Analysis of Farm Households' Technical Efficiency in Production of Smallholder Farmers: The Case of Girawa District, Ethiopia

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1 Amercan-Eurasan J. Agrc. & Envron. Sc., 13 (12): , 2013 ISSN IDOSI Publcatons, 2013 DOI: /dos.aejaes Analyss of Farm Households' Techncal Effcency n Producton of Smallholder Farmers: The Case of Grawa Dstrct, Ethopa Beyan Ahmed, Jema Haj and Endras Geta Department of Agrcultural Economcs, College of Agrculture and Envronmental Scence, P.O. Box 95 Dre Dawa, Haramaya Unversty, Ethopa Abstract: Though agrculture remans to be the most mportant sector of the Ethopan economy, ts performance has been dsappontng and food producton has been laggng behnd populaton growth. Ths gap between demand for and supply of food can be reduced by mprovng productvty ether through ntroducton of modern technologes or mprovng the effcency of nputs. However, as the potental to ncrease producton by brngng more resources nto use became more and more lmted, the effcency wth whch the farmers use avalable resources has receved the utmost attenton. Therefore, ths study was amed at analyzng the techncal effcency of farm producton of smallholder farmers n Grawa dstrct usng cross sectonal data collected from randomly selected 200 sample households durng year 2011/12 producton season. Cobb-Douglas producton functon was ftted usng stochastc producton fronter approach to estmate techncal, effcency levels and to dentfy factors affectng effcency levels of the sample farmers. The estmated results showed that the mean techncal effcency was 81.5% and t ndcated that there was a sgnfcant neffcency n farm producton n the study area. The dscrepancy rato ( ), whch measures the relatve devaton of output from the fronter level due to neffcency, mpled that about 75% of the varaton n maze producton was attrbuted to techncal neffcency effects. Among factors hypotheszed to determne the level of techncal effcences, educaton, lvestock holdng, extenson contact, farmers tranng, cultvated area and partcpaton to rrgaton were found to determne techncal effcences of farmers postvely whle socal status had negatve relatonshp wth techncal effcency. Hence, emphass should be gven to mprove the effcency level of those less effcent farmers by adoptng the practces of relatvely effcent farmers n the area. Besde ths, polces and strateges of the government should be drected towards the above mentoned determnants. Key words: Smallholder farmers Techncal effcency Cobb-Douglas and stochastc fronter INTRODUCTION countres). On the other hand, urban poverty has shown only a margnal declne especally due to the Agrculture s the manstay of Ethopan lmted capacty of the manufacturng sector to absorb economy contrbutng about 45 % to the GDP and the ncreasng number of economcally actve populaton 85 % to natonal export earnngs. It also supples a n towns as well as the negatve mpact on household proporton of the ndustral raw materals whle budget of ncreasng prces of food commodtes [3-6]. employng about 85 % of the populaton [1] and The root causes of poverty and chronc food around 95% of the country's agrcultural output s nsecurty n rural areas of the country are complex and produced by smallholder farmers [2]. Despte ts varous. One of the major contrbutng factors for the domnance, Accordng to the 2011 Human Development country's poverty and food nsecurty s degradaton of Report of the Unted Natons Development Program, natural resources. Snce there s a rapd populaton growth Ethopa s ranked 174st out of 187 countres n the human n the country, especally, n rural areas, the land sze per development ndex, wth a GDP per capta adjusted household declnes, as a result, people are forced to over wth the Purchasng Power Party of only USD 779 use the land whch leads to low productvty [7]. (compared to almost USD 2000 average for Sub-Saharan They also clear the forest for addtonal farm land, source Correspondng Author: Beyan Ahmed, Department of Agrcultural Economcs, College of Agrculture and Envronmental Scence, P.O. Box 95 Dre Dawa, Haramaya Unversty, Ethopa. 1615

2 of household energy, constructon and means of ncome. Ths unwse use of the farmng land and clearng trees degrades natural resources whch result n recurrent drought. Rsk adverse tradtonal farmng system and ranfall dependant agrculture s also the other contrbutng factors for low productvty and food nsecurty [8]. In addton, nsuffcent resources lke captal and sklls to nvest n new technologes and shortage of supply n agrcultural nputs have ther own sgnfcant share for n subsstence agrcultural and food nsecurty. Besdes, majorty of the people n rural Ethopa are stck to farmng, they do not have access to off-farm ncome generatng actvtes, mproved technology and employment opportuntes. As a result, more than 38% of rural households fall below the food poverty lne and 47% of