RESOURCE USE EFFICIENCY AMONG FISH FARMERS USING EARTHEN POND SYSTEM IN BENUE STATE, NIGERIA

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1 RESOURCE USE EFFICIENCY AMONG FISH FARMERS USING EARTHEN POND SYSTEM IN BENUE STATE, NIGERIA Simon T. Penda (Ph.D), Joseph C. Umeh (Ph.D) and Godwin P.Unaji Department of Agricultural Economics, University of Agriculture, Makurdi, Benue State, Nigeria. ABSTRACT The paper examined the resource use efficiency among earthen pond fish farmers in Benue state, Nigeria using Stochastic Frontier Production Function Model. The results of return to Naira invested shows that earthen pond system yielded 0.67, which implied that for every one naira invested, a return of N1.67 were obtained. And the rate of return on capital invested was 63% which is greater than the prevailing bank rate. The results of economic efficiency revealed an average of 82.9% the results showed that technical and allocative efficiency were relatively low. Stochastic frontier production function revealed that labour and fingerlings were found to be significant factors that contributed to the technical efficiency. Also only age and years of experience are significant factors in the inefficiency sources model. The results showed that there was inefficiency in the allocation of productive resources among fish farmers in the study area. Although results of the study have shown that fish farmers were inefficient in the application of productive resources, the low output prices and the imperfect condition of input markets in the study area may have constrained efficient use of production inputs. To improve efficiency in resource use efficiency in earthen pond fish production, the fish farmers should be availed of current technical and price information. The ownership structure revealed that most of the fish farms were owned by individuals who had little access to finance. Therefore, government participation in fish farming should be encouraged in the area to boost the quantity of fish available for consumption. Keywords: Resource Allocation, Fish Farming, Earthen Pond, Technical, Allocative and Economic Efficiencies 1.0 INTRODUCTION One of the greatest problems confronting millions of Nigerian today is lack of adequate protein intake both in quality for feed the nation s ever-growing population. This inadequately results in malnutrition. The resultant effect of serious deficiency in the amount of protein intake is that people s health is adversely affected, particularly mental capability, working productivity and eventually, the overall national economic growth Okoruwa and olakanmi, (1999) 5.The significant imbalance between food production and the expanding population has resulted in an everincreasing demand for fish consumption. This concern has been prompted about the efficient performance of fish farming production systems. Over the years, several people including government have always emphasized the need to increase fish production as priority without due consideration to the particular type of production environment in which to invest on with particular reference to economic analysis of the common pond systems. Furthermore, the efficiency or inefficiency of utilization of available resources for fish production has remained an unanswered question in the study area. An efficient method of production is that which utilizes the least quantity of resources in order to produce a given quantity of output. 2.0 OBJECTIVES OF THE STUDY i. To estimate the cost and returns of fish production in earthen pond in Benue State ii. To estimate the distribution of technical and allocative efficiencies of fish farmers using earthen ponds in Benue State 3.0 SIGNIFICANCE OF THE STUDY This study will assist fish farmers within the study area to plan and effectively manage production costs to realize higher returns from the enterprise 4.0 RESEARCH METHODOLOGY The study was conducted in Benue State, Nigeria, which has twenty-three local government areas. The study made use of both primary and 62

