Price Spread and the Determinants of Catfish Marketing Income in Anambra State, Nigeria

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1 JOURNAL OF AGRICULTURE & SOCIAL SCIENCES ISSN Print: ; ISSN Online: X /AWB/2010/ Full Length Article Price Spread and the Determinants of Catfish Marketing Income in Anambra State, Nigeria C.O.A. UGWUMBA 1 AND R.N. OKOH Department of Agricultural Economics and Extension, Anambra State University, Awka, Nigeria Department of Agricultural Economics and Extension, Delta State University, Asaba, Nigeria 1 Corresponding author s veecel326@yahoo.com ABSTRACT The study examined price spread and the determinants of live-catfish marketing income in Anambra State, Nigeria using primary data collected from 101 market participants via interview instruments. Data collected were analysed by means of descriptive statistics, Sherpherd s formular and Shepherd-Futrel method of determining marketing efficiency and by multiple regression. Results indicated that catfish marketing was gender biased in favour of women both at the wholesale (96.8%) and retail (96.7%) levels. Operationally, marketing efficiency was highest in channel I (67.06), than channel II (2.20), III (2.77) and IV (1.98). Again, the retailers were more efficient (82.33%) than the wholesalers (92.05%) in catfish marketing, meaning than the wholesalers expended more of their sales revenue on costs than the retailers. Catfish marketing income was positively and significantly influenced by gender, age and marital status. However, it was negatively and significantly affected by marketing costs. Operational efficiency and thus marketing income could be increased by tailoring policy towards measures that would reduce marketing costs such as the provision of infrastructural facilities (water, good roads, cheap means of transport, etc.), establishment of large commercial catfish farms in the State and the creation of credit lines for marketers through joint liability group action in the form of Cooperative Societies, Non-Governmental Organizations and other microfinance institutions Friends Science Publishers Key Words: Catfish marketing; Operational efficiency; Marketing income; Multiple regression INTRODUCTION Marketing with reference to Olukosi and Isitor (1990) involves all those legal, physical and economic services, which are necessary to make produce from the farm available to the consumers, thus marketing leads to the creation of form, place and time utilities (Okoh et al., 2008). It enables producers such as farmers as well as middlemen to earn income with which they purchase other useful goods and services (Ebe, 2007). The roles of marketing include: (i) Helping to bridge the gap between the needs of the producers and consumers (ii) Helping producers better understand the needs of the consumers so they can do a better job of marketing them (iii) Helping producers decide what to produce and when to produce. Efficient marketing requires relevant quantitative and qualitative information that will be reliable at the lowest cost (Kohls & Uhl, 1972). Thus, lack of market information, poor market structure, which leads to price instability, poor road network, high cost of transportation, low income of the farmers can affect marketing efficiency. In Anambra State live catfish markets are concentrated more in both the urban and rural towns close to the Anambra-Niger river banks complex. Participants in the marketing system may have to travel long distances in order to buy or sell their produce, a situation, which at times created gaps between supply and demand and possible hikes in product prices. More so, catfish being an agricultural product is bulky and perishable. It therefore, exerts various pressures on handling, packaging, transportation and sales with adverse antecedent effect on market prices. In addition, poor storage facilities coupled with improper handling and transportation stress lower quantity and cause losses leading to reduced market margins and poor returns. This signifies the existence of inefficiencies in the marketing system in the study area and thus the reason for this study to determine the operational efficiency of live catfish marketing in the State and variables that influence income realized by the marketers. MATERIALS AND METHODS The study area is Anambra State, which is one of the 36 States of the Federal Republic of Nigeria. It occupies an area of 4,416 km 2, 70% of which is arable land. Agriculture is the predominant occupation in the rural areas engaging more than 70% of the rural population. Marketing, including the marketing of live-catfish, is a vital non-farming occupation used to earn additional income outside farming To cite this paper: Ugwumba, C.O.A. and R.N. Okoh, Price spread and the determinants of catfish marketing income in Anambra State, Nigeria. J. Agric. Soc. Sci., 6: 73 78

