wondering how to choose the sample for estimating forecasting models. When we forecast inflation in 2014, for example, should we … applied to forecasting US real output growth and inflation, the proposed method tends to improve upon conventional methods. …While forecasting is a common practice in academia, government and business alike, practitioners are often left …

macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate … predictions for the three variables. In particular for inflation the TV-VAR outperforms, in terms of mean square forecast error … also shown to hold over the most recent period in which it has been hard to forecast inflation. …

Inflation is a far from homogeneous phenomenon, a fact often neglected in modelling consumer price inflation. This … study, the first of its kind for an emerging market country, investigates gains to inflation forecast accuracy by … aggregating weighted forecasts of the sub-component price indices, versus forecasting the aggregate consumer price index itself …

simple to construct and appear to work well in a variety of cases explored empirically and by simulation. The proposed … inflation. …

autoregessions in inflation and output gap measures. Density combination utilizes a linear mixture of experts framework to produce … detrending filters. The resulting ensemble produces well-calibrated forecast densities for US inflation in real time, in contrast …

to construct simple statistics to evaluate the local internal consistency of a forecasting exercise of a system of …

indices over the period 1995-2003. We find strong evidence in support of ‘thick’ modelling proposed in the forecasting …

an effect of a US shock. More generally, the models have a good forecasting performance over short horizons. …

volatilities, and a hierarchical specification for the prior means, improve model fit and forecasting performance. …