IJAAAR 8 (1): 39-45, 2012 International Journal of Applied Agricultural and Apicultural Research 39 © Faculty of Agricultural Sciences, LAUTECH, Ogbomoso, Nigeria, 2012

Effect of “Irkoy Gomni” Micro-credit scheme on Resource- Use in cattle fattening in Tillabery Region of Republic.

Maikasuwa 1, M. A. Ala 1, A. L. Jibir 2, M and Daouda 3, M

1Department of Agricultural Economics, Usmanu Danfodiyo University, Sokoto, Nigeria 2Department of Animal Sciences, Usmanu Danfodiyo University, Sokoto, Nigeria 3Ministry of Animal Resources, , Niger Republic

Abstract ______This study was carried out to ascertain whether credit obtained for cattle fattening has had any meaningful contribution to the resources used by the beneficiary farmers in Kollo LGA of Tillabery Region Niger Republic. One hundred loan beneficiary cattle fattening farmers were randomly selected out of a sampling frame of 732 beneficiaries with not less than 5 borrowing circles. One hundred non-beneficiary cattle fatteners who were immediate neighbours of the sampled beneficiaries were also randomly selected from an established sampling frame obtained from the village heads to make a total sample size of 200, comprising of 100 beneficiaries and 100 non beneficiaries. Data were analyzed using descriptive statistics, chi-square and multiple regressions. The results showed that cattle fattening was the most preferred economic activity for both the beneficiaries (94%) and their non beneficiary counterparts (91%). The chi- square value (5.192) showed no significant difference in preferences of the economic activities between the two sets of farmers. Credit delivered to the beneficiaries enabled them use higher quantities of feed (P<0.01)and labour resources (P<0.1) than their non-beneficiary counterparts. Similarly, credit delivered has brought about significant increase (P<0.01) in revenue accrued to the fattening business of the beneficiary farmers. Based on the results, it is recommended that the scope of the credit be expanded to cover more farmers in the area. ______Key words: Microcredit, ResourceUse, cattle, fattening