2 UGWUMBA AND OKOH / J. Agric. Soc. Sci., Vol. 6, No. 4, 2010 by women (Ugwumba & Obiekezie, 2008). The State is sectioned into 4 Agricultural Zones namely-onitsha, Awka, Ihiala and Aguata agricultural zones. About 120 actors along the catfish marketing channels were randomly selected and interviewed. They included 20 producers, 32 wholesalers, 32 retailers and 20 consumers. The consumers were smaller in number since their role in the survey was to provide confirmatory consumer prices from producers, wholesalers and retailers. It is noteworthy that majority of the marketing respondents especially the wholesalers (32), retailers (12) and consumers (12) were selected from Onitsha zone. This is because, only the zone housed the four major daily live-catfish markets in the State. The producers like the consumers were equally used to provide information on farm-gate price and marketing cost for very few of them that engaged in marketing outside their farms. Finally, structured interview instruments (i.e., 31 from wholesalers, 30 from retailers, 20 from producers & 20 from consumers) were fully utilized in the analysis. Data collected were analyzed by means of descriptive statistics, Sherpherd s formular, Shepherd-Futrel method of analyzing marketing efficiency and multiple regression. The Sherpherd s formular for marketing efficiency is given as: ME = V - 1 I Where: ME = index of marketing efficiency V = value of goods sold (consumer price) I = total marketing cost. While the Sepherd-Futrel method is stated thus: ME = TC x 100 TR 1 Where: ME = Coefficient of marketing efficiency. TC = Total cost incurred by marketing agents and producers combined. TR = Total value of products sold. The multiple regression model employed to examine the influence of socio-economic factors on catfish marketing income was implicitly defined as: Marketing Income (MKI) = f (GEN + AGE + MAS + EDU + EXP + ACC + COM + HOS) Where: GEN = marketers gender (Dummy: male=1; female=0) AGE = marketers age in years MAS = marketers marital status (Dummy: married=1; otherwise=0) EDU = marketers education (years of schooling obtained). EXP = marketers experience (years already spent in the business) ACC = access to credit (Dummy: accessed credit=1; otherwise=0) COM = cost of maketing in Naira (N) (note: $1= N145) HOS = household size (number of persons in the household). RESULTS AND DISCUSSION Socio-economic characteristics of catfish marketers: The socio-economic variables of catfish marketers considered in this study include gender, age, level of education, years of experience and average monthly income. Table I below shows the afore-mentioned variables analyzed by means of non-parametric statistics. The study revealed that majority of the wholesalers and retailers (96.8% & 96.7%, respectively) were women. This means that catfish marketing is gender biased in favor of women. A situation attributed to a tradition in the study area, which associates jobs related to cooking and smoking with the female folk. This result conforms to the findings of Aihonsu and Shittu (2008) on fish smoking and marketing; Ugwumba (2009) on fresh maize marketing. However, it differs from Ebe (2007) and Okoh et al. (2008), where men dominated the wholesale levels of fuel wood and rice marketing respectively. The catfish marketers attained an average age of 47 years (Table I). About 83.8% of the wholesalers and 46.7% of the retailers fell within the active energetic age bracket of years. This is an indication that catfish marketers are dynamic youths willing to take risks associated with catfish marketing in the State. The least participants were those below 31 years (10.0%) as well as those above 60 years (13.3%). The average catfish marketer had basic primary education and 14.8 years of experience in the business. Outside the 3 retailers (4.9%) that were uneducated, other marketers experienced various levels of education. By implication, this is a plus for the business since it shows that catfish marketing in the study area