Efficiency of Investor Owned Firms and Cooperatives Revisited

Transcription

1 Effcency of Investor Owned Frms and Cooperatves Revsted Rafat Soboh1, Alfons1 Oude Lansnk Gert van Djk2 1Wagenngen Unversty, Busness Economcs, the Netherlands, e-mal: 2Wagenngen Unversty and Unversty of Nyenrode, Wagenngen, the Netherlands, e- mal: Paper prepared for presentaton at the 113 th EAAE Semnar A reslent European food ndustry and food chan n a challengng world, Chana, Crete, Greece, date as n: September 3-6, 2009 Copyrght 2009 by [Rafat Soboh, Alfons Oude Lansnk, Gert van Djk]. All rghts reserved. Readers may make verbatm copes of ths document for non-commercal purposes by any means, provded that ths copyrght notce appears on all such copes.

2 Effcency of Investor Owned Frms and Cooperatves Revsted Rafat Soboh 1, Alfons 1 Oude Lansnk Gert van Djk 2 1 Wagenngen Unversty, Busness Economcs, the Netherlands, e-mal: Rafat.ewadasoboh@wur.nl; Alfons.OudeLansnk@wur.nl 2 Wagenngen Unversty and Unversty of Nyenrode, Wagenngen, the Netherlands, e-mal: Gert.vandjk@wur.nl Abstract. Provdng a performance measure of any frm s a crucal ssue, not only for the stakeholders of the frm, but also for polcy makers, labor unons, and economsts. The relevant performance measures should consder the objectves of the frm s owners. The ownershp structure of cooperatves s dfferent from that of nvestors owned frms, whch n prncple mples the need of dfferent tools to measure ther performance. Typcally, however, the performance of cooperatves and nvestor owned frm s mostly compared usng the same approach. In ths study, we use Data Envelopment Analyss (DEA) to compare the performance of dary cooperatves and nvestor owned frms n major European dary producng countres usng a tradtonal approach, whch vews both types of frms as cost mnmzers, and an alternatve approach, whch consders the objectves of the cooperatves. In the alternatves approach, two hyperbolc models were evaluated, one of them consder the frms to expand both output producton and use of materal to address the objectve of the owners of the cooperatves. The performance of the cooperatves changes across the two approaches form beng out performed by IOFs usng the tradtonal approach to outperformng IOFs when usng an approach that s n lne wth the objectve of the cooperatve. Keywords: DEA, hyperbolc effcency, cooperatves, Investor Owned Frms, Bootstrappng 1. Introducton Dary cooperatves n Europe have played an mportant role n the dary processng sector. In major dary producng-countres, such as Denmark, the Netherlands and Ireland, cooperatves process more than 85% of the total mlk producton (Van Bekkum, 2001). However, the performance of the cooperatves frms (CFs) and ther ablty to functon effcently n compettve and global markets n comparson to the Investor Owned Frms (IOFs) have been long debated n lterature (see: Soboh et al., 2009). The debate has ntensfed due to major trends n the past few decades such as globalzaton, changes n related polces, nternatonal trade lberalzaton and treates, and changes n consumers preferences (Soboh et al., 2009). Recently, due to the expected abolshment of the quota system n 2015 and the current fnancal crss, the debates are ntensfed on the compettve strength of the CFs and IOFs, and CFs are argued to have more sutable and sustanable organzatonal structure than IOFs (Van Campen, 2009). Cooperatves are not easly defned (Hnd, 1999) and do not have a standard ownershp structure lke IOFs (Chaddad and Cook, 2004 ). However, there s a general consensus n the lterature that cooperatves are generally seen as user-controlled, user-owned and user-benefct frm (Soboh et al., 2009). In the case of dary CFs, ths emphass on members control, ownershp and beneft to members s reflected n the mlk payment to members whch ncludes, n addton to mlk prce, a proporton of the dvdends (Zwanenberg et al., 1993). The members role and objectve n ther cooperatves s a major reason for debatng the argument and emprcal fndngs that CFs are techncally and economcally neffcent when compared