Asan Journal of Poultry Scence, 2015 ISSN 1819-3609 / DOI: 10.3923/ajpsaj.2015. 2015 Academc Journals Inc. Determnants of Poultry Farmers Partcpaton n Lvestock Insurance n Southwest Ngera O.K. Akntunde Department of Agrcultural Economcs, Unversty of Ibadan, Ibadan ABSTRACT Poultry brds are prmarly exposed to the rsk of death caused by varous types of dseases. In many cases, epdemc dseases can cause catastrophc losses from deaths of an entre stock of lvestock. In the lght of ths, ths study was desgned to examne the determnants of poultry farmers partcpaton n lvestock nsurance n southwest Ngera. Prmary data were obtaned wth the ad of structured questonnare from a cross secton survey of 403 poultry farmers drawn through mult-stage samplng procedure. Descrptve statstcs and logt model was used to analyze data obtaned. Majorty (81.4%) of the poultry egg farmers were males. Majorty (85.6%) were marred wth an average household sze of 5.4±1.7 members. The average age and mean years of experence were 45.5±9.1 and 10.0±5.05 years, respectvely. More than half (59.6%) of the poultry farmers were aware of lvestock nsurance polcy whle only 11.9% of the poultry farmers nsured ther poultry farms. Stock sze, rearng system, access to extenson servces and poultry rearng experence were sgnfcant varables that nfluenced the partcpaton of the poultry farmers n lvestock nsurance polcy. It s recommended that effectve servce delvery by nsurance servce provders wll ensure contnuty of farmers partcpaton n agrcultural nsurance. Also, the government should formulate a polcy that wll make lvestock nsurance more affordable to poultry farmers and adequate dssemnaton of knowledge on the benefts of lvestock nsurance by extenson agents s crucal to ncrease the level of partcpaton of poultry farmers n the use of lvestock nsurance polcy. Key words: Rsk, mtgaton, response, factors, egg, producton, logt INTRODUCTION Poultry enterprses are usually faced wth a lot of rsks and uncertantes, some of whch are natural hazard such as floods, drought, fre outbreak, dseases, pest attacks and theft. Snce, the poultry farmer cannot predct the probablty of occurrence of any of these and cannot bear these rsks and uncertantes alone, he s faced wth the opton of transferrng or sharng the rsks nvolved n the producton. Therefore, poultry farmers underwrte lvestock nsurance n order to mtgate the ll effects of rsks. Agrcultural nsurance s an economc component of farm management desgned to reduce the adverse effect of natural dsaster on farmers ncomes through the payment of ndemnty (Ajeh, 2010). In Ngera, the Government ntroduced agrcultural nsurance programme wth the trpartte am of broadenng farmers access to farm resources, postvely changng farmers atttude to rsk n ther choce of resource use and to acheve ncreased food supples n the market (Olubyo et al., 2009). The prevous studes have shown that agrcultural nsurance protects farmers aganst fnancal dsaster after sufferng any of the nsured rsks and the farmer s not only able to contnue n busness but also empowers the farmers to obtan farm credt (Hardaker et al., 1997; Olubyo and Hll, 2003; Epetmehn, 2010). 1
The Natonal Agrcultural Extenson and Research Lason Servces dentfed the followng as the benefts of agrcultural nsurance to farmers: (a) It protects farmers aganst fnancal dsaster after sufferng any of the nsured rsks for whch ndemnty (compensaton) s pad. The farmer s not only able to contnue n busness but also the stablty of hs ncome s enhanced, (b) Agrcultural nsurance empowers the farmers to obtan farm credt. Snce, nsurance guarantees protecton aganst crop and/or lvestock falure, the nsured farmer has greater confdence n obtanng loans, (c) It facltates better plannng and project mplementaton snce there s a hgh level assurance for contnuty n busness, (d) It serves as an assurance to banks and other fnancal nsttutons who grant loan for agrcultural purposes that loans gven wll be repad and (e) It buld farmers confdence n usng new technologes and makng greater nvestments n agrculture (NAERLS., 1991). Ngeran farmers are not very excted about takng an nsurance polcy. Ths can be traced to the less than satsfactory mage of the nsurance ndustry regardng loss