This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not su¢ciently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a...

In this study I use the Bayesian VAR framework to forecast the dynamics of output for the Romanian economy. I estimate several versions of Bayesian VARs and compare them in terms of forecasting statistics with two standard models, the OLS and the unrestricted VAR, as well as with a naïve...

Energy from the sun is weather-dependent. In modern electric grids that is a shortcoming; generation (and load) has to be regulated accordingly. This issue is a cornerstone for an effective transition to a renewable-based energy system. Weather forecast algorithms can predict photovoltaic...

В статье рассматривается проблема создания системы управления результатами деятельности предприятия. Предложены этапы, последовательность и алгоритм...

In this study, I estimate a monetary DSGE model using Bayesian techniques and I use the estimated model to forecast the Romanian GDP in the long run. For the 2008-2010 period, the forecasts with the model confirm the present consensus among the economists about a growth potential of 5 to 6% for...