Multivariate Time Series Analysis of Industry Development Indicators in Ethiopia

Abstract Background Industry development indicators are metrics that are used to evaluate an industry's growth and performance. This study's primary goal was to evaluate the relationship among Ethiopia's industry development indicators using a multivariate time series model based on World Bank data covering the years 1982–2021. Method Annual data covering the years 1982–2021 were used in a time series approach. A vector auto-regressive model was performed for interdependency modeling. Certain elements of the relationships between the variables of interest are frequently analyzed using structural vector autoregressive techniques. Results The results of the vector autoregressive model indicated that the current industry growth is positively related to one period lagged value of itself, industry GDP and manufacturing exports. And also, there exists a positive relationship between manufacturing exports and the first lag of itself, industry growth and manufacturing GDP. For a 1% increase in manufacturing exports, the industry growth rate increased by 0.37% in natural logarithms on average, ceteris paribus. Conclusion The current manufacturing growth of Ethiopia is significantly affected by the first lag of industry growth, industry GDP, manufacturing exports, and manufacturing GDP. And also, there is a unidirectional causality from industry growth to industry GDP, industry growth to manufacturing growth, manufacturing exports to industry growth, manufacturing exports to industry GDP, manufacturing growth to industry GDP, manufacturing exports to manufacturing growth, and manufacturing GDP to manufacturing growth in the short run.