compensatons and ths problem has created mxed feelngs towards Agrcultural nsurance by prospectve farmers and hence, the farmers become reluctant n ther wllngness to take an nsurance cover and also consderng the very low ncomes, the small szes of holdngs amed at subsstence producton, large scale gnorance and poverty and the adverse vew of other people s experences wth actvtes of nsurance companes n other sectors, peasant farmers are generally reluctant to patronze the nsurance market, let alone wllngly forgo a small payment n the form of premums n exchange for ther farm rsks (Olubyo et al., 2009). Despte the exstence of nsurance servces rendered by Ngeran Agrcultural Insurance Corporaton and other prvate frms n Ngera, there has been a low level of partcpaton of farmers buyng nsurance premum. It s n the lght of the above that ths study was conceved to examne determnants of partcpaton of poultry farmers n lvestock nsurance n southwest Ngera. The specfc objectves are to: C C C Determne the level of awareness of poultry farmers lvestock nsurance Profle the level of partcpaton n lvestock nsurance polcy by poultry farmers Examne the factors nfluencng the poultry farmers npartcpaton n lvestock nsurance polcy MATERIALS AND METHODS Study area: The study was carred out n Osun and Oyo states, Southwest, Ngera. Osun State has 30 local government areas wth an estmated populaton of 3.4 mllon (NPC., 2006) and land area of 14,875 km 2 on lattude 5 N and 8 N, between longtude 4 E and 5 E. The clmate s humd tropcal type wth a mean annual temperature of about 28 C and a mean annual ranfall of over 1600 mm. Oyo State has 33 Local Government Areas wth an estmated populaton of 5.6 mllon (NPC., 2006). The land area s 35,743 km 2 located wthn lattude 3 N and 5 N, between longtude 7 E and 9.3 E. The average temperatures are between 24 C and 25 C. Ranfall fgures over the state vary from an average of 1200 mm at the onset of heavy rans to 1800 mm at ts peak n the southern part of the state to an average 800 and 1500 mm at the northern part of the state. There are two dstnct ecologcal zones n both states; the ranforest and derved savannah zones. Major crops found n these states are yam, cassava, maze, rce, vegetables and cash crops lke cocoa, rubber, kolanut and ctrus. Rural households n the states rear sheep, goats, local chckens and pgs. Also, ntensve rearng of exotc breeds of cockerels, layers and broler brds have become popular n the study areas. 2
Source and type of data: The prmary data were obtaned wth the ad of well-structured questonnare that captured soco-economc/demographc characterstcs of poultry farmers and farm characterstcs. These nclude age of the poultry egg farmer, gender, level of educaton, poultry farmng experence, household sze and sources of credt. It also ncludes nformaton on awareness about the lvestock nsurance polcy and partcpaton n the polcy by the poultry farmers. Data collecton and samplng technque: A multstage samplng technque was employed n selectng the poultry farmers n the study areas. The frst stage was the purposve selecton of Osun and Oyo States from the sx states that made up the Southwest, Ngera, based on the hghest exotc-poultry populaton dstrbuton n Southwest, Ngera (FDLPCS., 2007). The second stage nvolved purposve selecton of sx (6) Local Government Areas (LGAs) from Osun State and eght (8) local governments from Oyo State. The sze of the local governments chosen from each state was based on avalable records of number of regstered members of the Poultry Assocaton of Ngera (PAN) n whch Oyo State has the hghest number of poultry farmers than Osun State. The purposve selecton of the local governments n each state was based on those wth the hghest number of regstered members of the Poultry Assocaton of Ngera (PAN). They are Iwo, Ejgbo, Irewole, Ayedre, Irepodun and Ilesa West n Osun State and Afjo, Egbeda, Lagelu, Aknyele, Atba, Oyo East, OnaAra and Oyo West n Oyo State. The thrd stage was the random selecton of two hundred and forty (240) and one hundred and eghty (180) poultry farmers selected from Oyo and Osun States respectvely proportonate to the sze of regstered members of the Poultry Assocaton of Ngera (PAN) n each state. Also, the