This study evaluated the profit efficiency of artisanal fishing in the Pru District of Ghana by explicitly computing profit efficiency level, identifying the sources of profit inefficiency, and examining the constraints of artisanal fisheries. Cross-sectional data was obtained from 120 small-scale fishing households using semistructured questionnaire. The stochastic profit frontier model was used to compute profit efficiency level and identify the determinants of profit inefficiency while Garrett ranking technique was used to rank the constraints. The average profit efficiency level was 81.66% which implies that about 82% of the prospective maximum profit was gained due to production efficiency. That is, only 18% of the potential profit was lost due to the fishers’ inefficiency. Also, the age of the household head and household size increase the inefficiency level while experience in artisanal fishing tends to decrease the inefficiency level. From the Garrett ranking, access to credit facility to fully operate the small-scale fishing business was ranked as the most pressing issue followed by unstable prices while perishability was ranked last among the constraints. The study, therefore, recommends that group formation should be encouraged to enable easy access to loans and contract sales to boost profitability.
Fish is a source of high quality and cheap animal protein essential to balancing diet. According to the World Bank [
Ghana has a lot of lakes, lagoons, and rivers for fish production [
Despite the above-mentioned natural potentials and significance of fish industry in the country, the sector faces some challenges that militate against its growth. These include perishability of fresh fish and lack of information about the management of the industry by these artisans [
Moreover, most studies in efficiency have not looked at the artisanal fishing subsector, especially in the study area. In the Pru District of Ghana where most households are into artisanal fishing and food security of great concern, the sustainability of the fishing business cannot be achieved without economic viability. The study, therefore, investigates the profit efficiency among artisanal fishers in the Pru District of Ghana by estimating their profit efficiency levels, identifying the sources of profit inefficiency and assessing some of the constraints of artisanal fishing.
The study was conducted in the Pru District which is geographically located in the Brong-Ahafo region of Ghana, and its capital is Yeji. The population is mainly rural with their primarily economic activity being agriculture. Due to the presence of the Volta lake in the district, fishing is a significant activity that employs the majority of the people (fishers, fishmongers, cold store operators, among others). Primary data collected from small-scale fishing households was used for the study. The data consisted of fishermen’s sociodemographic characteristics, inputs and outputs of fishing, the cost of fishing, and prices of fish, among others. A semistructured questionnaire was used to collect data through personal interviews. The communities well known for fishing activities were taken from the Fisheries Department under the Ministry of Food and Agriculture [MoFA], Ghana. Six villages were randomly selected, and twenty respondents were chosen from each community giving a total sample size of 120.
Sociodemographic characteristics were reported using descriptive statistics such as frequencies, percentages, and averages. The data was examined using stochastic profit frontier model and Garrett ranking technique.
Over the past three decades, the two main components of production efficiency, technical and allocative, have been analysed in literature. However, both measures can be merged into one system, where more efficient estimates can be obtained by the simultaneous estimation of the system [
The stochastic profit frontier model is specified as
Here
The main hypothesis tested in this study is whether or not there exists profit inefficiency in the operations of the sampled artisanal fishers in the study area. The null and the alternate hypotheses are stated as
The hypotheses above were tested with the generalized likelihood ratio test (
The study employed the Cobb-Douglas production function due to its flexibility and its popularity. It also meets the requirements of being self-dual; thus, it allows an examination of economic efficiency [
The Garrett ranking technique was used to rank constraints that militate against the activities of fishermen. The fishermen were allowed to rank constraints which were converted into score value using the formula for Garrett ranking technique as specified below:
The entire 120 respondents interviewed are males (Table
Demographic characteristics of the artisanal fishers in Pru District.
Variable | Category | Frequency | Percentage (%) |
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21–30 | 21 | 17.5 |
31–40 | 39 | 32.5 | |
41–50 | 32 | 26.7 | |
51–60 | 19 | 15.8 | |
>60 | 9 | 7.5 | |
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Married | 91 | 75.8 |
Single | 29 | 24.2 | |
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No formal education | 52 | 43.3 |
Primary/junior high | 52 | 43.2 | |
Senior high school | 16 | 13.3 | |
Tertiary education | 0 | 0 | |
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1–5 | 13 | 10.8 |
6–10 | 31 | 25.8 | |
11–15 | 36 | 30 | |
16–20 | 21 | 17.5 | |
>20 | 19 | 15.8 | |
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1–5 | 47 | 39.2 |
6–10 | 61 | 50.8 | |
>10 | 12 | 10 | |
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Off-farm | 34 | 28.33 |
Nonfarm | 86 | 71.67 |
Source: field survey, January 2015.
