Determinants of Technical Efficiency on Pineapple Farming

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1 Amercan Journal of Appled Scences, 1 (4): , 213 ISSN: N.D.M. Idrs e al., Ths open access arcle s dsrbued under a Creave Commons Arbuon (CC-BY) 3. lcense do:1.3844/ajassp Publshed Onlne 1 (4) 213 (hp:// Deermnans of Techncal Effcency on Pneapple Farmng 1 Nor Dana Mohd Idrs, 1 Chamhur Swar and 2 Basr Talb 1 Insue for Envronmen and Developmen (LESTARI), Unvers Kebangsaan Malaysa, Bang 436, Selangor D.E., Malaysa 2 Faculy of Economcs, Unvers Kebangsaan Malaysa, Bang 436, Selangor D.E., Malaysa Receved , Revsed ; Acceped ABSTRACT Ths sudy analyzes he pneapple producon effcency of he Inegraed Agrculural Developmen Projec (IADP) n Samarahan, Sarawak, Malaysa and also sudes s deermnans. In he sudy area, IADP plays an mporan role n rural developmen as a povery allevaon program hrough agrculural developmen. Despe he many prvleges receved by he farmers, especally from he governmen, hey are sll less effcen. Ths sudy adops he Daa Envelopmen Analyss (DEA) n measurng echncal effcency. Furher, hs sudy ams o examne he deermnans of effcency by esmang he level of farmer characerscs as a funcon of farmer s age, educaon level, famly labor, years of experence n agrculure, socey members and farm sze. The esmaon used he Tob Model. The resuls from hs sudy show ha he majory of farmers n IADP are sll less effcen. In addon, he resuls show ha relyng on famly labor, he years of experence n agrculure and also parcpaon as he assocaon s member are all mporan deermnans of he level of effcency for he IADP farmers n he agrculural secor. Increasng agrculure producvy can also guaranee he achevemen of a more opmal susanable lvng n an effor o ncrease he farmers ncome. Such nformaon s valuable for exenson servces and polcy makers snce can help o gude polces oward ncreased effcency among pneapple farmers n Malaysa. Keywords: Inegraed Agrculural Developmen Projec (IADP), Daa Envelopmen Analyss (DEA), Gross Domesc Produc (GDP), Consan Reurns o Scale (CRS), Ordnary Leas Square (OLS), Varable Reurns o Scale (VRS) 1. INTRODUCTION Agrculure remans an mporan secor of Malaysa s economy, conrbung 3 percen o he Gross Domesc Produc (GDP) and provdng employmen for 12 percen of he populaon Malaysa, 21. Sarawak s one of he saes ha conrbues abou 1.8 percen of he counry s commody producs; apar from he hree man crops whch are rubber, ol palm and cocoa, Sarawak also produces a number of frus and vegeables for he domesc marke, ncludng bananas, coconus, duran, local and overseas needs. Malaysa s among he major crop producers n he world and radonal crops play an mporan role n he oal agrculural producon. The prncpal objecves of he Thrd Naonal Agrculural Polcy of Malaysa (NAP 3) are o enhance food secury, ncrease producvy and he compeveness of he secor, deepen lnkage wh oher secors, creae new sources of growh and also o conserve and ulze naural resources on a susanable bass. In order o acheve he vson of a hgh-ncome counry, farmers are expeced o operae under a much more compeve condon and ncrease her effcences o survve. pneapples, rce, rambuans and ohers o susan he Correspondng Auhor: Nor Dana Mohd Idrs, Insue for Envronmen and Developmen (LESTARI), Unvers Kebangsaan Malaysa, Bang 436, Selangor D.E., Malaysa 426

2 Deermnng he exsng level of effcency wll be useful o mprove hese relaonshps ha can help farmers allocae her resources more wsely and also o asss he governmen n desgnng and searchng for new polcy ools o reach secor-specfc goals. 2. MATERIALS AND METHODS 2.1. Sudy Area and Daa Collecon The sudy area s he Inegraed Agrculural Developmen Projec (IADP) n Samarahan, Sarawak nvolvng 14 vllages locaed n he Cenral Dvson and Ulu Samarahan. I s one of he povery allevaon programs hrough agrculural approach. The am of hs projec s o promoe negraed approaches n he effor and acves of all deparmens and agences under he Mnsry of Agrculure and Agro-Based Indusry of Malaysa. I s also responsble n preparng he agrculural nfrasrucure and provdng suppor servces n hs area. One of he projec s objecves s o boos farm producvy and maxmze ncome of he farmng communy n order o reduce he ncome gap among he people n he Dvson. Followng he 25/26 producon perod, a quesonnare sudy was conduced and 124 farms growng pneapples were randomly denfed from srafed samplng