Agricultural productivity and supply responses in Ghana

The importance of Agricultural Supply Response (ASR) modelling cannot be over emphasised. Knowledge of its size provides a roadmap for designing a tailored agricultural policy based on suppliers’ responses to price and non-price incentives. In spite of its policy importance, limited amount of studies exist for Ghana. This study seeks to fill the gap and also sheds some light on how future agricultural policies in Ghana should be formulated. This study is conducted on a regional (ecological) group basis and at a crop-level. Apart from price and non-price factors, we have also accounted for technical inefficiencies, a problem that impedes the growth of agricultural production in Ghana. We employed the duality modelling technique (based on the profit function). This technique provides a more intuitive way of modelling and interpreting ASRs. We used the fourth wave of the Ghana Living Standard Survey (GLSS4), a cross-sectional dataset collected between 1998 and 1999. The analysis is based on six crops, grouped into industrial (cocoa and groundnut), food (maize, rice and cowpea) and staple (sorghum and millet combined and termed migso in the study). A sensitivity analysis is carried out to check the robustness of results. We found high national and ecological technical inefficiency scores. Nationally, technical inefficiency is in the neighbourhood of 53%. At the ecological levels, groundnut (industrial crop) farmers in the Coastal zone recording the highest inefficiency (83%) with the least inefficiency score coming from cowpea (food) farmers in the Savannah zone (30%). In a related outcome we found that technical inefficiency estimates and patterns are sensitive to the structure and composition of the dataset. Our supply elasticities support claims that farmers in Ghana will respond to both market (price) and non-price incentives. In terms of price incentives we found that, with or without technical inefficiency, farmers of food crops in the Coastal zone will respond the most to changes to outputs prices. Farmers in the Savannah zone for all crops but staples will be the least to respond to output price change. We found, however, that with production inefficiency accounted for, supply responses were relatively lower, reinforcing the arguments that earlier supply response estimates from other studies could have been inaccurately estimated especially where analysis failed to account for non-price factors. Moreover, the study estimates revealed that farmers in Ghana are would record a larger output supply responses to changes in inputs prices than output prices. Besides price, the study also found that all four non-price incentives - plot size, animal capital, family labour and education of household head - are important to the development of an effective agricultural policy regardless of whether technical inefficiency is accounted for or not. In some cases, output supply responses from non-prices factors outweighed price elasticities, again supporting the argument that ASR estimates are likely to be biased if non-price factors are omitted. These findings provide two policy signposts for the design of Ghana’s future agricultural policies. Firstly, the policy - aimed at increasing output and/or improving the sector’s competitiveness - must identify and address technical inefficiencies among smallholder agricultural farmers. Failure to address such inefficiencies would lead to suboptimal performance - operating on a lower production frontier. Secondly, the differences in crop-level ecological supply elasticities support regional-based agricultural policies rather than a one-size-fits all centralised agricultural policy