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

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Authors

Balcilar, Mehmet
Gupta, Rangan
Jooste, Charl

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Routledge

Abstract

We compare inflation forecasts of a vector fractionally integrated autoregressive 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.

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Keywords

Inflation, Long-range dependency, Vector fractionally integrated autoregressive moving average (VARFIMA), Economic policy uncertainty (EPU)

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Mehmet Balcilar, Rangan Gupta & Charl Jooste (2017) Long memory, economic policy uncertainty and forecasting US inflation: a Bayesian VARFIMA approach, Applied Economics, 49:11, 1047-1054, DOI: 10.1080/00036846.2016.1210777.