394

Christoph Behrens

University of the German Federal Armed Forces - Department of Economics ( email )

Holstenhofweg 85
Hamburg, 22043
Germany

Christian Pierdzioch (Contact Author)

University of the German Federal Armed Forces - Department of Economics ( email )

Holstenhofweg 85
Hamburg, 22043
Germany

Marian Risse

University of the German Federal Armed Forces - Helmut Schmidt Universit├Ąt ( email )

Holstenhofweg 85
Hamburg, 22008
Germany

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