The marketing survey of thirty products has been included in the consumer basket of Georgia. Information obtained from the respondents’ surveys on the current and consumable acceptable prices of products are used by this information to construct linear, indicative and linear models to reflect the change in time.
The often-disturbing adverse effects of inflation in developing economies such as Nigeria necessitates developing dynamic inflation forecasting models for appraising shocks on macroeconomic variables. This work utilizes the Box-Jenkins methodology to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict peak time inflation in Nigeria’s inflation time series from January 2001 to December 2015 obtained from National Bureau of Statistics, Abuja. A test of parameter estimates was performed on the suggested models and, using the AIC and BIC criteria, SARIMA(1,1,2)(2,0,1)12 model was identified as the most fitted model. The diagnostic test of the residuals using ACF and PACF of residual plots showed that they follow white noise process. The result of the monthly forecast indicated that Nigeria will experience high (double digit) inflation rates which will be at its peak in the months of August and September and its lowest rate occurs in January of the year. The information contained here can be useful to ensure monetary and fiscal policies that will stabilize the economy.
Marketing information is used by financial and insurance institutions, business enterprises and companies for planning, control, monitoring and forecasting purposes in business. One of the problems is the detection and investigation of factors, which influence the behavior of consumers. Such a basic factor is, for instance, the consumer prices index. The significance of this factor periodically changes and depends on the values of main indexes of economy such as export, import, taxes, labor force, unemployment, inflation level, etc., and also on the behavior of consumers, their taste, living standard and style. For the marketing research of this dependence it is necessary to construct mathematical models of the evolution of consumer prices. In the paper, a new auto regression model with disturbances is constructed for consumer prices. The model includes monetary aggregate amount and control function. A new formula is derived for the solution of an equation for the consumer prices index, which can be used in forecasting the inflation process. Using the data on the consumer prices index in Georgia, a numerical example is given, which illustrates the estimates of the coefficients of the constructed model and the inflation process forecast.