Domestic Credit Growth Analysis using ARIMA Technique: A Case Study of Kenya

Abstract

The aim of this paper is to technically analyze domestic credit growth in Kenya using the Box -Jenkin framework. Box -Jenkin technique uses ARIMA model, which is used to understand time series data and forecast future values of the observed data for a given period. The framework involves three iterative step to develop a model The first step involves model parameter identification. Unit root test show that domestic credit is stationary after the first difference. The ACF and PACF indicates cut off at lag zero in both cases. There are seasonal component in the ARIMA model. In the second step of model estimation, ARIMA(2,1,2)(1; 0; 0)12 is obtained as the best fit for the sample period under consideration. Model diagnostics test in the third step, proves that there ARIMA modeling assumptions are met. The estimated model is used to forecast credit growth for the next twelve monthly values in year 2024 upto December. The estimated model projects an increase trend in domestic credit growth for the year 2024, with the percentage growth rate ranging between 1.045 to 1.230 percent. The expected domestic credit value in December 2024 is yellow is highly likely to hit Kenya shilling 8.039 Trillions mark. Kenya government should put in place monetary policy that favors bank credit growth and competition in the banking sector.