2 secondary data. The main instrument for collecting primary data was structured questionnaire which was administered to a cross-section of fish farmers using earthen ponds. A multi-stage random sampling technique was used to obtain the data. First the state was stratified into the 3 agricultural zones of the state from which 3 L.G.A.s each were purposively chosen to give a total of 9 L.G.As used for the study. These nine L.G.As were purposively selected because of high concentration of active fish farmers in the study area. Secondly, a proportionate 70% was applied across the sampling frame in each local government area to randomly select 47 fish famers using earthen ponds from the list maintained by Benue State Agricultural and Rural Development Authority (BNARDA) extension agents. Data analysis was done using the descriptive statistics, budgetary technique and stochastic frontier production function model. 5.0 MODEL SPECIFICATION 5.1 Budgetary Technique: This involves the costs and returns analysis: Π=TR-TC.(1) TR=PQ.(2) π = total profit, TR = total Revenue (N) TC = total cost (N) P = unit price of output (N) Q = total quantity of output (kg) 5.2 Stochastic Frontier Production Function Model: This was used to analyze the productivity and technical, allocative efficiency of fish farmers using earthen ponds. The model according to Ogundari and Ojo (2006) 4 has been used by many empirical studies, for the fact that the functional form meets the requirement of being self-dual (ie allowing an examination of economic efficiency and isolating factors responsible for inefficiency). It is specified as: LnY = β o + β 1 lnx 1 + β 2 lnx β n lnx n + (V i U i ). (3) Ln = logarithm to base, Y= fish output (kg) X 1 = pond size X 2 = feeds X 3 = fingerlings X 4 = labour X 5 = fertilizer β 0 = constant term β 1. β 5 = Regression coefficients. V i are random variables which are assumed to be independent of U i, and normally distributed with zero mean and constant variance, V i i = are non-negative random variables which are assumed to account for technical inefficient in production and are often assumed to be independent of V i. The inefficiency of production, U i was model in terms of the factors that are assumed to affect the efficiency of production of farmers. The determination of technical inefficiency is defined by: U i 0 1 Z 1 + 2Z 2 + nzn (4) U i = Technical inefficiency Z i = education (years) Z 2 = Farming experience (years) Z 3 = age of culturists (years) Z 4 = household size Z 5 = contact with extension agents Z 6 = annual income (Naira) σ 0 σ 6 = parameters The technical efficiency of an individual pond was expressed as: TE i = Y i /y* (5) TE i = Technical efficiency of i th pond Y i = Observed output and Y* = frontier output. Allocative (cost) efficiency function is derived analytically and defined as follows: LnY = β o + β 1 lnx β n lnx n + (V i U i ).(6) Ln = logarithm to base, Y= fish output (kg) X 1 = cost of pond construction (N) X 2 = cost of labour (N) X 3 = cost of feeds (N) X 4 = cost of transportation (N) X 5 = cost of fertilizer (N) X 6 = Fingerlings costs N X7= cost of lime N β 0 = constant term β β 6 = Regression coefficients for allocative inefficiency U i 0 1 Z 1 2 Z n Z n (7) U i = Allocativel inefficiency Z 1 = education (years) Z 2 = experience (years) Z 3 = age (years) Z 4 = household size Z 5 = extension contact Z 6 = annual Income 0 6 = parameters Specific Allocative efficiency was computed as: AE i = Y* /Y m. AE i = Allocative Efficiency i th pond Y* = Frontier Output, Y m = optimum output. 63

3 Farm specific economic efficiency (EE) was estimated as the product of the Technical and Allocative Efficiencies. ie EE=TE x AE (8) 6.0 RESULTS AND DISCUSSION 6.1 Costs and Returns Analysis of Average Fish Farmers Using Earthen Ponds. The costs and returns analysis is presented in Table 1. The results revealed that the cost of feeds accounted for the largest proportion (26.0%) of the total cost of fish production. This was followed by the cost of labour (15.11%); cost of stock (9.71%). This showed that large amount of money was spent by fish farmers in the study area for purchase of feeds, labour and fingerlings. The fixed cost of production consists of cost of fixed assets such as pond, pumping machine, wheel barrow, shovel, harvesting materials, water basin which accounted for 43.08% of the total cost of production. The result also revealed that an average total cost N249, was incurred per annum by the farmers, while mean gross revenue of N405, was realized thereby returning an average gross margin of N255, and a profit of N156, The rate of return on investment (ROI) was 0.67, which implied that for every one Naira invested in fish production in earthen ponds by farmers, a return of N1.67 and a profit of N0.67 were obtained. The implication of this is that there is a considerable level of profitability in fish farming in the study area. This is consistent with the findings of Ashaolu et al (2005) 2 in their studies on profitability of fish farming. The rate of return per capital invested (RORCI) is the ratio of profit to total cost of production. It indicates what is end by the business by capital outlay, Awotide and Adejobi,(2007) 3. The results revealed that the RORCI of 63% is greater than the prevailing bank lending rate of 20%, implied that fish farming in Benue State is profitable. If a farmer takes loan from the bank to finance fish farming, he will be 67k better off on every one naira spent after paying the loan at the prevailing interest rate. TABLE 1: AVERAGE COSTS AND RETURNS OF FISH PRODUCTION IN EARTHEN POND IN BENUE STATE Item (annual) Amount (N) Percentage of total cost Feeds 64, Labour 37, Stock 24, Transport 3, Fertilizer 3, Water 4, Lime 3, Total variable cost (TVC) 141, Fixed inputs (FC) 107, Total cost (TC) 249, Total Returns (TR) 405, Profit (π) 156, Returns on investment 0.67 RORCI 0.63 Source: computed from field survey data, Maximum Likelihood Estimates of Stochastic Frontier Production Function The results as presented in Table 2 revealed the presence of technical inefficiency among the fish farmers in the study area. This was confirmed by the likelihood ratio and the significant of gamma. This implied that the one-sided random inefficiency component strongly dominate the measurement error and other random disturbance indicating 98.8% variation in actual output. 6.3 Elasticity and Returns to Scale The elasticity of variables with respect to fish farmers using earthen ponds revealed that labour (0.34) and fingerlings (0.229) were statistically significant at 5% and 10% probability level respectively. The positive and significant effects of labour and fingerlings implied that there was a direct relation between these variables and fish yield. Improving yield in fish farming requires the stocking of fast growing fingerlings of economically viable fish species, if the farmer must realize his objective of maximizing revenue and profit. Thus, the positive response of fish production to increased fingerlings utilization may 64

