This study was carried out to investigate the impact of the Ethiopian exchange rate and its volatility on international trade. Trade openness was used as a proxy for international trade in the study. The study’s general objective was to investigate how international trade responds to exchange rate levels and volatility. The study relied solely on secondary time-series data spanning the years 1992 to 2019. The Autoregressive Distributive Lag (ARDL) model was used in the study to investigate the long-term relationship between exchange rate level, volatility, and international trade performance. An error correction model was used to estimate the variables in the short term. To conduct the regression analysis, Foreign Direct Investment (FDI), Gross Domestic Product (GDP), and inflation were used as control variables. The finding of the study implies that: in the short term, the exchange rate level was found to negatively and significantly influence international trade. However, exchange rate volatility positively and significantly affects international trade both in the short and in the long term. In addition, gross domestic product, foreign direct investment, and inflation have a positive effect on international trade both in the short term and long term. This finding lends support to the J-curve effects, which suggest an initial loss in the short term followed by a dramatic gain in the long term. However, the findings of this study suggest that there is no significant gain from international trade to justify currency depreciation in Ethiopia.

The study examines the correlation between economic growth, investment, population growth and unemployment in Ethiopia. For the purposes of this study, secondary time series data collected from the National Bank of Ethiopia, IMF and World Bank databases were used. The study extracts the perceived relationship between the variables through principal component (PCA) analysis. Both the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity were used to determine the appropriateness of the dataset for PCA. The results revealed that an increase in unemployment is positively correlated, but in the opposite direction to economic growth, investment, total population and the working-age population. On top of the rapid spread of COVID-19, the present protests as a result of the political instability and ethnic problems across the country will lead to an increase in unemployment and the loss of many lives. Policymakers therefore need to emphasize and assure an increase in economic growth and investment in order to create more jobs in line with the increasing demand for jobs, particularly by young people. Moreover, the government must address the ongoing ethnic problems and political instability before it hits the economy adversely.

No abstract