What Impact Are EU Supermarket Standards Having on Developing Countries Export of High-Value Horticultural Products? Evidence from Kenya

Transcription

1 What Impact Are EU Supermarket Standards Havng on Developng Countres Export of Hgh-Value Hortcultural Products? Evdence from Kenya Solomon Asfaw, Dagmar Mthöfer, Hermann Wabel Unversty of Hanover, Germany Contrbuted Paper prepared for presentaton at the 105 th EAAE Semnar Internatonal Marketng and Internatonal Trade of Qualty Food Products, Bologna, Italy, March 8-10, 2007 Copyrght 2007 by Solomon Asfaw, Dagmar Mthöfer and Hermann Wabel. 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 What Impact Are EU Supermarket Standards Havng on Developng Countres Export of Hgh-Value Hortcultural Products? Evdence from Kenya Solomon Asfaw 1, Dagmar Mthöfer 2, Hermann Wabel 3 1, 3 Lebnz Unversty of Hanover, Germany, 2 Internatonal Centre of Insect Physology and Ecology (ICIPE), Kenya. solomon@fgb.un-hannover.de Summary European Unon (EU) retalers are settng global benchmarks for the producton of fresh food, and are askng ther supplers for produce to be certfed accordng to food safety and qualty standards. Complance to these standards for developng countres small-scale producers ental costly nvestment n varable nputs and long term structures. Lmted emprcal evdence exsts ether to refute or confrm the concern that the prolferaton and enhanced strngency of these standards margnalze smallholders from global market. Ths artcle therefore explores the costs of complance, factors explanng the smallholder decson to adopt EU prvate qualty standard and the mpacts of the standard on farm fnancal performance. We develop a two-stage standard treatment effect model to account for self-selecton as a source of endogenety. Analyss s based on a random cross secton sample of 439 small-scale export vegetable producers n Kenya whose producton was montored n 2005/2006. We demonstrate that adopters and non-adopters are dstngushable by ther asset holdng and household wealth, access to servces, labor endowment and level of educaton. Once we control for endogenety problem, we found that small-scale producers can beneft substantally from adoptng the standard at the farm level. KEY WORDS: Kenya, export vegetables, adopton, EurepGAP standard, mpact assessment 1. Introducton One way that Kenya and other sub-saharan Afrcan countres have attempted to reduce poverty and acheve hgher rates of growth s by dversfyng ther export portfolo away from prmary commodtes nto non-tradtonal exports wth more auspcous market trends (Harrs et al., 2001). Partcpaton n nternatonal trade s generally recognzed to favor economc growth and especally agrcultural exports would promote development n lowncome countres due to the lnk wth the rural economy (Aksoy, 2005). Extensve household surveys have shown that smallholders partcpatng n export vegetables, whether as producers or the workforce employed n the sector, are better off than nonexport smallholders, wth average annual household ncomes beng almost fve tmes hgher (McCulloch and Ota, 2002; and Humphrey et al., 2004). However, there s a concern that the prolferaton and enhanced strngency of food-safety standards that are mposed by hgh-ncome countres can negatvely affect the compettveness of producers n developng countres n partcular smallholders and mpede actors from these countres from enterng hgh-value food markets (Auger et al., 2005). An alternatve and less pessmstc vew emphasze that complance wth food-safety standards can be a catalyst for upgradng and modernzaton of developng country s food supply systems (Jaffee and Henson, 2004; Maertens and Swnnen, 2006). 85

3 The challenge especally for small-scale producers s the fact that hortcultural export s becomng ncreasngly compettve and sophstcated. Consumers requre hgh qualty produce and ths has to be traced back to the producer to ensure strct adherence to total qualty management (Jenson, 2004). The smallholders ablty to mantan and strengthen ther role n hortcultural exports wll depend on ther capacty to adapt to these changes and comply fully wth the emergng standards. Complance to these standards entals costly nvestments n such as varable nputs (n partcular, the swtch to approved pestcdes) and long-term structures (e.g., gradng shed, charcoal cooler, dsposal pt, tolet, and pestcde store). These nvestments are lumpy n nature and mostly specfc to the fresh export vegetable busness. The general vew n the lterature s that smallholders, especally the poorest ones, are ncreasngly beng squeezed out from hgh-standards export producton (Barrett et al., 1999; Dolan and Hamphrey, 2000; Farna and Reardon, 2000; Reardon et al., 2003; Weatherpoon and Reardon, 2003; Jeffee, 2003; Jensen, 2004; Okello, 2005). Partcpaton of small-scale producers n hgh-standards export producton s a necessary but not a suffcent condton for an enhanced welfare effect of hgh-standards agrcultural trade (Maertens, 2006). Faced wth hgh cost of complance and complexty of the standard, farmers examne the perceved beneft vs-à-vs the expected cost before makng a decson to adopt the standard. Theoretcally, complyng wth food-safety standards provdes a broad spectrum of potental drect and ndrect benefts to the farmers. Small-scale producers complyng wth the standard are expected to have hgh productvty and good qualty produce whch reduce the level of rejecton by the buyers and ncrease the return. The health and envronmental mpacts stemmng from changes n pestcde use and hygene practces assocated wth adopton are another mportant beneft. Adopters are expected to have better market access and stable ncome over tme compared to the non-adopters and n addton spll-over effects to domestc producton could beneft the domestc consumers (Henson and Jaffee, 2004). Much research addressed mpacts of standards on developng countres at a polcy level (Henson and Loader, 2001; Beghn and Burea, 2001; Jaffee et al., 2005; Henson and Jaffee, 2005; Alou and Kenny, 2005; Manarungsan et al., 2005), however less attenton has focused at the level of small-scale producers. The few exceptons, to the best of our knowledge, are the study by Okello (2005), who nvestgated on complance wth nternatonal food-safety standards for Kenyan green beans producers on case study bass. He found that resource poor farmers are lkely to be margnalzed by nternatonal foodsafety standards. However, they can overcome the captal barrer by bandng together nto cooperatve groups and then jontly nvestng n costly facltes. The study by Maertens (2006) and Mnten et al. (2006) focused on Senegal and Madagascar export vegetable ndustry respectvely and found a postve mpact of hgh standard export contract on smallholder welfare, ncome stablty and shorter lean perods. In ths paper we undertake an emprcal study of the mpact of complyng wth a most wdely known EU prvate food-safety standard on small-scale producers n Kenya. We addresses three man objectves: (1) to nvestgate the nature, magntude and sgnfcance of cost of complance wth EU prvate standards, (2) to examne factors explanng the smallholder decson to adopt EU prvate standard and (3) to estmate the mpacts of standard on farm fnancal performance. The organzaton of the rest of the paper s as follows. Secton 2 s devoted to a revew of trend n Kenyan hortcultural ndustry and the evolvng EU food-safety standards. The methodology and emprcal model s presented n secton 3. Secton 4 presents and dscusses the emprcal fndngs and secton 5 reports the conclusons and polcy mplcatons of the study. 86