to the IOFs. Those who advocate CFs model reject ths argument and demand a dfferent approach to evaluate the performance of the CFs emprcally. For nstance, Van Djk and Klep (2005) argued that CFs have double-objectves one of whch s to beneft members whle the other s to healthly functon n the compettve market. Addtonally, the members control on the CFs nvestment decsons, makes the CFs less wllng to be nvolved n rsky ventures and therefore more mmune to cope wth polcy changes (Soboh et al., n progress) or economcal crses (Van Campen, 2009). It s argued, on one hand, that the CFs are more benefcal to farmers and the rural development than proft maxmzng IOFs (Chavez, 2003). On the other hand, Hnd (1999) argued that the control and ownershp of members of the cooperatve cause CFs to be less orented to value added producton, less effcent n nput use (especally members product) and more focused on explotng economes of scale. Hence, cooperatves are argued to be less techncal, scale and cost effcent. Theoretcally, both arguments, of those who advocate the cooperatve form of frms and those who crtcze t, are defendable but hardly dsputed. However, emprcally- as far as we know- there s no concrete evdence of any of the arguments nether for such comparson n general nor for the European dary CFs n comparson to ther IOFs counterpart n partcular(see: Soboh et al., 2009). In ths study, usng Data Envelopment Analyss (DEA), we frst analyze techncal, scale and allocatve effcency of dary processng frms usng the tradtonal effcency technques. Second we use a hyperbolc approach to dary cooperatves and IOFs wth a specal emphass on the role of raw materals (.e. manly mlk delveres by the farmers) n two models. The frst model, measures the hyperbolc techncal effcency of the frms assumng they expand output and contract materals and other nputs smultaneously. The second model, measures the hyperbolc techncal effcency of the frms assumng they expand both output and materals and 1

3 contract the other nputs. These two hyperbolc measures provde us wth alternatve approaches to evaluate the techncal effcency takng nto account the cooperatve general objectve to serve the nterests of ther members as the major (f not the only) supplers of materals. Subsequently, we use bootstrappng technque to allow for statstcal nference. Ths paper uses Data Envelopment Analyss (DEA), outlned n (Färe et al., 1994). The DEA was used by many authors to evaluate and to compare the performance of cooperatves to IOFs, such as Doucoulagos and Hone (2000 ), Sngh, et.al. (2001) and Boyle (2004). However, ths study contrbutes to the lterature by addressng the nature of the cooperatve whch ams to serve ts members, whch s done n two ways. Frst, ths study provdes the frst emprcal comparson of the techncal, scale and allocatve effcency of European dary CFs and IOFs. The results of large IOFs and CFs are presented n more detal. Second, ths paper presents an alternatve approach to measurng techncal and scale effcency of cooperatves that explctly,.e. an approach that s n lne wth the dfferent objectves of CFs versus IOFs. The remander of the paper s presented as follows. The next secton presents the DEA models. Ths s followed by a dscusson of the data of the dary processng frms. In secton four we present the results of the DEA models. The concluson s provded n the ffth secton. 2. DEA Models for Modelng Effcency of the Frms The performance of dary cooperatves n comparson to IOFs has been studes by others usng DEA. Doucoulagos and Hone (2000 )used DEA to assess the techncal effcency of Australan dary processng frms usng data over the perod Ther results show a modest techncal progress and ndcate some convergence n productvty levels across regons. They conclude that the Australan dary sector s operatng at a hgh level of techncal effcency. Sngh, et.al. (2001) appled DEA to compare the performance of the dary cooperatves to the prvate sector n Inda. They concluded that cooperatves are more cost effcent than IOFs. Boyle (2004) nvestgated the economc effcency of Irsh