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This paper intends to contribute to the ongoing debate about whether and how restructured agri-food markets can provide viable market opportunities for small-scale farmers in South Africa. It analyses contract farming from the small-scale farmer perspective to better understand the implications for small-scale farmers of contractual arrangements with processing and/or marketing firms. The paper, based on empirical research conducted in the Limpopo Province of South Africa using a combination of qualitative and econometric analyses, argues that contract farming is not a panacea for small-scale farmers. On the one hand, contract farming improves agricultural production for contract farmers who benefit from increased incomes, enables better access to services and resources, and creates new opportunities to participate in markets. However, on the other hand, the results show that contract farming remains limited and mostly involves the already better-off, who have benefitted from specific development paths and public support. This case study shows that contract farming in itself does not appear to provide an efficient means of reducing poverty, nor does it provide an institutional tool through which to improve rural livelihoods. It does, therefore, not represent a tool appropriate for the majority of small farmers or for redressing the historical imbalances in the South African agricultural sector.
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Agrekon: Agricultural
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Demythifying contract
farming: Evidence from
rural South Africa
S. Freguin-Gresh , M. d'Haese & W. Anseeuw
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Demythifying contract farming: Evidence from rural South Africa, Agrekon:
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Agrekon
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DOI: 10.1080/03031853.2012.749567
DEMYTHIFYING CONTRACT FARMING:
EVIDENCE FROM RURAL
SOUTH AFRICA
S. Freguin-Gresh*, M. d’Haese** and W. Anseeuw***
ABSTRACT
This paper intends to contribute to the ongoing debate about whether and how restructured
agri-food markets can provide viable market opportunities for small-scale farmers in South
Africa. It analyses contract farming from the small-scale farmer perspective to better understand
the implications for small-scale farmers of contractual arrangements with processing and/or
marketing firms.
The paper, based on empirical research conducted in the Limpopo Province of South Africa
using a combination of qualitative and econometric analyses, argues that contract farming is
not a panacea for small-scale farmers. On the one hand, contract farming improves agricultural
production for contract farmers who benefit from increased incomes, enables better access to
services and resources, and creates new opportunities to participate in markets. However, on
the other hand, the results show that contract farming remains limited and mostly involves the
already better-off, who have benefitted from specific development paths and public support.
This case study shows that contract farming in itself does not appear to provide an efficient
means of reducing poverty, nor does it provide an institutional tool through which to improve
rural livelihoods. It does, therefore, not represent a tool appropriate for the majority of small
farmers or for redressing the historical imbalances in the South African agricultural sector.
Keywords: contract farming, small-scale agriculture, poverty, South Africa
1 INTRODUCTION
Poverty levels in South Africa remain high and concentrated, both socio-
economically and geographically, with the previously disadvantaged communities
within the rural areas particularly affected (Pauw & Mncube, 2007).1 In this con-
* CIRAD, UMR ART-Dev & Universidad Centro Americana, Instituto de Investigacion
y Desarrollo Nitlapan, Apartado A 242 Campus de la UCA, Managua, Nicaragua
(E-mail: freguin@cirad.fr).
** Department of Agricultural Economics, Ghent University, Coupure links 653, 9000 Gent,
Belgium.
*** CIRAD, UMR ART-Dev & University of Pretoria, Post-Graduate School of Agriculture and
Rural development , 0002 Pretoria, South Africa.
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25
Demythifying contract farming: Evidence from rural South Africa
text, agriculture, and particularly the small-scale sector, is considered as one of
the main economic sectors to revitalise the rural economy (National Planning
Committee, 2010). As such, the government has implemented several policies to
support the small-scale sector (DAFF, 2010). These initiatives have, however, had
only limited success (Anseeuw, 2004; Perret HWDO, 2005).
It is in this context that the development of integrated value chains with the
emergence of new private actors, partly a result of the global restructuring of
markets and the deregulation of the agricultural sector, is seen as an opportunity
for small-scale farmers. Indeed, the contractual arrangements accompanying these
evolutions represent a possibility for small-scale farmers’ integration into modern
value chains. Contract farming is generally considered as an attractive mechanism
for integrating poorer farmers into the open-market economy (Glover, 1984;
Key & Runsten, 1999; Poulton et al., 2010) and, subsequently, for increasing
production and farm income. But, as mentioned by Poulton et al. (2010), it may be
selective, excluding the poor and subjecting them to high risks and agribusiness
normalisation, while failing to increase incomes due to unequal bargaining power,
with the farmers losing out.