chldren under fve suffer from stuntng hunger [9,5]. Ths ncompatblty n the growth clearly requres mport of food and/or food ad unless the country mproves ts productvty by applyng mproved agrcultural technologes and sound crop producton and protecton practces. Therefore, f farmers are producng to supply the surplus to the market after feedng themselves wth reducng land per capta due to populaton growth, they need to adopt new farmng practces and ncrease ther effcency [10]. [11] also argued that future cereal producton growth need to come ncreasngly from yeld mprovements as there s lttle sutable land avalable for the expanson of crop cultvaton n the country. Emprcal fndngs ndcated that most underdeveloped and developng countres are facng both poverty and hgh populaton growth wth lmted economc resources. However, most farmers n these countres practce subsstence farmng wth low productvty. Ths may be attrbuted to hgh neffcences [12]. Accordng to [13], effcency measures are mportant as t s a factor for productvty growth. Such studes beneft economes by determnng the extent to whch t s possble to rase productvty by mprovng the neglected source of growth wth the exstng resource base and avalable technology. In the lght of the foregong dscusson: ths study examned farm household' techncal effcency of smallholder farm producton n Ethopa, usng Grawa dstrct of Oroma natonal Regonal State as a study area. Specfcally, ths study; To measure farm household techncal effcency of smallholder farmers and, To dentfy factors affectng farm households' techncal effcency n the study area MATERIALS AND METHODS The study was conducted n Grawa dstrct, East Hararghe, Oroma Natonal Regonal State, Ethopa. Accordng to [1], Grawa dstrct has a total populaton of 263,924 of whch 133,780 are male and 130,144 are female and total area of the dstrct s about km2 wth densty of The clmatc condton of the study area 48.9%, 31.1% and 20% of Grawa dstrct s kolla, Wona dega and Dega of Agro-ecologcal zones, respectvely. It s also characterzed by dfferent land scapes wth the alttude rangng from 1215 to 3405 meter above sea level (m.a.s.l). The annual ranfall ranges from 550 to 1100 mm wth annual temperature rangng from C. The lvelhood of the dstrct bascally orgnates from mxed farmng. It comprses crop producton and lvestock rearng. Major types of crops grown n the area are sorghum, maze, common beans, hghland pulses and many other vegetable crops lke potatoes, onon, garlc and leafy vegetables. Lvestock rearng s the secondary source of lvelhood for the rural people n the area [14]. As sources of nformaton both prmary and secondary data sources were used. The prmary data were collected usng sem-structured questonnare that was admnstered by the traned enumerators. In addton to prmary data, secondary data were also collected from relevant sources such as agrcultural and rural development offces of the dstrct and other relevant nsttutons for general descrpton and to augment prmary data. To have a relable nformaton and mportance of farm effcency, a two stage random samplng technque was used to select sample households for ths study. In the frst stage, four kebeles were selected randomly. In the second stage, the sample farmers were selected usng smple random samplng technque from each kebeles proportonal to the total number of households of the kebeles. Fnally a total of 200 sample respondents were ntervewed. Data Analyss: To address the objectves of the study, both descrptve statstcs and stochastc fronter approach were employed. The descrptve statstcs such as mean, percentages, standard devaton and frequency of occurrence were used to analyze soco-economc characterstcs of respondents and farm households' techncal effcency of rrgaton users and non-users Stochastc Producton Fronter Model: Besdes allowng for techncal neffcency such stochastc producton 1616

3 fronter models also acknowledge the fact that random farmer; Trm = transportaton means; Eam = Economc shocks outsde the control of the farm operator can affect actve members; Ftr = Farmers tranng; Sos = Socal output. Followng [15], the SFP model s defned as. status of the head; WRd = Whether road dstance; NEc = Number of extenson contact per croppng season; IRP= lny = ln f( x, ) + ( 1) partcpaton to rrgaton farmng; = number of respondent; The and -coeffcents are unknown Where: Y s total value of agrcultural output and are parameters to be estmated, by the method of maxmum nput varables, x s a vector parameter to be estmated lkelhood, usng the STATA Software. A Cobb-Douglas and s the total error term. The total error term n equaton [16] could be decomposed nto ts respectve two components as: = V - U (2) below. functonal form whch ncludes both the conventonal nputs and exogenous factors beleved to affect neffcency was the one consdered n ths specfc study. The fnal verson of the model estmated was ndcated as