A Bayesian Analysis of the Efficiency of Growth and Inflation Forecasts for Germany
38 Pages Posted: 19 Jul 2017 Last revised: 20 Apr 2018
Date Written: March 7, 2018
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
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