This paper intends to contribute to the ongoing debate about whether and how
restructured agri-food markets can provide viable market opportunities for small-
scale farmers in South Africa. Based on empirical research into contract farming
in the Limpopo Province of South Africa, the paper analyses the determinants of
participation in contracts and estimates their implications in terms of livelihoods.
The South African case is particularly interesting. On the one hand, due to the
historical imbalances in access to land and secure tenure regimes, input and output
markets, infrastructures and quality control systems, small-scale farmers face high
transaction costs. Moreover, the differences in scale of trade between the small-
scale farmers and agribusinesses put the farmers at a disadvantaged bargaining
position (D’Haese & Van Huylenbroeck, 2005). On the other hand, the well-
developed value-chains and the public supports available, in particular through
land reform and positive action programmes, represent incentives and should
contribute to a conducive market and production environment (DAFF, 2010).
,QWKH¿UVWVHFWLRQDOLWHUDWXUHUHYLHZDQGEDFNJURXQGLQIRUPDWLRQRQFRQWUDFW
IDUPLQJ DUH SUHVHQWHG ZLWK D VSHFL¿F IRFXV RQ 6RXWK$IULFD 7KLV LV IROORZHG
in the second section, by the methodology used in the research study. Through a
combination of qualitative and quantitative approaches, we will establish a typol-
RJ\RIIDUPKRXVHKROGVDQGDQDO\VHWKHVLJQL¿FDQFHDQGGHWHUPLQDQWVRIFRQWUDFW
farming and of farm incomes. The results of these are presented in section three.
This will then lead, in section four, to wider conclusions on the role of agricultural
contracts in general and in revitalising South Africa’s previously marginalised
small-scale farming sector in particular.
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26
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
 %$&.*5281'21&2175$&7)$50,1*
 &RQWUDFWIDUPLQJDQGW\SHVRI
DJULFXOWXUDOFRQWUDFWV
&RQWUDFWIDUPLQJFDQEHGH¿QHGDVDQDJUHHPHQWEHWZHHQDIDUPHUDQGDEX\HU
ranging from simple oral arrangements to formal written documents, in which
SDUWLHVUHVSHFWLYHO\FRPPLWWRVHOODQGEX\VSHFL¿FYROXPHVRUDFUHDJHVXQGHUSUH
established conditions (Glover, 1984; Minot, 1986). The buyer can be a local or a
transnational agribusiness (processor, exporter, retail outlet or shipper), a private
plantation, a parastatal with its own production, or local merchants (greengrocers,
wholesalers, hawkers, brokers, etc.).
In institutional economics, contract farming is described as a hybrid agreement
that positions itself between the two extremes of the institutional arrangement
spectrum, namely spot markets and market integration. In spot markets, products
are sold and bought immediately, at a price set during the transaction and with no
LQYROYHPHQWRI WKHEX\HU LQWKHSURGXFWLRQRULQ WKHGH¿QLWLRQ RIWKHFRQGLWLRQV
of the transaction. At the other extreme, full vertical integration implies that the
buyer controls all stages of production, processing and distribution throughout the
value chain. Between these poles, contract farming allows the buyer a measure of
control (decision-making rights) over production without formally engaging in
farming activities (Grosh, 1994; Ménard, 2005). The allocation of risk depends
on the terms of the contracts. As such, contract farming provides a response to
market failures with respect to inputs, credit, insurance, information and outputs,
by reducing the associated transaction costs, monitoring, transfer of goods and
bargaining and enforcement (Key & Runsten, 1999; Poulton et al., 2010).
The literature on contract farming differentiates between three classic types
of contracts according to their main objectives, the transfer of decision-making
rights and the shifting of risk from the farmer to the buyer (Key & Runsten, 1999;
Mighell & Jones, 1963; Minot, 1986). 0DUNHWVSHFL¿FDWLRQFRQWUDFWV refer to pre-
harvest agreements that engage a buyer in providing a market outlet to a farmer
under pre-established conditions often related to price, quantity, quality and timing.