dary cooperatves over the perod He argued that cooperatves are not effcent for two reasons: (a) cooperatves suffer from techncal neffcency because of prncpal-agent problems and allocaton neffcency due to horzon problems; (b) cooperatves prces for raw mlk are neffcent. Each of the above studes used the same approach on CFs and IOFs to measure and compare ther performance. In ths study we use two dfferent approaches to evaluate the performance of the cooperatves. The frst s the tradtonal, s measurng the overall effcency of the frms and decomposes t nput orented techncal, scale and allocatve effcency. The tradtonal approach vews the frms as cost mnmzers and gnores the dfferent nature of CFs and IOFs. The second,.e. the alternatve approach, s measurng techncal effcency of the frms assumng that frms expand output(s) and materals and smultaneously contract other nputs wth equal proportons. 2.1 Tradtonal Effcency Approach and Models In ths approach we measure the nput-orented techncal, scale and allocatve effcency. The models vew the CFs and the IOFs as cost mnmzng frms, n whch all nputs, ncludng the materals, are beng contracted. The nput-orented techncal effcency, n whch nputs and materals are contracted whle keepng output at fxed level, s expected to be hgher for IOFs than for the CFs. For the IOFs, as owners are solely nterested n proft, materals- manly raw mlk- are consdered to be a regular nput, whle materals for the CFs are more complex and are not vewed as smply an nput snce the supplers of raw mlk are themselves the owners. The owners of the CFs, the supplers of raw mlk, am to maxmze ther return by obtanng a hgh payment for raw materals whle at the same tme- lke other frms- want cost mnmzaton for all other nputs and producton factors. Therefore, the cooperatves are expected to have a lower value of the nput-orented techncal effcency. The scale effcency of the CFs s expected to be lower than that of the IOFs. The CFs are not totally free n choosng ther scale of operatons, by default they are oblged to process and market all members producton. IOFs on the other hand choose the optmal scale to process the quantty of materal that maxmzes ther proft. The average allocatve effcency of the CFs s expected to be lower than of the IOFs. CFs are not assumed to be proft maxmzers or cost mnmzers; nstead, they am to mnmze a dfferent objectve functon whch ams to pay hgher mlk prce than the IOFs, n addton to mnmzng all other costs. And snce IOFs are proft maxmzers, hence cost mnmzers as well, they are expected to have a hgher value of the allocatve effcency (equal to one), whle CFs, as they are not cost mnmzers for ther raw materal, are expected to have lower allocatve effcency than IOFs. Before representng the lnear programmng needed to measure the tradtonal models, to measure the nput-orented techncal effcency and scale and allocatve effcences, t s necessary to ntroduce some 2

4 notatons. Consder a frm that uses a vector of nputs (x) and a vector of raw materal (m) to produce a vector of output (y). The DEA nput-orented model to measure the techncal effcency for frms, =1,...,N, that produce one output usng three nputs ncludng the raw materal s calculated form the followng non-lnear program: mnφ φ, λ y φm φx vrs, + Yλ, Mλ, Xλ, N1' λ = 1, λ, (1) Whereφ s the overall techncal effcency score ( φ [0,1]) for the th frm, Y s the (1 N) vector of observed vrs output, M s the (1 N) of observed use of raw materal, X s the matrx of observed nputs and λ s a (Nx1) vector of ntensty varables (frm weghts). The constrant N 1 ' λ = 1 (wth N1 beng an Nx1 vector of ones) mples the sum of the lambdas equals one and allows for a varable return to scale (VRS) technology. Here, the overall techncal effcency measures the mnmum proportonal contracton n observed nputs (x) and raw materal (m) subject to the constrants mposed by the observed nputs and the technology. Ths s llustrated n Fgure 1 lne (1). To measure the scale effcency for the two models above we modfy both models to exclude the constrant N1 ' λ = 1 1. Ths wll produce