is handled by experienced people working with new and sound ideas (courtesy of their education) that would improve their volume of business and income. Monthly income of catfish marketers: The marketers realized income as returns from catfish marketing business. This is also presented in Table I. Majority of the wholesalers (80.6%) netted above N90,000 per month, while most of the retailers (73.3%) realized below N90,000. This means that catfish marketing, though mostly handled at the wholesale and retail levels by women, is more profitable at the wholesale level. The reason could be that wholesalers are younger, more energetic and more educated than the retailers and therefore possess the qualities and resources to control bigger volumes of business. Effect of socio-economic characteristics of catfish marketers on marketing income: The multivariate 74

3 FACTORS DETERMINING CATFISH MARKETING IN NIGERIA / J. Agric. Soc. Sci., Vol. 6, No. 4, 2010 analysis of the multiple regression version was adopted to predict the effect of socio-economic characteristics (predictors) of catfish marketers on catfish marketing income (predictand). The predictors used were gender of the marketer represented by GEN, age (AGE), marital status (MAS), education (EDU), marketing experience (EXP), access to credit (ACC), cost of marketing (COM) and household size (HOS). The MINITAB software statistical package was used to run the analysis and the output is presented in Table II. However, the regression equation is: MKI = GEN AGE MAS EDU EXP ACC COM HOS Result of the regression analysis showed that the coefficient of gender was positive and statistically significant at 5 percent. Since this was specified as a dummy (male=1 & female=0), the female marketers dominated the business and earned virtually all income from catfish marketing. Marketers age is positively correlated with marketing income and statistically significant at 1%. This implies that older marketers are more likely to earn income from catfish marketing than younger ones. This is contrary to a priori expectations. The optimism and the mental and physical energy required in catfish marketing, because of the bulkiness of the product decline with age. This result is at variance with the negative and significant relationship recorded by Ebe (2007) on fuel wood marketing and Ugwumba (2009) on fresh maize marketing. The coefficient of marital status is positively related to marketing income and significant at 5% level of probability. This implies that catfish marketing is limited to married people especially married women who lean on the financial support of their husbands and relatives to flourish in the business. Education has a coefficient that is statistically insignificant (T-cal 1.45 < T-tab 2.10, P=0.5). However, it is positively signed implying that level of education has a positive but weak influence on income realized by catfish marketers. Mejeha (2005) reported same direct relationship between level of education and the amount of income and savings. Marketing experience is negatively correlated with catfish marketing income suggesting that marketers with little experience but possess huge resources demanded to operate especially at the wholesale level could do well in the business. Result of the regression analysis also show that marketing experience has no significant effect on marketing income (T-cal 1.32 < T-tab 2.10, P=0.5). Access to credit is insignificant but negatively correlated with catfish marketing income. The reason could be that marketers who did not access credit are more likely to realize income than those who did. Those who accessed credit might be over-burdened by repayment of the loans. Further result of the analysis shows that household size has a coefficient that is statistically significant at 5% Table I: Distribution of catfish marketers according to socio-economic characteristics (n=61) Variable Wholesaler Retailer Mean/Mode Gender Frequency % Frequency % Male Female female Age Above Level of education No formal education primary Above Vocational training Years of experience Above Monthly income Less than 30, ,001 60, ,001 90, , , , , Above 150, Table II: Effect of socio-economic characteristics of catfish marketers on marketing income Predictor Coefficient St Dev T P Constant ** GEN ** AGE * MAS ** EDU EXP ACC COM ** HOS R-Sq = 78.8% R-Sq(adj) = 75.5% F-statistic = Durbin-Watson statistic = 1.96 Source: Field survey, 