Thus, the farmer delegates a part of the risk to the buyer, while keeping control
RYHUSURGXFWLRQ%RWKWKHIDUPHUDQGWKHEX\HUEHQH¿WIURPWKHSULFHSUHPLXPRQ
WKHTXDOLW\DQGWKHVWDELOLW\LQWKHÀRZRIVXSSO\RISURGXFWVWRVSHFL¿HGPDUNHWV
0DQDJHPHQWSURYLGLQJ SURGXFWLRQPDQDJHPHQW FRQWUDFWV are similar to
marketing contracts. These contracts, however, delegate some of the farmer’s
control over the production process to the buyer. In terms of these contracts the
DGRSWLRQRIVSHFL¿FIDUPLQJSUDFWLFHVODQGSUHSDUDWLRQSODQWLQJGDWHVVHHGOLQJV
fertilizer application rates and dates, etc.) or the choice of post-harvest manage-
ment practices will come under the technical supervision of the buyer to attain
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27
Demythifying contract farming: Evidence from rural South Africa
higher quality and to control the timing of output. The buyer recoups the costs of
extension from the proceeds of marketing a higher-quality product according to
the timing of demand.
Finally, UHVRXUFHSURYLGLQJFRQWUDFWV are the closest arrangement to full ver-
tical integration and require not only that the buyer provide a market outlet to
the farmer but also that he delivers input packages on credit and corresponding
technical assistance in its use. These result in the buyer having major control over
production with the contract shifting most decision-making rights and risks to the
buyer (Figure 1).
Figure 1: Typology of contracts
Source: Adapted by the authors from Mighell & Jones (1963) and Minot (1986)
Contract farming may overcome certain constraints small-scale farmers are
typically faced with in developing countries, such as access to resources (inputs,
services, and information) and markets. In South Africa, black small farmers
struggle with access to resources as a result of the marginalisation which occurred
through discriminatory policies under apartheid (Eastwood et al., 2006). Today,
about 1.2 million black small farmers occupy 18 per cent of the farm land (13
per cent of the communal land in the former homelands and 5 per cent of land
redistributed through land reform). These farmers mainly engage in family-based,
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28
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
subsistence agriculture (compared to around 40,000 large-scale farmers, owning 82
per cent of the privately owned agricultural land, characterised by highly intensive
farming activities and producing 95 per cent of the country’s marketed agricultural
output). Most of them lack access to resources (land, water, infrastructure, and
credit facilities). Consequently, contract farming could facilitate their access to
information, technical assistance, credit and inputs, reduce the uncertainty around
marketing their products, improve their integration into modern value-chains and,
consequently, increase their farm incomes (Glover, 1984; Key & Runsten, 1999;
Minot, 1986; World Bank, 2007), as well as providing institutional mechanisms
WRDGGUHVVWKHGLI¿FXOWLHVWKH\IDFH+RZHYHUFRQWUDFWIDUPLQJFRXOGSRWHQWLDOO\
also lead to increasing market segmentation and exclusion (Little & Watts, 1994;
Porter & Phillips-Howard, 1997a, 1997b; Poulton et al., 2010; Vorley et al., 2007)
or remain limited in terms of the number of farmers involved, limiting the overall
impact (Losch et al., 2010).
 'HYHORSPHQWDQGVFDOHRIFRQWUDFWIDUPLQJ
LQ6RXWK$IULFD
Contract farming has a long history in South African agriculture (Karaan, 1999;
Kirsten & Sartorius, 2002a, 2002b; Louw et al., 2006; Porter & Phillips-Howard,
1997a, 1997b; Ortmann & King 2010). The historical development of agricultural
contracts can be traced to the early 1900s in relation to the emergence of
FRRSHUDWLYHV2UWPDQQ.LQJ7KLVKLJKOLJKWVWKHVLJQL¿FDQW
role of contracts in the development of white commercial agriculture. Indeed,
XQWLO WKH V ZKLWH IDUPHUV EHQH¿WHG IURP LQSXW VXSSOLHV VHHGV IHUWLOL]HUV
chemicals and credit), marketing facilities through various boards and service
provision (storage, transport) organised by the cooperatives through various
institutional arrangements. Due to discriminatory policies, black farmers located
in the homelands had only limited, if any, access to most domestic markets, and
consequently to their contracts. They commercialised their outputs – when they
were able to generate surpluses – on informal local markets within the homelands.