φcrs - the nput orented techncal effcency assumng constant return t scale- whch wll be used to measure the scale effcency (SE), whch equals to φ crs. φvcrs The cost effcency s computed by solvng the LP model (2): where mn λ, x&, m& s. t : y x& m& Xλ N1' λ = 1 λ m& and w x& x + Yλ Mλ cost gven the nput prces ( + w m m& x& denote materal cost and other nputs quanttes, respectvely, of the th frm that mnmze the w ) and raw materal prces ( w ). The overall effcency s defned as the rato of x actual to mnmum cost: OE = C &, where C s the actual cost defned as ( w x x + wmm ) and C & s the C mnmum cost whch s obtaned by solvng model (2). The overall effcency OE of the dary processng frm s calculated as followng: OE TE SE AE = (3) In whch TE s nput orented techncal effcency assumng varable return to scale, and AE s the allocatve effcency of the frm (). m SE s the scale effcency 1 We don t wrte down the models of the constant return to scale here to avod repetton. 3

5 2.2 Hyperbolc Models to ncorporate CFs Nature In ths alternatve approach we consder two hyperbolc models. In the frst model, we measure the hyperbolc techncal effcency consderng the frm to radally expand output and radally contract nputs and materals smultaneously wth equal proportons; ths s presented n model 4 whch s llustrated n Fgure 1 wth lne (4). In the second model, we measure the hyperbolc techncal effcency consderng an aspect of the CFs whch am, not only to expand the total turnover, but also materals, whle contractng all other nputs smultaneously wth equal proportons (see model 5). In the frst model (model 4), we vew each frm (of both types) as an IOF, whle n the second model (model 5), we vew each frm (of both types) as a cooperatve. Our expectaton s that, on average, the CFs wll score lower wth the frst hyperbolc techncal effcency model rather than wth the second one. Ths s due to the nature of the CFs whch s assumed to maxmze the revenue of the mlk delvered by ts members (raw mlk whch makes up the major part of materals). max ϑ, λ s. t : ψy ψ ψ 1 λ 1 1 { ψ : ( ψy ) P( λ x ; λ m ) } m 1 x N1' λ = 1 + Yλ Mλ Xλ The techncal effcency n whch nputs (x) are contracted and both output (y) and raw materal (m) are smultaneously expanded s measured n model 5 and llustrated n Fgure1 wth lne (5). The techncal effcency s expected to be hgher for cooperatves. (4) max ϑ, λ s. t : ϑy ϑm ϑ 1 1 { ϑ : ( ϑy ; ϑm ) P( λ x ) } x N1' λ = 1 λ + Yλ + Mλ Xλ (5) Fgure 1 llustrates the three models (the tradtonal and the two alternatve ones). For smplfcaton, we use two dmensons: output (y) and materals (m). Lne (1), n Fgure 1, llustrates the tradtonal stuaton where materal s contracted whle output s held fxed. Lnes (4) and (5) llustrate the two hyperbolc models, where lne (4), n Fgure 1, presents the stuaton where materals s contracted whle output s expanded, whle lne (5), n Fgure1, presents the stuaton where materal and output are expanded. Gven the assumed objectve of CFs to pay a hgh prce for nputs delvered by ther members (materals), the cooperatves are expected to be located further to the rght corner, whle IOFs are expected to be located left upper corner n Fgure 1. Fgure 1: The Drecton of the dfferent Models. 4

6 Y Bootstrap Method The bootstrap method s an establshed statstcal resamplng method used to perform nference n complex problems. If the data generatng process (DGP) characterses the true data generaton well and s mmcked n the resamplng smulaton, then the bootstrap method s well-performed n valdatng statstcal nference. The bootstrap s manly to approxmate the samplng dstrbuton of the estmator (n ths study: nput-orented, hyperbolc and scale effcences). To approxmate ths samplng dstrbuton we use the emprcal dstrbuton of the resampled estmate, whch s obtaned from the Monte Carlo resamplng dstrbuton of the estmaton procedure (n ths case the DEA). Repeated re-samples are obtaned from an estmate of the DGP are used n the estmaton procedure to produce repeated estmates (Lothgren and Tambour, 1999). In ths study, we use the bootstrappng method suggested by Smar and Wlson (2007) to avod sample bases of the techncal and hyperbolc effcency measures, and we use the bootstrappng approach n Lothgren and Tambour (1999) to correct for data bases when measurng scale effcences. We use Hall percentle ntervals based on dfferences to construct 95% confdence nterval for nput-orented and hyperbolc techncal effcency and scale effcency. 