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The purpose of this paper is to examine the connections of agricultural productivity, access to credit and farm size in Africa using Ghana as a case study.

The paper employs mixed methods – quantitative and qualitative strategies for data collection and analyses. The hierarchical competitive model was used for the quantitative analyses supplemented with qualitative analyses using key informant interviews, focus group discussions and household case studies.

The results show that there is significant relationship between credit from formal and informal sources and agricultural productivity. Thus access to formal and informal credit increases farm household agricultural productivity by about 0.10 (p=0.05) and 0.45 (p < 0.01), respectively. The quadratic terms of formal and informal credit as well as farm size were found to significantly influence agricultural productivity. The implication of this is that the relationships between formal credit, informal credit and farm size on one hand and agricultural productivity on the other are non-linear in nature. The interactions of formal credit with informal credit; informal credit with farm size; and formal and informal credit with farm size have significant relationships with agricultural productivity. The amount of remittance received by farm households has negative and insignificant influence on agricultural productivity. Market access is also an insignificant determinant of agricultural productivity in Ghana.

This paper provides new insights on whether the scale of production (farm size as proxy) and access to financial services (credit as a proxy) matter in promoting agricultural productivity in Africa using Ghana as a case study. Thus the paper is of relevance to policy-makers and practitioners in Africa and Ghana in particular who are seeking to make informed policy decisions on effectively incorporating credit provision into the agricultural transformation agenda of the continent.

The purpose of this paper is to examine the causal relationship between the copper price dynamics and economic growth in Zambia over the period from 1995 to 2015.

The study uses a data set assembled from five difference sources: the heritage foundation; the London metal exchange index; the Penn World Tables version 9.0; the total economy database; and the World Bank Development Indicators. The paper employs the Bayesian Model Averaging (BMA) approach as the estimation technique.

The estimates demonstrate that there exists a positive and significant relationship between movements in copper prices and economic growth in Zambia. The study draws policy implications from these findings.

This study is limited to the period from 1995 to 2015, this is due to lack of data on the country’s institutional indicators, trade openness and the real exchange rate.

There have been calls to diversify the economy of Zambia due to the recurring chaotic events, which are often induced by over-dependence on copper exports. Thus, the study findings will be useful to academia, policy makers and stakeholders with vested interest in the economy of Zambia.

To the best of the author’s knowledge, this is the first empirical study to investigate the causal relationship that exists between copper prices and economic growth in Zambia. The existing empirical studies in the domain have devoted their attention on establishing the relationship between commodity price movements and exchange rates in Zambia.