4 2. Kenyan Fresh Export Producton 2.1. Overvew of the Hortcultural Sector Compared to many Afrcan countres, the hortcultural export ndustry of Kenya s now by far the largest exporter of vegetables to the EU and has been for about a decade the country s second most mportant foregn exchange earner n the agrcultural sector, after tea (Jaffe et al., 2005). The major export vegetable crops are green beans, peas and Asan vegetables (such as karella, chlles, aubergnes and okra) wth beans and peas mostly beng exported to the EU. The man flowers exported nclude roses, carnatons, statce and a varety of summer flowers (voor den Dog, 2003). The vast majorty of ths produce (89.4%) s destned for Europe, wth the UK market absorbng the major share 71% n Kenya also exports Asan vegetables to the Mddle East market (Harrs et al., 2001). There are varous players actve n the export market channels of fresh fruts and vegetables n Kenya. Small-scale producers often operate as ndvduals or as a member of out-grower schemes. Fgure 1 shows the hgh-value vegetable supply chan to llustrate the dfferent choces the actors have n sellng ther produce. Fgure 1 Here The strength of the hortculture export sector can be attrbuted to several factors. Frst, Narob s locaton as a centre of ar transport between Europe and the East and Southern Afrcan regon, and Kenya s role as a major tourst destnaton, ensure that there s suffcent northbound ar cargo to transport exports. Second, preferental treatment under the Lomé Conventon between Afrcan Carbbean Pacfc (APC) countres and the EU provdes concessonary access for Kenyan flowers and vegetables to the European market. Thrd, the sustaned demand for hortcultural products as a result of hgh and growng ncomes n Europe provdes a stable and growng market for Kenyan producers. Fourth, close co-operaton wth the supermarket chans n Europe and a smooth adaptaton to the new crtera defned n the varous labels by supermarkets and other market sources. Fnally, the presence of ample local and nternatonal nvestors, partcularly n the cutflower busness, provdes Kenya wth an added advantage (Markandya et al., 1999; voor den Dog, 2003) Role of Small-scale Producers The fgures on the number of small-scale farmers nvolved n export fresh frut and vegetable producton n Kenya vary dependng on the source and year of estmaton. Estmates from the early 1990s suggest that smallholders suppled over half of the export frut and vegetable producton (Kmenye, 1993; Jaffee, 1995). More recently, the Hortcultural Crops Development Authorty (HCDA) estmated that 40% of exported frut and 70% of exported vegetables are produced by smallholders (Harrs et al., 2001). Accordng to ntervews wth four leadng exporters, Dolan and Humphrey (2000) conclude that just 18% of vegetables for export come from smallholders. They further make the case that smallholders are beng squeezed out of export producton because of the dffculty of ensurng complance wth food safety and qualty requrements mposed by supermarkets and other buyers. They argue that these requrements are leadng exporters to grow ther own produce or purchase from large-scale commercal farms. On the other hand, exporters may wsh to under-report the share of ther producton that comes from smallholders to satsfy European buyers who are suspcous of smallholder qualty control (Harrs et al., 2001). Jaffee (2003) ntervewed several exporters and estmates that smallholders account for 27% of exported fresh vegetables and 85% of exported fresh frut, for an average of 47% of fresh frut and vegetable exports. A recent revew and update estmated the current number at about 12,000 smallholders producng for the vegetable export market n nne dstrcts of Kenya (Mthöfer et al., 2006). Prevous estmates range from 13-16,000 (Jaffee, 87

