COMESA Secretariat Ben Bella Road, P.O. Box 30051, Lusaka, Zambia

*Corresponding Author E-mail: MSukati@comesa.int

Accepted 20 August, 2015

This paper investigates the concept of vector autoregression (VAR) and cointegration using a bivariate model of global oil prices and headline Consumer Price Index (CPI) in South Africa. The study aims to determine how much of inflation is driven by oil prices. Particular attention is paid to the theoretical underpinnings of cointergration analysis and the application of STATA software to undertake such analysis and perform test statistics. This study has observed that global oil prices are one of the key drivers of inflation in South Africa. Further, the estimate of the coefficient for the CPI show that when the price of oil is high, the consumer price index slowly adjusts upwards to match the oil prices, while the oil price attempts to adjust down, probably due to high commodity prices and reduced consumer demand, leading to reduced demand for oil. Increase in oil prices in South Africa is associated with higher inflation compared to other countries. This is not surprising since South Africa is an oil importing country and has limited policy control over oil prices.

Keywords: VAR, Consumer Price Index, Oil Prices, STATA, South Africa

How To Cite This Article:

Mphumuzi Angelbert Sukati. Cointegration Analysis of Oil Prices and Consumer Price Index in South Africa using STATA Software. Swift Journal of Social Sciences and Humanity 1(2), pp. 013-023.