Contract farming in South Africa has been analyzsd for small-scale farmers
LQ WUDGLWLRQDO YDOXH FKDLQV VXFK DV WHD VXJDUFDQH WLPEHU WREDFFRÀRZHUV DQG
beverages (Kirsten & Sartorius, 2002b). These schemes appear, however, to be
PRUHWKHUHVXOWRIVSHFL¿FLQLWLDWLYHVRIODUJH HVWDWH DFWRUV GXULQJ WKH DSDUWKHLG
and pre-liberalisation period, than what McMichael and Myhre (1991) call the
“restructuring of agrifood markets”. Quantifying the scale of contract farming,
ZKDWHYHUWKHOHYHORIDQDO\VLVLVH[WUHPHO\GLI¿FXOW:KHUHDVVRPHDXWKRUVDWWHPSW
to estimate the scope of its development in Africa (Grosh, 1994; Little & Watts,
1994), most studies in this respect focus on its impact on the farm and household
(e.g. Bellemare, 2010a, 2010b; Maertens & Swinnen, 2009). In a study on contract
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29
Demythifying contract farming: Evidence from rural South Africa
farming in South Africa, Vermeulen et al. (2008) estimated its scale in the fresh
produce sector and assessed the level of participation of small-scale farmers. This
research shows that almost 80 per cent of the volumes of fruits and vegetables
supplying the South African processing industry (21 per cent of the production)
was exchanged through contracts and that between 70 per cent and 100 per cent of
the produce sold in supermarkets was supplied under contract, while the meat and
egg sectors favoured full vertical integration (Vermeulen et al., 2008). This study
DOVRVKRZHG WKDWRQO\SHUFHQW RIWKHFRQWUDFWVLGHQWL¿HGLQYROYHG VPDOOVFDOH
IDUPHUVZLWKIHZVXSSOLHUV7KHVHUHVXOWVFRQ¿UPWKH¿QGLQJVRISUHYLRXVVWXGLHV
which show that contract farming, for fresh produce in particular, usually implies
a small number of producers, and very few small farmers (Table 1).
Table 1: Extent of contract farming in South Africa for selected commodities
6XEVHFWRU RIIDUPHUVXQGHU
FRQWUDFWV
RIVPDOOVFDOHDQG
HPHUJLQJIDUPHUV
XQGHUFRQWUDFWV
RI6RXWK$IULFDQ
IDUPHUVXQGHU
FRQWUDFWV
Sugar cane 16 045 14 445 small-scale
growers (8% of
sugarcane production)
+ 385 emerging
growers
1.2%
Timber 50 000 15 000 4%
Cotton 3 000 0.2%
Processed fruits,
snack and nuts
2 709 209 0.2%
All fresh fruits and
vegetables
3 430 278 0.3%
Processed
vegetables
350 87 ns
Sources: authors’ compilation from Vermeulen 2008; FAO 2004; South African Sugar Association 2011; FAO Expert
Consultation on Contract farming in Africa, Johannesburg, South Africa (4–7 May 2009).
* The Department of Agriculture, Forestry and Fisheries’ annual report 2009/10 estimates 40 000 commercial farm units
in 2007 and 1.2 million small-scale farms in the former homelands.
3 METHODOLOGY
Measuring the contribution of agricultural contracts to farmers’ welfare levels is
methodologically challenging. Contracts are often not randomly distributed among
households (Barrett et al., 2010) and their access needs to be instrumented in a
regression analysis of their impact on welfare (Bellemare, 2010b). In this paper, a
three-step selection model is developed, addressing the determinants of access to
contracts, as well as the decision to market produce, while estimating the impact
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30
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
of contracts on income and not on welfare. Secondly, the econometric model is
entwined with a qualitative approach that studies a typology of households and
their development paths. This enables us to draw more informed conclusions on
the reasons why some farmers are being excluded from markets and/or contract
farming. The combination of standard econometric models with qualitative
analyses is particularly original and relevant.
 6LWHVHOHFWLRQDQGVDPSOH
Data for this study was collected from farm households in the Greater Tzaneen
Municipality in the Limpopo Province2 (Figure 2). Within the greater municipality,
the survey was conducted in the region of Nwa’Mitwa which includes the
settlements of Mandlakhazi, Mbekwani, Nwa’Mitwa, Nwadjaheni and Babanana
as well as the private farms surrounding the community (Jaffray, Welverwacht,
Taganashoek, La Dauphine, Duplex and Uitzoek).
