Forecasting Inflation With a Random Walk

Pablo Pincheira and Carlos A. Medel ()

Working Papers Central Bank of Chile from Central Bank of Chile

Abstract: The use of different time-series models to generate forecasts is fairly usual in the forecasting literature in general, and in the inflation forecast literature in particular. When the predicted variable is stationary, the use of processes with unit roots may seem counterintuitive. Nevertheless, in this paper we demonstrate that forecasting a stationary variable with driftless unit-root-based forecasts generates bounded Mean Squared Prediction Errors errors at every single horizon. We also show via simulations that persistent stationary processes may be better predicted by unit-root-based forecasts than by forecasts coming from a model that is correctly specified but that is subject to a higher degree of parameter uncertainty. Finally we provide an empirical illustration in the context of CPI inflation forecasts for three industrialized countries.

Date: 2012-07
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-for, nep-mon and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.bcentral.cl/documents/33528/133326/DTBC_669.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:669

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 ().