Summary: This paper examines the longterm forecast performance of cointegrated systems relative to forecast performance … of comparable VAR that fails to recognize that the system is characterized by cointegration. I use Monte Carlo simulation …, as well as a vector autoregression based upon the levels of the data. Alternative measures of forecast accuracy (full …

Summary: This paper examines the longterm forecast performance of cointegrated systems relative to forecast performance … of comparable VAR that fails to recognize that the system is characterized by cointegration. I use Monte Carlo simulation …, as well as a vector autoregression based upon the levels of the data. Alternative measures of forecast accuracy (full …

business surveys data and to aggregate the nation-wide forecast into the Euro-zone forecast, we propose using an approach based …

Monthly time-series data based on agricultural commodities tend to present strong and particular patterns of … domestic supply of three agricultural commodities in Argentina between 1994 and 2008, which observe the patterns of seasonality …

forecast error (RMSFE) of 1.0% per year at a four-year horizon for the period between 1971 and 2004. The same RMSFE is … naive (no change) forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year, respectively. Our model outperforms … the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have …

Forecasting the nominal exchange rate has been one of the most difficult exercises in economics. This study employs the … identified cointegrated vector. Out of sample forecasting analysis of parsimonious short run dynamic error correction model is …

deflator, it provides a root mean square forecasting error (RMFSE) of 1.0% at a four-year horizon for the period between 1971 … and 2004. The relationship is tested for cointegration. All three variables involved in the relationship are proved to be … integrated of order one. Two methods of cointegration testing are used. First is the Engle-Granger approach based on the unit …

obtained for the USA is characterized by A1=4.0, A2=-0.03075, and t1=2 years. It provides a root mean square forecasting error … (RMFSE) of 0.8% at a two-year horizon for the period between 1965 and 2002 (the best among other inflation forecasting models …) and has a perfect parsimony - only one predictor. The relationship is tested for cointegration. Both variables are …

model of interest rate determination. The empirical part consists of a cointegration analysis with an error correction … model in different forecasting exercises. …