Inflation is a monetary phenomenon. While this statement is widely accepted in terms of a long-run relationship, the quantity theory has been made operational also for the short-run dynamics of inflation by so-called Pstar models. An error correction model with quarterly data for the Euro Area...

This paper revisits inflation forecasting using reduced-form Phillips curve forecasts, that is, inflation forecasts that use activity and expectations variables. We propose a Phillips-curve-type model that results from averaging across different regression specifications selected from a set of...

This study presents extensive results on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging can be...

Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the...

We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary...

We present results from an extensive study on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging...

US inflation appears to undergo shifts in its mean level and variability. We evaluate the performance of three useful models for capturing such shifts. The models studied are the Markov switching models, state space models with heavy-tailed errors, and state space models with compound error...

We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary...

We evaluate the ability of several univariate models to predict inflation in a number of countries and at several forecasting horizons. We focus on forecasts coming from a family of ten seasonal models that we call the Driftless Extended Seasonal ARIMA (DESARIMA) family. Using out-of-sample Root...

The aim of this paper is to investigate the evidence and implications of time-variation and asymmetry in the persistence of U.S. inflation. We evaluate these features by comparing the out-of-sample forecast performance of two specifications, a Quantile Auto-Regressive (QAR) model and a...