Figure 2: Location of the study area
The selection of the study area was based on the following criteria:
1. Agro-climatic conditions and importance of agriculture
The area is characterised by relatively good agro-climatic conditions with a
tropical/semi-arid climate (average temperature of 25°C, with annual rainfall of
between 500 and 700 mm) and by relatively homogeneous soils (alluvial and sandy
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31
Demythifying contract farming: Evidence from rural South Africa
RQWKHWRSDQG ÀDW DUHDV FOD\ VRLOVLQWKHORZHUO\LQJ DUHDV 'HVSLWH DGLVWLQFW
dry season, crop production is possible throughout the year under irrigation. As a
result, agriculture is well developed and is the most important economic activity
in the Mopani District where the study area is located.3
2. Historical background, land characteristics and poverty prevalence
The southern part of Nwa’Mitwa is located on tribal lands that were part of the
Gazankulu Homeland. Agriculture is representative of the prevailing situation
in the former homelands, consisting of small plots with communal land tenure,
cropping and livestock systems based on traditional practices, farming activities
dedicated to family consumption, high demographic and land pressure, etc. Most
households face a daily struggle with poverty, particularly due to the high average
age of the population as well as general under- and- unemployment. The northern
part consists of commercial farms. This sub-region is subject to land claims and
some governmental projects have been implemented.
3. Market proximity, off-farm jobs and contract farming opportunities
The proximity to commercial farms both located in the study region and in the Great
Letaba River Valley, one of the leading regions for fruit and vegetable production,
has enhanced the development of agricultural wage labour opportunities and the
presence of contract farming. The population of the study area is estimated at around
16 000 households (Municipal Demarcation Board, 2006) of which, according to
RXU¿QGLQJV LDERXW DUHLQYROYHGLQDJULFXOWXUHLQFOXGLQJOLYHVWRFNDQG
self-consumed cropping activities in gardens and (ii) 82 are private land owners.
A probability sample was not possible because exact lists of community members
were unavailable. It was consequently decided to conduct:
(a) 110 surveys using a questionnaire among a random group of respondents geo-
graphically spread over the area, which allowed, considering the available time
and resources, us to capture the existing diversity and to provide the necessary
information for the establishment of a typology. The survey was random but
the number of commercial and contract farmers was purposefully higher. Four
cases were deleted from the analysis due to missing data, resulting in a data set
of 106 valid cases.
EFRPSOHPHQWDU\LQWHUYLHZVDPRQJVHOHFWHGKRXVHKROGVLGHQWL¿HGGXULQJWKH
¿UVWLQWHUYLHZVLQRUGHUWREHWWHUXQGHUVWDQGWKHLUVSHFL¿FWUDMHFWRULHV
(c) 36 complementary surveys among farmers engaged in contracts and also
LGHQWL¿HGLQ¿UVWURXQGRILQWHUYLHZV
(d) 239 additional short surveys to check how representative the results were in
relation to the size of the population in the region.
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32
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
The dataset is rich and representative regarding the diversity of farming systems
and contracts in the study area. Firstly, it combines quantitative and qualitative
data. Secondly, as we will show in the analysis, it covers a whole range of farming
systems ranging from less developed and subsistence small-scale systems to more
advanced large-scale and commercial ventures. Thirdly, it includes farmers with
and without contracts and assesses the type of agreements they are involved with.
Finally, the dataset enables comparison across farm households with different
land tenure regimes and different levels of governmental support, including
EHQH¿FLDULHVIURPODQGUHIRUPSURJUDPPHV
 4XDOLWDWLYHGDWDDQDO\VLV
Two methodological approaches were used to analyse agriculture and rural
livelihoods. Firstly, an agrarian systems diagnostic approach was implemented in
order to characterise the agro-ecological, technical, historical and socio-economic
IDFWRUV LQÀXHQFLQJ WKH WUDQVIRUPDWLRQ RI WKH UXUDO HQYLURQPHQW &RFKHW 
Devienne, 2004; Dufumier, 1996). Then agricultural practices were analysed (such
as combinations of crops and livestock and their productivity levels) which were
subsequently linked to the asset endowment and households’ development paths
to establish a consistent typology. Secondly, a livelihood approach was applied
WRHDFKLGHQWL¿HGW\SHRIKRXVHKROGDLPLQJDWXQGHUVWDQGLQJWKHFRPELQDWLRQRI
activities and income sources.
