Role of Agricultural Credit on Production Efficiency of Farming Sector in Pakistan- A Data Envelopment Analysis

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1 Pak. j. lfe soc. Sc. (2011), 9(1): Pakstan Journal of Lfe and Socal Scences Role of Agrcultural Credt on Producton Effcency of Farmng Sector n Pakstan- A Data Envelopment Analyss Sama Ayaz, Sofa Anwar*, Maqbool Hussan Sal and Zakr Hussan Department of Economcs, Unversty of Sargodha, Sargodha-Pakstan Abstract The study dentfed the sources of producton neffcency of the farmng sector n dstrct Fasalabad n the Punjab provnce of Pakstan. Data Envelopment Analyss (DEA) technque was utlzed at farm level survey data of 300 farmers for the year The overall mean effcency score was 0.78 ndcatng 22 percent neffcency of the sample farmers. Computed effcency scores were then regressed on farm specfc varables usng Tobt regresson analyss. Farmng experence, educaton, access to farmng credt, herd sze and number of cultvaton practces showed constructve and sgnfcant effect on the farmer s techncal effcency. Key words: Agrcultural credt, DEA, Techncal effcency, Tobt analyss Introducton Farmng credt s provded for the purpose of producton and development. Producton loan s specfed for agrculture nputs consstng of seeds, fertlzer, plant protecton measures, poultry/anmal feeds and medcnes, water charges, labor etc. The development loans were suppled for purchase of agrculture equpments.e. tractors, cutter bnders, threshers, trolley, spray machnery and nstallaton of tube wells, etc. To help out small farmers by extendng loans to them on easy terms, government made agrcultural credt polces (Hanf et. al., 2004). Easy avalablty and access to credt resulted n rapd development of farmng sector. It provdes ablty to the farmers and entrepreneurs to dversfy agrculture sector by undertakng new nvestment or adopt new technology. Rural credt market comprsng of formal and nformal sector, play a sgnfcant and an actve role n rural economy (Adams and Ftchett, 1992; Aleem, 1990). The nsttutonal agrcultural credt has shown a consderable affrmatve nfluence on agrcultural productvty n Pakstan (Iqbal et al., 2003). *Correspondng Author: Sofa Anwar, Department of Economcs, Unversty of Sargodha, Pakstan Emal: sofa_ageconomst@yahoo.com The formal agrcultural credt accessble to the farmer before ndependence was taccav loans and loans from co-operatve socetes. Farmers havng no land or small farmers partcularly depended upon these sources to fulfll ther credt needs. Government of Pakstan has extensvely used the subsdzed agrcultural credt polces to acheve hgher agrcultural growth through relaxng monetary lmtaton. Snce the 1950s the provson of agrcultural credt n Pakstan s a sgnfcant component to mprove the rural economy (Zubar, 1989; Malk etal., 1991). In 1950s, two credt nsttutes.e. Agrcultural Development Fnance Corporaton (ADFC) and the Agrcultural Bank were orgnated to overcome ths credt shortage. In 1961, these credt nsttutes were merged and appeared as Agrcultural Development Bank of Pakstan (ADBP), now Zara Taraqat Bank Lmted (ZTBL). By the end of 1972, the Commercal Banks (CBs) and Domestc Prvate Banks were specfed targets to provde the faclty of agrcultural credt. Commercal banks were mostly chargng hgh nterest rate as compared to ZTBL (Bashr and Azeem, 2008). Presently n Pakstan, the formal agrcultural credt nsttutons nclude ZTBL, a prncpal source of formal agrcultural lendng, Commercal Banks, Federal Bank for Cooperatves and also some nongovernmental organzatons (NGOs). The government practces the credt polcy to protect the nterest of small and medum farmers by provdng them loans on easy terms; to facltate them n case of any natural hazards and dsaster. Mnstry of Food, Agrculture and Lvestock s playng an actve role to montor agrcultural credt dstrbuton and take sgnfcant steps to remove the hurdles n credt dsbursement (Iqbal et al., 2003). Accordng to Zubar (1989) the mpact of nsttutonal credt comes through fnancng of seed and fertlzer. Quresh and Shah (1992) opned that formal loans postvely affect agrcultural output through fnancng of captal nvestment and t s more benefcal than fnancng of seed and fertlzers. Informal credt sector conssts of professonal moneylenders, frends, relatves, and commsson agents, etc. Though the nformal sector s chargng hgh nterest rate but stll ts contrbuton s larger 38

