the random walk model, suggests that the forecasting performance of the monetary model is superior. …

(Gaussian, Lasso-LARS, Lasso-Landweber) in forecasting the U.S. real house price growth. We also compare results with forecasts …-suited model for forecasting the U.S. real house price. Among the least square models, the individual regression with house price …

interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting … Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed …-of-sample forecasting. Finally, we argue that this new methodology can be used as an early warning system for forecasting sudden house …

generate recursive forecasts over 2000Q1-2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables …Inflation forecasts are a key ingredient for monetary policymaking - especially in an inflation targeting country such …. As such, other variables,e.g. such as alternative measures of inflation that might be of interest to policymakers, do not …

competing model consistently and significantly beats the LoLiMoT's performance in forecasting South African inflation. …The conduct of inflation targeting is heavily dependent on accurate inflation forecasts. Non-linear models have … increasingly featured, along with linear counterparts, in the forecasting literature. In this study, we focus on forecasting South …

beneficial to purge the FCI of the real effects of inflation, economic growth and interest rates, and use the identified FCI in …

Forecasting aggregate retail sales may improve portfolio investors’ ability to predict movements in the stock prices of … the retailing chains. Therefore, this paper uses 26 (23 single and 3 combination) forecasting models to forecast South …

benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1859 …