The GlobalGAP standard, small-scale farmers and donor support

In 2005, several retailers in the European Union (EU) made compliance with the GlobalGAP standard a mandatory requirement for their suppliers. For small-scale farmers in developing countries this poses a threat of exclusion from lucrative export horticulture supply chains (Humphrey, 2008). Obtaining GlobalGAP certification can be very challenging for farmers in developing countries. Depending on their initial situation, it may require adjustments in farm management and production and oftentimes large investments in farm infrastructure and equipment, such as pesticide storage, sanitary facilities, chemical sprayer equipment and pesticide disposal pits (Asfaw et al., 2009b, Mausch et al., 2009, Chemnitz et al., 2007). For small-scale farmers, the financial burden of adopting GlobalGAP is particularly high, since the costs of compliance are to a large extent fixed costs. In addition, smallholders often have only limited access to liquidity or credit to finance these high initial investments (Asfaw et al., 2009b, Narrod et al., 2009, Okello, 2005, Mausch et al., 2009). Furthermore, GlobalGAP requires the implementation of practices such as integrated pest management, traceability and record keeping. These practices are often not known or not yet applied by small-scale farmers and the access to extension services that provide information and trainings on these topics is limited in most developing countries (Humphrey, 2008).

Recognizing these barriers to adoption several donors have implemented development programs supporting small-scale farmers to adopt the GlobalGAP standard. Donor interventions usually focus on GlobalGAP group certification, which can make certification feasible for smallholders. In particular, group certification exploits scale economies by centralizing requirements (e.g., establishing joint pesticide storage) and reduces individual certification fees, as only the square root of group members is checked during the external audit. Furthermore, a group structure reduces the transaction costs of dealing with large numbers of dispersed smallholders and thus also makes the provision of advice and trainings more viable (Will, 2010). However, obtaining GlobalGAP group certification is by no means less challenging than compliance at the individual level. Farmer groups must implement a Quality Management System (QMS) that guarantees that all members comply with the GlobalGAP standard, even though only a random sample of group members is inspected

74 during the external audit. Implementing and running the QMS is a costly, time consuming and administratively challenging task that usually cannot be undertaken by smallholders alone (Humphrey, 2008, Will, 2010). In practice, different group certification models that vary with respect to the institutional arrangement for the QMS have been implemented and supported by donors (Humphrey, 2008, Will, 2010, Graffham et al., 2007b). One model often applied is a producer-managed group, where a cooperative or farmers’ association runs the QMS (in some cases with the support of a donor) and owns the GlobalGAP certificate. An alternative model is an outgrower-scheme of an exporter, where the exporter manages the farmer group and owns the certificate (GTZ, 2010). Donor support usually extends to the formation of farmer groups, the implementation of GlobalGAP requirements at the farm level, and the development and operation of the QMS. Besides financial support that partially covers compliance and certification costs, donors often offer technical assistance and training programs to both farmers and exporters (Will, 2010, Humphrey, 2008, Graffham et al., 2007b).

Even if barriers to initial adoption can be successfully addressed through these support programs, the question remains in how far donor-assisted standard adoption is sustainable in the long run. Recent evidence suggests that donor subsidies of the initial costs of GlobalGAP adoption may well enable disadvantaged farmers and exporters to achieve certification, but they may still not be able to maintain the standard without continued support. Graffham, Karehu & MacGregor (2007), e.g., describe eleven case studies of exporter outgrower schemes in Kenya that achieved GlobalGAP adoption with the support of donors. However, of the eleven certification groups only two were running sustainably and these were managed by the two largest exporters in Kenya. Similarly, for the case of Madagascar, Bignebat &

Vagneron (2011) report that of 1198 lychee producers that were certified at the height of GlobalGAP related donor interventions in 2007/2008 only 120 remained certified after the withdrawal of donors in 2009. Several reasons are discussed that may explain the limited sustainability of donor-assisted GlobalGAP certification. A key concern is whether farmers indeed derive monetary benefits from certification that make the renewal of the certification worthwhile. An important aspect may be the fact that there are high recurrent costs of compliance, such as the costs of the external audit and the operation of the QMS, that have to be incurred annually. Even though these are usually lower than the initial investment costs, they can still amount to a substantial share of farmers’ revenues and thus represent a barrier to the renewal of the certification once donor support ends. Another potential reason for the disadoption of standards may be the lack of important value chain linkages. If during the

75 support phase the focus lies exclusively on upgrading farm-level processes, an important opportunity may be missed to build long-term partnerships that facilitate farmers’ access to high-value export markets. Last but not least, if quality management systems are not sufficiently developed and QMS staff is not adequately qualified at the time of donor withdrawal, groups are likely to lack the capacities to run the QMS in the absence of external support (Graffham et al., 2007b, Humphrey, 2008).

