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Inflation forecast plays a very important role for stabilizing the economy. In Vietnam, inflation is measured via consumer price index (CPI). CPI’s changes depend on many factors in which the merchandises’ price changes are direct factors and those changes are not difficult to observe. The aim of our research is to propose a CPI forecasting model based on the change of merchandise pricing since such a model has not been built so far. A comprehensive study has been carried out to understand the effects of price changes of merchandises on CPI. After that Nonlinear Smooth Transition Regression Model and Mining Association Rules are applied to build the model. The model parameters were configured and justified using actual data collected in two years 2008-2009. The results showed the accuracy of the model for CPI forecast in Vietnam and the model can also be used to predict the price changes of merchandises.

Building CPI Forecasting Model by Combining the Smooth Transition Regression Model and Mining Association Rules