 4XDQWLWDWLYHDQDO\VLV
The econometric approach aimed at analysing the determinants of the uptake of
contracts and contract farming’s contribution to the households’ farm income.
7KHDQDO\VLVZDVGRQH LQ WKUHH VWDJHV ,QWKH¿UVWLQVWDQFHD SURELW PRGHO ZDV
XVHG WR DQDO\VH WKH XSWDNH RI FRQWUDFWV 7KH VHFRQG VWHS WKH ¿UVW PRGHO RI D
Heckman model) was a probit analysis of factors determining whether or not
farmers commercialise their agricultural produce (if not, they are considered
to be subsistence farmers). The third step (the second model of the Heckman
model) was a regression analysis of the determinants of farm income for farmers
participating in markets. The independent variables included the probabilities of
KDYLQJDFRQWUDFWVDYHGUHVXOWVRIWKH¿UVWSURELWPRGHODQGWKHLQYHUVHPLOOVUDWLR
that was saved from the second probit model. The estimation of the probit model
as well as the Heckman procedure (models two and three were jointly estimated)
was done using Stata. A description of the Heckman model is given in Appendix 1.
The rationale behind this approach is the latent endogeneity and selection-bias
issues around the uptake of contracts and commercialisation of on-farm income.
While market orientation, as opposed to the choice of subsistence production, is
intrinsically linked to farm income, we suspected selection biases and corrected
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33
Demythifying contract farming: Evidence from rural South Africa
these by estimating a Heckman model (Greene, 2000). We also suspected that the
uptake of contracts would be endogenous to farm income as a buyer’s decision to
procure from a certain region and within that region from a number of sellers, is
not random (Barrett HWDO, 2010; Bellemare, 2010b). Because the analysis seeks
to test whether contract farming increases farm income, we needed to instrument
the uptake of contracts to address these potential endogeneity problems while
controlling for the decision to sell agricultural produce. Following Wollni and
Zeller (2007), we introduce the probabilities obtained from the probit model on
uptake in the farm income model. It is worth noting that farmers who had contracts
were marketing their produce, while not all farmers who were marketing had
contracts. Contract uptake is instrumented by the importance of off-farm income in
the total household income.4 Furthermore, there is no theoretical reason to assume
a causal relationship between the share of income from off-farm sources and
agricultural income. Likewise, the likelihood to market produce is instrumented
E\ WKH OHYHO RI WUDQVIHUV KLJK VRFLDO JUDQWV DQG UHPLWWDQFHV PD\ LQÀXHQFH WKH
likehood that farmers commercialise, but they are exogenous and arguably not
necessarily causally linked to farm income.
7KH LQGHSHQGHQW YDULDEOHV VHOHFWHG IRU WKH ¿UVW SURELW PRGHO DUH VLPLODU WR
those commonly used in the literature for similar models (Bolwig et al., 2009;
Miyata et al., 2009; Wollni et al., 2010; Wollni & Zeller, 2007) namely (a)
household characteristics (household size, age and gender of the head); (b) assets
endowments (land area, size of the cattle herd) and (c) share of off-farm income
in total income.
The model for household i then becomes:
iiiiii arealandJHQGHUsquaredDJHDJHizehouseholds& __ 543210
DDDDDD
iii uIDUPoffLQFRPHsharecattle ___
76
DD
(1)
with Ci being a dummy variable (0/1) indicating if the household has a contract or
not, and ui being the error term. The probability of Ci=1 is calculated by a probit
PRGHO VLPLODU WR WKH ¿UVW VWHS RI WKH +HFNPDQ PRGHO JLYHQ LQ HTXDWLRQ  LQ
Appendix 1.
Independent variables for the second probit model were similar to exogenous
KRXVHKROG FKDUDFWHULVWLFV LQ WKH ¿UVW PRGHO KRXVHKROG VL]H DJH DQG JHQGHU RI
the head), supplemented with the level of education of the head and income from
transfers. As mentioned above, we consider the two latter variables as relevant
because these additional income sources will determine the choice of farming
V\VWHPZLWKRXWGLUHFWO\LQÀXHQFLQJWKHIDUPLQFRPH
The model is for household i:
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34
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
iii squaredDJHDJHizehouseholds _
3210
EEE
E
ii educationJHQGHU 54
EE
iiii vedracesUHPLWJUDQWVsocial inftan_ 876
EEE
(2)
with viEHLQJWKHHUURUWHUP7KLVIXQFWLRQLVWKH¿UVWVWHSRID+HFNPDQVHOHFWLRQ
model as explained in Annex 1.