number of poultry farmers selected n each selected Local Governments Area s proportonate to the sze of regstered members of the Poultry Assocaton of Ngera (PAN) n each LGAs. In all, total of four hundred and twenty (420) poultry farmers. However, due to ncomplete responses, only four hundred and three (403) questonnares were used for the analyss. Analytcal technques: Data collected were analyzed wth descrptve statstcs and logt regresson model. The descrptve statstcs was used to examne the level of poultry farmers awareness and partcpaton n lvestock nsurance polcy whle the logt regresson model to determne the factors nfluencng poultry farmers wllngness to partcpate n lvestock nsurance lvestock polcy. Logt regresson model: The logt regresson model s a unt or multvarate technque whch allows for estmatng the probablty that an event occurs or not by predctng a bnary dependent outcome from a set of ndependent varables. There are two reasons for choosng Logt model for ths study nstead of lnear probablty and probt models accordng to Rahman and Alamu, (2003). Logt model ensures producton of probablty of choce wthn (0, 1) range. Ths s an advantage over lnear probablty model and t s easer and more convenent to compute than probt model. The logt model s based on cumulatve logstc probablty functon and t s computatonally tractable. Accordng to Gujarat and Porter (2009), t s expressed as: P=E Y= 1 = β 1 + β2x+ 2 β3x X 1 (1) For ease of estmaton, Eq. 1 s further expressed as: 3
z 1 e P= = 1+ e- 1+ e Z z (2) Where: P = Probablty of an event occurrng Z= β 1 + β2x (3) The emprcal model of the logstc regresson for ths study assumed that the probablty of the poultry farmers partcpaton n lvestock nsurance polcy s expressed as: P b e 1 e 0 b X b X b X b X b X b X b X b X b X 1 1 2 2 3 3 4 4 5 5 6 6 7 7 7 7 10 10 b0b 1X1 b2x b3x b4x b5x b6x b7x b10 2 3 4 5 6 7 X10 (4) P range between zero and one and t s non-lnearly related to Z. Z s the stmulus ndex whch range from mnus nfnty to plus nfnty and t s expressed as: Z=ln P = b 0+b1X 1+b2X 2+ +b7x 7 +u 1-P (5) To obtan the value of Z, the lkelhood of observng the sample was formed by ntroducng a dchotomous response varable. The explct logt model s expressed as: Y= b0+b 1X 1+b2X 2 + +b10x 10 +u (6) Where: Y = Dchotomous response varable (1 for poultry farmers who partcpated n lvestock nsurance polcy, 0 otherwse) X 1 = Age of farmers (years) X 2 = Years of formal educaton (years) X 3 = Gender (dummy = 1 f female, 0 otherwse) X 4 = Household sze (number of persons) X 5 = Hred labour (man-days) X 6 = Poultry rearng experence (years) X 7 = Access to Extenson servces (dummy = 1 f yes, 0 otherwse) X 8 = Access to Credt (dummy = 1 f yes, 0 otherwse) Poultry farms characterstcs: X 9 = Rearng system (dummy = 1 f battery cage, 0 otherwse) X 10 = Stock sze (number of layers stocked) b 1 -b 10 = Coeffcents of stmulus varables b 0 = Constant term u = Error term 4
RESULTS Soco-economc characterstcs of poultry egg farmers and farm characterstcs: Table 1 presents soco-economc characterstcs of poultry egg farmers. Majorty (70.5%) of the poultry farmers were below 50 years of age wth an average age of 45.5±9.1 years. Poultry farmers were mostly male (81.4%). Most of the poultry farmers were marred (85.6%) wth average household sze of 5.4±1.68 persons. Majorty had secondary educaton (45.2%) followed by those wth tertary educaton (36.7%). More than half (56.3%) of the poultry farmers had between 5-10 years of poultry farmng experence wth the mean years of experence beng 10.0±5.1 years. Majorty (70.0%) of the poultry farmers had an access to credt whle the remanng (30.0%) were dscovered not to have access to any source of credt. Also, majorty (73.9%) of the poultry farmers had access to lvestock extenson servces. Poultry farm characterstcs: Table 2 shows that half (50.4%) of the poultry egg farmers preferred to rase Harco breed of hen whle a few (2%) rased Rhode Island Red. Majorty (87.3%) of the farmers stocked pullets. Farm sze was classfed followng Adene and Oguntade (2006), Ob et al. (2008) and Arowolo et al. (2012). Farms havng between 500 and 2000 brds were Table 1: Soco-economc characterstcs of poultry farmers Characterstcs Frequency