2009 **significant at 5% level of probability; *significant at 1% level of probability level of probability and negative. This implies that marketers with smaller households are more likely to realize more income from the business. This conforms to a priori expectations since small households encourage savings and boost resources highly needed to advance in catfish marketing. However, it contradicts Ebe (2007) and Ugwumba (2009) who found a positive relationship between household size and incomes from fuel wood supply and fresh maize marketing, respectively. They hinged the positive relationship on the fact that fuel wood harvesting and selling likewise roasting and selling of fresh maize needed more hands, which large households could provide. 75

4 UGWUMBA AND OKOH / J. Agric. Soc. Sci., Vol. 6, No. 4, 2010 Table III: Cost structure for catfish marketing by middle men Variable Wholesaler & Retailer TC (%) Wholesaler % of TC Retailer % of TC Purchases Variable Costs Transportation Loading Off-loading Security Storage Association dues TVC Fixed costs Rent Local govt. rate Depr. Of eqpts Interest on loans TFC TC Table IV: Per kilogram price spread and margins of catfish marketing obtained through different channels (N/kg) Variable\Channels I II III IV Net price realized by producer (98.5) (68.7) (73.44) (66.46) Wholesaler s net margin (26.16) (13.23) Retailer s net margin - - (25.88) (20.31) Cost of marketing (1.46) (5.11) 5.06 (0.68) 0.32 (0.07) Consumer s price (100) (100) (100) (100) Gross market margin (1.46) (31.27) (26.56) (33.53) Marketing efficiency (Sherpherd formular) Table V: Estimation of marketing efficiency Sherpherd formular and Shepherd-Futrel technique Item Wholesaler & Retailer Wholesaler Retailer Value of product sold (consumer price N/kg) (V) N N N Marketing cost (I) (N /kg) N N N Marketing efficiency(me) (Serpherd formular- (V/I) -1) Total revenue (TR) N142,029,750 N118,207,200 N23,822,550 Total cost (TC) N128,381,728 N108,809,306 N19,611,924 Marketing efficiency(me) (Shepherd-Futrel (TR/TC x 100) 90.39% 92.05% 82.33% Source: Field survey, 2009 Cost of marketing is negative ( ) and highly significant at 5% level of probability (T-cal > T-tab 2.10). This result is in agreement with a priori expectations and the records of Gadre et al. (2003) and Ahmed (2007) who reported a negative relationship between cost of marketing and income earned from it. The higher the marketing cost the lower the marketing margins cum marketing efficiency and consequently smaller mean net income realizable. The overall significance of a regression is usually assessed by the F-statistic value. In this case the F- statistic value of indicates that the socioeconomic characteristics of catfish marketers significantly influenced catfish marketing income. The R-Sq value of 78.8% implies that actually 78.8% of the variation in catfish marketing income is explained by gender, age, marital status, education, experience, access to credit, cost of marketing and household size. Cost of marketing has the highest significant influence on catfish marketing income. Catfish marketing channels: Marketing channels indicate how various market participants are organized to accomplish the movement of a product from producer to the final consumer. They are classified according to channel levels and the number of channel levels differs by product and by rural and urban location. The distribution channels for catfish in the study area are shown in Fig. 1. The channels ranged from zero-level to three-level channels. In the rural markets, the channels ranged from zero-to-two-level channels. In the urban markets the channel levels for catfish ranged from one-level-to-three-level channels. The higher levels of distribution channels led to increased marketing costs and hence constituted welfare loss to the final consumers. Operational efficiency in the marketing of catfish: Operational efficiency can be measured by cost-benefit analysis. The various marketing functions performed by different agencies and comparison of cost incurred can give an appropriate measure of efficiency, which is presented subsequently. 76