5 1995) to 80,000 smallholders producng vegetables and fruts for the export market (Karuga and Masbay, 2004) One of the dffcultes n estmatng the number of partcpatng smallholders s the defnton of the same. Wth an excepton of Mthöfer et al. (2006), n most of these estmate small-scale producers are defned as farmers wth less than 10 acres of land whle medum-scale and large-scale producers are farmers wth between 10 to 20 and larger than 20 acres respectvely (Harrs et al., 2001). Ths defnton was re-dscussed wth experts from Kenya, and majorty of the experts concluded that ths defnton does not reflect the realty on the ground. The experts nstead defned small-scale hortcultural producers as farmers wth less than 5 acres of land under hortculture, whereas farmers wth 5 to 10 acres of land and greater than 10 acres under hortcultural producton as medum- and large-scale producers, respectvely. Ths s the defnton appled throughout the paper European Prvate Food-safety Standards European consumers are ncreasngly concerned about possble health consequences of pestcde resdues. Even consumers who are not part of the growng organc food movement are ncreasngly wary of agrcultural chemcals (Dolan et al., 1999). In 1990, the U.K passed the Food Safety Act whch oblged food retalers to demonstrate due dlgence to ensure that the food they sell s safe and the resultant supermarkets developed codes of practce. In practce, ths means that supermarkets have become much more nvolved n mposng requrements on how food s produced throughout the commodty supply chan, even to the degree of montorng and controllng hortcultural producton n developng countres (Dolan et al., 1999). These changes were ntally amed at addressng the problem of mcrobal contamnants n food. They later evolved to cover three broad areas: ) pestcde resdue standards, ncludng pestcde usage, handlng, and storage as well as dsposal of pestcde contaners and leftover pestcdes, ) hygene standards, ncludng santaton of gradng and storage facltes and general personal hygene, and ) traceablty requrements, ncludng documentaton of producton actvtes, especally pestcde usage, plantng and sprayng dates, and labelng of graded produce (Jaffee et al., 2005). Many of the ndvdual qualty and food-safety standards of retalers n EU have been harmonzed, wth two promnent common standards beng the Brtsh Retal Consortum (BRC) standard and European Retaler Produce Workng Group for Good Agrcultural Practces (EurepGAP). Companes supplyng branded fresh and processed food products use BRC, whch has been n operaton snce 1996 and t covers basc safety and qualty requrements, ncludng HACCP (Hazard Analyss Crtcal Control Pont). EurepGAP s the most wdely known example of a common EU prvate standard. It s a model of on-farm assurance that s beng promoted to growers of fresh food as a mandatory standard and t s regarded as a condton of entry to EU markets and s unlkely to provde prce premum. The EurepGAP gudelnes reflect a harmonzaton of the exstng safety, qualty, and envronmental gudelnes of the major European retalers, and are a response to ncreasng consumer nterest n food-safety and envronmental ssues (EurepGAP 2003). The detaled producton protocols were frst developed for frut and vegetables and now also cover flowers and grans. EurepGAP has a growng membershp of retalers, ncludng leadng food retalers such as Sansbury s, Tesco, Safeway, Coop Itala, Belgan Wholesale Markets, Watrose and Kesko. It hopes to become the global player n agrcultural producton standards and verfcaton frameworks. The man focus s food-safety, but the protocols also addresses a number of ssues concernng the envronment (sol, water, and wldlfe conservaton), occupatonal health and safety, complant procedures and nternal audts (EurepGAP 2003). EurepGAP offers four optons to producers who seek to obtan certfcaton under the standard. Under Opton 1, an ndvdual farmer apples for certfcaton. The farmer must 88

6 carry out an nternal self-nspecton and undergo an external nspecton by a certfcaton body, whch s a certfcaton enterprse accredted by EurepGAP. Under Opton 2, a group of farmers apples for a group certfcate. Farmers must establsh an nternal management and control system, perform ndvdual self nspectons and group nternal nspectons before recevng an external verfcaton by a certfcaton body. Under Optons 3 and 4, ndvdual farmers or farmer groups that have already mplemented another standard can apply for a EurepGAP benchmarked scheme certfcate,.e. EurepGAP recognzes the exstng standards scheme as beng equvalent to the EurepGAP standard (EurepGAP 2003). 3. The Theoretcal Framework Adopton and dffuson of nnovatons theory (Davd, 1969; Rogers, 1995; Sundng and Zlberman, 2001) has been wdely used to dentfy factor that nfluence an ndvdual s decson to adopt or reject an nnovaton. An nnovaton s defned as an dea, practce or object that s perceved as new by ndvdual or other unt of adopton. The perceved newness of the dea for the ndvdual determnes hs or her reacton to t (Rogers, 1995). Rogers dentfes fve characterstcs of an nnovaton that affect an ndvdual s adopton decson. These are (1) relatve advantage, whch s the degree to whch an nnovaton s perceved as beng better than the dea t supersedes; (2) compatblty, or to the degree to whch an nnovaton s perceved as consstent wth the exstng values and belefs, past experences and the needs of potental adopters; (3) complexty, whch s the degree to whch an nnovaton s perceved as relatvely dffcult to understand and use; (4) tralablty, or the degree to whch an nnovaton may be used expermentally on a lmted bass; and (5) observablty, whch s the degree to whch the results of an nnovaton are vsble to others. The relatve advantage and observablty of an nnovaton descrbe the mmedate and long-term economc benefts from usng t whereas compatblty, complexty, and tralablty ndcate the ease wth whch a potental adopter can learn about and use an nnovaton (Rogers, 1995). For the purpose of ths study, EurepGAP food safety standard s consdered as an nnovaton. The adopton and certfcaton of ths standard cannot be seen as a sngle event that takes places on a farm. It rather must be descrbed as a process over tme wth dfferent stages from the frst knowledge of the standard untl ts mplementaton. The process of complance can be descrbed as a process, whch conssts of at least three stages: 1) nformaton, 2) decson and 3) mplementaton. At the frst stage, the nformaton stage, the producer obtans nformaton and knowledge on the standard. He or she becomes aware of the exstence of the standard and gans knowledge on how the standard works. The nformaton stage s essental to pass to the subsequent steps of the complance process, as certan knowledge on the standard s necessary to form an atttude toward the standard and to make a decson. It s vtal to emphasze the crtcal mportance of ths stage n developng countres lke Kenya. In such countres the largest number of producers faces great dffcultes n accessng nformaton, due to lmtatons ncludng the lack of formal educaton and poor nfrastructure. These lmtatons create obstacles to nformaton access. At the second stage, the decson stage, the producer makes a decson on the mplementaton of the standard. Once the decson to mplement the standard s made, the producer enters the mplementaton stage. The mplementaton stage conssts of the actual adopton of the standard and the ntroducton of the standard s requrements on the farm. The manner n whch agrcultural households respond to nterventons s a crtcal factor n determnng the relatve merts or demerts of alternatve opton. In economc theory, the problem of producton, consumpton and labour supply decsons are usually analysed separately through the behavour of the three classes of agents (Sadoulet and de Janvry, 1995). The frst one s producers who maxmze net revenue wth respect to levels of products and factors, subject to constrants determned by market forces and technology, 89