Where: V s the symmetrc error term, accounts for factors outsde the control of the farmer U s the techncal neffcency, accountng for random varatons n output due to neffcency and assumes postve values. The emprcal stochastc fronter producton model that was appled to the analyss of data was specfed as follows: lnvao = + ln LAB + ln OXN + ln CULA ln FRT + ln OFRT + ln SEED + V U Where subscrpts refer to the number of observaton of th the farmer; ln = logarthm to base e, VOA = represents the annual total agrcultural output of household n monetary term U = + EDU + Age + NEC + Fas Lsh + Trm + Sex + Cula + Of Sfs + Eam + Ftr + Sos + WRd + IRP (3) (brr), OXN = total ox power utlzed (oxen-days), CULA = total area under cultvaton (n hectares), LAB = total human labor n man days utlzed, CFRT = materal nputs of chemcal fertlzer (kg), SEED c costs of seeds (brr) and OFRT = organc fertlzer. It s assumed that the neffcency effects are ndependently dstrbuted and U arses by truncaton (at zero) of the normal dstrbuton wth mean U and varance equaton:. Where U s defned by the th Where U = techncal neffcency of the farmer; Age= Age of household head; Fas = Famly sze; Lsh = Lvestock holdng; Cula = cultvated land area; Sex = sex of household head; Of = off/non farm ncome; Sfs =Sol fertlty status; Edu = years of formal educaton of the th 2 (4) lnvao = + ln LAB + ln OXN + ln CULA ln FRT + ln OFRT + ln SEED V ( + Edu + Age + NEc + Fas Lsh + Trm + Sex + Cula + Of + Sfs Eam + Ftr + Sos + WRd + IRP ) Where; 1, 6, are the coeffcents of parameter estmates of nput varables, IRRP s a dummy varable havng value of 1 f household has access to rrgaton technology and value of 0 f household has no access to rrgaton technology, 1, 15, are the coeffcent of parameter estmates of the neffcency varables and, e, s the dsturbance term ncluded n the model and other varables are as defned n equaton [11, 12]. The techncal th effcency of producton for the farm s defned by: (5) Te = exp(-u ) (6) The predcton of the techncal effcences s based on ts condtonal expectaton, gven the observable value of ( V- U ). The techncal effcency ndex s equal to one f the farm has an neffcency effect equal to zero and t s less than one otherwse. RESULTS AND DISCUSSION Results of analyss of soco-economc characterstcs of the surveyed households are presented n Table 1. They show that the average age of the sample household heads was 41 years. The average numbers of economcally actve members n the famly of the sample households was 2.92 male equvalents (ME). The average years of formal schoolng of the sample farmers was grade 3. Extenson agent contacts on average about 20 days 1617

4 Table 1: Descrptve statstcs for contnuous varables Varables Mean SD Mn Max Income ,200 Crop ncome Lvestock ncome Labor Land Fertlzer Organc Age Famly sze Actve force Educaton Extenson Lvestock holdng N-F ncome Whether road dst Source: own survey result (2013). Table 2: Descrptve statstcs for dscrete varables Varables Number % Sol fertlty status Fertle Not fertle Socal status Partcpated Not Tranng Partcpated Not Source: Own survey result (2013). wth the farmers n a year. The study showed that out of the 200 sample households 190 own (rear) lvestock. The mean lvestock holdng for the sample households was 3.64 n Tropcal Lvestock Unt (TLU). The major sources of non/off-farm ncome n the study area were remttance, petty trade, salary, daly laborer and guard. The mean non/off- farm ncome of the sample households was brr. Access to weather road s a determnant of proftablty and sustanablty of agrcultural produce or proxy to agrcultural marketng servces. Weather road servces as a brdge whch connects small holder farmers to dfferent market places. The mean dstance between the vllages and the weather road n mnutes for the sample households was found to be mnutes. Table 2 shows that 63% of the sample households have got farmers tranng; Farmers tranng are a tranng gven by farmers at a farmers tranng center by dfferent responsble organs to mprove the farmers' ablty to adopt new technology, crop and anmal yeld, marketng servces, nput applcaton and natural and water resource conservatons. In the study area sol nfertlty was not a major problem. About 64% have good sol fertlty, only 36% of them reported that ther land was ether medum or not fertle. Accordng to the survey result, 10% of the sample households were headed by females and the rest 90% were headed by male. Out of the total respondents, 34.5% partcpated n socal organzatons. Among the sample majorty of them, 77 % of the households transport ther produce on donkey back and 23% of the households use other transportaton facltes. Table 3 summarzes the Cobb-Douglas producton fronter result of the effcency estmaton parameters used n the model n whch total values of agrcultural output s the dependent varable and total labor, both norganc and organc fertlzers, oxen