Forecasting Performance 12+

📒 This research attempts to make comparison of the forecasting performance of regression models and time series models. The primary purpose behind this research was to find out which of the two models - regression model and univariate non seasonal ARIMA model - is more accurate and appropriate for forecasting purposes in the real world, keeping in view the cost of the model building. The research utilized data on Pakistan's exports. The performance of regression models was compared with that of ARIMA models by using the statistics, TIC, RMSPE, MAE, MPE and MAPE. The comparison indicates that the ARIMA models perform much better than the regression models. It was also observed that the plots of actual values of the variables and those of the predicted values based on ARIMA model were closer than those of regression model. This result further supports that the ARIMA models perform better than the regression models. On the basis of the findings and discussion, it is strongly recommended that findings of the this research work may be implemented in policy making, especially in planning and development in developing countries like Pakistan because it is cost effective and more accurate.