Long memory, economic policy uncertainty and forecasting US inflation: a Bayesian VARFIMA approach
| dc.contributor.author | Balcilar, Mehmet | |
| dc.contributor.author | Gupta, Rangan | |
| dc.contributor.author | Jooste, Charl | |
| dc.date.accessioned | 2026-02-06T18:43:59Z | |
| dc.date.issued | 2017 | |
| dc.department | Doğu Akdeniz Üniversitesi | |
| dc.description.abstract | We compare inflation forecasts of a vector autoregressive fractionally integrated moving average (VARFIMA) model against standard forecasting models. U.S. inflation forecasts improve when controlling for persistence and economic policy uncertainty (EPU). Importantly, the VARFIMA model, comprising of inflation and EPU, outperforms commonly used inflation forecast models. | |
| dc.identifier.doi | 10.1080/00036846.2016.1210777 | |
| dc.identifier.endpage | 1054 | |
| dc.identifier.issn | 0003-6846 | |
| dc.identifier.issn | 1466-4283 | |
| dc.identifier.issue | 11 | |
| dc.identifier.orcid | 0009-0003-9044-4464 | |
| dc.identifier.orcid | 0000-0001-9694-5196 | |
| dc.identifier.scopus | 2-s2.0-84980338782 | |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.startpage | 1047 | |
| dc.identifier.uri | https://doi.org/10.1080/00036846.2016.1210777 | |
| dc.identifier.uri | https://hdl.handle.net/11129/13864 | |
| dc.identifier.volume | 49 | |
| dc.identifier.wos | WOS:000390872700001 | |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Routledge Journals, Taylor & Francis Ltd | |
| dc.relation.ispartof | Applied Economics | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_WoS_20260204 | |
| dc.subject | Inflation | |
| dc.subject | long-range dependency | |
| dc.subject | economic policy uncertainty | |
| dc.title | Long memory, economic policy uncertainty and forecasting US inflation: a Bayesian VARFIMA approach | |
| dc.type | Article |