4.3. Sampling and survey design

To analyze the impact of certification on farmers’ incomes and to identify the determinants of sustainable implementation of the GlobalGAP standard we carried out a panel data survey of Thai fruit and vegetable farmers in 2010 and 2011. The survey collected comprehensive quantitative and qualitative information on a wide range of topics, including socio-economic and farm characteristics, agricultural production and input use, marketing decisions, compliance with standards, group membership and participation in trainings. The first survey covers a one-year interval from March 2009 to the end of February 2010 and represents the time period before GlobalGAP certification for adopters in our sample. GlobalGAP certification took place in the first half of 2010, and thus the second survey covering the period from March 2010 to February 2011 corresponds to the situation after GlobalGAP adoption. In the remainder of this chapter, we will refer to the first survey interval as 2009 and to the second survey interval as 2010.

In our research area a development program was implemented that supported small-scale farmers to obtain GlobalGAP certification. During the preparation phase of the first survey round, the project was ongoing and none of the participants had been certified. Hence, we divided our study population into four strata (1) program participants who are likely to adopt GlobalGAP (N=118), (2) program participants who are not likely to achieve GlobalGAP certification (N=237), (3) participants in program regions (N=approx. 710), and (4) non-participants outside program regions (N=approx. 415).

For the sampling of program participants, we were provided with a complete list of all participants, including their location and anticipated adoption status⁶⁰

60 During the preparation phase of the first survey in the beginning of 2010, 118 households were listed as prospective adopters by the development project. At this stage, farmers were classified as likely adopters if they were in the adoption process and expected to achieve certification in mid 2010, i.e. within the duration of the development project. By the end of the project, only 82 of the 118 adopters achieved certification.

. In order to have a

76 sufficiently large number of adopters for our analysis, we decided to include all prospective GlobalGAP adopters in our sample. Of the 118 households listed as prospective adopters, 97 were available for interviews. In addition, we randomly selected 49 program participants from the list of likely non-adopters.

For the control group complete lists were not available. Therefore, we used the random walk method to sample non-participants. For the internal control group, non-participating households were sampled in program villages, provided that they produce at least one of the products considered for GlobalGAP certification by program participants in the respective village⁶¹. Since our internal control group is exposed to the activities of the development program and thus potentially affected by spillover effects, we additionally sampled non-participating households outside the program region. For this purpose, we identified ten districts that have similar agro-ecological conditions as the program districts and that are also major production areas for the products considered for GlobalGAP certification in the development program. The selection of these districts was accomplished in close consultation with local experts including Thai professors of agriculture and stakeholders of the development program. In total, we interviewed 287 farmers in 2010 of which 146 are program participants, 85 are non-participants within the program region, and 56 are non-participants outside the program region. In the econometric analysis, we use sampling weights⁶²

In the follow-up survey that was carried out in 2011, we were able to reach 76% of the 287 households that were interviewed in the first survey round. Of the 218 households interviewed in the second survey round, 124 are program participants, 56 are non-participants in program regions and 34 are non-participants outside program regions. We only include 214 households in the analysis, because four of the interviewed households stopped to cultivate fruit and vegetables (F&V) during the study period.

to account for the oversampling of program participants in general and prospective adopters in particular.

There are several reasons for the occurrence of sampling attrition in the second survey round.

First, for some of the households the contact information given was incorrect or they have moved away, and second, some households were not available for interviews. The results of

61 The following products were selected for certification: lychee, durian, mangosteen, papaya, dragon fruit, cantaloupe, mango, asparagus, green okra, spring onion, yard long bean, different kinds of herbs and green leafy vegetables.

62 Sampling weights are calculated as the inverse of the sampling fraction, i.e., the total number of households in each population divided by the number of samples drawn from that population.

77 attrition probit tests (Fitzgerald et al., 1998) and pooled tests (Becketti et al., 1988) revealed that attrition in our study is nonrandom and significantly influenced by the age of the household head, the location of the household and by participation in the development project.

Therefore, we use inverse probability weights⁶³ that correct for sampling attrition that is based on observable characteristics. Inverse probability weights give more weight to individuals who are likely to attrit than to households that are likely to remain in the sample (Baulch and Quisumbing, 2011).