An Empirical investigation of the relations between macroeconomic variables and the industrial sector performance in Sri Lanka

Abstract

The study investigates the nexus between macroeconomics behaviour and industry indices performance including all share price index (ASPI) movements in Sri Lanka for the period 1994-2013, using monthly series of the corresponding variables. The objective was achieved by identifying the influence of macroeconomic variables on major industrial price index and ASPI. The statistical techniques used include the unit root Augmented Dickey Fuller test in order to fulfill the objective of stationary for all the time series. 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 co-integrated with at least one cointegrating vector. A Granger causality test was used in order to find the direction of causality between industry performance and macroeconomic behaviour and finally Vector Error Correction Model (VECM) was developed to forecast the long term behaviour. The findings imply that the causality between industry performance and macroeconomic variables runs unilaterally or entirely in one direction. The results reveal that the average prime lending rate (AWPR), inflation rate, exchange rate of Britain Pounds (GBP) and Japanese Yen (JPY) affect all the five major industries while exchange rate of USD does not influence on telecommunication industry. Moreover, all the macroeconomic variables have significant influence on diversified holding industry and hotel and travel industry. Therefore, the best fitted VECM was established in diversified holdings industry and hotel industry indices. From the results, it was inferred that the movement of industry indices reflect the macroeconomic condition of the country and can therefore be used to predict the future path of industry indices behaviour. The results derived in this study can be effectively used for investment and finance decisions.