power, cultvated area and seed cost are an nput varables. The result shows that labor, both norganc and organc fertlzers, oxen power and seed costs were sgnfcant varables. Ths result s found to be smlar to the fndngs of [17, 18]. The estmated parameters of the fronter producton functon equaton and related statstcal test results obtaned from the analyss are presented n Table 3. The neffcency component of the dsturbance term (u) s sgnfcantly dfferent from zero. Therefore, the null hypothess of techncal neffcency (H 0: Sgma u=0) s rejected. Ths ndcates that there s statstcally sgnfcant neffcency n the data. The lamda ( ) value s also greater than one n all the cases. Ths s a further ndcator of the sgnfcance of neffcency. It s evdent from the results presented n Table 3 that the estmate of gamma ( ) s large and sgnfcantly dfferent from zero, ndcatng a good ft and the correctness of the specfed dstrbutonal assumpton. Moreover, the estmate of, whch s the rato of the varance output to varance of error term, was Ths means that more than 75% of the varaton n output among the farm households s due to dfferences n techncal neffcency. The lkelhood rato test s hghly sgnfcant at 10% ndcatng that the n-effcency effects are sgnfcant n the stochastc fronter model and suggest the sutablty of t than the ordnary least squares (OLS) estmaton technque n the tradtonal producton functon model. Determnants of Techncal Effcency: As t was ndcated n Table 4, the results ndcate that techncal effcency s sgnfcantly nfluenced by seven explanatory varables. 1618

5 Table 3: Maxmum-lkelhood estmates of the fronter model Varables Coeffcent SE Z Constant *** Labor 0.307*** Land Fertlzer 0.021*** Organc 0.017*** Oxen ** Seed *** Sgma-squared Lambda ( = U/ V ) Number of obs = 200 Gamma ( = 2/( ) Prob > ch = Log-lkelhood functon = Source: own survey result. ** and *** means sgnfcant at 5% and 1% probablty levels,respectvely. Table 4: Maxmum-lkelhood neffcency effect estmates of the fronter model for Varables Coeffcent SE Z Constant Age Sex Educaton ** Non/off-farm ncome Famly sze Economcally actve force Cultvated land * Lvestock holdng * Irrgaton partcpaton *** Farmers tranng ** Extenson * Transportaton Socal status 0.834** Sol fertlty Weather road dstance Log-lkelhood functon = Wald ch (6) = Number of obs = 200 Prob > ch = Mean effcency = Source: own survey result. *, ** and *** mean sgnfcant at10%, 5% and 1% probablty level respectvely. Educaton enhances the ablty of farmers to see, decpher and make good use of nformaton about producton nputs, thus mprovng the effcent use of nputs. That s, an educated farmer has the capacty to understand and adopt mproved technology that would shft hs or her producton fronter upwards. In ths study; there was statstcally sgnfcant and postve relatonshp between the effcency level and educaton of the household head at less than 5% probablty level, whch was smlar wth most emprcal fndngs [16,19,20]. Lvestock provdes draught power, transport servce; manure and cash ncome to fnance crop producton. Besdes, pack anmals are used for tmely transportaton of the crops to a threshng pont. Snce threshng s conducted usng anmal power, the avalablty of lvestock especally durng peak perods s vtal. It helps reduce post harvest loses. Therefore, n ths study lvestock holdng postvely affect the level of techncal effcency at 10% statstcal level of sgnfcance. As regards lvestock holdng, the result n ths study s n lne wth the fndngs of several other emprcal works [8,16,21,22]. Extenson contacts were postve and statstcally sgnfcant at 5% probablty level. Extenson servces are assumed to help n dffuson and adopton of new technologes. Besdes ths, extenson Servces offer gudance to the farmers related to the use of varous resources such as fertlzer and provde consultancy servces when farmers face the problems of dsease and pest attacks on ther crop by managng ther scarce resources more effcently. Ths result s also consstent wth other fndngs of [21,23]. Results of ths study ndcated that there was a postve and statstcally sgnfcant relatonshp between cultvated area and techncal effcency. Ths varable s manly justfed on the ground that those farmers wth bg cultvated area can better dversfy ther crops. It s not unlkely that large farms can quckly utlze exstng resources and mght have a greater ablty to access modern nputs on tme. Ths result s n fact related to the fndngs of [20,24]. Partcpaton n small-scale rrgaton was postvely related and statstcally sgnfcant at less than 1% probablty level wth farm household techncal effcency. Household wth rrgaton can use ther land properly throughout the year by producng short term vegetable and chat to obtan cash needed. Irrgaton also used to escape from rsk of crop falure and dversfy ther source of ncome. Ths fndng s n confrmaton wth the fndngs of [20,25,22]. Farmers' tranng has postve and statstcally sgnfcant relatonshp wth techncal effcency at less than 5% probablty level. Ths may be due to the fact that tranng provdes the farmers wth new nformaton n terms of nput utlzaton, sol conservaton wth multpurpose vegetatve crops, rsk averson, storage, keep from wld damage, marketng ther fnal outputs, technology adopton and savng aspects. Ths result s n fact related to the fndngs of [21]. Socal status has negatve and statstcally sgnfcant relatonshp wth techncal effcency at less than 5% probablty level. The effect of socal status on effcency s manly justfed on the ground that those farmers wth 1619

