DSGE models have recently received considerable attention in macroeconomic analysis and forecasting. They are usually …

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related … overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by …

the problem of impulse response estimation in VAR-based systems. The BGSVAR is designed as a robust empirical framework … structural dynamics of VAR-based models and produces better impulse response estimates than the LASSO and BVAR …

In this paper, we compare two fundamentally different judgmental demand forecasting approaches used to estimate demand …

inflation down to the 2% target level. The time varying model also performs remarkably well in forecasting and delivers …

This paper performs a comparative analysis of estimation as well as of out-of-sample forecasting results of more than … estimates of the migration function. Out-of-sample forecasting results indicate the following: (i) the standard fixed effects … variables estimators, (iv) forecasting performance of heterogenous estimators is mediocre in our data set. …

-term predictions. Due to the characteristics of the residuals, a bootstrapping method of forecasting was also used, yielding even …

This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The …

forecasting occur much less frequently than indicated by existing tests. …