Inflation rates are highly persistent and extremely difficult to predict. Most statistical predictions based on … inflation forecasting that does not specify or estimate any predictive regressions, but rather starts by estimating a … contemporaneous relation between inflation rate and a short-term interest rate, and then relies on the forward interest rate curve to …

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 … estimates, as we show in a Monte Carlo exercise. In an application to euro-area inflation we find that our forecasts compare …

) models, with and without financial frictions, for output growth and inflation in the period 1992 to 2011. We find strong … react in a timely fashion to changes in the environment, leading to real-time forecast improvements relative to other … methods of density forecast combination, such as Bayesian model averaging, optimal (static) pools, and equal weights. We show …

) models, with and without financial frictions, for output growth and inflation in the period 1992 to 2011. We find strong … react in a timely fashion to changes in the environment, leading to real-time forecast improvements relative to other … methods of density forecast combination, such as Bayesian model averaging, optimal (static) pools, and equal weights. We show …

for output growth and inflation from 1992 to 2011. We find strong evidence of time variation in the pool's weights … environment, leading to real-time forecast improvements relative to other methods of density forecast combination, such as …

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To … forecasting models from among the different candidates. I find that VAR_m2 is the best monthly model to forecast inflation in … properties of inflation in Vietnam. Then, I compute the pseudo out-of-sample root mean square error (RMSE) as a measure of …

inflation rates of Turkey and propose a new weighting scheme, the time-varying simple weighting method. Our guiding principle … the exhaustive literature of forecast combinations and apply our newly developed combination method to test for the … prospective credibility of the inflation-targeting regime of the central bank of the Republic of Turkey …

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 …

States. Similarly, our quarterly forecast for the US inflation rate consistently outperforms the Survey of Professional …Are survey-based forecasts unbeatable? They are not. This paper introduces online price indices to forecast the … Consumer Price Index. We find that online price indices anticipate changes in official inflation trends more than one month in …

overall inflation forecast errors. Perhaps more importantly, relatively small core inflation forecast errors appear to mask …Against the backdrop of an ongoing review of the inflation-targeting framework, this paper examines the real …-time inflation forecasts of the Bank of Canada with the aim of identifying potential areas for improvement. Not surprisingly, the …