6 bg socal oblgaton were busy and cannot better manage Thus government has to gve due attenton for adult ther farm. Ths result s consstent wth the fndngs of educaton strengthenng and establshng both formal and [17]. nformal type of framers' educaton. The study also revealed that lvestock holdng has a CONCLUSIONS AND RECOMMENDATIONS sgnfcant nfluence on the techncal effcency of smallholders. Therefore, farmers have to get nformaton Ths study was undertaken wth the objectve of on artfcal nsemnaton and anmal husbandry has to be dentfyng factors that affect the farm households' mproved to get better level of techncal effcency. techncal effcency of smallholder farmers n Grawa The work ndcated that extenson contact has dstrct, Oroma Natonal State of Ethopa. The study postve and sgnfcant effect on techncal effcency. employed the stochastc fronter approach and both Snce extenson servces are the man nstrument used n prmary and secondary data were used. Prmary data were the promoton of demand for modern technologes, collected through household survey from a sample of 200 approprate and adequate extenson servces should be households usng sem-structured questonnare. provded. Secondary data were collected from relevant sources to Access to farmers tranng has a postve nfluence supplement the prmary data. Data analyss was carred on techncal effcency. Therefore, better tranng faclty out usng descrptve statstcs and econometrc has to be produced va the establshment of adequate technques. The Cobb-Douglas stochastc fronter rural nsttutons and strengthenng of the avalable producton was estmated, from whch TE extracted. farmers tranng to mprove farm productvty. The results from the producton functon showed that The analyss also ndcated that partcpaton to small fertlzer, norganc, labour, oxen power and seed were scale rrgaton s a crucal factor n determnng techncal statstcally sgnfcant. The study also ndcated that effcency of farmers. Therefore, farmers have to work to 81.5% was the mean levels of TE ths n turn mples that mprove the rrgaton nfrastructure and ncrease ther farmers can ncrease ther farm producton on average by partcpaton to rrgaton farmng to dversfy both crops 19.5% when they were techncally effcent. and ncome base sources n farm household producton. In the second step of the analyss, relatonshps between TE and varables that expected to have effect on REFERENCES farm effcency were examned. Ths was reled on maxmum lkelhood estmaton of fronter model of 1. CSA (Central Statstcal Agency of Ethopa), neffcency effect, where techncal neffcency, expressed Statstcal Abstract of Ethopa, Central Statstcal as functons of 15 ndependent varables. Among them, Agency, Adds Ababa: Ethopa. educaton, frequency of extenson contact, lvestock 2. MoARD (Mnstry of Agrculture and Rural holdng, cultvated area, farmers tranng; socal status Development), Ethopa's agrculture sector and partcpaton to rrgaton were found to be polcy and nvestment framework: Ten Year Road statstcally sgnfcant to affect the level of techncal Map ( ). effcency. 3. FEWS NET (Famne Early Warnng Systems Thus, the results of the study gve nformaton to Network), Ethopa food securty Outlook. polcy makers and extenson workers on how to better am efforts to mprove farm effcency as the level and ekadal_08_20 fnal_ext.pdf. specfc determnant for techncal effcency. These 4. FAO (Food and Agrcultural Organzaton), fndngs stresses the need for approprate polcy Measurng the Impact of Food Securty Related formulaton and mplementaton to enable farmers Programmng. Workshop Report 6th and 7th of reduce ther neffcency n producton as ths s expected December, The Food and Agrculture to have multpler effects rangng from farm productvty Organzaton, Rome, Italy growth to economc growth and poverty reducton at 5. WFP (World Food Program) and FAO (Food and macro level. Agrcultural Organzaton), The State of Food Based on the study fndngs therefore, the followng Insecurty n the World, Vale delle Terme d recommendatons were made; Educaton was very Caracalla, Rome, Italy. mportant determnng factor that has postve and 6. WFP(World Food Program), Ethopa Food sgnfcant effect on farm household TE n the study area. Securty Outlook October, 2011.USAID, Ethopa. 1620

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