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Do German economic research institutes publish efficient growth and inflation forecasts? A Bayesian analysis
Christoph Behrens1, Christian Pierdzioch1, Marian Risse1
1Department of Economics, Helmut Schmidt University, Hamburg, Germany.
Journal of Applied Statistics
|June 16, 2022
Summary
We reexamined German economic forecasts using Bayesian additive regression trees. Results show forecast efficiency varies, with longer-term predictions less reliable than short-term ones.
Area of Science:
- Economics
- Econometrics
- Computational Statistics
Background:
- Economic forecasting is crucial for policy and investment.
- Assessing forecast efficiency helps understand model reliability.
- Previous studies often used linear models, potentially limiting accuracy.
Purpose of the Study:
- To reexamine the efficiency of German growth and inflation forecasts.
- To compare the performance of Bayesian additive regression trees (BART) against standard linear models.
- To investigate forecast efficiency across different time horizons and institutions.
Main Methods:
- Utilized Bayesian additive regression trees (BART) for forecast efficiency analysis.
- Employed data from four leading German economic research institutes (1970-2016).
- Tested both strong and weak forms of forecast efficiency.
Main Results:
- Strong form of forecast efficiency was rejected.
- Evidence against weak form efficiency found for longer-term growth and inflation forecasts.
- Weak efficiency could not be rejected for short-term forecasts and institute-level disaggregated data.
- BART significantly outperformed standard linear models in forecast accuracy.
Conclusions:
- German economic forecasts exhibit varying degrees of efficiency.
- BART offers a more accurate approach to evaluating forecast efficiency compared to linear models.
- Policy implications arise from the differing efficiency of short-term versus long-term forecasts.
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