Summary of Research

This study investigates the causes of declining output performance in the Ghanaian fruit pro-duction industry. Average industrial output level is lagging far behind that of competing na-tions (for instance, the productivity of Ghana pineapple farms is 60 T/Ha compared to 120 T/Ha for Cost Rica (Gatune et al, 2013) despite Ghana’s excellent relative comparative ad-vantage (i.e. labour, climate, location) for fruit production. The inability of the industry to meet both local and export demand-volumes has caused some major processing and exporting companies struggling to get raw materials to close down or relocated to other countries lead-ing to job losses in both rural and urban areas, loss of international market share and foreign exchange the country urgently need. The aim of this study is therefore to identify and ana-lysed the factors hindering successful and efficient performance of the fruit crop industry (i.e.

we assessed why Ghana’s fruit crop production industry remains below its potential).

In light of the above mentioned problems, our study, which uses cross-country farm-household survey data to identify and analyze potential ways of enhancing farmers’ efficiency of production in the fruit industry, is a giant step in the right direction. Empirical insight gained from this study could serve as a valuable guideline to policy makers in formulating future performance enhancing programs to boost output in the industry.

In order to effectively study the industry, the three major fruit sectors (i.e. mango produc-tion sector, pineapple producproduc-tion sector and banana producproduc-tion sector) of the industry were selected and subjected to a detailed empirical analysis. The empirical results are obtained us-ing a cross-country farm-household survey data of fruit farmers in all the major fruit produc-ing regions of Ghana. Therefore, this dissertation is a collection of three papers organised into three chapters (2 – 4). Each chapter studied in detail a sector of the industry and the major findings are summarised below. Based on economic theory and statistical tests, different econometric estimation techniques were employed to analyse the research questions which were posed in each essay.

122 5.2. Summary of Findings in Each Essays/Papers

Chapter Two (first essay/paper): The study uses metafrontier estimation technique to derive performance estimates of mango farmers given the technology available to both their zonal production frontier and the industrial production frontier (metaproduction). This estimation technique enables us to distinguish production shortfall due to technological gaps (which we argue is outside the control of farmers) from that of technical inefficiency (which is under the control of farmers). The data and estimation technique used in this study revealed that, be-sides technical inefficiency, technology gaps plays an important part in explaining the produc-tion performance of farmers in one zone in comparison with farmers in other zones.

This has important implication for policy targeting program design. For instance, in the northern zone where 94% of farmers are estimated to be making full use of available tech-nologies yet lag behind the industrial output by 52%, imply; policy intervention programs designed to improve the production environment (e.g. building roads and power supplies, or creating a favourable credit market for farmers etc.) which aid facilitation of technology trans-fer to bridge the technology gap will have a huge impact on output performance.

The middle and southern zones have an average zonal technical efficiency of 79% and 80%

respectively, with relatively high proportions of farmers having less than 50% efficiency score. In these two zones, it will be economically more prudent to design programs which enhance farmers’ managerial capabilities or skills; thereby enabling them to increase output towards their zonal frontier by making better use of existing technologies⁵³.

In general the study reveals that there is much scope for output improvement in all zones, however, attainment of maximum output is possible only if the causes of inefficiency due to technology gaps and farmers effectiveness of using available resources are properly ad-dressed.

Chapter Three (second essay/paper): This study employs both logistic and metafrontier models to analyse stated research objectives. For example, we analysed the proportion of farmers cultivating the MD2 variety in each production system and identify the factors

53 Efficient use of current know-how implies more output can be produced with existing input endowment.

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encing the adoption of MD2 variety using a logistic regression model. The result shows that, out of 404 pineapple farmers sampled across the three regions, only 74 (18%) farmers are cultivating the MD2 variety. The analysis of factors influencing the adoption of MD2 reveals that; farmers with higher off-farm income, capable of installing irrigation facilities to irrigate their farms, having access to regular and reliable pineapple market as well as farms located in the eastern regions are more likely to adopt the MD2 variety.

Metafrontier analytical technique was used to assess the current productivity level of or-ganic and conventional pineapple producers using a cross sectional data set gathered from 404 farm-households in three regions where commercial production is most concentrated. The results of our analysis reveal that the majority of farmers in both systems was operating on or near their group as well as the industrial frontier (i.e. 97% mean TE and 95% mean MTR).

This implies that there is not much scope for output expansion or productivity gain given the current state of technology available to the industry. Therefore, to substantially enhanced pro-ductivity level in the industry, government policies should aim at agricultural-research (R&D) development framework which not only encourages but expedites technological progress through the introduction of modern production techniques. Design of productivity enhance-ment programs by policy makers’ aim at making the industry more competitive should priori-tize investment in agricultural infrastructures which support technology transfer. For instance, improving conditions of rural-urban road networks to support quick and effective transporta-tion of inputs/outputs will aid facilitatransporta-tion of technology transfer to the less develop and re-source starved regions of the industry.

Chapter Four (third essay/paper): This paper analyses the production performance of commercial banana producers using a cross-section data of 120 randomly sampled farmers in the Volta region of Ghana⁵⁴. By means of stochastic frontier approach, output distance func-tion estimafunc-tion technique was used to estimate technical efficiency and explore complemen-tarity and substitution effects in production inputs and outputs. Farmers in our sample data produce a mixture of crops in addition to banana production. Hence, an output distance func-tion was deemed appropriate because it allows us to explore changes in the levels of outputs in relation to the frontier output mix (PPF). The empirical result showed that, the marginal

54Field survey was carried in 2012.

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rate of transformation (MTR) between banana and other crops produced by farmers is nega-tive and significantly different from zero (see table 4.2 in chapter four).

The result of the first order input elasticities also reveals that, all inputs monotonicitly in-creased banana production in the region. However, evidence of a decreasing return to scale (RTS = 0.468) could not be attributed to farm size as prescribe by economic theory. A plausi-ble explanation could be due to the obsolete nature of production technique⁵⁵ (dominated by traditional production tools) currently being employed in the region.

The result of the efficiency model as defined in equation (9) and presented in Table 4.3 shows an average performance score of 86%. This implies given the current state of production tech-nology in the region, a 14% improvement in output is theoretically possible if causes of pro-duction inefficiency could be eliminated. Household and socioeconomic factors such as farm-ers’ education level, experience in farming, household size and regular contact with extension workers were found to improve production performance (i.e. reduce inefficiency). However, the magnitude of economic gain as revealed by the estimated coefficients (see table 4.4 in chapter four) is not high enough to sustain the industry in the long run given the highly com-petitive nature of international trade. Hence, Policy measures which facilitate the transition from current traditional production techniques to use of modern production technologies in conjunction with improvement in transport, logistics and technical support services will en-hance performance on a sustainable basis in the sector (i.e. such measures which enen-hances both quality and volume supplied could help improve the comparative advantage of the indus-try).