3. Data Data on dary processng frms n sx European countres (Belgum, Denmark, France, Germany, Ireland and the Netherlands) coverng the year 2004 come from AMADEUS 2. The data set used for estmaton conssts of 133 frms among whch 90 are IOFs and 43 are CFs. The model dstngushes one output (total turnover) and three nputs (fxed assets, materal cost, and employment cost). The outputs and nputs are expressed n Euros of 1996 (base year) by deflatng the monetary values wth ther Tornqvst prce ndexes (Coell et al., 2005). The dary plants n these countres are typcally producng more than one product. However, the only relevant output avalable n the data set s total turnover. Total turnover represents the total operatng revenue from sellng all products produced by the processng company. Turnover (output) s deflated usng the countres harmonzed ndex of consumer prces for mlk, cheese and egg. Fxed asset s measured as the value of physcal land, buldngs, machnery, and the non-physcal fxed assets: such as the goodwll, patents, brands, and market shares. The value was deflated usng the average value M 2 AMADEUS s a European fnancal data base prepared by Bureau van Djk and contans more than 5 mllon prvate, cooperatve and publc companes. The data-base s collected from reports produced by the chamber of commerce of the dfferent European countres. AMADEUS unfed the fgures of the fnancal statements of the dfferent countres. 5

7 of the prces ndex of the agrcultural gross fxed captal formaton and the prce ndex of the agrcultural machnery and equpment per country. The AMADEUS data base ncludes materal cost, reflectng the cost of purchasng the nput materals before the processng operaton starts. Ths nput manly conssts of raw mlk purchased by the dary plant. We used the deflated EC-ndex of producer prces of the cows mlk per country as the deflator for the materal cost. Labor cost s deflated usng the nomnal value of the labor cost ndex n total ndustres (excludng publc admnstraton). The prce ndexes vary over the years and the dfferent countres but not over the frms or over ther type, mplyng dfferences n the composton of nputs and output or qualty dfferences are reflected n the quantty (Cox and Wohlgenant, 1986). Addtonally, the quanttes also reflect dfferences n prces of the producton factors between the two types of frms; a hgher the mlk payment mples a hgher quantty of materals. Table 1 provdes the means and standard devatons of turnover, fxed assets, raw materal, labor and prces. It shows that CFs have, on average, a hgher average value of the output and the three nputs than IOFs. Table1: Descrpton of the Data. Varable Dmenson Mean (n) Standard devaton Type IOFs (90) CFs (43) IOFs CFs Quanttes Output (turnover) 10 6 Euros Fxed assets 10 6 Euros Materals 10 6 Euros Labor 10 6 Euros ,52 Prces Output (turnover) 1996= Fxed assets 1996= Materals 1996= Labor 1996= Results The results of the DEA models and the bootstrappng measures all were obtaned usng the package FEAR (Wlson, 2008). Secton 4.1 presents the results of the tradtonal approach and Secton 4.2 presents the alteratve approach of the two hyperbolc models. 