Original scientific paper
https://doi.org/10.1080/1331677X.2017.1314826
Combined forecasts to improve Survey of Profession Forecasters predictions for quarterly inflation in the U.S.A.
Mihaela Simionescu
orcid.org/0000-0002-6124-2172
Beata Gavurova
orcid.org/0000-0002-0606-879X
Luboš Smrčka
Abstract
The main aim of this study is to evaluate and improve the Survey
of Professional Forecasters (S.P.F.) quarterly inflation rate forecasts.
According to the Diebold–Mariano test, on the horizon 1991:Q1–
2015:Q1, there were no significant differences in accuracy between
the four types of predictions provided by SPF (mean forecasts,
median predictions, predictions of financial service providers [f1]
and predictions of non-financial service providers [f2]). The main
contribution is given by the use of the algorithm for stochastic
search variable selection in order to construct Bayesian combined
predictions. Considering the horizon 2013:Q1–2015:Q1, the proposed
Bayesian combined predictions for rate of change in the quarterly
average headline consumer price index (C.P.I.) level outperformed
the initial experts’ expectations. The combined predictions based on
the Bayesian approach and principal component analysis for core
inflation and personal consumption expenditures inflation improved
the accuracy of S.P.F. predictions and naïve forecasts on the horizon
2015:Q1–2016:Q1.
Keywords
Forecasts; combined forecasts; stochastic search variable selection; inflation
Hrčak ID:
182568
URI
Publication date:
1.12.2017.
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