improve the transparency of machine learning-based forecasts. Applying the framework to Turkey reduces forecast errors by at …

paper show that the real-time consideration of these forecasts has the potential to improve the precision with which past … forecasts is also aptly demonstrated through the use of simulation techniques, density functions, and event probability … forecasts. …

cointegration tests, VAR models with an error-correction term, impulse responses, variance decompositions and forecasts generated … Indian real output. Finally, forecasts generated for the period 2012-2016 are promising; total tourism expenditure compared … to the previous half-decade will grow at a similar pace and optimistic forecasts are generated for the case of LTS, BTS …

This paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabilistic forecasts and …

cointegration tests, VAR models with an error-correction term, impulse responses, variance decompositions and forecasts generated … Indian real output. Finally, forecasts generated for the period 2012-2016 are promising; total tourism expenditure compared … to the previous half-decade will grow at a similar pace and optimistic forecasts are generated for the case of LTS, BTS …

. This is accomplished by making use of consensus forecasts of GDP growth and by studying the properties of distributions of … specific consensus forecasts. Information contained in the distributions can be used to make uncertainty assessments of future …

used an econometric model similar to the one used by Kitchen and Monaco (2003), and I made forecasts regarding the economic … growth of Romania. The model is combining different individual forecasts of GDP in order to supply a final result regarding … making projections regarding the economic growth, I consider that future research regarding forecasts of GDP should rely more …

This paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabilistic forecasts and …