Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis
Pablo Pincheira and
Carlos A. Medel ()
Working Papers Central Bank of Chile from Central Bank of Chile
Abstract:
We explore the ability of several univariate models to predict inflation in a number of countries and at several forecasting horizons. We place special attention on forecasts coming from a family of ten seasonal models that we call the Driftless Extended Seasonal ARIMA (DESARIMA) family. Using out-of-sample Root Mean Squared Prediction Errors (RMSPE) we compare the forecasting accuracy of the DESARIMA models with that of traditional univariate time-series benchmarks available in the literature. Our results show that DESARIMA-based forecasts display lower RMSPE at short horizons for every single country, except one. We obtain mixed results at longer horizons. Roughly speaking, in half of the countries, DESARIMA-based forecasts outperform the benchmarks at long horizons. Remarkably, the forecasting accuracy of our DESARIMA models is surprisingly high in stable inflation countries, for which the RMSPE is barely higher than 100 basis points when the prediction is made 24- and even 36-months ahead.
Date: 2012-08
New Economics Papers: this item is included in nep-for and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://www.bcentral.cl/documents/33528/133326/DTBC_677.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:chb:bcchwp:677
Access Statistics for this paper
More papers in Working Papers Central Bank of Chile from Central Bank of Chile Contact information at EDIRC.
Bibliographic data for series maintained by Alvaro Castillo ().