5 FACTORS DETERMINING CATFISH MARKETING IN NIGERIA / J. Agric. Soc. Sci., Vol. 6, No. 4, 2010 Fig. 1: Marketing channels for catfish in Anambra State Farmers Consumer Wholesale Retailers Wholesale Consumer Consumer Retailers Consumer Channel: I II III IV Cost structure for catfish marketing by middlemen: Cost management is a very important aspect of any business venture and greatly determines the profitability and success of the business. In catfish marketing many costs are incurred and mostly at the wholesale level of the business. These various marketing costs as well as their analysis are shown in Table III. Outside cost of security, which the retailers did not incur, wholesalers and retailers incurred other marketing costs including purchases, transportation, loading, offloading, storage and association dues as variable costs. They also incurred a few fixed costs such as rent, Local Government rates, depreciation of equipments and interest on loans. Apart from the cost of purchasing a kilogram of catfish, the wholesalers spent N37.03/kg on other variable and fixed cost items, while the retailers expended just N5.06 on the same items. Transportation cost alone constituted N29.61/kg or 80% of this cost as against the N0.15 or 3% spent on them by the retailers. This high cost of transportation borne by the wholesalers in the cost of transacting their businesses might be attributed to long distances covered to procure the product, poor conditions of roads, tolls taken by security personnel. It might also be due to high cost of fuel/diesel and spare parts. The least cost spent by the wholesalers was depreciation costs (N 0.03/kg) and that of the retailers, cost of off-loading (N 0.10). At last, the wholesaler spent a total of N to purchase and sell one kilogram of catfish, while the retailers bought and sold the same quantity for N Market margins and price spread: Price spread refers to the difference between consumer price and producer price for an equivalent quantity of farm produce and in this case for one kilogram of live catfish. This spread consists of marketing costs and margins of the intermediaries, which ultimately determine the overall efficiency of a marketing system. It is useful in determining the efficiency of the catfish marketing system. The cost and margin for each agency in the various channels is given in Table IV. Share of the producer: The producer s share in naira was highest (98.5%) in channel I and lowest (66.46%) in channel IV. This high share was made possible due to the total elimination of middlemen intervention between producers and consumers. This result tallies with the deduction by Stone (2006) that a successful small-scale operation is profitable only when producer works to develop a market and sells catfish directly to consumers. Lower producer s share recorded in channels II, III and IV was, because the producers marketed their produce through the wholesalers and retailers who reaped away large amount from the consumers. Share of the wholesaler: The wholesaler s net margin share was 26.16% of consumer s price in channel II and 13.23% in channel IV. It was also observed that the quantity of catfish handled by this agency was very large compared to the retailers. Share of the retailer: This agency was the final link between the wholesalers and the consumers and played an important role in delivering the goods and services at the desired time and place. The net margin of retailers in consumer price was worked out to 25.88% and 20.31% in channels III and IV, respectively. Gross market margin: The percentage gross market margin was 1.46, 31.27, and 33.53% in channels I, II, III and IV, respectively. The marketing margin was lowest in channel I due to absence of market intermediaries. Catfish marketing efficiency: Analysis of marketing efficiency for the four channels was done by means of the Sherpherd formular, while that of the wholesalers and retailers was computed using Sherpherd formular and Shepherd-Futrel method. The results are profiled in Table IV. Result of the analysis (Table IV) above explains that marketing efficiency (ME) calculation using only Shepherd formular was much higher in channel I (67.06), than in channels II (2.20), III (2.77) and IV (1.98). This means that the higher marketing margins taken away by the market intermediaries in channels II, III and IV resulted in poor efficiency recorded by them. These results agree with the records of Gauraha et at. (2007) for rice marketing and Gadre et al. (2003) for onions marketing, which indicated highest marketing efficiency figures for producer-consumer channels. Results of analysis of coefficients of marketing efficiency using Sherpherd formular and Shepherd-Futrel technique as shown in Table