7 secondly consumers who try to maxmze utlty wth respect to the quanttes of goods consumed, subject to constrants determned by market forces, ncome, household characterstcs and tastes and thrdly the workers who try to maxmze utlty wth respect to ncome and lesure subject to constrants determned by the market wages and total tme avalable and worker characterstcs. The agrcultural household model recognzes that the household decson maker s often engaged smultaneously n producton, consumpton and work decsons. The household has a dual role of producer and consumer, and makes producton, labour allocaton, and consumpton decsons that may be nterdependent of one another dependng on market forces. By consumng all or part of ts own output, whch could alternatvely be sold at a gven market prce, the household mplctly purchases goods from tself. By demandng lesure or allocatng ts tme to household producton actvtes, t mplctly buys tme, valued at the market wage, from tself (Sngh et al., 1986). Ths household behavour has necesstated the ntegraton of the three decson problems nto a sngle household problem. The basc structure of the agrcultural household model (Sngh et al., 1986) also known as the household farm model s based on the assumpton that for any producton cycle, the household maxmzes a utlty functon: U = u( cm, rm, l; Tu ) (1) c We assume that households derve utlty from consumpton of on-farm goods ( m ), market goods ( r l m ), lesure (home tme) ( ) and vector of other factors that shft the utlty T functon ( u ). The household maxmzes utlty subject to a set of constrants, namely cash ncome constrants, (equaton 2), tme constrants (equaton 3) and technology constrant (equaton 4). N N [ p Q c m ) w x + E ] [ p m rm ] = 1 D ( (2) m = 1 l l (G ) (3) + a ( la ( G ), x ( G ), G ; Z u Q Q ) (4) Where Q and p, denote the quantty and prce of farm output respectvely; w and x m represent the prce and a vector of nputs used for farm producton actvtes respectvely, D and l a are total household labor endowment and labor devoted to own farm actvtes, respectvely; Z u denotes a vector of exogenous farm and communty level characterstcs that shft the producton functon whereas E and G represent unearned ncome and adopton of EurepGAP code of practces, respectvely. As ts mentoned n the prevous chapters, ts consdered that the adopton EurepGAP code of practces wll ncrease complexty and reduce flexblty that translate nto ncreased labor allocated for farm producton actvtes. In ths case, the amount of labor devoted to own farm actvtes l a and possbly the use of other farm nputs x are a functon of G, the adopton of EurepGAP standard. A technology-constraned measure of household ncome s obtaned by substtutng Equaton (4) nto Equaton (2) (Huffman, 1991; Fernandez-Cornejo et al., 2005). 90

8 N N [ p ( Q ( la ( G ), x ( G ), G ; Z u ) c m ) w x + E ] [ p m rm ] = 1 m = 1 (5) The Lagrangan technque s used to solve the household utlty maxmzaton problem. The Lagrangan soluton to the household constraned maxmzaton problems yelds a system of frst order condtons, whch consttute the structural form of the model. The structural form of the model can then be solved for the reduced form of the model that gves the endogenous varables as a functon of exogenous varables. The frst-order condtons for optmalty can be obtaned by maxmzng the Lagrangan expresson L over a set of choce varables. L w = U ( c N = 1 m, r m, l ; T x ( G ) + E u ) + λ N m = 1 p m r m N = 1 [ p { Q ( l ( G ), x ( G ), G ; Z )} c ] + µ ( a ( D l l ( G ) ) (6) The EurepGAP adopton decson may be obtaned from the followng Kuhn-Tucker condtons: L = λ P ( Q / l ) µ = (7) l a [ ] 0 a [ p (( Q / l )( l / Q )' + ( Q / x )( x / Q )' + Q / G ) L = λ G a a w( x / G )'] µ ( l / G )' = 0 L x = a [ p ( Q / x ) w] = 0 λ (9) L = U = 0 c p c λ (10) m L = U = 0 r p r λ m (11) m L = U = 0 l µ l (12) where U c, U r and U l are the partal dervatves of the functon U. We assume the producton functon s concave and that G and l a 0. The EurepGAP adopton decson condton s obtaned from the optmalty condtons, Equaton (8) and Equaton (7) and Equaton (11), nothng that the expresson n brackets n Equaton (8) s the total dervatve dq / dg. Thus we obtan p ( dq / dg ) w ( dx / dg )' ( µ / λ )( dl a / dg )' = 0 (13) But from Equaton (11) and Equaton (12), µ λ = p ( U / U ), then / m l r p ( dq / dg ) w ( dx / dg )' ( p ( U / U )( dl / dg )' = 0 (14) The left-hand sde of ths expresson may be nterpreted as the margnal beneft of adopton of EurepGAP, p ( dq / dg) mnus the margnal cost of adopton, whch ncludes the m l r a a (8) u m 91

9 margnal cost of the producton nputs, w( dx / dg)', and the margnal cost of labor ( pm ( U l / U r )( dla / dg)', brought about by adopton of EurepGAP. It wll not be optmal to adopt f the margnal beneft of adopton falls short of the margnal cost of adopton. 4. Emprcal Model And Data Followng Greene (1997) and Fernandez-Cornejo et al. (2005), a two-stage standard emprcal model s developed to account for self-selecton as a source of endogenety. The frst stage conssts of the adopton decson model for dentfyng determnants of EurepGAP adopton and the second stage s the mpact model that provdes estmates of the mpact of adoptng EurepGAP protocol on household ncome. 4.1 The Adopton Decson Model Equaton (14), mpled by the Kuhn-Tucker condtons, s the central for the EurepGAP adopton decson. Consderng a frst-order approxmaton and addng a dsturbance terms, the adopton decson can be emprcally represented by: G = β Χ + u (15) where, Χ are non-stochastc vectors of observed farm and non-farm characterstcs and u s random dsturbances assocated wth the adopton of the new technology. Assumng that the dsturbances are ndependently and dentcally normally dstrbuted, the probt transformaton can be used to model the adopton decson. The probt model assumes that the error term of the model follows a normal dstrbuton between and the value β X such that the area under the curve represents the probablty that EurepGAP protocol s adopted. Hence, the larger the area under the curve, the hgher s the probablty of adopton. The functonal form of for a probt model F (cumulatve dstrbuton functon) may be defned as follows: β X 2 1 t F ( β X ) = exp( ) dt (16) 2 2 π The parameters of the probt model were estmated by maxmzng the lkelhood functon K n equaton (17). The lkelhood functon s specfed as the product of the probabltes of adoptng D and not adoptng ( 1 D ) and ts log s maxmzed wth the respect to the unknown parameter. K = G (1 G ) (17) G = 1 = 0 G 4.2 The Impact Model An econometrc mpact model s specfed, whch statstcally controls for factors consdered relevant, and for whch there are data, by holdng them constant, so that the effect of adopton can be estmated. The model developed takes nto consderaton that unobservable factors may cause farmers complyng wth food-safety standards to earn hgher ncomes than non-complant farmers, resultng n an overestmaton of the adopton effect and use nstrumental varable technques to purge the dependence of adopton. The predcted probablty of adopton, obtaned from the adopton decson model, s used as an nstrument for estmatng the effect of adoptng EurepGAP n the mpact model. 92