4.1 The Results of the Tradtonal approach Results n Table 2 show that IOFs, on average, are more techncally, scale and allocatve effcent than CFs, hence, more overall effcent. The CFs are techncally less effcent when compared to IOFs, CFs are slghtly less scale effcent than IOFs, and CFs are less allocatvely effcent than IOFs. Usng the tradtonal approach, n whch frms are consdered to mnmze cost (and contract the quantty of materals), CFs are outperformed by IOFs n ther techncal, scale and allocatve effcences. Treatng the materal as an nput, whch has to be mnmzed, provdes us wth an expected lower performance of the CFs. On average, the nput orented techncal effcency of the IOFs s more than 50 percent hgher than the one of the CFs. The results of the techncal effcency also reflect dfferences n for example prces pad for raw materals between CFs and the IOFs, where CFs s expected to pay hgher total prce. On average, the scale effcency of the IOFs, usng the tradtonal approach, s 10 percent hgher than the one of the CFs. Ths dfference n scale effcency suggests that CFs are operatng on a less optmal sze than IOFs. Ths fndng may be due to the fact that CFs are more restrcted n choosng ther optmal sze due to ther oblgaton to process all what members provde to the CFs. On average, the allocatve effcency of the IOFs s 20 percent hgher than the one of the CFs. Ths dfference of the allocatve effcency suggests that the CFs are less successful n mnmzng costs than IOFs (as assumed to be more of proft orented frms). The latter fndng suggests that CFs may have another objectve rather than mnmzng costs, CFs may be more nterested n payng a hgh mlk prce to ther farmers. These results do confrm the hypothetcal expectatons of the CFs performance when compared to the IOFs. The dfference of the techncal and scale effcences between the CFs and IOFs are statstcally sgnfcant 6

8 as ther confdence ntervals do not overlap. Therefore, the overall performance of the CFs usng the tradtonal model s lower than the IOFs over all effcency. Table 2: Overall effcency and ts decomposton for CFs and IOFs (95% confdence nterval n parentheses) Techncal effcency Scale effcency Allocatve effcency Overall effcency CFs ( ) ( ) IOFs ( ) ( ) The results of the alternatve approach Table 3 presents the results of the two hyperbolc effcency models (model 4 and model 5). Model 4 expands outputs and contracts materals along wth other nputs, whereas model 5 expands outputs and materals and contracts the use of other nputs. Results of model 4 n Table 3 show that CFs score, on average, n the frst hyperbolc model (model 4) whch says that CFs can ncrease ther output wth 65.9 percent contract ther nputs (ncludng 1 materals) by ( ( 1 ) *100 = )39.7 percent. The IOFs, on the other hand, scored on average n the frst hyperbolc model (model 4), whch says that the IOFs can expand ther output wth 43 percent and contract ther nputs wth 30.1 percent. CFs score slghtly hgher n the second hyperbolc model (model 5) than the frst hyperbolc model wth 1.638, whch says that CFs can on average expand output and materals by 63,8 percent and decrease the use of nputs (excludng materals) by ( 1 ) 1 ( *100 =) 39.0 percent effcent n contractng ther nput (excludng materals). The IOFs score worse n the second hyperbolc model (model 5) rather than n the frst hyperbolc model wth 1,647, whch mples a potental for expanson of outputs and materals by 64,7 percent ther and a 39.3 percent contracton of nputs (excludng materals). When movng from model 4 to model 5, the scale effcency has also mproved for the CFs (from 1.21 to 1.10) whle t has worsened margnally for the IOFs (from 1.09 to 1.10). The results of the bootstrappng show that all dfferences n techncal and scale between CFs and the IOFs are not sgnfcant at the crtcal 5% level n model 4 and model 5. In the frst hyperbolc model (model 4), the hyperbolc techncal and scale effcences of the cooperatve (1.659) and (1,21) le wthn the confdence nterval of the hyperbolc techncal and scale effcences of the IOFs [1,14-1,74] and [0,89-1,97], respectvely. The stuaton s smlar for the hyperbolc techncal and scale effcences of the IOFs (1,430) and (1,091) whch are also located wthn the CFs confdence nterval for both measures [1,21-1,92] and [0,88-1,47], respectvely. The bootstrappng results of the second hyperbolc model (model 5) are smlar to the results of the frst model n terms of locaton wthn the confdence ntervals. The hyperbolc techncal and scale effcences of CFs (1.638) and (1,10) le wthn the confdence nterval of the hyperbolc techncal and scale effcences of the IOFs [1,03-1,97] and [0,73-1,43], respectvely. The stuaton s smlar for the hyperbolc techncal and scale effcences of the IOFs (1,647) and (1,10) whch are also located wthn the CFs confdence nterval for both measures [1,09-2,61] and [0,73-1,43], respectvely. Table 3: Hyperbolc Techncal and Scale Effcences for CFs and IOFs (95% confdence nterval n parentheses) Model (4): Contract Materals Model (5): Expand Materals Techncal Effcency Scale Effcency Techncal Effcency Scale Effcency CFs (1,21-1,92) 1,21 (0.88-1,47) (1.09-2,61) 1,10 (0,73-1,43) IOFs (1,14-1,74) 1,091 (0,89-1,43) (1,03-1,97) 1,10 (0.89-1,48) Although the dfference of the measure between the two s not sgnfcant at the crtcal 5% level, t shows that the performance of the CFs mproved by 8 percent whle the IOFs performance s worsened by 17 percent when movng from a model that contracts materals to a model that expands materals. Ths change of the performances between the two models, suggest that CFs are more orented to ncreasng materal costs (e.g. through a hgher prce), whereas IOFs are more focused on decreasng materal costs. Addtonally, the dfference of the scale effcency between the CFs and the IOFs reduced to zero n the second model, whch 7

9 mples that CFs are more scale effcent when materals and output are expanded rather than when the CFs expand only the output whle contractng materals and other nputs. 4.3 The performance of the largest CFs and IOFs In Appendx A, we present the results of the ten largest CFs and IOFs n terms of turnover. Arla and Fresland are the only two CFs whch are techncally effcent usng the tradtonal and both alternatve approaches. Campna and Glanba are only techncally effcent usng model 1, whle Nordmlch s techncally effcent n both hyperbolc models (model 4 and 5). Results n Appendx A show that scale effcency of the largest CFs s rather poor n both model 1 and model 4, and mproved sgnfcantly usng model 5. Nordmlch and Arla are the only two CFs that are scale effcent n the second hyperbolc model (model 5). However, Fresland and Campna are the least scale effcent usng the tradtonal mdoel and the frst hyperbolc model (model 4). The average mprovement of the scale effcency from model 4 to model 5 s 19 percent for the ten largest cooperatves and only three percent for the ten largest IOFs. The allocatve effcency of the CFs s generally very low, whch suggests that the objectve of large CFs dffers from the objectve of large IOFs. Among the ten largest IOFs, there are fve IOFs techncally effcent usng model 1. The number of techncally effcent IOFs drops dramatcally (to only two IOFs) when measured usng model 5; ths drop n the number of effcent IOFs n model 5 s n lne wth the fndng n secton 3.2 whch showed that IOFs perform worse n model 5 rather than model 1 and 4. More detals can be vewed from the Appendx. 5. Conclusons The rason d etre of cooperatves dffers from the one of IOFs. Therefore n order to evaluate the effcency of the cooperatves, a dfferent approach should be consdered,.e. an approach that takes nto account the dfferent objectves of the owners of the cooperatve. Comparng the performance of CFs to the one of the IOFs usng the same model mposes the same behavoral characterstc on ether type of frm. CFs, as user-owned, user-controlled and user benefcary frms are more restrcted to members nterest n processng ther own producton and recevng the hghest overall payment for ther product whch serves as the materal to the cooperatve. Therefore, materals have a dfferent role for CFs rather than for IOFs. The role of materal n CFs nfluences the choce of the nput bundle by the cooperatve frm to produce output, t restrcts the choce of the optmal sze, and mples a devaton from cost mnmzng behavor. Our emprcal fndngs show that, on average, the CFs under-perform the IOFs n ther nput-orented techncal, scale, allocatve effcences. However, the performance of the CFs n comparson to the IOFs mproved when consderng the model that expands the use of materals and output. Addtonally, the dfferences n the scale effcences between CFs and IOFs dsappear. The mprovement of techncal effcency and the dsappearance of the dfference n scale effcency suggest that materals have dfferent roles n CFs and IOFs due to dfferent objectves of the two frm types. To provde a relevant comparson of the performance of the CFs wth the IOFs analysts should ncorporate the nterest of the owners of the frm. The overall concluson s that CFs and IOFs need dfferent tools to evaluate ther performances, comparng the performance of the CFs to IOFs s not sutable f the same approach s used assumng same objectves to the two types of frms. 8

