Application of Grey Theory to the Field of Economic Forecasting

Grey theory was proposed by Prof. Deng [1] for more than 30 years. It has been successfully applied in many academic fields, such as electrical engineering, education, mechanical engineering, agriculture, high-tech sectors and so on [2-8]. Grey theory is famous for easy calculation and satisfactory result. Comparing to other methods, grey theory need only as few as four data could be modeled to forecast. There is no normality test needed beforehand and there is no level of significance test afterward. This is because that it is impossible to find any regularity based only on these four raw data. The criteria for testing the availability of modelling is relative percentage error (RPE) and average relative percentage error (ARPE) which are most commonly adopted. Therefore, the grey theory is suitable for short term forecasting or temporary reference for making decision or strategy when only limited data in hands.