Percentage Age (Years) <30 33 8.2 30-39 99 24.6 40-49 152 37.7 $50 119 29.5 Mean = 45.5 S.D = 9.1 Gender Male 328 81.4 Female 75 18.6 Martal status Marred 343 85.1 Sngle 37 9.2 Dvorced 7 1.7 Wdowed 16 4.0 Household sze 1-3 44 10.9 4-6 290 72.0 >6 69 17.1 Mean = 5.4 S.D = 1.7 Level of educaton (years) No formal educaton 7 1.7 Adult educaton 4 1.0 Prmary educaton 62 15.4 Secondary educaton 182 45.2 Tertary educaton 148 36.7 Poultry farmng experence (years) <5 36 8.9 5-10 227 56.3 11-16 105 26.1 >16 35 8.7 Mean = 10.0 S.D = 5.1 Access to credt No 121 30.0 Yes 282 70.0 Access to lvestock extenson No 105 26.1 Yes 298 73.9 Feld survey data, 2013 5
Table 2: Poultry Farm s characterstcs and system of management practce by the farmers Parameters Frequency Percentage Breeds of Hen Harco 203 50.4 Bovan nera 104 25.8 Domnant black 29 7.2 Rhode Island red 8 2.0 Isa brown 59 14.6 Stock type Day old chcks 51 12.7 Pullets 352 87.3 Stock sze 500-2000 129 32.0 2001-9999 235 58.3 $10000 39 9.7 Mean = 4924.2 S.D = 3838.9 Poultry system Deep ltters 97 24.1 Battery cage 306 75.9 Mortalty rate <5 110 27.3 5-10 216 53.6 11-20 70 17.4 >20 7 1.7 Mean = 7.7 S.D = 4.9 Feld survey data, 2013 consdered as small scale commercal farms, those farms havng more than 2000 brds and flock sze whch s less than 10000 brds were regarded as a medum commercal farm whle those havng 10000 brds and above s classfed as large commercal poultry farms. The result shows that the medum scale poultry egg farmers consttuted more than half (54.3%) of the farmers. Also, the least number (13.6%) of the farmers are large scale operators whle the small scale consttuted 32.0% of the poultry egg farmers. The average flock sze was 4924.2±3838.9 layers. Majorty (75.9%) of the poultry egg farmers operated battery cage system whle lesser number (24.1%) of the farmers reared ther brds on deep ltter system. The average mortalty was 7.7±4.9%; 27.3% of the farmers had less than 5% of mortalty, 53.6% of the poultry egg farmers had 5-10% of mortalty rate, 17.4% of the farmers had 11-20% of mortalty rate whle 1.7% of the farmers had more than 20% of mortalty rate. Awareness and partcpaton of poultry farmers n lvestock nsurance polcy: Table 3 shows that more than half (59.6%) of the poultry farmers were aware of lvestock nsurance polcy. Table 4 reveals that only 11.9% of the poultry farmers nsured ther poultry farms. Determnants of poultry farmers partcpaton n lvestock nsurance: The factors determnng the poultry farmers partcpaton n lvestock nsurance are presented n Table 4. The dagnostcs statstcs revealed that the ch square dstrbuton whch was used to test the overall model adequacy was sgnfcant at 1% (χ 2 = 106.11, p<0.0000). The result of the logt regresson n Table 5 shows that stock sze, rearng system, access to extenson servces and poultry rearng experence were sgnfcant varables that nfluenced the partcpaton of the poultry farmers n lvestock nsurance polcy. Both access to extenson servces and poultry rearng experence were sgnfcant at 10% sgnfcance level whle rearng system and stock sze were sgnfcant at 5 and 1%, respectvely. However, gender, age of the poultry farmers, household sze, years of educaton, access to credt and labour were not sgnfcant. 6
Table 3: Dstrbuton of poultry farmers by awareness of lvestock nsurance Characterstcs Frequency Percentage No 163 40.4 Yes 240 59.6 Total 403 100.0 Source: Feld Survey Data (2013) Table 4: Dstrbuton of poultry farmers by partcpaton n lvestock nsurance Characterstcs Frequency Percentage No 355 88.1 Yes 48 11.9 Total 403 100.0 Source: Feld Survey Data (2013) Table 5: Determnants of poultry farmers partcpaton n lvestock nsurance Explanatory varables Coeffcents Standard error t-value Age of poultry farmers 0.0200 0.03030 0.66 Gender (female = 1) -0.6132 0.88360-0.69 Years of formal educaton 0.1817 0.14250 1.28 Household sze 0.1048 0.14230 0.74 Years of poultry rearng experence 0.0769* 0.04130 1.86 Access to credt 1.2189 1.77940 1.56 Access to lvestock extenson 1.9884* 1.05180 1.89 Hred labour -0.0012 0.02450-0.05 Rearng system(dummy = 1 f battery cage, 0 otherwse) 1.1821** 0.56640 2.09 Stock sze 0.0003*** 0.00005 5.05 Feld Survey Data (2013), *Sgnfcant at 10% level, **Sgnfcant