Introduction ordinary go to waste to feed their animals. Each region in Niger Republic is The number of livestock in Kollo LGA is currently working hard to develop its estimated to be 189,937.81 Tropical agribusiness potential. This requires that Livestock Units (TLU) with available they identify commodities in which their roughage of 321,062.190 metric tons which region has a comparative advantage. Kollo is more than enough in term of dry matter LGA has identified fattening beef cattle as content (DDRA/KOLLO (2009). a competitive activity for farmers in the A fattening operation conducted in area. It gives the farmers yearround work Libore in Kollo LGA between 1980 to1985 and provides them with extra income. on loan beneficiary farmers with amount They can make use of different assorted distributed ranging from 50,000 to75,000 farm byproducts such as millet stalk, rice Fcfa per farmer revealed through farm straw, rice bran, sugarcane tops which budgeting analysis that farmers were 40 Maikasuwa, M. A. Ala , A. L. Jibir, M and Daouda, M gaining net profit ranging between 10,000 and13 0 53′ North and Longitudes 1 030′ to 25,000Fcfa,(SAEIA/KOLLO,1985). Also and2 055′ East. It shares common borders another fattening study conducted on with Dosso State in the East, and sheep in Senegal as reported by Charles LGAs in the North, Tillabery and (2000) shows that farmers are gaining Tera LGAs in the West and Say LGA in profit of up to 50,000Fcfa. A fattening the South. It covers a land area of project conducted using local breeds such approximately 9,408 square kilometers as Djielli, Azawak, and Bororo produced and has a population of about 418,912, profits that created positive incentives to Service Departmental du Development producers and reflected an efficient use of Communautaire (SDDC) ( 2009). The climate domestic resources. Participating farmers is characterized by wet and dry seasons. like appreciated the use of these breeds The latter comprises a dry and cool period because the average increase in weight is (Harmattan) followed by a hot weather. good (between 500g to 1,200g/day), Rainfall starts in late June and ends in (DDRA/KOLLO,2009). At such rate of early September, mean annual rainfall gain, it takes three to four months to ranges from 300 to 500 mm (SDDC, 2009). achieve a selling weight of 350 to 400kg. The system of livestock husbandry is Similarly, due to the reduced length of intensive and semiintensive types. The time during which capital is tied up, most common animals found include farmers felt that profits realized in cattle, goats, sheep, camels, horses and fattening the local breeds were donkeys. Animals rely on natural grazing significantly high because of reduced and crop residues as their sources of feed, interest cost. Through this project poor however, generally there is lack of people especially women can earn drinking water for livestock. additional income which will be helpful for their livelihood. Sampling technique This study was carried out to From the list of beneficiaries ascertain whether credit obtained has had obtained at the bank, 732 beneficiaries any meaningful contribution to the with at least five borrowing cycles were resources used by the beneficiary farmers. sorted out from which 100 farmers were The information might be useful in randomly selected for the study. deciding whether there was any need for Beneficiaries with not less than five scalingup credit delivery for cattle borrowing cycles experience were chosen fattening in the study area. because they would have had measurable impact as explained by Sunita (2003) that Methodology some indicators could be verified in cases The Study Area where people benefited from such a The study was conducted in Kollo programme at least for not less than five Local Government Area (LGA) of cycles. In this case, the accumulated Tillabery State in Niger Republic. Kollo benefits of the previous loans and their LGA is situated in the sahel vegetational incomes, as well as the increased zone and lies between Latitudes 12 0 30′ experience of the beneficiaries in Microcredit Scheme on Resource use in Cattle Fattening 41 managing the loan efficiently contributed the following equations .The function that to help in consumption smoothing as well gives the best fit in terms of R 2, direction, as in asset building. One hundred non magnitude and significance of the beneficiary cattle fatteners who were regression coefficient was selected .The immediate neighbours of the sampled function was estimated through multiple beneficiaries were also randomly selected regression analysis. The regression model from an established sampling frame employed in the study is of the general obtained from the village heads to make a implicit form: total sample size of 200, comprising of 100 Q = f(x 1,x 2,x 3,x 4,x 5,x 6, x7 +…………+ e) beneficiaries and 100 non beneficiaries. (1) Where; Data collection Q = final weight of animal (in kg) Primary data were collected using X1 = weight of stock (in kg) questionnaires administered by the X2 = medication (in mg) researchers with the help of trained X3 = feeds (in kg enumerators between October to X4 = labour(in manday) December 2010. The period chosen X5 = Water intake (in liters) corresponded to the time when farming X6 = housing (in m 2) activities were almost finished and people X7 = access to credit (dummy variable were less busy. Data collected covered whereby beneficiary is scored 1and zero, variables such as amount of credit otherwise ) e = error term received by the beneficiaries, quantities of Access to credit was used as dummy labour, feed, medication, water and variable to demarcate between housing . Current market prices were used beneficiaries and non beneficiaries. to put values on the variables considered Dummy variable is quite a versatile .The variables used in estimating the variable because it can be used to show consumption pattern were calculated on differences in the constant terms of monthly basis and then reported for the regression equations estimated for year. The housing component was categories of observations. It can also be evaluated using straightline method of used to show differences in the regression depreciation. coefficients of the same variables in different categories. The point to note here Data analysis is that, instead of estimating a separate Regression analysis and chisquare regression equation for each group, we were the main analytical tools used. Data have been able to estimate one equation collected were analyzed using Statistical for both groups and at the same time show Package for Social Sciences (SPSS) the difference between them software (version 16). Data generated (Olayemi,1998). from the study were subjected to several The linear function estimated is of the algebraic forms amenable for regression general form: analysis , such as linear model, double Q = a + b 1x1 + b 2x2 +b 3x3 +b 4x4 +b 5x5 log , quadratic functions as represented in +b 6x6 +b 7x7 +e(2) 42 Maikasuwa, M. A. Ala , A. L. Jibir, M and Daouda, M

