The difficulty in modelling inflation and the significance in discovering the underlying data generating process of inflation is expressed in an ample literature regarding inflation forecasting. In this paper we evaluate nonlinear machine learning and econometric methodologies in forecasting the...

We investigate whether fluctuations in U.S. inflation rates are better described by infrequently occurring large shocks or by frequently occurring small shocks. We estimate a model that encompasses the two hypotheses within the framework of non-Gaussian state-space models. Our results indicate...

In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out-of-sample forecasting exercise is designed with multiple horizons, a large database of 501 series, and 50 forecasting methods, including new ML techniques proposed here,...

In general, central banks are concerned with keeping the inflation rate stable while also sustaining output close to an efficient level. Under "inflation targeting", forecasts of the evolution of the general price level are an essential input for policy decisions and these are usually released...

Anchored inflation expectations are of key importance for monetary policy. If long-terminflation expectations arewell-anchored, they should be unaffected by short-term economic news. This letter introduces newsregressions with multiple endogenous breaks to investigate the de- and re-anchoring of...

This paper presents a set of new core inflation measures for Brazil based on the Singular Spectrum Analysis (SSA) method. The measures are based on the official target used in the Brazilian inflation targeting regime. The period of analysis ranges from the beginning of the inflation targeting...

In this paper, we study the fit and the predictive performance of the Phillips curve for euro area inflation with regard to different inflation series, time periods and predictor variables, notably different global factors. We compare the relative performance of a large set of alternative global...

To evaluate the price forecasts, we use two data frequencies i.e., annual and quarter with two most demanding techniques, i.e., ARIMA and VAR models to forecast the four index of inflation, named, Consumer Price Index (CPI), Wholesale Price Index (WPI), GNP Price Deflator (GNPPD), and Implicit...

The use of different time-series models to generate forecasts is fairly usual in the forecasting literature in general, and in the inflation forecast literature in particular. When the predicted variable is stationary, the use of processes with unit roots may seem counterintuitive. Nevertheless,...