10 Unlke the tradtonal selectvty model n whch the effects are calculated usng the subsamples of adopters and non-adopters separately, the mpact model uses all the observatons and s known as a standard treatment effects model, used by Fernandez- Cornejo et al. (2005). In ths model the observed ndcator varable, G, ndcates the presence or absence of some treatment, whch n ths case adopton of EurepGAP standard (Greene, 1997). Formally, gven the unobserved or latent varable and ts observed counterpart, the treatment-effect equaton, whch s the bass for our mpact model can be expressed as: * G = β X + u (18) Y = α V + γ G + e (19) * G = 1f, G > 0, otherwse ; G = 0 (20) * G s the unobservable or latent varable for EurepGAP adopton, G s ts observable counterpart (dummy for adopton of EurepGAP), Y s a vector denotng the farm netncome 1, V s a matrx of exogenous varables thought to affect farm fnancal performance and X are non-stochastc vectors of observed farm and non-farm characterstcs determnng adopton. e and u s random dsturbances assocated wth the mpact model and the adopton of EurepGAP. Note that we cannot smply estmate (2) because the decson to adopt may be determned by unobservable varables that may also affect ncome. If ths s the case, the error terms n (1) and (2) wll be correlated, leadng to based estmates of γ, the mpact of adoptng EurepGAP. We can correct for the selecton bas by assumng a jont normal error dstrbuton, and usng a two-step procedure. In the frst step we use a probt model to estmate adopton. Usng the probt results, we compute the nverse Mll s rato for each observaton. In the second step, we lnearly regress ncome on the explanatory varables and the nverse Mll s rato (Greene, 1997). The reduced form of the frst stage adopton model s ADOPTION = f [(household characterstcs (AGEH, GEND, EDU1, EDU2, FEMA, CHIL), asset holdng and household wealth (LIVE, LAND, FERT, FACI, MACH), communcaton behavor (RADI, TVUS, TRAI, MOBI, EXTE) and access to servces (CRED, CONT, GROU, DIST, IRRI, EXPO, OFFF)] Where the dependent varable adopton of EurepGAP standard (ADOPTION) equals one, f the household has commenced to comply wth EurepGAP code of practces durng 2005 croppng season, and zero otherwse. It s generally assumed that the household s am to maxmze ts expected utlty subject to varous constrants determnes the decson to adopt an nnovaton. Based on ths assumpton, the followng observable factors are hypotheszed to affect the adopton decson. Frst, the household s endowment wth famly labor s expected to postvely affect the probablty of adopton, gven the labor-ntensve nature of export vegetable producton. Labor varable n the model nclude the number of adult females (FEMA) and chldren 1 Net-ncome s computed as total revenue from all export vegetables mnus all varable cost ncludng famly labor per croppng season. The value of famly labor was approxmated by the exstng wage rate n the nearest vllage. 93

11 under 15 years of age (CHIL). The age of household head (AGEH) and hs or her educatonal attanment (EDU1) as well as that of other household members (EDU2) capture dfferences n the qualty of management. We expect educaton of household head and members to postvely nfluence EurepGAP adopton although the drecton of the age effect mght be ambguous. Age s usually taken as a proxy for experence and s expected to have a postve mpact on adopton of an nnovaton. However, t s argued that there s a certan threshold of age beyond whch the ablty of farmers to take rsk and adopt nnovatons decreases. Ths means that young farmers are more lkely to face the rsks assocated wth nnovatons, e.g. uncertanty n return and unfamlarty of the technology and to adopt them than ther old counterparts. Also, the drecton of the gender (GEND) effect s not clear a pror. Farm resource endowment varables such as the value of lvestock (LIVE), value of farm machnery (MACH) and faclty ndex (FACI 2 ) are expected to have a postve mpact on adopton of EurepGAP snce these varables are a good proxy for measurng the capacty of households to nvest n new nfrastructure necessary for the complance and take rsks. The coeffcent of land sze (LAND) can take ether sgn dependng on alternatve form of land use, thus representng opportunty cost of land. Communcaton and nformaton related varables nclude level of agrcultural tranng (TRAI), total hours spent on lstenng to rado per week (RADI), total hours spent on watchng televson per week (TVUS), access to moble phone (MOBI) and dstance to extenson servce (EXTE). We expect these varables to enhance the ablty of farmers to quckly acqure, synthesze and respond to changes, thereby ncreasng the probablty of adopton of EurepGAP adopton. Access related varables cover access to credt (CRED), access to formal contract (CONT), duraton of group membershp (GROU), use of rrgaton (IRRI), partcpaton n off-farm actvtes (OFFF), dstance to nput seller (DIST) and number of years the household has been producng export vegetables (EXPO). Smallholders n Kenya can hardly afford to make the necessary nvestment to comply wth EurepGAP code of practces ndvdually and hence seek to get a certfcate under Opton 2, whch requres farmers to organze themselves n a group. Thus, the stronger and more cohesve the group s, the hgher the probablty to acqure and analyze nformaton and to mplement the protocol. For the second stage, the mpact model, household net-ncome from export vegetables s taken as a dependent varable. The prmary nterest s to analyze whether EurepGAP has an effect on the ncome of the households. Descrpton and descrptve summary of the explanatory varables used n the model are presented n Table 1 below. Table 1 Here 4.3. Data Source and Sample To generate the emprcal bass for answerng the research questons, data collecton was conducted at vegetable grower level. A mult-stage samplng procedure was used to select dstrcts, sub-locatons and small-scale vegetable producers, respectvely. The frst stage was to select fve dstrcts purposvely from two major vegetable producng provnces (namely Nyer, Krnyaga, and Murang'a Dstrcts n Central Provnce and Meru Central 2 Faclty ndex: D ht = ΣD h (1-P ) P = n /n where G h = 1 f household h has access to faclty ; the facltes are havng cemented floor, number of rooms, access to ppe water, and beng less than 100 meter from water source; P s the probablty of havng faclty ; n = number of households whch have a faclty ; and n = total number of households. (McCulloch and Ota, 2002) Durable goods ndex: G h = ΣG h (1-P ) P = n /n where G h = 1 f household h possesses durable ; P s the probablty of havng durable good ; n = number o households whch have durable ; and n = total number of households. The tems used to compute the ndex are refrgerator, sofa set, swng machne, rado, televson, bcycle, motorcycle and car. (McCulloch and Ota, 2002) 94

