Agriculture trade remains the economic fulcrum of most African countries as the continent continues to host the largest percent of arable land. This research analyzed the Economic Community of West African States (ECOWAS) and China’s agricultural products trade determinants based on 19 years (2000-2018) panel dataset of West African countries aggregate agricultural products exports ($) and macroeconomic variables; GDP, population, arable land, language investment, and trade association(WTO)) as predictors. The PPML estimation method was employed due to its prediction accuracy, the size of the data, and potential hetroskadacity issues. With a 78.5% prediction power, the model explained the variation in ECOWAS-China agricultural trade (Exports). GDPj, lnPOPj, lnPOPi, and lnARLj, LndLj, ConfInsj, and WTOij were positive and statistically significant determinants of trade as hypothesized by existing trade literature. In addition, the China’s population (lnPOPj) had a value of 0.5877, which is significant at the 5% level, indicating that a 1% increase in the Chinese population significantly increases trade in agricultural products with ECOWAS states. The coefficient of distance (Dij) is -4.4573 statistically significant at the 1% level, indicating that distance between partners impedes trade flow. There are unidentified barriers that delay the progress of trade in agricultural products between ECOWAS and China. Based on the above findings, Investments in ECOWAS arable lands demand urgent attention if significant progress in exports is expected, additionally, governments of both partners should assist Agricultural research and development to identify and rectify stifling trade barriers. Furthermore, as trade between ECOWAS and China has not yet reached its full peak, studies on export determinants of individual Agro-commodities and potentials are needed to enrich literature.
The role of oil price on the macro-economy has been intensely researched. However, oil remains one of the most important energy sources for production. Concerning China, there are projections that the country’s energy consumption would have risen to 18 billion barrels per day in the next two decades. Given China’s heavy reliance on oil, we reexamine the impact of oil price on the US dollar-Renminbi rate and the Shanghai index using daily data from 4/01/2010 to 29/03/2021. In our analysis, we apply the Nonlinear ARDL technique in the presence of structural breaks and find that oil price has asymmetric impact on exchange rate and stock price in the short-run alone. However, the asymmetry is only in terms of magnitude and not in terms of effect direction. Oil price is found to appreciate the Renminbi vis-à-vis the US dollar and to increase stock price significantly both in the short-run. We find that accounting for structural breaks is necessary for cointegration in using oil price to explain both variables.
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