Vector Autoregressive Model Selection: Gross Domestic Product and Europe Oil Prices Data Modelling

 We consider the problem of model selection in vector autoregressive model with Normal innovation. Tests such as Vuong's and Cox's tests are provided for order and model selection, i.e. for selecting the order and a suitable subset of regressors, in vector autoregressive model. We propose a test as a modified log-likelihood ratio test for selecting subsets of regressors. The Europe oil prices, Brent, and the real gross domestic product, GDP, data are considered as real data. Since the Brent data does Granger-cause the GDP data, so we suggest the vector autoregressive model and select optimal model based on the model selection test. The analysis provides analytic results show that the Vuong's, Cox's and proposed test are the appropriate test for order and model selection for vector autoregressive models with Normal innovation. In simulation study, the power of proposed test at least is as good as the power of Vuong's test.