Short Term Inflation Forecasting: The M.E.T.A. Approach

Abstract

Forecasting inflation is an important and challenging task. In this paper we assume that the core inflation components evolve as a multivariate local level process. This model, which is theoretically attractive for modelling inflation dynamics, has been used only to a limited extent to date owing to computational complications with the conventional multivariate maximum likelihood estimator, especially when the system is large. We propose the use of a method called "Moments Estimation Through Aggregation" (M.E.T.A.), which reduces computational costs significantly and delivers prompt and accurate parameter estimates, as we show in a Monte Carlo exercise. In an application to euro-area inflation we find that our forecasts compare well with those generated by alternative univariate constant and timevarying parameter models as well as with those of professional forecasters and vector autoregressions.JEL Classification: C32, C53, E31, E37.

Core Inflation and Trend Inflation

“…In addition to the literatures discussed above on core and trend inflation, this work is related to three other large literatures. First, our modeling framework extends work estimating common factors of multiple inflation series, including Cristadoro, Forni, Reichlin, and Veronese (2005), Amstad and Simon M. Potter (2007), Altissimo, Mojon, and Zaffaroni (2009), Boivin, Giannoni, and Mihov (2009), Reis and Watson (2010), and Sbrana, Silvestrini, and Venditti (2015). Mumtaz and Surico (2012) introduce stochastic volatility and time-varying factor dynamics into a model of 13 international inflation rates.…”

Core Inflation and Trend Inflation

“…In addition to the literatures discussed above on core and trend inflation, this work is related to three other large literatures. First, our modeling framework extends work estimating common factors of multiple inflation series, including Cristadoro, Forni, Reichlin, and Veronese (2005), Amstad and Simon M. Potter (2007), Altissimo, Mojon, and Zaffaroni (2009), Boivin, Giannoni, and Mihov (2009), Reis andWatson (2010), andSbrana, Silvestrini, andVenditti (2015). Mumtaz and Surico (2012) introduce stochastic volatility and time-varying factor dynamics into a model of 13 international inflation rates.…”