4 be attributable to farmers goal to realize optimal benefits from the resources employed in production. The mean technical efficiency as presented in Table 3 was this implied that on the average, the fish farmers are able to obtained 54.9% potential output from a given mix of production inputs. In the short-run, there is scope for increasing output by 45.1% by adopting the techniques and technologies employed by the best fish farmers. The frequency distribution of technical efficiencies obtained from the stochastic model are presented in Table4. The results showed that majority (57.49%) of the respondents operated below efficiency level of 60%, while less than 42.51% were technically efficient as they attained efficiency level greater than 60%. TABLE 2: RESULTS OF MAXIMUM LIKELIHOOD ESTIMATES OF COBB-DOUGLAS FRONTIER PRODUCTION FUNCTION FOR TECHNICAL EFFICIENCY FOR EARTHEN POND IN BENUE STATE Variable Parameters Coefficients Constant β * (11.169) Ln pond size β 0.069(0.707) Ln feeds β (-0.843) Ln fingerlings β 0.229***(1.833) Ln labour β 0.340**(2.094) Ln fertilizer β 0.039(1.026) Inefficiency Model Constant Z (1.023) Level of education Z 0.811(1.126) Years of experience Z (-1.364) Average age (yrs) Z 3.26**(2.37) Household size Z 0.598(0.815) Extension contact Z (-1.36) Annual income (N) Z ***(-1.89) Sigma square 8.74*(14.268) Gama 0.988*(99.85) Log (likelihood) Mean technical efficiency *significant at 1%, **significant 5% and ***significant 10% Source: field survey data, 2012 TABLE 3: SUMMARY STATISTICS AND DISTRIBUTION OF TECHNICAL EFFICIENCY OF EARTHEN POND FISH FARMERS IN BENUE STATE T.E Range Frequency Percentage Total Mean Minimum 0.08 Maximum 0.86 Source: computed from field survey data, Technical Inefficiency Model This explains the relationship between farmers socio-economic and management factors and their effects on inefficiency. The signs and significance of estimated coefficients had important implications on the technical inefficiency of the farmers.the analysis revealed that the coefficients of age of farmers (3.26) and annual income (-1.78) were found to be statistically significant at 5% and10% respectively. The results concerning the influence of farmers age indicated that the older the farmer, the higher his technical efficiency. This is expected because since the older the farmers, the higher the experience and as the experience increases, the more the farmer gets used to farm 65

