This paper compares the out-of-sample forecasting accuracy of five classes of time series models for market shares of … employ a random-walk with drift (Naive), a univariate ARIMA, a near-VAR and a general BVAR. The out-of- sample forecasts are … also compared against forecasts generated from structural econometric market share models (SEM). Using four accuracy …

deflator, it provides a root mean square forecasting error (RMFSE) of 1.0% at a four-year horizon for the period between 1971 … Johansen cointegration rank test based on a VAR representation, which is also proved to be an adequate one via a set of … are cointegrated in corresponding intervals. The VAR and vector error correction (VEC) models are estimated and provide …

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 … variety of specification tests and the Johansen cointegration rank test based on the VAR representation. Both approaches …

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed … pseudo out-of-sample forecasting exercise with US real-time data yields that the mixed frequency VAR substantially improves … frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon …

There are many econometric methods for forecasting by different economic variables in the future. recently, the … procedures of dynamic forecasting either for univariate or multivariate models were available for estimation on the software … models, with respect to, estimation, choosing the best fit model for forecasting by the economic variables, i.e., labor and …

Comparative analysis of economic structure and forecasts generated from simultaneous equation, VAR and autoregressive …

The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single … single-equation MS models tend to perform slightly better than linear VAR models when no leading information is available … than linear VAR models. …

-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a ‘ProbVAR’. At any … short-term interest rate, stock returns or corporate bond spreads. The forecasting performance is very good for the United …

This paper evaluates the performance of 11 vector autoregressive models in forecasting 15 macroeconomic variables for … outperforms others at all horizons for any of the variables, the Bayesian VARs and Bayesian Factor Augmented VAR models on average …