Multivariate Time Series Analysis of Industry Development  Indicators in Ethiopia from 1982 to 2021

Getachew Abate

dc.contributor.author	Getachew Abate
dc.date.accessioned	2023-07-13T08:22:58Z
dc.date.available	2023-07-13T08:22:58Z
dc.date.issued	2023-07
dc.identifier.uri	http://ir.bdu.edu.et/handle/123456789/15499
dc.description.abstract	Background: Industry development indicators refer to a set of measures used to assess the performance and growth of industries. The main aim of this study was to assess the relationship between industry development indicators in Ethiopia using multivariate time series model from World Bank data from 1982 to 2021. Method: A time series technique using annual data for the period 1982-2021 is utilized. Multivariate generalized autoregressive conditional heteroscedasticity and vector auto regressive models were performed for volatility and interdependencies modeling, respectively. Structural vector autoregressive analyses are often used to analyze certain aspects of the relationships between the variables of interest. Results: The results of the diagonal BEKK (1, 1)-GARCH model showed that volatility is explosive, it means that the volatility of the development indicators are growing at an accelerating rate over time and potentially more extreme and 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 association 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. The FEVDs result indicates that, at the first and second horizon most of the variations of the series were explained by their own shock. Conclusion: From the vector autoregressive model, 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. The implication of the study is that both domestic policymakers and development partners should support and motivate the growth of manufacturing sectors and manufacturing exports, since this is a necessary condition for promoting industry growth. Keywords: Industry growth, Manufacturing, MGARCH, Structural VAR and VAR	en_US
dc.language.iso	en_US	en_US
dc.subject	Statistics	en_US
dc.title	Multivariate Time Series Analysis of Industry Development Indicators in Ethiopia from 1982 to 2021	en_US
dc.type	Thesis	en_US