2 Role of Agrcultural credt n producton effcency than the formal sector owng to low transacton cost, easy access and procedures. Moreover, nformal credt s also avalable for consumpton, socal ceremones and for non-productve purposes. Nonnsttutonal credt s more costly and not adequately large to promote growth and nvestment. Thus t has no helpful contrbuton n agrcultural producton. Varous vewponts are expressed about the economc mpact, equalty and adequacy of credt for the recpents. The true emprcal estmaton of the credt mpact was dffcult due to the fungble nature of credt and as t was ambguous f the estmated mpact of credt explans the borrowng restrants or the ndstngushable borrower s characterstcs (Davd and Mayer, 1980). The effcency of farmng credt system and shadow prce of captal n Pakstan Punjab was calculated by Sal and Carter (1996). Through endogenous swtchng regresson method t was found that the borrowers produced 48 percent more output than the non-borrowers. Farmers havng no loans could make Rs addtonal ncome for one rupee loan; an ndcator of neffcency of captal market. If shadow prce s greater than the opportunty cost of captal, the provson of subsdzed credt has no economc ratonale to mprove the small farmer s access to credt. The techncal and allocatve effcency are the two elements of effcency of producton unts. The techncal effcency descrbes the potental of producton unts to attan maxmum level of output holdng nput level fxed. The allocatve effcency (AE) llustrates the capacty of producton unts to use optmal proporton of nputs (factors) for same level of output. To estmate the total economc effcency (EE), the techncal and allocatve effcency estmates are combned. The techncal effcency estmaton of credtors and non credtors n Pakstan was the man objectve of ths study. The techncal effcency estmaton was carred out through Data Envelopment Analyss (DEA) method whle sources of neffcency were examned through Tobt model. Effcency Analyss The producton effcency estmaton had mperatve mplcatons for both economc theory and polces. Such analyss allowed the assessment of probable ncrease n output together wth the effcency enhancement (Farrell, 1957). To estmate techncal effcency, there are two commonly used approaches, the Data Envelopment Analyss (DEA) a nonparametrc technque and Stochastc Fronter Analyss (SFA), a parametrc approach. Under Data Envelopment Analyss the functonal form was not specfed for the producton technology and t also dd not nclude the error terms, whereas n SFA, a specfed functonal form was used for the effcency estmaton and the error terms were also ncluded for neffcency measurement (Farrell, 1957; Färe et al., 1990). Data Envelopment Analyss (DEA) DEA was used as an apparatus for evaluatng and mprovng the performance of producton unts. The DEA effcency estmaton technque generates an effcency boundary from the gven sample of producton unts (farmng households n ths study). The constructed effcency boundary lne shows the practces of the effcent farms and the farmers below that lne are called neffcent producton unts. The estmaton of techncal effcency (TE) through DEA can be ether nput or output orented under constant as well as varable returns to scale (CRS and VRS). The TE scores obtaned through nput orented and output orented methods possess the smlar values under constant returns but dffer under varable returns to scale technology (Coell, 1996). Output-Orented DEA The present study estmated techncal effcency of farmng households under output-orented technque explanng that how much feasble output s maxmzed for gven level of nputs. Accordng to Farrell (1957) output-orented effcency measure could be descrbed through the followng dagram: Source: Coell, 1998 In above fgure dstance AB s techncal neffcency whch s the quantty through whch producton could be rased wth no nput ncrease. Consequently the techncal effcency scores under output-orented method s TE=OA/OB. If nformaton about prce s avalable then prce lne could be drawn. As PP n above fgure and allocatve effcency s AE=OB/OC. And thus economc effcency would be EE=TE*AE=OA/OC. The obtaned effcency scores of all these types were always surrounded wth the closed nterval 0 and 1. 39

