Forecasting the industrial sector growth in Rwanda using Box

Forecasting the industrial sector growth in Rwanda using Box–Jenkins (BJ) methodology

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In the three main sectors that constitute a country’s economy we find the industrial sector regarded as the secondary sector of the economy after the agricultural sector which is the primary sector of the economy. This sector of the economy comprises of of economic activities performed by companies, organizations and people engaged in the production of services and goods in a given field reason why industries are categorized according to the goods and services they produce.

The government of Rwanda makes projections of its revenues in order to model its monetary and fiscal policy for it to achieve that objective it is better to have a model that can estimate the future values of revenues that can be generated from the industrial sector as one of the three main sectors that makes up the economy of Rwanda.

A successful time series forecasting is imperatively dependent on an appropriate fitting model. Industrial sector in Rwanda is one of important factors of the economic growth in Rwanda, with the development of the industrial sector in Rwanda, predicting the future behavior of this sector output comprises uncertainty due to the ignorance of mathematical and statistical techniques while doing predictions. The interest of this study is to find an ARIMA model which is most appropriate to forecasting industrial growth in Rwanda using Eviews.

The Box-Jenkins methodology is the one which was used in this paper and based on the research obtained, we identified the model appropriate to forecasting industrial output in Rwanda as ARIMA (2,1,10). And based on the model selected the estimated forecast of the industrial output in Rwanda will increase on average of 0.35 percent quarterly in the period of 2021Q1 to 2023Q1 and on the average of 0.32 percent from 2023Q2 to 2023Q4. The results of the forecasting unit price of coffee export using Eviews is stable enough.

Keywords: time series, industry, box-Jenkins methodogy, stationarity, forecasting.

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