frame Analycal Procedures for Measurng Techncal Effcency Ths sudy uses a wo-sep approach. In he frs sep, he DEA model s used o measure echncal effcences of farms as an explc funcon of dscreonary varables. In he second sep, farm-specfc varables ha are assumed o affec he effcency of he farm are used n a Tob regresson framework o explan varaons n measured effcences of farmers. Therefore, we begn by frs provdng a bref descrpon of he DEA, followed by he Tob s model Daa Envelopmen Analyss DEA s a nonparamerc mehod of esmang echncal effcency of farmers. I s a lnear programmng mehod proposed by Farrell (1957) o calculae he non-paramerc boundary and he effcency ndex for a parcular farm s obaned by comparng he npu and oupu obaned. I also does no requre he assumpon of adjacen echnologes or dsrbuon neffcency. Accordng o Farrell (1957), effcency s expressed as he acual producon of a farm compared wh he maxmum oupu ha can be acheved, whch s a 427 reference o a producon froner. Therefore, he effcency of farm producon s he average dsance measuremen s oupu from he froner level. Coell (1996) developed such a mul sage mehodology and a compuer program (DEAP) whch mplemens a robus mul-sage model among oher opons (Alemdar and Oren, 26). A rao of echncal effcency scores obaned from under CRS and VRS assumpon measure scale effcency. Accordng o Coell (1996), DEA model based on he Consan Reurns o Scale (CRS) s saed as follows: mn θ θ, λ subjec o y + Yλ θx Xλ λ Where: θ = The scale of echncal effcecy for each farm λ = As N 1 vecor of consans y and x = The oal oupu and farm npus, = 1,2,...,n (1) The value of θ 1 ndcaes he level of producon reflecs he producon froner and echncally effcen farms. The Equaon 1 has used he assumpon ha all farms operae a an opmal scale. However, consrans such as fnance and mperfec compeon ha occur a he feld cause only par of he farm o operae a ha level. Therefore, he above model can be esmaed based on he Varable Reurns o Scale (VRS), whch evaluaes he effcency of farms based on her capables. VRS model s formed by nserng he consrans N1 λ n Equaon 2, where N1 s N 1 vecor (Coell, 1996): mn θ θ, λ subjec o y + Yλ θx Xλ N1' λ= 1 λ (2) Consrans of N1 λ = 1 ndcae he neffcency of a farm evaluaed agans oher farms of smlar sze. In hs way, he effcency of he farm can be evaluaed based on echncal and scale effcency. Techncal effcency descrbes he ably of farms o acheve maxmum producon wh he use of npus gven whle he scale effcency s he rao beween CRS and VRS.

3 The dfferences for boh show he levels of scale neffcency of producon of farmers. The oupuorened DEA model based on he VRS s saed as follows (Coell e al., 22): max ϕ ϕ, λ subjec o ϕ y + Yλ x Xλ N1' λ= 1 λ (3) where, 1 ϕ< and ϕ-1 s an ncrease n he rao of oupu ha can be acheved by farmers -h, wh a gven quany of npus whch s consan. 1/ϕ s he echncal effcency whch has a value beween and 1 n Equaon 3. The fndngs also explan scale effcency. Ths sudy uses he program DEAP 2.1 (Coell e al., 22) o measure he echncal effcency of he oupubased DEA model Tob s Analyss The presen sudy uses a censored regresson o analyze he role of farm-specfc arbues n explanng effcency n producon of crops. We use a wo-sage approach where he Tob model s used o run a regresson of he npus and farm-specfc characerscs as ndependen varables agans he effcency scores. Tob s model was nroduced by Tobn (1958) nvolvng a censored regresson model of he economy (Hayash, 2) and frs analyzed n he economerc leraure (Maddala and Lahr, 29). As he effcency ndex derved from daa envelopmen analyss s bound beween and 1 values, hus s suable for use as a smulaon analyss o denfy he deermnan of echncal effcency among farmers. Effcency ndex derved from he Equaon 4 can be used as a measure of he performance of farmers. Based on prevous sudes, he nfluence of effcency of farmers by Ordnary Leas Square (OLS) has been used by Deller and Nelson (1991) o denfy hs facor hrough a regresson model. Snce he measuremen of effcency s censored wh he value beween and 1, hence some argumens sae ha he esmaon of OLS s nconssen and neffcen (Mugera and Feahersone, 28). For ha reason, hs sudy used he Tob Model o replace OLS (Ray, 24). The Tob Model was also used by Bravo- Urea e al. (27); Chavas and Alber (1993); Feahersone e al. (1997); Fred e al. (1999) and Rowland e al. (1998). 