12 and Makuen Dstrcts n Eastern Provnce) based on the ntensty of export vegetable producton, agro-ecology, types of crop produced and accessblty. These dstrcts represent the major export vegetable producng areas, whch accordng to the current update on the number of smallholders producng for the vegetable export market (Mthöfer et al., 2006), cover approxmately half of the share of all smallholder vegetable export producers. Overall, 21 sub-locatons 3 were randomly selected from the fve dstrcts based on proportonal to export vegetable producers sze. Lsts of all smallholders n export producton, whch were compled for that update at the sub-locaton level (Mthöfer et al., 2006), served as a samplng frame for ths study. A total of 439 export vegetables producer households were selected randomly for the ntervew. Data collecton took place durng the 2005/2006 croppng season. The survey was conducted through sngle vsts (re-call survey) and season-long montorng of household producton practces. The data were collected by traned enumerators supervsed by the researcher usng structured questonnares, whch covered a broad range of soco-economc aspects of the rural lfe from household composton and asset poston to agrcultural producton and nput use. The re-call survey questonnare covered specfc nformaton on the characterstcs of household members, household ncome (both farm and off-farm), household assets such as land sze, lvestock ownershp, farm machnery and household equpments and access to dfferent servces lke credt, rrgaton, formal contract and group membershp. The respondents were also asked a host of questons related to costs and benefts assocated wth complance wth EurepGAP standard. The season-long montorng survey questonnare prmarly focused on nputs and outputs related to export vegetable producton. Besdes personal ntervews, a seres of formal and nformal farmer group dscussons have been conducted to understand the export supply chan and to get more nformaton on the ntangble benefts of complance wth the standard. 5. Results The data analyss s performed n two steps. Frst a descrpton of the socoeconomc characterstcs of the sample of export vegetable producers comparng adopters and nonadopters s presented. Secondly, the results of the regresson are dscussed Descrptve Statstcs As presented n Table 1 the average age of the farm households n the research area s 45.7 years. The majorty of the sampled households are male headed (85%) and on average the household sze measured n adult equvalents s The average number of female household members of the sample s 2.8 whereas adult members between years and chldren less than 14 years make 3.6 and 1.7, respectvely. The hghest grade attaned by household head s 8.6 and other adult household members except the head 9.6. The average farm sze and number of plots owned by households are 3.01 acres and 2.04, respectvely and 95% of the total land area owned by the respondents s perceved as fertle land. The average number of tropcal lvestock unts owned s 2.06 and ts equvalent monetary value s estmated at 20,884 KSh. The average durable goods ndex and faclty ndex s 0.86 and 1.21, respectvely. Fourteen percent of the respondents partcpate n off-farm actvtes, 73% have access to readng prnted materals, 87% have access to moble phone, 95% have access to rrgaton water, 34% have adopted EurepGAP protocol and only 17% are EurepGAP certfed. The average gross annual ncome from export vegetables amounts to 3 Sub-locaton s the lowest admnstratve unt n Kenya 95

13 33,864 KSh. On average the sample households spent 8.2 hours per week watchng ther own or neghbors televson and 27.3 hours per week lstng a rado. Majorty of the sampled households are grower group member wth the average years of group membershp 2.04 and partcpaton n export producton busness 4.33 years. Ch-square and t-test procedures are used for some selected varables as a startng pont to compare EurepGAP adopter categores and results are presented n Table 2 and 3. From Table 2 the access and communcaton related varables such as partcpaton n off-farm actvtes, access to credt servce, partcpaton n agrcultural tranng, use of televson, readng prnted materals, access to moble phone, group member and opnon leadershp are statstcally sgnfcant below the 0.1 level of probablty. However, there s no sgnfcant dfference between the two-adopter categores n terms of use of rrgaton water. The result depcts that adopters of EurepGAP have hgher levels of access to credt, tranng, readng prnted materals and use of televson than the non-adopters. The adopters also consder themselves as opnon leaders, have hgher levels of access to moble phones and are to a hgher share a member of grower groups than ther counterparts. Those who are a member of a group are 96% EurepGAP adopters and 67% non-adopters whle 32% of the adopters and 17% of the non-adopters have access to credt servces. Those who had partcpated n agrcultural tranng are 58% adopters and 43% non-adopters whereas 63% adopters and 47% non-adopters consder themselves as opnon leaders. Those who use televson are 64% adopters and 44% non-adopters whle 94% of adopters and 84% of the non-adopters have access to moble phone. Table 2 Here From Table 3 the wealth related varables such as land sze, tropcal lvestock unts owned, durable goods ndex, faclty ndex, number of farm machnery owned, and the household characterstcs varables such as educaton level of the head and other adult household members, dependency rato, chldren below 14 years of age and adults between years of age are statstcally sgnfcant dfferent below 0.1 level of probablty between the two groups. Moreover, access and communcaton related varables such as access to moble phone use, televson use, duraton of group membershp, number of major tranng subjects and amount of credt used dffer sgnfcantly below 0.1 level of probablty. However, there s no sgnfcant dfference between the two groups n terms of some household characterstcs varables such as age, number of female household members and household sze. Table 3 Here The results suggest that EurepGAP adopters have hgher level of household members educaton, larger land sze, more lvestock, hgher number of farm machnery, hgher level of durable good and faclty ndexes than the non-adopters. The level of partcpaton n grower groups member, amount of credt receved, level of tranng, ntensty of televson use and duraton of moble use are also sgnfcantly hgher for EurepGAP adopters compared to ther counterpart. As shown n the Table 3, actual mean household net-ncome from export vegetables s also sgnfcantly hgher for EurepGAP adopters than for nonadopters Costs and Benefts of EurepGAP Complance Implementaton of EurepGAP necesstates changes of producton practces and/ or nvestment n nfrastructure. Ths mposes substantal costs on smallholder export farmers. These costs are a major hurdle that has to be overcome especally for small-scale producers n order to acheve the certfcate. Our survey estmates approxmately 37,000KSh per group member to mplement EurepGAP and acheve the certfcate, whch s approxmately 30% of the total annual crop ncome of the adopters. The man costs (30300 KSh) are for the buldngs and facltes that farmers must establsh as a pre-condton of mplementng the standard. These two cost elements comprse represent the nonrecurrng costs: a one- 96