V shows an overall efficiency index of 0.28 for wholesalers and retailers together; 0.33 and 0.24 for wholesalers and retailers respectively, using the Sherpherd formular. This result accorded the wholesalers a slightly higher efficiency than the retailers. On the other hand, the Shepherd-Futrel technique, which has been proved to be a better method of calculating marketing efficiency (Arene, 2008) yielded coefficients of marketing efficiency of 90.39% for the middlemen; 92.05% for the wholesalers and 82.33% for the retailers. These results are indications that 90.93%, 92.05% and 82.33% of their sales revenue are taken up by costs. That is, the lower the coefficient of marketing efficiency the higher the level of efficiency. Efficiency of catfish marketing could therefore be 77

6 UGWUMBA AND OKOH / J. Agric. Soc. Sci., Vol. 6, No. 4, 2010 increased by adopting those measures that would increase revenue, reduce marketing cost and thus lower the coefficient of marketing efficiency. Therefore, in the study area the retailers were more efficient (82.33%) than the wholesalers (92.05) in the marketing of catfish. This result compares favorably with the 54.06% and 61.32%, respectively recorded for retailers and wholesalers in fresh maize marketing by Ugwumba (2009). CONCLUSION Catfish marketing in the area was gender biased in favor of women, because they were in the majority both at the wholesale and the retail levels. The marketers mean age was 47 years, implying that most of them were dynamic youths willing to take risks associated with catfish marketing in the State. The business was more profitable at the wholesale level than at the retail level, though wholesaler s profitability was drastically reduced by high marketing costs, which totaled 80% for the wholesalers and 5% for the retailers per kilogram of fish sold. The marketing margin was lowest in channel I and highest in channel IV. This was attributed to the absence of market intermediaries in channel I. The retailers were more efficient (82.33%) than the wholesalers (90.05) in the marketing of catfish. Catfish marketing income was influenced by gender and marital status; however, it was markedly affected by marketing costs, making marketing costs the biggest determinant of marketing income in live-catfish marketing business. REFERENCES Aihonsu, J.O.Y. and A. Shittu, Value addition: comparative economic analysis of fish processing technologies in two fishing communities in Lagos State. In: J.C. Umeh,C.P. Obinne and W. Lawal (eds.), Prospects and Challenges of Adding Value to Agricultural Products: Proc. FAMAN 22 nd Annual Conference, Markurdi, Nigeria, pp: Arene, C.J., Economic Analysis of Agricultural and Rural Development Projects. SNAAP Press Ltd, Enugu, Nigeria Ebe, F.E., Economic Study of Fuel Wood Marketing and Consumption in Enugu State, Nigeria. Ph.D. Dissertation. University of Nigeria, Nsukka Gadre, A.V., J.M. Talathi and S.S. Wadkar, Price Spread in Marketing of White Onion in Raigad District of Maharashtra State. Retrieved from: nic.in/journal 2. pdf Gauraha, A.K., K.N.S. Banafar, P.K. Verma, V.K. Choudhary and B.C. Jain, Marketing Strategies of Rice in Chhattisgarh: A Case Study. Retrieved from, cabstractsplus.org/abstracts.aspx? Ac No Kohls, R.L. and J.N. Uhl, Marketing of Agricultural Products, 2 nd edition. Macmillan Publishing Coy, Inc. New York Mejeha, R.O., Determinants of Savings Mobilization in the Rural Economy of Abia State, Nigeria. Ph.D Dissertation. Michael Okpara University of Agriculture, Umudike, Nigeria Okoh, R.N., C.O.A. Ugwumba and H.O. Elue, Gender Roles in Foodstuff Marketing in Delta-North Agricultural Zone: The Case of Rice. In: J.C. Umeh,C.P. Obinne and W. Lawal (eds.), Prospects and Challenges of Adding Value to Agricultural Products: Proc. FAMAN 22 nd Annual Conference, Markurdi, Nigeria, pp: Olukosi, F.O. and S.U. Isitor, Introduction to Agricultural Marketing and Prices. Living Books Series, Abuja, Nigeria Ugwumba, C.O.A. and A.A.Obiekezie, Impediments to the Development of Live-Catfish Retail Markets in Anambra State, Nigeria. Nigerian J. Res. Prod., 13: Ugwumba, C.O.A., Analysis of Fresh Maize Marketing in Anambra State, Nigeria. J. Res. Natl. Dev., 7: (Received 22 April 2010; Accepted 29 April 2010) Ahmed, N., Value Chain Analysis for Hilsa Marketing in Coastal Bangladesh. Agriculture News 33, Department of Fisheries Management, Bangladesh Agricultural University, Dhaka, Bangladesh 78