Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance

This paper develops a Bayesian vector autoregressive model(BVAR) for the leader of the Portuguese car market to forecast the market share. The model includes five marketing decision variables.The Bayesian prior is selected on the basis of the accuracy of the out-of-sample forecasts. We find that our BVAR models generally produce more accurate forecasts of market share. The out-of-sample accuracy of the BVAR forecasts is also compared with that of forecasts from an unrestricted VAR model and of benchmark forecasts produced from univariate (e.g., Box-Jenkins ARIMA) models. Additionally, competitive dynamics of the market place are revealed through variance decompositions and impulse response analysis.