Agricultural income is regressed against (a) the household structure (age,
gender), (b) farm characteristics (number of active people on the farm, land, access
to irrigation and land tenure regimes) and (c) the probability of access to contracts
The model then becomes for household i:
iiiiii tenureprivatelandJHQGHUDJHPHPEHUVactive
Y
543210 __
J
J
J
J
J
J
iiii Z,0L&edraesbeneficariUHIRUPland 9876 inf__
J
J
J
J
with IMi being the inverse mills ratio/lambda, and Zi the error term.
The second step of the Heckman procedures is expressed by equation (1) and
solved as presented in Annex 1, for those households participating in the market. It
should be noted that due to the relatively low number of cases in this second step,
the number of variables was limited and the results were interpreted with care.
However, the outcome of the econometric models is compared and triangulated
with the qualitative data analysis.
4 RESULTS
 +RXVHKROGW\SRORJ\
Of the 106 households interviewed, seven types of farming systems were
LGHQWL¿HG 7DEOH  )RXU FULWHULD ZHUH XVHG L WKH VL]H DQG WKH W\SH RI ODQG
(garden, communal area, private land); (ii) the commercialisation of agricultural
products, including the buyers (spot markets, local merchants, supermarkets,
processors, export agents) and the destination of the products when sold (local,
domestic, export markets); (iii) the combination of crops and livestock (share of
staple food, of fruits and vegetables, of livestock in the farm production value) and
asset endowment (equipments, irrigation systems etc.) and (iv) access to and the
importance of off-farm income.
7KH W\SRORJ\ HQDEOHV WKH LGHQWL¿FDWLRQ RI GLIIHUHQW KRXVHKROG VWUDWHJLHV
DQGWKHTXDQWL¿FDWLRQ RIWKHGLVWULEXWLRQ RIFRQWUDFWVZLWKLQWKH VWXG\DUHD7KH
typology presented in this article includes all households interviewed, including
DJURXSVLJQL¿FDQWLQWHUPVRIQXPEHURIKRXVHKROGVEXWZKLFKLVQRWHQJDJHG
in the commercialisation of its production. It was decided to keep this group to
DGGUHVVWKHLVVXHRI VFDOH DQG VLJQL¿FDQFH RIFRQWUDFWVZLWKLQWKH VWXG\ UHJLRQ
The other six types enable the analysis of the conditions of engagement and entry
barriers regarding contractual agreements.
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35
Demythifying contract farming: Evidence from rural South Africa
Table 2: Typology of farming households in the Greater Tzaneen Municipality
Q RIWKHVDPSOH RI++LQDUHD
Micro-farmers cultivating residential gardens
for self-consumption, depending on off-farm
activities, remittances and social grants
15 14.2 53.8
Subsistence small-scale farmers depending on
off-farm income, combining staples for self-
consumption and vegetables for local markets
28 26.4 39.6
Small-scale producers of staples and F&V for
local markets, depending on off-farm activities
and social grants
6 5.7 4
Medium-scale producers specialised in
vegetable production for the local and
domestic markets
24 22.6 1
Emerging industrial chicken and vegetable
producers
16 15.1 0.2
Extensive commercial farmers, producers of
fruits mainly for the domestic market
11 10.4 1
Intensive commercial producers of fruits
and vegetables for the domestic and export
markets
6 5.7 0.4
7RWDO 106 100 100
Notes: *Number of detailed questionnaires to a random group of respondents allowing for the capturing of the diversity
of household types. **Based on the results of the 239 short interviews conducted and being representative of the
population in the study area.
4.1.1 Micro-farmers cultivating residential gardens for
self-consumption, depending on off-farm incomes
(n=15)
The micro-farmer group is very heterogeneous in terms of livelihoods. These
mostly female-headed households implement survival strategies to cope with very
low incomes and take any opportunity that allows them to improve their livelihoods
such as small irregular jobs in the service sector in the community, casual agricultural
labour, social grants and remittances (with the younger, active population often
having migrated). However, despite engaging in these diverse activities, these
households seldom succeed in generating an income above the poverty line. In
terms of farming, they have no or very poor access to land and consequently rely
only on the cultivation of residential gardens. They combine starchy staples and
vegetable production for family consumption, producing only during the rainy
season due to a lack of access to irrigation water. As a result, farming activities are
limited and contribute only marginally to this group’s subsistence (21 per cent of
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36
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
JOREDOLQFRPH:LWKLQVXI¿FLHQWDFFHVVWRDVVHWV DQGLQVXI¿FLHQWSURGXFWLRQWKLV
group is mainly excluded from markets and farming provides only a basis for food
security.