3 A ya z et a l To estmate the techncal effcency of the sample producton unts, the subsequent mathematcal model of lnear programmng was consdered: m ax y, 1,..., k The Tobt model was estmated wth the help of computer software SAS verson 9.1. Instead of common regresson arrangement, the restrcted dependent varable was used as estmated effcency scores bounded between 0 and 1. The management of soco economc and envronmental characterstc of farmer could affect the effcency and productvty of the farmers. It was often argued by Ureta & Pnhero (1997) that t s dffcult to assess all the factors affectng effcency of the farmer but the varables consdered most mportant nfluencng factors were measured. In present study, the DEA scores of effcency obtaned n the output orented CRS model were regressed on varous explanatory varables. The explanatory varables ncluded n ths study were: operatonal area, farmng experence, educaton, household sze, herd sze, dummy of credt, cultvaton practces number and plant protecton measures. To measure the mpact of farm specfc and soco economc characterstcs on the neffcency of farm, the followng form of Tobt model was used: y S.T. n 1 y n 1 x n y x 0 0 Where: y = maxmum producton level, y = the producton of the th producton unt, xn = the nth factor of producton used on th producton unt, x0 = the nth factor of producton used on the Eff 0 1 X1 2 X 2 3 X 3 4 X 4 producton unt beng tested, and = the weght assgned to th producton unt. 5 X 5 6 X 6 7 X 7 8 X 8 The consequental techncal effcency was estmated n the form of a fracton between the examned producton ponts of the producton unt beng analyzed (y) and the maxmum output pont (y). The producton unts havng 1 effcency pont were sad to be techncally effcent whle the producton unts that were techncally neffcent havng score strctly lower than one. The estmated effcency scores of the producton unts are bounded by 0 and 1. The effcency estmates through DEA are the radal effcency measures showng unt ndfference.e. the estmated effcency ponts do not vary wth the transformaton of estmaton entres (Coell et al., 1998). Two weaknesses were observed of DEA approach: t s only an nvestgatve approach and does not prescrbe any helpful technque to reduce neffcency and calculated measures of neffcency are confused wth measurement error (Lovell, 1993; Ray, 2004). Where: Eff = Effcency Scores (from frst stage DEA) X1 = Operatonal land holdng of the th farm n acres. X2 = farmng experence of the th farm s operator n years. X3 = educaton level of the th farmer n years. X4 = number of famly members of th farmer, X5 = Herd sze of the th farmer n anmal unts. X6 = Dummy of credt of th farm (1, f farmer was obtanng loan, zero otherwse ) X7 = number of cultvaton practces s of th farm, (hoeng and weedng etc) X8 = No of sprays for Plant protecton of the th farm, α s = the undentfed parameter to be estmated. µ = the error term. Data The prmary data was collected through wellstructured comprehensve questonnare. The sample of 300 farmers was collected from two tehsls of Fasalabad dstrct; namely Fasalabad and Jaranwala. In each tehsl farm households were ntervewed, whch were further dvded nto two categores, credt and non-credt users. The questonnare contaned nformaton about soco-economc profle of respondent, operatonal land, producton of varous crops, cost of producton, lvestock nformaton and Tobt Regresson Analyss The effcency analyss also need to determne that why effcency dffers among the farmers practcng the same farmng operatons. To examne the factors affectng the techncal effcency or neffcency otherwse, the techncal effcency ndex acqured from DEA were further regressed wth the farm specfc varables by utlzng Tobt regresson technque. 40

4 Role of Agrcultural credt n producton effcency value of farm mplements. Data on farmng nputs ncluded use of seed, fertlzer, rrgaton, labor and machnery. The ntervewng schedule covered nformaton about use of credt, sources of credt, loanng amount, purpose of loan, tme lag between loans appled for and loan dsbursement, cost of obtanng loan and repayment schedule. Result and Dscusson The descrptve statstcs of farms provded n Table 1 showed farmer s annual output and pattern of nput use and farm specfc varables of total sample of 300 farms. The average annual gross farm output value was Rs. 55,497. The hghest reported value of output was Rs. 98,000 and the lowest value was Rs. 28,460. The average gross ncome from sale of mlk was Rs. 38,012 per year. The labor nput expressed n man days, ncludes famly labor and permanent hred labor. The mean value of labor was only days per acre for a year, whch translates to 2 days per week rangng from only 3 hours to 9 days per week. The average annual use of fertlzer nutrents