10 References Boyle, G. E. (2004). The Economc Effcency of Irsh Dary Marketng Co-operatves. Agrbusness 20, Chaddad, F. R. and Cook, M. L. (2004). Understandng New Cooperatve Models: An Ownershp-Control Rghts Typology. Revew of agrcultural Economcs 26, Chavez, M. E. (2003). Cooperatves: Rural Development and Decent Work. In Increasng productvty of rural work. Unted Natons Headquarters, New York: Deputy Drector-General Internatonal Co-operatve Allance (ICA) & Coordnator of the Commttee for the Promoton and Advancement of Cooperatves (COPAC). Coell, T. J., Rao, D. S. P., O Donnell, C. J. and Battese, G. (2005). An Introducton to Effcency and Productvty Analyss. 2nd edn, New York: Sprnger. Cox, T. L. and Wohlgenant, M. K. (1986). Prces and qualty effects n cross-sectonal demand analyss. Amercan Journal of Agrcultural Economcs 68, Doucoulagos, H. and Hone, P. (2000). The Effcency of the Australan Dary Processng Industry. The Australan Journal of Agrcultural and Resource Economcs 44, Färe, R., Grosskopf, S. and Lovell, C. A. K. (1994). Producton Fronters. Cambrdge: Cambrdge Unversty Press., 296. Hnd, A. (1999). Cooperatve Performance Is there a Dlemma? Journal of Cooperatves 14, Lothgren, M. and Tambour, M. (1999). Testng scale effcency n DEA models: a bootstrappng approach. Appled Economcs 31, Smar, L. and Wlson, P. W. (2007). Estmaton and nference n two-stage, sem-parametrc models of producton processes. Journal of Econometrcs 136, Sngh, S., Coell, T. and Flemng, E. (2001). Performance of Dary Plants n the Cooperatve and Prvate Sectors n Inda. Annals of Publc and Cooperatve Economcs Soboh, R. A. M. E., Oude Lansnk, A., Gesen, G. and Van Djk, G. (2009). Performance Measurement of the Agrcultural Marketng Cooperatve: The Gap Between Theory and Practce. Revew of Agrcultural Economcs. (forthcomng).. Soboh, R. A. M. E., Oude Lansnk, A. and Van Djk, G. (2009). Dstngushng Cooperatves form Investor Owned Frms usng Logstc Regresson. Wagenngen Unversty, workng paper. Van Bekkum, O.-F. (2001). Cooperatve Models and Farm Polcy Reform. In Explorng Patterns n Structure- Strategy Matches of Dary Cooperatves n Regulated vs. Lberalzed Markets. Assen, The Netherlands: Konnkljke Van Gorcum, Van Campen, J. (2009). De economsche crss en de voedselcrss. In NCR-Rabobank Symposum. Utrecht- The Netherlands (21-Aprl-2009): Charman of Nederland Cooperate Raad (NCR) and board charman of Royal Cosun Van Djk, G. and Klep, L. (2005). Als 'de market' faalt ( Inledng tot cooperate) Den Haag: Sdu Utgevers bv. Wlson, P. W. (2008). FEAR1.12: A Software Package for Fronter Effcency Analyss wth R. Soco-Economc Plannng Scences. Copyrght Paul W. Wlson (2009). Zwanenberg, A., Dauchy, D., Keane, M. and Hamsvoort., V. d. (1993). The complcatons of Fnancng Dary Cooperatves. In EAAE- semnar, Fnancng of the European Agrculture. Wagenngen- The Netherlands. 9

11 Appendx A: The Results of the 10 Largest CFs and IOFs Tradtonal Models 1-3 Hyperbolc Model 4 Hyperbolc Model 5 Name TE SE AE TE SE TE SE Coop ARLA FOODS AMBA KONINKLIJKE FRIESLAND FOODS N.V. 3 ZUIVELCOÖPERATIE CAMPINA U.A. NORDMILCH EG GLANBIA PUBLIC LIMITED COMPANY CANDIA (CEDILAC) BELGOMILK A SA SODIAAL INTERNATIONAL DRENTS OVERIJSSELSE COÖPERATIE KAAS BA. IOF COGESAL MIKO DANONE SA SAS ENTREMONT ALLIANCE NESTLE PRODUITS LAITIERS FRAIS S,A, CORMAN GOLDSTEIG KÄSEREIEN BAYERNWALD GMBH SA INGREDIA GLACES THIRIET SAS LAITERIE DU VAL D'ANCENIS MOLKEREI - LAITERIE WALHORN It s owned 100 percent by the cooperatve Fresland. 10