Capital Market Predictive Power on the Development of the Nigerian Economy: An Impulse Response and Variance Decomposition Approach (Published)
The study is an empirical investigation of the contributions of the Nigeria’s capital market to the development of Nigerian economy. Most researchers focused on capital market and growth nexus, where as we deviated by focusing on the role played by capital market in ensuring reduction of unemployment and poverty in Nigeria. Specifically, we investigated the contributions of market capitalization (MCAP), value of share traded (VST) and all share index (ASI) to unemployment rate (UNPR) and poverty (NPI) reductions in Nigeria within the period 1981 to 2017. The data series used were sourced from the annual statistical bulletin of the central bank of Nigeria (CBN) and Nigeria stock exchange (NSE). Preliminary analyses of stationarity and cointegration tests revealed that the series were non stationary at levels; and cointegrated respectively. The result of the impulse response functions (IRF) and variance decompositions from the two models considered revealed that the contributions of the capital market to poverty reduction in Nigeria is highly insignificant, while it contributes fairly to unemployment reductions in Nigeria within the study period. Conclusively, the research reveals that the Nigeria capital market is not contributing optimally to the development of Nigeria’s economy as this is evident on its abysmal contributions to poverty and unemployment reductions. In line with the findings of this work, we recommend that the Nigeria capital market should be repositioned in a way that it can optimally contribute to the reduction of unemployment and poverty in Nigeria.
This study aims to determine and analyze the influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and the exchange rate of rupiah/US dollar towards the transmission on CPO export prices of Indonesia. This study uses quantitative analysis model with the approach of vector autogression model (VAR) which includes three main analysis tools namely Granger causality test, impulse response function (IRF) and forecast error decomposition of variance (FEDV). The variables which are used in this research are world petroleum price, world soybean oil price, CPO price of Rotterdam, CPO export price of Indonesia, fresh fruit bunch price and real exchange rate (real exchange rate). From Granger Causality test result, The price transmission process takes place the plot as follows: world crude oil prices significantly influence the CPO price of world (Rotterdam) which will significantly influence the world soybean oil prices and so on have a significant influence on the value of the real exchange rate which will influence the price of fresh fruit bunches and ultimately have a significant influence on CPO price export of Indonesia. From the estimation result of VAR model, there are significant influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and rupiah/US dollar exchange rates simultaneously to the transmission on CPO export prices of Indonesia. Based on analysis of Impulse response and variance decomposition, in the first period, one hundred percent average variability of CPO export price growth is significantly explained by the average growth of CPO export prices itself. In the subsequent period, the average variability of CPO export price growth is significantly explained by the average growth of CPO export price itself as well as other variables.