Advances in Management and Applied Economics
Stock market performance and economic growth Empirical Evidence from Kenya using Causality Test Approach
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This study investigates the causal relationship between stock market performance and economic growth in Kenya for the period 2001-2010, using quarterly secondary data. The objective was to empirically analyze using the Granger causality test and establish the link between stock market performance and economic growth (i.e. whether stock market performance causes economic growth or itself is a consequence of increased economic activity). Although there are numerous empirical researches conducted with regard to the correlation between financial market and economic growth, majority of them have focused on the implication of banks and the credit markets on economic growth. No single research had constituted an in-depth study of the causal relationship between stock market performance and economic growth in Kenya before. The investigation of the causal relationship was conducted using the popular Granger causality test based on the Vector Autoregressive (VAR) model. The statistical techniques used include the unit root Augmented Dickey Fuller test in order to fulfill the objective of stationarity for all the time series in their levels and first differences. The Johansen co-integration test was used to investigate whether the variables are cointegrated of the same order taking into account the trace statistics and the maximum eigen-value tests. The variables were found to be cointegrated with at least one co-integrating vector. Finally, a Granger causality test was used in order to find the direction of causality between stock market performance and economic growth within the estimated model. The findings imply that the causality between economic growth and stock market runs unilaterally or entirely in one direction from the NSE 20-share index to the GDP. From the results, it was inferred that the movement of stock prices in the Nairobi stock exchange reflect the macroeconomic condition of the country and can therefore be used to predict the future path of economic growth.
ISSN: 1792-7552 (Online)