output gap estimates and forecast horizons, the results point clearly to a lack of any usefulness of real-time output gap … estimates for inflation forecasting both in the short term (one-quarter and one-year ahead) and the medium term (two-year and … forecast real GDP growth, particularly in the short term, and some appear also useful in the medium run. No single output gap …

output gap estimates and forecast horizons, the results point clearly to a lack of any usefulness of real-time output gap … estimates for inflation forecasting both in the short term (one-quarter and one-year ahead) and the medium term (two-year and … forecast real GDP growth, particularly in the short term, and some appear also useful in the medium run. No single output gap …

, subsequently, we didn't see the inflation they predicted. We show that these puzzles disappear in a Vector Autoregressive model … much of the inflation dynamics in the 2012-2014 euro area missing inflation episode. Consequently, economists and models … that excessively focused on the global nature of inflation were liable to miss the contribution of deflationary domestic …

We use several US and euro-area surveys of professional forecasters to estimate a dynamic factor model of inflation … featuring time-varying uncertainty. We obtain survey-consistent distributions of future inflation at any horizon, both in the US … and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that …

forecasters is consistent with evidence on mean forecast errors. We find considerable evidence of inflation-gap persistence and …We provide a new way to filter US inflation into trend and cycle components, based on extracting long-run forecasts …, then estimating parameters, and then extracting the stochastic trend in inflation. The trend-cycle model with unobserved …

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 U.S. inflation based on autoregressive and structural models of the …

modifies a wage–price-setting (WPS) model to forecast U.S. inflation over one- to three-year horizons. The out …-of-sample forecast results show that productivity growth is a useful predictor of inflation, in the sense that the modified WPS model … improves upon some univariate benchmark models during the 1990Q1–2020Q2 period. Since the early 2000s, forecast accuracy can be …

This paper proposes an empirical investigation of the impact of oil price forecast errors on inflation forecast errors … oil price forecast errors to the explanation of inflation forecast errors, whatever the country or the period considered …. Second, the pass-through of oil price forecast errors to inflation forecast errors is multiplied by around 2 when the oil …

, introducing slack into models estimated using headline PCE inflation data or conventional core inflation data causes forecast …Using state-space modeling, we extract information from surveys of long-term inflation expectations and multiple … quarterly inflation series to undertake a real-time decomposition of quarterly headline PCE and GDP-deflator inflation rates …

In this paper we develop a small open economy model explaining the joint determination of output, inflation, interest … Zeitpunkten werden präsentiert und diskutiert. -- Mehrländermodell ; Prognose ; Bayesianische Ökonometrie …