428 Brefly, Tob s model can be wren as follows: y * = x ' β +,= 1,2,3,...,n (4) y = y * f y * > c;dan y = c,oherwse (5) where, y s a DEA effcency ndex used as a dependen 2 varable, x s N(, σ ) and {y,x }( = 1,2,...,n) s a vecor of ndependen varables relaed o farm-specfc arbues, value of c s known. y * s a laen varable. β s an unknown parameer vecor assocaed wh he farm-specfc arbues and ε s an ndependenly dsrbued error erm ha s assumed o be normally dsrbued wh zero mean and consan varance, σ 2. A Tob regresson model applyng he maxmum lkelhood approach s used o esmae he model n Equaon 4 such ha Equaon 6: 1 L = (1 F) e[1/ 2 σ ](y βx) 2 2 (6) 2 1/2 y= y> (2 σ ) β x / σ where, F = e. 1/2 (2 ) The Equaon 5 refers o he effcency score of farmers 1% (y = c) and he second erm represens neffcen farmers (y > c). F s normally scaered n he β x / σ. Farm level echncal effcency scores are used n he regresson model o show he relaonshp beween he measuremen of he effcency and characerscs of farmers. Based on he leraure, several varables have been denfed o explan he echncal effcency levels among farmers n he sudy area. The varables are age, educaon level, famly labor, year of agrculural experence, assocaon parcpaon and farm sze. Jusfcaons for ncluson of hese varables are based on surveys and nervews conduced durng he research survey n whch hese varables affec her producvy. Therefore, he hypohess of he sudy esmaes ha hese varables also nfluence he level of echncal effcency of farmers n he sudy area. 3. RESULTS AND DISCUSSION 3.1. Descrpve Sascs A sudy on he performance of farmers s conduced o deermne s ably o provde maxmum oupu wh he gven npus. Therefore, he DEA effcency score

4 can be summarzed o show how much supposedly he farmers maxmum oupu producon s whou addon of npu f can be consdered as he bes echncal effcency. DEAP 2.1 program developed by Coell (1996) was used o calculae he echncal effcency of farmers pneapple culvaon n IADP Samarahan, Sarawak. The echncal effcency s esmaed by usng he approach of maxmzng he oupu subjec o consan npu and evaluaed on he CRS and VRS. Scores for echncal effcency, scale effcency and he level of he poson of each farmer were esmaed (Table 1) Effcency Score Table 1 shows he descrpve sascs for he resuls of echncal effcency of pneapple farmers as classfed. Scores rangng from -1% show ha he esmaon of he CRS for farmers s less han.2. On he average, all of hem are far from he maxmum oupu capacy ha s n he nerval of %, whou ncreasng he npu whch s abou Ths reflecs he average level for farmers o be able o maxmze oupu wh a arge ncrease n oal s more han 8%. When he VRS echnology s assumed, he average echncal effcency s hgher han.2. Ths shows ha farmers can produce her oupu around 7-74% by usng he same npus. The VRS echncal effcency s used o measure he relave declne n oupu ha s no a resul of he consan reurn o scale. The scores of echncal effcency n CRS and VRS are o deermne wheher he rend s of farmers operang a ncreasng reurn o scale or reurn o declne. If he score of echncal effcency a VRS s larger han CRS, hs means ha he farmers are ncreasng her scale of reurns. Meanwhle, scale effcency measures he relave loss of oupu due o he consan s reurns o scale represened by he value of one or close o one. The resuls of hs sudy show ha on average, here were no farmers operang a ha sage (Table 2). Based on hese prncples, he analyss of he resuls of hs sudy shows ha all farmers who are neffcen are n he poson of operang a ncreasng reurns o scale. Ths resul s conssen wh prevous sudes by Byrnes e al. (1987) and Wu e al. (23). Accordng o he heory, ncreasng reurns o scale suggess ha he ncrease of oupu s hgher han npus. In conras, he dmnshng reurn o scale ndcaes ha he ncrease of oupu s less han he ncrease n npus. 429 Table 1. Frequency dsrbuons of echncal effcency scores obaned wh he DEA model DEA Effcency scores CRS VRS SE 1. 2 (1.6) 5 (4.) 42 (33.9) (.8) 1 (.8) 43 (34.7) (.8) 2 (1.6) 16 (12.9) (.8) - 5 (4.) (1.6) 3 (2.4) 13 (1.5) (2.4) 3 (2.4) 1 (.8) < (91.9) 11 (88.7) 5 (4.) Mean Mnmum Maxmum Sandard devaon Sources: Feld survey (25) Table 2. Effcency of pneapple producon based on he scale of producon among farmers n IADP samarahan, sarawak Producon scale Frequency Percenage Increase Reurn o Scale (IRS) Consan reurn o scale (Opmal) Decrease Reurn o Scale (DRS) Toal Sources: Feld survey (25) Table 3. Varables used n he ob model Varables Defnon TE Techncal effcency score Age Year of age Level of educaon 1= Secondary school and above, = ohers Famly labor 1= Yes, = No Agrculure experence Year of agrculure experence Assocaon 1= Member of assocaon, = ohers Land Sze of farm Table 4. Summary sascs for varables n he Tob regresson model Sandard Varables Mean devaon Mnmum Maxmum Age Level of educaon Famly labor Agrculural experence Assocaon Land Sources: Feld survey (25)

