of comparable VAR that fails to recognize that the system is characterized by cointegration. I use Monte Carlo simulation … knowledge of cointegration rank. Furthermore the results indicate that a cointegration modeling of credit risk should be favored …

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 …

of comparable VAR that fails to recognize that the system is characterized by cointegration. I use Monte Carlo simulation … knowledge of cointegration rank. Furthermore the results indicate that a cointegration modeling of credit risk should be favored …

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 …

the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have …