was kg per acre whereas average rrgaton level was acre nches per acre. The table 1 showed that average expendtures on cash nputs were Rs. 6, per acre and average annual expendture on lvestock was Rs. 12,234 per anmal. Addng years of schoolng not only mproves the effcency of farmers but also enhanced ther capablty to understand and adopt new methods and technques of farmng (Olagunju and Adeyemo, 2007). Table 2 presented frequency dstrbuton of educaton level for credtors and non credtors ncluded n study. The table showed that 36 credtors (24 percent) had 8 years of educaton. And the majorty of the non credtors (30 percent) had 10 years of educaton. The mean educaton level of credtors was 7.78 years and 8.28 years for non credtors. These results are somewhat contradctory to the study of (Bashr and Azeem,2009). Accordng to them educaton level of loanee was more than non credtors. Despte of the fact that sample area was almost the same.e. Fasalabad, the only possble reason mght be source of credt as UBL credtors were ncluded there. Based upon the farmng experence, the practcal knowledge and sklls whch a farmer ascertan through the number of years spent n farmng actvtes, progress and mprovement n the producton actvtes of a farmer could easly be observed. Generally t was beleved that farmer who had more farmng experence mght be more effcent and productve through tral and error (Olagunju and Adeyemo, 2007). Table 3 showed that 40 percent of non credtors had 11 to 20 years of farmng experence, whereas 27 percent credtors belonged to ths category. More years of experence were noted for credtors (43 percent) than non credtors (33 percent) excess to 20 years. Table 1 Descrptve Statstcs of the physcal nputs and output Varable Mean Std. Dev. Mnmum Maxmum Output and Inputs Gross farm output/year (Rs./acre) Gross ncome/year from sale of mlk (Rs./anmal) Labor days/year (man days/acre) Fertlzer Nutrents/year (Kg./acre) Irrgaton/year (per acre nch) Cash nputs/year (Rs./acre) Expendtures on lvestock/year (Rs./anmal) Source: Feld Survey 2009 Table 2 Dstrbuton of Educatonal Attanment of Respondents credtors non credtors Years of educaton Percent Percent No educaton Prmary educaton Mddle Metrc Secondary educaton Hgher secondary educaton Graduate Total Source: Feld Survey

5 A ya z et a l Table 3 Dstrbuton of Farmng Experence of Respondents Credtors Farmng Experence 23 up to to to to to 50 Total Source: Feld Survey 2009 Table 4 Dstrbuton of Household Sze of Respondents Credtors Household Sze 10 7 Less than to to to to and above Total Source: Feld Survey Non Credtors Non Credtors Table 5 Dstrbuton of Techncal Effcency of Borrowers and non-borrowers (DEA) Effcency score Farms usng credt (percent) Farms not usng credt (percent) Total Mnmum 1 1 Maxmum Table 4 showed the frequency dstrbuton of household sze of borrowers and non borrowers ncluded n the study. Majorty of the respondents n both categores, had large famly sze as 85 borrowers (57) and 81 non borrowers (54 ) fallng wthn the range of 5 to 9 famly members. These results are n lne wth Bashr and Azeem (2009).Accordng to them 80 and 82 loanee and non loanee farmers were havng 5-9 famly members. Effcency Estmates through Data Envelopment Analyss (DEA) The techncal effcency of farmers n dstrct Fasalabad was estmated by applyng output orented Data Envelopment Analyss (DEA) under constant returns to scale. The estmated mean effcency of 300 sample farmers was 78 percent. The output orented techncal effcency explaned that how much feasble output s maxmzed for a gven level of nput. There s scope for the farmers to mprove ther effcency about 22 percent. The resultant effcency scores from DEA were further dvded nto two categores: namely borrowers and nonborrowers. The dfferent levels of techncal effcency and percentage of farmers showed that more percentage of farmers usng credt were at hgh effcency level (Table 5). The results also ndcated a techncal effcency range from 0.23 to 1.00 for nonborrowers and from 0.42 to 1.00 for borrowers. The effcency dstrbuton had shown that, 20 percent of non-borrower farmers and 14 percent of borrowng farmers are below 60 percent level of effcency. Ths level of effcency showed that 6 percent farmers not usng credt are at low effcency level. The table also explaned that 50 percent of borrowers are above 80 percent effcency level whle the percentage of nonborrowers was 45. Techncal Ineffcency sources The techncal effcency scores from frst stage Data Envelopment Analyss examned that there exsted 22 percent neffcency of respondent farms. Thus to nvestgate the factors affectng techncal effcency of sample, Tobt model was appled. In Tobt model, the effcency scores from DEA were regressed on operated area, farmng experence, educaton of household head, dummy of credt (1=borrower, 0=non-borrower), household sze, herd sze (anmal 42