14 tme nvestment to set up the mplementaton. The other 18% (6,700) are the recurrng costs of complance (protectve clothng, record keepng, salary for the grader etc). The costs for external audtng, certfcaton, tranng and sol analyss are not ncluded n the cost calculatons snce they have so far been met by others, e.g. NGO s and exporter companes. Unlke large-scale farms who can purchase all of the requred equpment and facltes wthn sx or seven months (a maxmum of one year), small-scale farms cannot afford these costs all at once and hence they tend to prepare for the requrement n two or three years. Indeed many of the smaller producers who decde to adopt the protocol are forced to rely on loans and external support even though some rely on ther own fnancal resources. Ths result s also supported by Mausch (2007) fndngs where he found that contracted largescale farm reaches ts break-even pont after a year whle the contracted smallholder farm needs more than two years to break even. Beyond the costs, Fgure 2 hghlghts a number of wder benefts from complance wth EurepGAP perceved by the farmers. Smallholder growers who adopted the protocol apprecated hghly to be part of a group gong through the EurepGAP complance process. They were assured of markets wth buyers who offered the best prce as well as tmely payment. Many also perceved that mplementaton of EurepGAP at the farm level ncreased qualty of producton and reduced the amount of reject by the buyer. Under EurepGAP, agrochemcals are stored and handled by traned ndvduals and many growers felt that ther health s better protected. Lkewse the nstallaton of dsposal pts for the waste generated on the farm, clean tolets, baths and hand-washng facltes had clearly brought better hygenc condtons at the farm. Growers complyng wth EurepGAP are proud of the neatness of ther farms compared to before complance. Another perceved beneft s mproved barganng power wth ther major buyers. Pror to EurepGAP, growers were often prce takers and hardly negotated wth ther buyers on dfferent marketng arrangements but many farmers confrmed that by complyng wth EurepGAP they wll be n a better poston to bargan wth ther buyers especally on prce. Fgure 2 Here 5.3. The Adopton Decson Model Results To further nvestgate f the above observed dsparty between the adopters categores affects a farmer s decson to adopt EurepGAP protocol at the farm level, we estmate a probt regresson (Table 4) that estmates the predcted probabltes of adopton of EurepGAP protocol by smallholder export vegetable farmers. The null-hypothess that all varables can be dropped s rejected at less than the 1% level of sgnfcance and the Wald Ch-square s Table 4 Here Among the statstcally sgnfcant varables n the adopton model, the coeffcent of female household members takes postve sgn corroboratng our hypothess. However the number of chldren below the age of fourteen s negatvely assocated wth the probablty of adopton. The status of women n the study area s ntmately lnked to ther labor but also responsblty for the cultvaton and preparaton of food. Predomnantly women are responsble for labor ntensve task of plantng, weedng and harvestng of the crop, e.g. pckng of French beans, thus provde most labor for export vegetable producton. Therefore households wth more female household members tend more lkely to adopt the standard than ther counterparts. Even though the coeffcent s not sgnfcant, young farmers seem more lkely to adopt the protocol and take the rsk assocated wth the technology than the older farmers. Educaton s a very mportant determnant of the adopton of new technologes. We hypotheszed that the decson whether to adopt EurepGAP or not s not necessarly made by the head of the household alone but also by other educated adult members of the household. Our fndngs also support ths noton. As shown n Table 4, the coeffcent value 97

