We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated...

We study the inflation uncertainty reported by individual forecasters in the Survey of Professional Forecasters 1969-1999. Three popular methods of estimating uncertainty from survey data are analysed in the context of models for forecasting and asset pricing. We find that inflation uncertainty...

This paper is organized in two parts, the presentation of the model of inflation for Romania, and the results of different scenarios starting from the base model. The purpose of the paper is to present an efficient instrument for the simulation and research of inflation and its determinants in...

The purpose of the paper is to present an efficient instrument for simulation and research of inflation and its determinants in Romania, with a focus on the short-term impact of changes in money, foreign exchange and wage policies and controlled prices as well as the impact of external shocks as...

We study the inflation uncertainty reported by individual forecasters in the Survey of Professional Forecasters 1969-2001. Three popular measures of uncertainty built from survey data are analyzed in the context of models for forecasting and asset pricing, and improved estimation methods are...

This paper compares forecast performance of the ALI method and the MESMs and seeks ways of improving the ALI method. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. The ALI method is found to produce better forecasts than...