Where: Q, x 1 to x 7, are as earlier presented in table 1. The Table indicates defined that majority of both beneficiaries (94%) a = intercept term and non beneficiaries (91%) choose b1b7 = regression coefficients fattening as the most preferred economic The quadratic function is estimated as activity. This finding may not be follows: unconnected with the fact that the study Q = a + b 1x1 + b 2x2 +b 3x3 +b 4x4 +b 5x5 area fell within the sahelosaharian zone +b 6x6 +b 7x7 b8x12 b9x22 b10 x32 b11 x42 which is only conducive for animal b12 x52 b13 x62 b14 x7X1 x2x3 x4x5x6 x7………. husbandry (SDR, 2003) on the one hand. +e (3) On the other, the high preference for The power function is specified as fattening exhibited by the two categories follows: of farmers may be associated to the Q = a x 1b1 x2b2 x3 b3 x4b4 x5b5 x6b6 closeness of the study area to the country’s x7b7 …………… +e. (4) state capital (Jean, 1993) bringing about This is usually expressed in logarithmic increased demand for meat. This implies form as: that giving the necessary incentives to the LogQ =loga+ b 1log x1 + b 2logx 2 two sets of farmers, all of them will +b 3logx 3 +b 4logx 4 +b 5logx 5 +b 6logx 6 engage in livestock fattening business. +b 7logx 7 + loge…..(5) This shows the important place fattening enterprise occupies in the lives of the two Results and Discussion sets of farmers in the study area. The chi People in Kollo LGA are engaged in a square statistics depicted no significant number of economic activities to earn a difference between beneficiaries and non living. Common activities in the area were beneficiaries the most preferred economic identified and presented to the farmers to activities. select the most preferred in terms of income generation and the result is

Table 1: Farmers response to the most preferred economic activities Expectation Beneficiaries Non beneficiaries F % F % Fattening 94 94 91 91 Rearing sheep 1 1 3 3 Petty trade 4 4 3 3 Crop Marketing 1 1 0 0 Buy cart 0 0 1 1 Dry season farming 0 0 2 2

Total 100 100 100 100 Field survey 2010 χ2 = 5.192 ns (p <0.10), df = 5 Microcredit Scheme on Resource use in Cattle Fattening 43

Table 2 presents results of the output of the non beneficiaries. Three of regression analysis. Credit was assigned these explanatory variables i.e. credit a dummy variable to demarcate between (X 7), feed (X 3) and labour (X 4) were beneficiaries and non beneficiaries. significant at 1%, 1% and 10%, Double log, Linear, Semilog and respectively meaning that they had Quadratic regression models were used significant contribution to the output of for the estimation (Maikasuwa, 2007). the beneficiaries. This suggested that an Semilog model was selected to be the increase in the use of these resources leadequation based on the fact that it while keeping others constant would provided the best fit. The statistical significantly increase the output of criteria used to assess the fitness of the beneficiaries. This finding concurs with models were the coefficient of Olagunju (2007) Who explained that determination (R 2), the F statistic and increase in feeds and labour due to the t statistic. credit would be translated into increase The R 2 denoted the percentage of in output and income of the variation in the dependent variable that beneficiaries. Credit was significant at was accounted for by the variation in the 1% meaning that it was a crucial variable independent variables (Thomas, 2007). and had brought about significant The value for the coefficient of increase in revenue generating capacity determination for the model was 0.872 of the beneficiaries from cattle fattening. which implied that 87.2 % of the This is in line with Damisa et al., (2010) variation in the revenue generated from who reported a significant positive the enterprise was explained by impact of credit on livestock variation in the explanatory variables productivity. Awotide et al., (2010) used in the model while the remaining realized an increase in the foundation proportion not explained was attributed stock of cattle from 43 to 53 due to to the error or random distribution in credit. the model. The Ftest showed the overall test The coefficients of all the of significance of the regression equation explanatory variables except water and and was significant at 1% level showing housing (X 5 and X 6) were positive .The that the regression equation was fit. On positive coefficient of these variables the whole, beneficiaries income indicated that they contributed more in increased more than that of non determining the output of the beneficiaries. This should be attributed beneficiaries. The negative coefficient of to the credit support given to the X5 and X 6 suggested that they beneficiaries by the scheme contributed more in determining the

44 Maikasuwa, M. A. Ala , A. L. Jibir, M and Daouda, M

Table 2 : Regression results showing factors influencing output in cattle fattening Variables Regression Coefficient Linear Semilog Double log Quadratic

Stock 0.0168 0.081 0.169 140.814 (0.011) (0.427 ) (0.416) (0.145) Medicare 0.064 0.000 0.31 0.060 (1.038) (0.589) (0.489) ( 0.460) Feed 0.412 0.001 0.476 0.182 (82.789***) (17.305***) (9,370***) (399.806***)