5 Table 5. Resuls of he Tob regresson analyss Varable Tob SE -rao Sgnfcance Consan Age Level of educaon Labor Experence Assocaon Acre R-square.6414 Adjused r-square.623 Sources: Feld survey (25) 3.3. Deermnan Facors Furher analyss was conduced usng Tob o denfy he deermnans of echncal effcency among pneapple farmers. In hs analyss, he score of echncal effcency of CRS and VRS of he farmers are used as he dependen varable, whle he ndependen varables conss of he varable of age, educaon level, use of famly labor, agrculural experence, parcpaon n assocaon and land acreage. Defnon of he varables are shown n Table 3. The SHAZAM programs were used o analyze and he model esmaed s as follows: TE=β +β Age+β Educaon+β Labour β Experence+β Assocaon+β Farmsze+ε Table 4 shows he summary sascs for he varables used n he Tob regresson model. The average age of he pneapple farmers s 51 years old and 64% of he farmers has secondary educaon and above. Due o he dversy of crops, labor nensve asssance among pneapple farmers (23%) are necessary. The farmers have a mean of 32 years of agrculural experence, whle on average each farmer runs almos 4 acres of land for pneapple planaon. In addon, mos of he farmers are acvely nvolved n he agrculural assocaon (93%) as a way of geng nformaon and asssance from he IADP as npu n ensurng he smooh runnng of he projec. In order o ge he nformaon on deermnans of neffcency, effcency scores were regressed upon some demographc nformaon of he farmers and he envronmenal varables. Techncal effcency score was used as he dependen varable. Snce he scores are bounded n beween zero o one, he use of he ordnary leas-square regresson model s unsuable. Hence, a Tob analyss model was employed. Table 5 shows he Tob regresson resuls ha examned he 43 relaonshps beween echncal effcency scores and age, level of educaon, labor uses, agrculural experence, parcpaon n assocaon and land sze. As seen from he able, relyng on labor (1% level), parcpang n assocaon (5% level) and land sze (1% level) have sgnfcan effecs on effcency scores. Sgns of he parameers are posve and as expeced. Ths ndcaes ha farms wh he addon of famly labor are more effcen. Farms wh less famly labor usage are neffcen. Durng he survey, was found ha he farmers are helped by her chldren and vllagers especally when harvesng he crops. Ths s o avod damage due o he delay n harvesng he agrculural produc. Assocaon parcpaon also has a posve relaonshp wh he level of echncal effcency among pneapple farmers. Ths shows ha he more acve he farmers are n her nvolvemen n he farmer assocaon and n he socey, he more nformaon of farm acves carred ou and agrculural npu dsrbuon hey have compared o hose who do no jon he assocaon. I can also provde he farmers he opporuny o share nformaon and modern pracces wh oher farmers. Sgns of he area parameer are posve and as expeced. Ths ndcaes ha he bgger farms are more effcen and hs resul s conssen wh he resul by Gul (26). Meanwhle, he farmer s age s negave and s no sgnfcanly relaed o echncal effcency and hs resul s suppored by Onyenweaku e al. (24). Farmng experence s posve and no sgnfcanly relaed o echncal effcency. The fndngs are conssen wh he resuls by Rahman and Umar (29) and Idong (27). Ths means ha beng an experenced farmer s no good enough o acheve hgher level of effcency. However, hs resul conradcs ha of Onyenweaku and Nwaru (25). Educaon shows no sgnfcan relaonshp wh echncal effcency. Ths resul s conssen wh ha of Onu e al. (2) bu does no ally wh ha of Onyenweaku and Effong (25). A logsc analyss s also performed and shows ha farmer-relaed varables such as famly labor, agrculural experence and land areas are more mporan han he varables of age and farmers educaon n deermnng he effcency level n IADP Samarahan, Sarawak. The resuls of hs sudy are conssen wh he fndngs of he sudy conduced by Coell e al. (22); Dhungana e al. (24); Bnam e al. (24); Spellman e al. (28) and Wadud and Whe (2).