15 of educaton level of the head and other adult household member except the head takes a postve sgn and sgnfcant ndcatng the postve effect of ntra-household lteracy on the adopton decson of EurepGAP. Ths result shows that, even f the household head s llterate, the presence of an adult lterate person n the famly plays a crucal role n ncreasng the probablty of the household to adopt the protocol. Ths s n lne wth the thought that an educated member of the household confers a postve externalty on the llterate agents n the household by sharng the benefts of hs or her lteracy (Basu et al., 2000; Asfaw and Admasse, 2002). The household decson to adopt EurepGAP s also postvely and strongly related to the level of agrcultural tranng receved pror to EurepGAP adopton, whch once agan ndcates the mportance of knowledge n the adopton decson. Land sze s negatvely assocated wth EurepGAP adopton, whch mples that havng less land sze has not been a serous constrant to the adopton of practces n the sampled areas. However households wth more fertle land seem more lkely to adopt the practces compared to ther counterparts. Households wth relatvely bg land sze n the study area tend to focus more on producton of cash crops such as coffee and tea, whch requres bgger areas unlke export vegetable crops. As expected, the number of farm machnery and value of lvestock varables takes postve sgn corroboratng our hypothess. Ths mples that the hgher the capacty of the household to absorb rsk and make an nvestment on addtonal actvtes, the greater the lkelhood of adoptng the protocol. Faclty ndex s another crucal varable that substantally explans the household decson to adopt the protocol. It shows a strong and postve assocaton wth the adopton decson. Contrary to the fndngs of Okello (2005), we fnd no evdence that access to extenson servce ncrease the lkelhood of adopton of the standard. Ths result sounds counterntutve at frst sght. Nevertheless, they make more sense f we closely consder the nformaton channels n the export supply chan. Unlke other agrcultural nnovaton, the prvate sector such as exporter companes and NGOs play a crucal role n dssemnatng the nformaton concernng EurepGAP. Majorty of the exporters n Kenya have got traned techncal personnel at the grass root level who provdes techncal servces for the smallholders producng export crops for them. The techncal personnel vst the farmers on frequent bass and provde the necessary nformaton and servces and hence the role of government extenson personnel s very lmted related to export crops. However other communcaton related varables such as rado use and televson use ncrease the lkelhood of a farmer adopton decson. Rado s extensvely used n the research area and the prmary purposes of lstenng are the news and entertanment features. However there are agrcultural programs on televson and rado, whch could ncrease awareness about new emergng standards and nfluence the adopton decson and the more a farmer lstens to the rado or watches TV, the more lkely h/she s to learn of EurepGAP contrbuton. As expected, the coeffcents of many access related varables have ther hypotheszed sgns. The varable group membershp takes postve sgn n lne wth our hypothess. Ths mples that farmers who have been a group member for long years are more lkely to adopt EurepGAP standard vs-à-vs farmers wth few years of group membershp. As dscussed n the background, smallholders partcpatng n export vegetable busness often organze themselves n a group to delver ther produce to ther buyer and apply for EurepGAP certfcate. Often, grower groups provde some of the servces farmers requre to meet the standard and most export farmers afflated wth farmer groups depended on a techncal assstant ether hred by the group or the buyer (exporter) to meet techncal requrement of the standard (e.g. pest scoutng, record keepng, pestcde applcaton etc) and hence the dynamcs and cohesveness of the group plays a very crucal role for the mplementaton of the protocol. In hs study Okello (2005) also presented smlar results. Surprsngly, the experence n export producton measured by the tme perod a farmer has produced for export market, has negatvely assocated wth the adopton decson n contrary to our expectaton. However, the length of tme the farmer has produced wth a 98

16 formal contract ncreases the probablty of adopton of EurepGAP. The lkelhood of adoptng the protocol does also seem to ncrease sgnfcantly wth use of rrgaton. Most export crops are susceptble to water stress especally durng pod fllng, whch results n wrnkles and spots on the pods. Such qualty s rejected by most buyers that enforce EurepGAP. The amount of credt does seem to have a postve mpact on adopton decson behavor though not sgnfcant. Gven the requred nvestment to establsh the necessary nfrastructure to comply wth the standard, access to credt servce plays a very crucal role n mtgatng the fnancal constrants faced by many smallholders. Partcpaton n off-farm actvtes s strong and negatvely correlated wth the adopton decson. Ths underlnes the mportant role of the opportunty costs of labor for a technology that s labor demandng The Impact Model Results Net-ncome from export vegetables sgnfcantly dffers for adopters and non-adopters of EurepGAP standard. However, whle llustratve, a comparson of means can only lead to a defnte concluson n an deal expermental settng. Unlke controlled experments, condtons other than the treatment are not equal n farm surveys. Thus, these dfferences n mean household ncome cannot necessarly be attrbuted to adopton of EurepGAP. To measure the fnancal beneft of adoptng the standard, t s necessary to take nto account the fact that ndvduals that adopt EurepGAP mght have earned a hgher ncome even f they had not adopted. Hence, to control for ths sample selecton bas we estmated a separate mpact model. Thus, the model examnes whether the dfferences n ncome between the adopter categores dsappear when one takes nto account other dfferences between the households. The results presented n table 5 show that ths s not the case. Table 5 Here Explanatory varables n the mpact model nclude a dummy for EurepGAP adopton, several ndcators of household characterstcs (such as age and household sze), household assets (such as land sze, number of farm machnery, value of lvestock, and durable goods ndex), and partcpaton n off-farm actvtes. A seres of dummy varables for dfferent dstrcts s also ncluded to represent heterogenety n agro-ecologcal condtons. Results show that the coeffcent assocated wth the nverse Mll s rato s not sgnfcant, ndcatng that the correcton for selectvty bas s nsgnfcant n ths model. Adopton of EurepGAP standard s strongly and postvely assocated wth household netncome. All other thngs kept equal adoptng EurepGAP protocol results n an ncrease n net export vegetable ncome of 5,271 KSh. However, the fact that some small-scale producers beneft sgnfcantly from adoptng the standard does not necessarly mply the whole sector s better off. The standard s postve mpact on poverty and pro-poor development depends on the scale of adopton. Accordng to data from FoodPlus secretarat, the legal body of EurepGAP, by June 2006 about 33 large-scale producers and 10 smallholder farmer groups wth 267 members were certfed for EurepGAP standard for frut and vegetables under Opton 1 and 2, respectvely. The survey on the number of export smallholders conducted n preparaton for ths survey arrved at about 3,400 smallholders who n September 2005, were n the process of EurepGAP certfcaton n the nne dstrcts surveyed from Central and Eastern Provnce of Kenya (Mthöfer, 2006). Ths mples that from September 2005 to June 2006 not much progress was made n terms of ncreasng smallholder certfcaton and further, taken the approxmately 12,000 smallholders n export producton, the scale of adopton seems to be rather low for achevng a drect sgnfcant mpact on whole sector. If we compare ths fgure wth the total number of stallholders nvolved n export producton, the scale of adopton seems to be much lower to brng sgnfcant mpact on pro-poor rural development. The age of household head s negatvely and strongly assocated wth the net-ncome, whch suggests that the age of the head poses consderable constrants upon a household s ablty to obtan hgher ncome from export vegetables. Age s usually taken as a proxy for 99