Long memory, economic policy uncertainty and forecasting US inflation: a Bayesian VARFIMA approach

C-Tier
Journal: Applied Economics
Year: 2017
Volume: 49
Issue: 11
Pages: 1047-1054

Score contribution per author:

0.335 = (α=2.01 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:taf:applec:v:49:y:2017:i:11:p:1047-1054
Journal Field
General
Author Count
3
Added to Database
2026-01-24