Testing Linkages amongst 5 African Emerging Markets

Abstract

The goal of most empirical studies in econometrics and other social sciences is to determine whether a change in one variable causes a change in or help to predict another variable. Granger causality modeling approach is quite popular in experimental and non – experimental fields which involve some dynamic econometric time series methodologies. In this research, granger causality and co-integration tests were employed in the empirical modeling of five selected African countries and the data was obtained from Morgan Stanley Capital International (MSCI) index. The results alternated between unidirectional and non-causality among the selected tests, we tested for stationarity in the variables using the Augmented Dickey – Fuller (ADF) procedure. The variables proved to be integrated of either I(1) or I(2). Johansen co-integration test reveals that at 5% level of significance, we have at least four co-integrating pairs among the variables. This verifies the fact that when two or more time series are co – integrated, there must be either bi-directional or unidirectional Granger causality between them. Our findings reveal that Tunisia Granger cause Kenya and also Tunisia Granger cause Morocco.