6 Role of Agrcultural credt n producton effcency Table 6 Regresson Results through Tobt Model Parameter Parameter Estmate Standard Error t Value Approx Pr > t Intercept * <.001 Operatonal area Farmng experence * Educaton years * Credt dummy ** Household sze ** Herd sze *** Total cultvaton practce number * Total plant protecton numbers ** Note: * Indcates that the coeffcent was sgnfcantly dfferent from zero at 0.01 probablty level; **Indcates that the coeffcent was sgnfcantly dfferent from zero at 0.05 Probablty level; *** Indcates that the coeffcent was sgnfcantly dfferent from zero at 0.10 Probablty level unts), cultvaton practce, and numbers of plant protecton measures. Table 6 descrbed the parameters estmated through Tobt regresson model whch llustrated the extent of factors affectng techncal effcency of farms. Sx of the 9 parameters were statstcally sgnfcant at 0.05 probablty level, whch suggests a farly good ft of the model. The postve sgn statstcally sgnfcant at 0.05 probablty level of the credt dummy ndcated that access to credt would result a decrease n neffcency of the farms. For a one percent ncrease n the access to credt; techncal effcency of farmers wll ncrease by 0.04 percent. The small value of credt coeffcent was may be due to the fungble nature of credt as t was also argued by Von and Adam (1980) that fungblty had consderably declned the expected effect of all the ten observed credt projects n Latn Amerca. Access to agrcultural credt allows farmer s tmely use of farm nputs and applcaton of new and modern technology whch ultmately ncrease output of the farms. The credt dummy showed the hghest coeffcent value than all other factors determnng techncal effcency. Varous studes lke Sal and Carter (1996), Feder, et. al. (1990), Zubar (1989) and Quresh and Shah (1992), confrmed these results through dfferent estmaton technques. Operatonal area showed negatve sgn; large farm sze ncreased neffcency of farms but nsgnfcantly. The household sze also exhbted negatve relatonshp wth techncal effcency and was sgnfcant at 0.05 probablty level. The large famly sze ncreased neffcency of farms by percent. The total number of plant protecton measures was statstcally sgnfcant at 0.05 probablty level but had negatve correlaton wth techncal effcency wth the coeffcent value of More number of sprays (pestcdes and weedcdes) s not solely responsble for pest control but also ndcated the heavy pest attack further deteroratng the productvty. Concluson The study employed a two stage estmaton technque to examne the mpact of agrcultural credt on techncal effcency and ts determnants for rural farmers n Fasalabad. In frst stage the techncal effcency was calculated usng output orented DEA. In the second stage the farm specfc characterstcs were used n Tobt regresson model to examne the factors effectng farmng effcency. The results ndcated that o.78 average effcency score wth mnmum value 0.42 for credt user and mnmum value 0.23 for non-credt users. Tobt regresson results provded the ndcaton that farmng experence, educaton, access to farmng credt, herd sze and number of cultvaton practces had postve and sgnfcant correlaton wth effcency of the farmer. Recommendaton The agrculture sector of Pakstan stll suffers from low productvty, expensve fnancal support to the farmers, neffcent market structure and mproper research. Thus to develop farmng sector and to ncrease the farmng effcency t was recommended to enhance the accessblty of small and margnal farmer to formal agrcultural credt. Loan for the lvestock should be enhanced and ths would defntely enhance farmer s ncome and ultmately would reduce poverty. References Adams DW and AF Delbert, Edted by Informal Fnance n Low-ncome Countres, Westvew Press, Colorado. Aleem I, Imperfect nformaton, screenng, and the costs of nformal lendng: A study of rural credt market n Pakstan. World Bank Economc Revew, 4: Bravo-Ureta BE and AE Pnhero, Techncal, economc and allocatve effcency n peasant farmng: Evdence from the 43

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