Macroeconomic Instabilities, Capital inflow and Manufacturing Sector Growth Nexus in Ethiopia: Evidence from ARDL Model
DOI:
https://doi.org/10.66777/w2q7r653Keywords:
Manufacturing sector, Capital inflow, Macroeconomic instabilities, ARDLAbstract
Background: Currently, world economy is experiencing frequent macroeconomic shocks due to natural and anthropogenic factors. The manufacturing sector is one victim of such macroeconomic disturbances. In this study we examined the drivers of manufacturing sector growth in Ethiopia.
Methods: To achieve the stated objective, we use the time series data-set spanning from 1992 to 2022. ARDL model were used to analyze the collected data.
Result/findings: The result of ARDL bounds test indicates that there is a long run relationship between manufacturing value added and the explanatory variables. The long run ARDL estimation revealed that foreign direct investment (FDI), Inflation and exchange rate volatility have statistically significant long run impact on manufacturing value added. FDI has a positive long run impact on growth of manufacturing value added whereas inflation and exchange rate have a negative long run impact. The result of error correction model (ECM) shows that the explanatory variables (FDI, inflation, exchange rate, labor productivity and export earnings) are statistically significant in determining the growth of manufacturing sector in the short run. The error correction coefficient estimated at -0.534 is highly significant and has the correct negative sign. This implies that there is a very high speed of adjustment to equilibrium.
Recommendation: Some policy measures should be taken to boost manufacturing sector. The study strongly recommends the government to revise and re-formulate the fiscal and monetary policies to control the macroeconomic instabilities in the country. Government should also create conducive environment to attract foreign direct investment.
Downloads
Downloads
Published
License
Copyright (c) 2026 Journal of Interdisciplinary Science and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.