Detail publikace

Search for Predictors of Inflation Using VAR and BVAR

Autor: PhDr. Jaromír Baxa Ph.D.,
PhDr. RNDr. Josef Stráský Ph.D.,
Typ: Články v recenzovaných časopisech
Rok: 2014
Číslo: 33
ISSN / ISBN: ISSN 2336-2782
Publikováno v: Stráský, J., & Baxa, J. (2014). Search for Predictors of Inflation Using VAR and BVAR: The Case of Czech Republic. Bulletin of the Czech Econometric Society, 21(33).
Místo vydání: Praha
Klíčová slova:
JEL kódy: C11, C32, C52, C53
Citace: Stráský, J., & Baxa, J. (2014). Search for Predictors of Inflation Using VAR and BVAR: The Case of Czech Republic. Bulletin of the Czech Econometric Society, 21.
Abstrakt: Forecasting inflation is generally considered a challenging task as forecasters face fundamental uncertainty about the proper selection of variables driving inflation dynamics. In this paper, we investigate the forecasting performance of variables representing economic activity, monetary policy and survey data within VAR and BVAR models. We propose a scoring algorithm to evaluate their forecasting performance based on various criteria such as the mean square error, the mean absolute error and the Diebold-Mariano test. A one-year horizon is considered for the forecasts and they are constructed by the chain rule using monthly data. We also determine the forecast accuracy on sub-periods, showing that in a low volatility periods the forecast accuracy can be significantly improved by selecting models using square-root errors. Our results suggest that the survey data have strong predictive power, especially when accompanied by a broad money measure. The survey data outperform also the indicators of economic activity, probably due to their forward-looking nature. VAR models outperform univariate models in pseudo out-of-sample forecasting, but employing Bayesian restrictions via Minnesota prior did not further improve the forecasting performance.
Ke stažení: Strasky-Baxa-2014.pdf
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