, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to …

We evaluate the forecasting performance of six different models for short-term forecasting of Macedonian GDP: 1) ARIMA …

forecasting accuracy within factor modelling framework. Nested data means disaggregated data or sub-components of aggregated … mean square error is employed as the standard tool to measure forecasting accuracy. According to this empirical study we … enhance Latvian GDP forecasting accuracy. The efficiency gain improving forecasts is about 0.15-0.20 percentage points of year …

from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation …, Survey of Professional Forecasters, and the Michigan Survey. While useful in developing models of forecasting inflation …

Michigan Surveys of Consumers. While these measures have been useful in developing models of forecasting inflation, the data …

This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs … Carlo experiment, and in forecasting 4 macroeconomic series of the UK using time-varying parameters vector autoregressions … (TVP-VARs). Restricted models consistently improve upon their unrestricted counterparts in forecasting, showing the merits …

finance; for such tasks as pattern reorganization, and time series forecasting, have dramatically increased. Many central … banks use forecasting models based on ANN methodology for predicting various macroeconomic indicators, like inflation, GDP … ANN model with conventional univariate time series forecasting models such as AR(1) and ARIMA based models and observed …

-- 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …