Abstract: Electricity price has often been analyzed using univariate time series approach, where for example autoregressive and moving average models were used to model and forecast. But these univariate econometric models are not able to capture the evolution and the interdependencies between multiple time series; to measure the effect of each independent variable on dependent variable. This research project was aimed to measure the effects of Consumer Price Index CPI; fuel price FP and gasoil price GP on electricity price EP in Rwanda. This study used a vector autoregressive model to evaluate the effects of the oil price and consumer price index on electricity price in Rwanda. The model used observed secondary data from 2006 to 2015 on oil price, and consumer price index. Unit root test was conducted in order to know if the data are stationary. The co-integration approach was employed to investigate the long-run relationship between electricity price and variables mentioned above. Ordinary least square was adopted as estimation technique of the parameters to test their adequacy, also Granger causality tests were used to analyze the dynamic relationship between electricity price and its independent variables. The impulse response functions and variance decomposition were used to show how the fluctuations in oil prices and consumer price index affect the electricity price in Rwanda. In this study, Eviews software was used for data analysis and the results revealed that the considered variables are not co integrated, means that there is no long run relationship among the variables.
Keywords: Vector autoregressive, VAR model, Consumer price index, inflation, and Oil price.
Title: Effect of Oil Prices and Inflation on the Cost of Electricity in Rwanda: A Multivariate Time Series Approach
Author: Sylvere NYANDWI, Dr. Mung'atu Joseph, Dr. Ndengo Marcel
International Journal of Management and Commerce Innovations
ISSN 2348-7585 (Online)
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