MODELLING RATES OF INFLATION IN KENYA:AN APPLICATION OF GARCH AND EGARCH MODELS

Abstract

The e ects of in ation on the economy are diverse and can both be bene cial or detrimental to the economy. The negative e ects are however most pronounced and comprises a decrease in real value of money as well as other monetary variables. As a result uncertainty over future in ation rate may discourage consumers. It may also lead into decrease in foreign investments in a country. The purpose of this study was to determine an e ective Arch-type model for forecasting Kenya's in ation. Using Kenya monthly in ation data from January 1990 to December 2015, the performance of GARCH and EGARCH type models were analyzed to come up with the best model for forecasting Kenyan in ation data. Since the in ation series is non-stationary, the Consumer Price Index (CPI) was rst transformed to return series by logarithmic transformation. Afterwards, the data was tested for the presence of ARCH e ects and serial correlation using both Ljung Box Pierce Q test and Engle Arch test. The test showed presence of heteroscedasticity and correlation in the in ation return series which is a key feature of a nancial time series data.The project adopted AIC and BIC approach in selecting the the best model. From the tted models EGARCH(1,1) had the smallest AIC and BIC values followed by the GARCH(1,1) model. Model diagnostic test was conducted on the selected model EGARCH (1,1) to determine its adequacy and goodness of t. QQ plot was tted to the residuals of the model and fairly straight line was produced looking roughly linear.Furthermore weighted Ljung Box Test on standard squared residuals showed the absence of correlation in the model. In conclustion, EGARCH(1,1) model is the best

model for forecasting Kenyan in ation data.