6 4. CONCLUSION The objecve of hs sudy was o apply a wo-sep mehodology o nvesgae he echncal effcency and assess he facors ha nfluence he effcency of crop producon n IADP Samarahan, Sarawak. The lack of emprcal sudes n Malaysa, whch focus on he facors affecng he effcency of he crop producon, movaed hs sudy. Mos of he pneapple culvaors n IADP Samarahan scored less han.5, whch means hey were operang a an neffcen level and should be more producve o manan he number of npus and o produce a he producon froner level of he border or bes pracces. The polcy mplcaon from hs sudy suggess ha he nroducon of conrac labor o asss farmers n farm work, he srenghenng of assocaon and acve parcpaon and he ncrease n he area of crops are mporan facors n conrbung o he mprovemen of echncal effcency among pneapple farmers n achevng he arge of pneapple producon of 16, ons/acre n IADP Samarahan self (MAAI, 28). I s mporan o conrbue o he ncrease n food secury and compeveness n he agrculural secor o acheve he producon arge of 25 onnes/acre n order o generae ne ncome of RM283 (MPIB, 21). Increasng agrculural producvy and susanably n he use of naural resources can also guaranee he achevemen of a more opmal susanable lvng n an effor o ncrease he farmers ncome n lne wh he recommendaons of he hrd objecve of he Naonal Agrculural Polcy. 5. ACKNKOWLEDGEMENT Fnancal asssance provded by IRPA EA 281, Lnkng Envronmen and Rural Povery: Formulang Resources Uses, Governance and Susanable Polces, Insue for Envronmen and Developmen, Unversy Kebangsaan Malaysa s graefully acknowledged. 6. REFERENCES Alemdar, T. and M.N. Oren, 26. Measurng echncal effcency of whea producon n souheasern anaola wh paramerc and nonparamerc mehods. Pak. J. Bol. Sc., 9: Bnam, J.N., J. Tonye, N. Wandj, G. Nyamb and M. Akoa, 24. Facors affecng he echncal effcency among smallholder farmers n he slash and burn agrculure zone of Cameroon. Food Polcy, 29: DOI: 1.116/j.foodpol Bravo-Urea, B.E., D. Sols, V.M. Lopez, J. Marpan and A. Tham e al., 27. Techncal effcency n farmng: A mea-regresson analyss. J. Prod. Anal., 27: DOI: 1.17/s Byrnes, P., R. Fare, S. Grosskopf and S. Kraf, Techncal effcency and sze: The case of Illnos gran farms. Eur. Rev. Agrc. Econ., 14: DOI: 1.193/erae/ Chavas, J.P. and M. Alber, An analyss of economc effcency n agrculure: A nonparamerc approach. J. Agrc. Res. Econ., 18: Coell, T., A Gude o DEAP Verson 2.1: A Daa Envelopmen Analyss (Compuer) Program. Unversy of New England, Ausrala. Coell, T.J., S. Rahman and C. Thrle, 22. Techncal, allocave, cos and scale effcences n bangladesh rce culvaon: A non-paramerc approach. J. Agrc. Econ., 53: DOI: /j b4.x Deller, S.C. and C.H. Nelson, Measurng he economc effcency of producng rural road servces. Am. J. Agrc. Econ., 73: DOI: 1.237/ Dhungana, B.R., P.L. Nuhall and G.V. Narea, 24. Measurng he economc neffcency of Nepalese rce farms usng daa envelopmen analyss. Aus. J. Agrc. Resource Econ., 48: DOI: /j x Farrell, M.J., The measuremen of producve effcency. J. Royal Sa. Soc., 12: Feahersone, A.M., M. Langemeer and M. Isme, A nonparamerc analyss of effcency for a sample of kansas beef cow farms. J. Agrc.Appled Econ., 29: Fred, H.O., S.S. Schmd and S. Yasawarng, Incorporang he operang envronmen no a nonparamerc measure of echncal effcency. J. Prod. Anal., 12: DOI: 1.123/A: Gul, M., 26. Techncal effcency of apple farmng n Turkey: A case sudy coverng spara, karaman and ngde provnces. Pak. J. Bol. Sc., 9: Hayash, F., 2. Economercs. 1s Edn., Prnceon Unversy Press, New Jersey, ISBN-1: , pp: 683. Idong, I.C., 27. Esmaon of farm level echncal effcency n smallscale swamp rce producon n cross rver sae of Ngera: A sochasc froner approach. World J. Agrc. Sc., 3:

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