The remaining 2.5% belong to other religions. The mean household size is 9.13. Hence, on the average about 9 people live in a household and depend on the household head for their livelihoods. The size and composition of a household influence the magnitude of fishing activities of the household. This is because most fishermen use family labour. Apart from fishing, 28.3% of the fishermen engage in other economic activities such as rearing of farm animals, construction, crop farming, fetish priesthood, lottery, mechanic, and petty trading. The remaining 71.7% are solely engaged in fishing. Additionally, the minimum years of experience in fishing are 3 years while the maximum is 36 years. The mean year of experience is 16.59 years. This means that fishers have long-term experience in fishing.
The factors influencing profit of inland fishing in the study area are presented in Table
Estimated coefficients of the stochastic profit frontier model for fishermen.
Variable | Coefficient | Std. error |
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Cost of maintenance |
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0.0873 |
Cost of storage |
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0.0579 |
Price of labour |
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0.1171 |
Price of needle |
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0.1721 |
Price of rope |
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0.2601 |
Price of paddle |
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0.8511 |
Price of boat |
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0.1097 |
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0.0342 | |
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Source: field survey, January 2015.
Table
Determinants of profit inefficiency of inland fishing in Pru District.
Variable | Coefficient | Standard error |
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Age of the household |
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0.0471 |
Household size |
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0.1251 |
Educational level |
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0.0849 |
Number of years in inland fishing |
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0.0525 |
Constant |
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3.1210 |
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Source: field survey, January 2015.
However, Itam et al. [
Artisanal fishers interviewed in the study area ranked some constraints that militate against their activities. The summary of the ranking is presented in Table
Constraints ranked by the artisanal fishers in Pru District.
Constraint | Percent position of constraint | Mean score | Rank |
---|---|---|---|
Finance (access to credit) | 8.791667 | 76 | 1st |
Unstable prices | 14.99702735 | 70 | 2nd |
Storm | 16.16124 | 69 | 3rd |
Seasonality of fishing | 20.26771 | 66 | 4th |
Perishability | 31.97589 | 59 | 5th |
Source: authors’ computations.
Similarly, Itam et al. [
This study applied the stochastic profit frontier to a sample of small-scale fishing households to estimate the level of profit efficiency and identify sources of profit inefficiency using Pru District as a case study. The study concluded that the average measure of profit efficiency is 81.66%, suggesting that about 82% of prospective maximum profit was gained due to production efficiency. Artisanal fishers are as a result losing 18% of their potential profit due to inefficiency. Predictably, the study revealed that the benefit of small-scale fishers could be increased through the reduction of input prices. Profit efficiency can, therefore, be improved through educational training programmes geared towards the improvement of technical and managerial skill of the fishers. Also, the age of the household head and household size increase the profit inefficiency level while experience decreases inefficiency level. From the Garrett ranking, access to credit was ranked as the most pressing issue followed by unstable prices while perishability was ranked as the least among the constraints. The study, therefore, recommends that micro-policies oriented towards easy access to credit are crucial to boosting fish production in Pru District in particular and Ghana in general. Contract sales in the fishing industry are highly recommended since it has the potential to create an accessible market for the fisherman and minimize perishability as well as increasing the profit levels. The wide variation in the output price between the major and lean season is a critical area to be tackled. This suggests that focusing on skill and managerial development of the fishers alone may not produce the desired results. Long-term infrastructural development such as storage facilities (e.g., establishment of cold store in the fishing communities) is particularly important to assure these small-scale fishers that if market surpluses are experienced during the main season, the output could be stored in safer places for the next season. This could ensure steady prices throughout the year and that artisans could be sure of having relatively stable income and minimize hunger particularly in the lean season. Finally, the Ministry of Fisheries, Ghana, should consider subsidizing some of the inputs to boost productivity.
The authors declare that they have no conflicts of interest.