Abstract:
Manufacturing sector growth is an essential to building national technological and
industrial capacity, creating broad-based job opportunities, and improving income.
The general objective of this study is to study the determinants of manufacturing sector
growth in Ethiopia through time series analysis by using the quarterly time Series data
in the year 2011-2022. The Johannes co-integration test suggests that there was one
co-integration vector, which confirm VEC model. Based on the result of granger
causality test, there were bidirectional causality as well as a unidirectional causality
between the determinants of manufacturing variables in the study area. From the
Vector Error Correction model, Employment in Agriculture, Employment in Industry,
Employment in Service, Labor force, Foreign direct investment net flow, manufacturing
value added, manufacturing export has a positive significant effect on manufacturing
sector growth at 0.05 level of significant while exchange rate, inflation and
manufacturing import has a negatively effect. According to the result of Variance
decomposition, more of the variation of all variables explained by their own effect in
short-run and becomes decrease in long run. Moreover, the contribution of one
variables for the variation of the other variables were minimum in short-run and it
increase to almost medium effect in long run. After check model adequacy within
appropriate methods and performance of forecast determined, the Quarterly data of
2023-2027 used to forecasting and the result indicates that, there was an increment of
inflation rate, manufacture export, exchange rate, Employment in industry and
decreasing Employment in Agriculture, Employment in service, Manufacture import,
manufacturing sector growth, Foreign direct investment net flow, manufacture value
added and labor force. These results may be causes due to political instability, Weak
domestic market supply due to agricultural production constraints and steady
devaluation of the local currency and the increment of unemployment in the country.