at 5% level, ***Sgnfcant at 1% DISCUSSION Most of the poultry farmers were n ther actve and productve years who can easly adopt new nnovatons that could enhance poultry producton. The result mpled that modern poultry farmng s stll predomnantly a male occupaton lkely because of the hgh level of rsk nvolved, labour ntensve and other husbandry processes whch are not attractve to most women. Consstent wth ths fndng are the studes of Lawal et al. (2009), Adsa and Aknkunm (2012) and Uzokwe and Bakare (2013). Most of the poultry farmers were marred (85.6%) wth average household sze of 5.4±1.68 persons. More than half of the poultry farmers had between 5-10 years of poultry farmng experence. Ths s expected to manfest n hgh level poultry management as the longer the years of poultry farmng experence, the more exposed the farmer becomes and the more effcent the farmer s expected to be n poultry management. Majorty of the poultry farmers had access to lvestock extenson servces. Ths mples, that majorty of these poultry farmers had access to advsory servces and adequate nformaton on mproved poultry management technques. Medum scale poultry egg farmers consttuted more than half of the farmers. Also, the least number (13.6%) of the farmers are large scale operators whle the small scale consttuted 32.0% of the poultry farmers. More than half of the poultry farmers were aware of lvestock nsurance, however, few of the farmers nsured ther poultry farms. Ths ndcates a preponderance of low partcpaton n lvestock nsurance by the poultry farmers n the study area. Ths result confrms the fndngs of Ajeh (2010) who revealed the low partcpaton of poultry farmers n agrcultural nsurance n Kwara state of Ngera. Ths s probably due to constrants to farmers partcpaton n agrcultural nsurance whch nclude fears that clams may not be pad; nadequate knowledge on the benefts of lvestock nsurance, delay n payment of compensaton and hgh premum rate. However, the mplcaton of the result s that the layers chcken farmers n the study area have to mtgate aganst producton rsks that mght occur through other means. 7
The coeffcent of years of poultry rearng experence of the farmers was found to be postve and sgnfcant at 10% mples that the longer the years of poultry rearng experence, the more exposed the farmer becomes and the hgher ther partcpaton n lvestock nsurance polcy. The coeffcent of accessblty to extenson servces by the poultry farmers was found to be postve and sgnfcant at 10% mplyng that the hgher the access to extenson servces by the poultry farmers, the hgher ther partcpaton n lvestock nsurance. Ths result s nconsstent wth fndngs of Farayola et al. (2013), who confrmed contacts wth extenson agents to be nsgnfcant n nfluencng the farmers partcpaton n agrcultural nsurance scheme. The coeffcent of poultry rearng system of the farmers whch was found to be postve and sgnfcant at 5% mples that the poultry farmers that operate battery cage system tend to nsure ther poultry farms. The coeffcent of stock sze of was found to be postve and sgnfcant at 1% mples that poultry farmers wth larger stock tend to nsure ther poultry farms than small scale poultry farmers. Ths result on stock sze obtaned from ths study s smlar to the prevous study of Oynbo et al. (2012), who reported farm sze as a sgnfcant varable that nfluenced the probablty of partcpaton of the farmers n agrcultural nsurance scheme. Ths result s expected as the rsk s hgher n the large scale farms than small farms. Also, most of the large scale poultry farmers have access to credt and they have to nsure ther farms as one of the condtons to obtan the loans. Ths study concludes that stock sze and rearng system n that order were the most mportant factors determnng the poultry farmers partcpaton n lvestock nsurance polcy. Also, gender, age of the poultry farmers, household sze, years of educaton, access to credt and labour were found not to be the determnants of poultry farmers partcpaton n lvestock nsurance polcy. The concluson of ths study dsagrees wth the smlar studes conducted by Mshra and Godwn (2006), Oynbo et al. (2012) and Farayola et al. (2013), who reported that the coeffcent of age of the farmers whch was found be negatve