Long-Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation
Rangan Gupta () and
Stephen Miller ()
Additional contact information
Heni Boubaker: International University of Rabat, BEAR LAB, Technopolis Rabat-Shore Rocade-Sale, Morocco
No 201869, Working Papers from University of Pretoria, Department of Economics
We report the results of applying semi-parametric long-memory estimators to the historical monthly series of U.S. inflation, and analyze their empirical forecasting performance over 1, 6, 12, and 24 months using in-sample and out-of-sample procedures. For comparison purposes, we also apply two parametric estimators, the naive AR(1) and the ARFIMA(1, d, 1) models. We evaluate the forecasting accuracy of the competing methods using the mean square error (MSE) and mean absolute error (MAE) criteria. We evaluate the statistical significance of forecasting accuracy of competing forecasts using the Diebold-Mariano (1995) test. Overall, our results preforms slightly better than the Lahiani and Scaillet (2009) threshold estimator based on the MSE and MAE criteria. This improvement in performance does not prove significant enough to cause a rejection of the null hypothesis of equality of predictive accuracy. The Boubaker (2017) estimator, on the other hand, significantly outperforms the time-invariant estimators over longer horizons. Over shorter horizons, however, the Boubaker (2017) estimator does not exhibit a significantly better predictive performance than the time-invariant long-memory estimators with the exception of the naive AR(1) model.
Keywords: long memory; wavelet analysis; time-varying persistence (search for similar items in EconPapers)
JEL-codes: C13 C22 C32 C54 E31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets, nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201869
Access Statistics for this paper
More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().