estimated trend. Based on output growth and inflation forecasts and a comparison to revised output gap estimates from policy …

separate inclusion of a labor market in the model helps to anchor inflation even in a situation of adaptive expectations, a … positive output gap and inflation above target. The estimation results show that the adaptive learning model does a better job … and inflation far above the central bank target. …

sticky price model, conditional on historical measures of inflation forecasts. Overall, the evidence is unfavorable to the … that the poor performance of the sticky information approach is driven by two key elements. First, predicted inflation in … the sticky information model places substantial weight on old forecasts of inflation. Because these consistently …

quantities faster. These results may explain the current labour market behaviour seen after the introduction of the inflation …

and disadvantages of the various output gap measures. First, I examine the usefulness of the output gap for inflation …

money in forecasting euro-area inflation. We compare the predictive performance within and among various classes of … contains relevant information for inflation in some model classes. Money-based New Keynesian DSGE models and VARs incorporating …

Time series regressions indicate that age structure has significant forecasting power on Swedish inflation. The results … corresponding to the stipulated inflation target. The age model is also considerably better than the consensus forecasts and it is …

The paper proposes two econometric models of inflation for Azerbaijan: one based on monthly data and eclectic, another … based on quarterly data and takes into account disequilibrium at the money market. Inflation regression based on monthly … data showed that consumer prices dynamics is explained by money growth (the more money, the higher the inflation), exchange …

This paper builds a short-term inflation projections (STIP) model for Latvia. The model is designed to forecast highly …) benchmarks. Across inflation components, the forecast accuracy gains are 20-30% forecasting 3 months ahead and 15-55% forecasting …

In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out … identify the key variables to predict inflation, thus helping to open the ML black box. Despite the evidence of no universal … of mean-squared error. Moreover, the results indicate the existence of nonlinearities in the inflation dynamics, which …