Labour 0.079 0.006 0.003 0.019 (0.302) (1.779*) (0.011) (0.026) Water 0.002 6.253 0.216 0.0000 2 (0.500) (1.07) (0.605) ( 0.249) Housing 0.228 0.002 0.033 1.216 (1.321) (1.035) (1.049) (0.743) Credit 0.168 0.098 343.853 (1.157) (4.412***) (0.980) 1.649 4.818 0.552 106.467 Constant (0.686) (161.162***) (0.190) (0.392) R2 99.4 87.2.0 81.9 100 F value 4639*** 8.923*** 14.850*** 134500***

Source: Field survey, 2010. ***: significant at 1% , **: significant at 5% , * significant at10% figures in brackets are t values

Conclusion and Recommendations increase in the standard of living of more From the results of the study, it can people in the area. be concluded that, cattle fattening was the most preferred economic activity in the References study area. Also, credit delivered to the beneficiaries enabled them use significant Awotide, D.O. Ajibide, A. and Ambil, O. I. amount of feed and labour resources. (2010). Assessment of Agricultural Similarly, credit delivered has brought Credit on Livestock Farmers in about increase in revenue accrued to the Egba Division of Ogun state, fattening business of the beneficiary Nigeria. In: J.N. Nmadu, M.A. Ojo, farmers. Based on the results, it is U. S. Mohammed, K. M. Baba, F. D. recommended that the scope of the credit Ibrahim, and E. S. Yisa . be expanded to cover more farmers in the Proceedings of 11 th Annual area. Ultimately, this shall bring about Conference of the Nigerian Association of Agricultural Microcredit Scheme on Resource use in Cattle Fattening 45

Economists held at New lecture Assessment of HIV/AIDS on theatre, school of Goats production in Sokoto State. Agriculture and agricultural In: U. Haruna, S.A. Jibril, Y.P. Technology, Federal University of Mancha and M. Nasiru (eds). Technology, Gidan Kwano, Minna, Proceedings of 9 th Annual Niger State. Conference of the Nigerian DDRA/KOLLO (2009). Direction Association of Agricultural Departemental des Ressources Economists Held at 1000 Seater Animal de Kollo, Rapport annuel Theatre, Abubakar Tafawa Balewa 2009. P :27. University, Bauchi. 5 th – 8th Nov. Damisa, M.A. Kehinde, E. A. and 2007. Omokore, D. F. (2010). Impact of Olayemi, J.K. (1998) Element of Applied Credit and the farmers Econometrics . Elshaddai Global Characteritics on livestock Ventures ltd No15,Ago Ilorin productivity in the Northern St,Mokola U.I.P.O Box 22520 GUinea savannahof Nigeria. In: Ibadan Nigeria. Pp 109110 J.N. Nmadu, M.A.ojo, U. S. SAEIA/Kollo (1985).Service Mohammed, K. M. Baba, F. D. D’Arrondissement de L’Elevage et Ibrahim, and E. S. Yisa. de Industries Animal de Proceedings of 11 th Annual Kollo.Rappor annuel 1985. Conference of the Nigerian Service departemental du development Association of Agricultural comunautaire (SDDC) (2009) Economists held at New lecture Presentation du department de theatre, school of Agriculture and Kollo.Pp :110. agricultural Technology, Federal Strategie de Developement Rural( SDR) University of Technology, Gidan (2003) :Secretariat Kwano, Minna, Niger State. excutif ;Gouvernement de la Charles T. (2000). Document de Republique du Niger :Pp :15. capitalisation sur les MARP et Sunita P. (2003) Factors Impeding the PIPO dans la region de Poverty Reduction Capacity of Louga.http://www.pnud.ne/rens Microcredit: Some Field e/Biblioth%c3gue/Aquadev01.pdf Observations from Malawi and .P :36 Ethiopia. African Development Bank Jean, P. (1993 ). “Animal production in the Economic Research Papers NO tropic and sub-tropic ”. First edition 74 (January). P: 24. Macmillian Press Ltd., London. Thomas A. (2007). Econometrics. Thoas Maikasuwa M., A., U. B. Kyiogwom and I. Andren and Ventures publishing. Mohammed (2007). Impact Bookboon.com