forecasting ability has been compared to that of a linear univariate benchmark (ARIMA) model. Main forecast diagnostics have been …

-term relationship. We finally conclude by comparing the forecasting ability of these two approaches with classical models such as Random …

horizons, the STVAR model increases its forecasting ability over the linear models, whereas the NN model does not outperform …

horizons, the STVAR model increases its forecasting ability over the linear models, whereas the NN model does not outperform …

different types of econometric models for oil price forecasting. Several specifications have been proposed in the economic …). The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should … common sample and common data. Fourth, we evaluate the forecasting performance of each selected model using static and …

We assess the power of artificial neural network models as forecasting tools for monthly inflation rates for 28 OECD … countries. For short out-of-sample forecasting horizons, we find that, on average, for 45% of the countries the ANN models were … models can also serve as a credible tool for forecasting inflation. …