Search for Predictors of Inflation Using VAR and BVAR: The Case of Czech Republic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F14%3A10312080" target="_blank" >RIV/00216208:11230/14:10312080 - isvavai.cz</a>

Výsledek na webu

<a href="http://ces.utia.cas.cz/bulletin/index.php/bulletin/article/view/207" target="_blank" >http://ces.utia.cas.cz/bulletin/index.php/bulletin/article/view/207</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Search for Predictors of Inflation Using VAR and BVAR: The Case of Czech Republic

Popis výsledku v původním jazyce

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 indica

Název v anglickém jazyce

Search for Predictors of Inflation Using VAR and BVAR: The Case of Czech Republic

Popis výsledku anglicky

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 indica

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Bulletin of the Czech Econometric Society

ISSN

2336-2782

e-ISSN

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Svazek periodika

21

Číslo periodika v rámci svazku

33

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

37

Strana od-do

22-58

Kód UT WoS článku

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EID výsledku v databázi Scopus

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