Application of Consistency and Efficiency Test for Forecasts

The purpose of this study is to evaluate forecast efficiency by using forecast of food price inflation, consumer price index general, GDP per capita and Money supply data of Pakistan. It is therefore designed to analyze forecasting efficiency by applying consistency and efficiency criteria for annual data covering the period 1975 to 2008. Forecasts are obtained from ARIMA (auto regressive integrated moving average) model specification. Four forecasting accuracy techniques, such as, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Theil’s Inequality Coefficient (TIC) are used to be able to select the most accurate forecast model .Later on these forecasts are evaluated on the basis of consistency and Efficiency criterion defined. We found food price forecast are consistent and efficient, therefore can be used in policymaking and management decision. Forecasts test may be used before any further appliance. Keywords: Food price Forecasts, ARIMA forecasts, Consistency test, Conditional Efficiency test.