and sgnfcant whch mples that the older the farmers, the lower ther partcpaton n agrcultural nsurance scheme. The study recommends that the government should formulate a polcy that wll make lvestock nsurance more affordable to poultry farmers by ncreasng the present level of subsdy granted for lvestock nsurance cover. Ngeran Agrcultural Insurance Company (NAIC) should endeavour to keep to contractual arrangements of ndemnfyng the farmers n the advent of dsease outbreak so as to allay the fears of other farmers that clams may not be pad. Also, adequate dssemnaton of knowledge on the benefts of lvestock nsurance by extenson agents s crucal to ncrease the level of partcpaton of poultry farmers n the use of lvestock nsurance polcy to mtgate aganst rsk n poultry enterprse. ACKNOWLEDGMENT The authors are grateful to Mr Phllp On of offce of FADAMA, Oyo State, Ngera state headquarters, MrSalawu Ismal of Department of Agrculture and Food Securty, Oyo state Local Government Cvl Servce Commsson and MrAdelakun of ADP, Osun state for ther assstance n feld survey and techncal assstance. REFERENCES Adene, D.F. and A.E. Oguntade, 2006. The structure and mportance of the commercal and vllage based poultry ndustry n Ngera. FAO Poultry Producton Systems, FAO, Rome, Italy, October 2006, pp: 1-102. 8
Adsa, B.O. and J.A. Aknkunm, 2012. Assessng partcpaton of women n poultry producton as a sustanable lvelhood Choce n Oyo State, Ngera. Int. J. Plant Anm. Envron. Sc., 2: 73-82. Ajeh, P.C., 2010. Poultry farmers' response to agrcultural nsurance n delta State, Ngera. J. Agrc. Sc., 1: 43-47. Arowolo, R.O.A., K.O. Soetan, O.O. Arowolo and O.O. Sodmu, 2012. The level of awareness and use of antcoccdals n poultry farms n South Western Ngera. Afr. J. Pharm. Pharmacol., 6: 3158-3164. Epetmehn, F.M., 2010. Agrcultural nsurance n Ngera and ts economc mpact. J. Bus. Manage., 2: 1117-3653. FDLPCS., 2007. Current ssues n the control of avan nfluenza n Ngera. Proceedngs of the Stakeholders Meetng wth Poultry Assocaton of Ngera by Dr. Mohammed Dantan Sadu, October 30, 2007, Abuja, Ngera. Farayola, C.O., I.A. Adedej, P.O. Popoola and S.A. Amao, 2013. Determnants of partcpaton of small scale commercal poultry farmers n agrcultural nsurance scheme n Kwara State, Ngera. World J. Agrc. Res., 1: 96-100. Gujarat, D.N. and D.C. Porter, 2009. Basc Econometrcs. 5th Edn., McGraw-Hll Irwn, New York, ISBN: 9780071276252, Pages: 922. Hardaker, J.B., R.M. Hume and J.R. Anderson, 1997. Copng wth Rsk n Agrculture. CAB Internatonal, Wallngford, Pages: 274. Lawal, B.O., D.O. Tormro and B.A. Makanjuola, 2009. Impact of agrcultural extenson practces on the Ngeran poultry farmers' standard of lvng: A perceptonal analyss. Trop. Subtrop. Agroecosyst., 10: 465-473. Mshra, A.K. and B.K. Goodwn, 2006. Revenue nsurance purchase decsons of farmers. Appled Econ., 38: 149-159. NAERLS., 1991. Practces of agrcultural nsurance n Ngera. Extenson Bulletn No. 10, Natonal Agrcultural Extenson and Research Lason Servces (NAERLS), Abuja, Ngera. NPC., 2006. Analyss of Ngeran 2006 census results. Natonal Populaton Commsson (NPC), Abuja, Ngera. Ob, T.U., O.A. Olubukola and G.A. Mana, 2008. Pro-Poor HPAI rsk reducton strateges n Ngera: Background paper. DFID Pro-poor HPAI Rsk Reducton Strateges Project, Afrca/Indonesa Regon Report No. 5, South Afrca. Olubyo, S.O. and G.P. Hll, 2003. Beyond the rsk factor: Bank lendng to small-scale peasant farmers n Ngera. Afr. Rev. Money Fnance Bank., 2: 12-21. Olubyo, S.O., G.P. Hll and J.P.G. Webster, 2009. Econometrc analyss of the mpact of agrcultural nsurance of farmng systems n the mddle belt, Ngera. Afr. J. Food Agrc. Nutr. Dev., Vol. 9. Oynbo, O., R.O. Abdulmalk and R.A. Sam, 2012. Determnants of crop farmers partcpaton n agrcultural nsurance n the federal captal terrtory, Abuja, Ngera. Greener J. Agrc. Sc., 2: 21-26. Rahman, S.A. and J.F. Alamu, 2003. Estmatng the level of women nterest n agrculture the applcaton of logt regresson model. Ng. J. Sc. Res., 4: 45-49. Uzokwe, U.N. and E.A. Bakare, 2013. The effects of clmate varablty on poultry producton n Ose Local government area of Ondo State, Ngera: Soco-economc characterstcs and perceptons of farmers. Int. J. Agrc. Bosc., 2: 39-44. 9