5 production processes and techniques and hence increased technical efficiency. The results showed that the coefficients of annual income had a negative influence on inefficiency of these farmers. This means that the higher amount of annual income reduce technical inefficiency of these farmers and this suggests that farmers who are involved in other income generation activities are re-investing the proceeds on fish farming. 6.5 Maximum Likelihood Estimates for Allocative Efficiency Model The maximum likelihood elasticity parameter estimates of cost function of farmers are presented in Table 4. The elasticity parameters of pond (0.56), cost of transportation (-0.05) and cost of fertilizer (0.269) were found to be statistically significant at 5%, 10% respectively. This means they exert significant influence on the cost of production of pond fish production in the study area. The distribution and descriptive statistics of allocative efficiency presented in Table 5 shows that less 53.2% of the fish farmers operated at allocative efficiency level of 0.1 to 1.4 which is below the mean efficiency while 46.8% of the fish farmers operated above the mean allocative efficiency, they are within the range of 1.41 and above. The mean allocative efficiency is This means that the average farmers are able to obtained 45.9% potential output from the given mix of cost inputs. This implies that if the average farmer in the sample was to achieve allocative efficiency level of its most efficient counterpart, then the average farmer could realize 54.12%. A similar computation for most allocative inefficient farmer revealed cost saving of 68.55%. 6.6 Cost Inefficiency The results revealed that the coefficients of farmers experience (0.55) and contact with extension agents (0.68) were positive and statistically significant at (P 0.05). a positive and significant coefficient of these variables implied that these factors led to increase in allocative inefficiency. 6.7 Descriptive Statistics of Economic Efficiency of Fish Farmers Using Earthen Pond in Benue State The predicated efficiencies (EE) estimates as inverse of cost of efficiencies differs among farmers ranging between 0.10 and 2.03 with a mean of 0.83 as presented in Table 6. TABLE 4: RESULTS OF MAXIMUM LIKELIHOOD ESTIMATES OF THE COBB-DOUGLAS FRONTIER PRODUCTION FUNCTION FOR ALLOCATIVE EFFICIENCY IN EARTHEN POND IN BENUE STATE Variable Parameters Coefficients Constant β (-0.001) Ln cost of pond size β **(2.01) Ln cost of labour β (1.035) Ln cost of feeds β (-0.823) Ln cost of transport β ***(1.709) Ln cost of fertilizer β ***(1.688) Ln cost of fingerlings β (1.026) Ln cost of lime β (0.231) Inefficiency model: Constant Z (-0.01) Ln education (yrs) Z (-0.655) Ln experience (yrs) Z **(2.891) Ln age (yrs) Z (0.967) Ln household size Z (-0.488) Ln extension contact Z **(2.043) Ln annual income Z (0.655) Sigma square 0.454*(5.051) Gamma 0.66**(3.006) Log (likelihood) Mean allocative *significant at (P<0.01), **significant at (P 0.05), ***significant at (P 0.10). Source: field survey data,

6 TABLE 5: SUMMARY STATISTICS AND DISTRIBUTION OF ALLOCATIVE EFFICIENCY OF FISH FARMERS USING EARTHEN POND IN BENUE STATE Allocative efficiency range Frequency Percentages Total Mean Minimum 1.0 Maximum 3.18 Source: field survey data, 2012 TABLE 6: SUMMARY STATISTICS OF EFFICIENCY OF FISH FARMERS USING EARTHEN POND IN BENUE STATE Index Mean Standard deviation Minimum Maximum Technical Efficiency Allocative Efficiency Economic Efficiency Source: field survey data, CONCLUSIONS AND RECOMMENDATIONS 7.1 Conclusions The study examined the efficiency of resources use in earthen pond fish production in Benue state, Nigeria. The results showed that there was gross inefficiency in the resource use efficiency among the fish farmers in the study area. Apart from pond size and fertilizer which had allocative efficiency index of 2.01 and 1.7 respectively, inputs such as labour, feeds, fingerlings, lime were over-utilized. This means sub-optimal resource allocation in fish farming. Inadequate and timely access to finance and fertilizer by many farmers may responsible for the under-utilization of pond size and fertilizer in the production process. While the use of home mixed fish feeds (ie kitchen wastes and poultry droppings) and family labour which is a readily available pool by majority of the farmers may be responsible for the over-utilization of these inputs. This aggress with the findings of Olarinde and Kuponiyi (2004) 7, Akanni and Adeokun (2004) 1, Oladeebo et al (2006 )6. The technical and allocative efficiency of fish farmers using earthen pond in the study area were relatively low. The relatively low technical know-how coupled with the relative abundance of some inputs may be responsible for the inefficient use of production resources among the fish farmers in the area. The low output prices and the imperfect condition of input markets in the study area may have constrained efficient use of production inputs. 7.2 Recommendations i. To improve efficiency in resource use in earthen pond fish production, access to current technical and price information is needed by the farmers and the Benue state government should introduce relevant policies to support farmers in this direction. ii. Fish farmers in Benue State should adapt cost effective measures in fish production to earn better returns. iii. Fish production using earthen ponds is also recommended as a good strategy for managing youth unemployment and a critical weapon to alleviate poverty in Benue State. 67

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