4.1.2 Subsistence small-scale farmers depending on
off-farm income, combining staples for
self-consumption and vegetables for
local markets (n=28)
The second group consists of couples composed of a retired person and an active
person engaged in a permanent activity (small business). Social grants or off-farm
income are invested in an irrigation system which provides water for domestic
use, for the sale of drinking water to the community and for irrigation purposes
(manual only). Unlike the micro-farmer group, these households have access to
a plot of arable land in the communal lands (on average one hectare), allowing
them to cultivate staples and vegetables and to keep an orchard (usually mangoes).
They may also have a small herd of cattle that grazes on communal land and may
fatten pigs. Their produce is sold on spot markets within the community or to local
PHUFKDQWV7KH IDUPLQJ DFWLYLW\ DOORZVWKHPWRKDYHIRRG DQG D¿QDQFLDOEDVLV
but, for most of them, farming is not considered to be a productive activity (17
per cent of total income). They furthermore have no investment capacity and rely
heavily on social grants for their subsistence.
4.1.3 Small-scale producers of staples and fruits and
vegetables for local markets, depending on
off-farm activities and social grants (n=6)
The third group combines small-scale farming (28 per cent of global income),
off-farm activities (taxi, small business) and social grants, which represent a
VLJQL¿FDQWSDUWRIWKHLULQFRPH2IIIDUPLQFRPHLQYHVWHGLQDQLUULJDWLRQ
system, has allowed them to develop marketable year-round vegetable production.
These households have access to a plot in the communal area (average size 1.8
hectares) which they cultivate in addition to a garden. Products are sold on spot
markets or to local merchants. For this group, farming is a productive activity and
the basis of their livelihoods; they would like to develop their farming activity
if their constraints can be overcome (limited access to resources, lack of credit,
GLI¿FXOWLHVLQFROOHFWLQJDQGWUDQVSRUWLQJWKHLUSURGXFWVWRPDUNHWVHWF
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37
Demythifying contract farming: Evidence from rural South Africa
4.1.4 Medium-scale producers specialised in vegetable
production for the local and domestic markets
(n=24)
These households are better endowed (largest plots in communal lands) and due
WR PRUH HI¿FLHQW LQIUDVWUXFWXUH SULYDWH ERUHKROHV LUULJDWLRQ V\VWHPV WUDFWRUV
and private vehicles) they have been able to develop a marketable vegetable
production (up to three cycles per year) which they sell to local merchants, to fresh
produce markets or under formal contracts to supermarkets (organic production-
PDQDJHPHQW FRQWUDFWV), to processors or restaurants (PDUNHWLQJ FRQWUDFWV). As
a result of successful but expensive practices, farming has become the pillar of
their livelihood (67 per cent of total income), the rest being non-farm sources.
)DUPLQJ LV D SUR¿WDEOH PHDQV RI H[LVWHQFH WR WKHP EXW ZLWKRXW WKH VXSSRUW RU
WKHRSSRUWXQLWLHVIURPZKLFKWKH\EHQH¿WWHGRQWKHEDVLVRIWKHLUSHUVRQDOVRFLDO
networks in order to access production factors and market opportunities, or both,
they would not have been able to develop this activity.
4.1.5 Emerging industrial chicken and vegetable
producers (n=16)
These households are specialised in intensive vegetable production under PDQDJH-
PHQWSURGXFWLRQFRQWUDFWV with agribusinesses and/or industrial broiler production
under UHVRXUFHSURYLGLQJFRQWUDFWV with a local agribusiness (Bushvalley). Agri-
culture is their only economic activity. The viability and the sustainability of this
specialised and intensive but expensive farming system is questionable, both in
agro-ecological as well as economic terms. It is not clear if the farmers engaged
in this production system would have had the means to invest and renew their
equipment and to develop an economically sustainable activity without massive
external (mostly governmental) support.
4.1.6 Extensive commercial farmers, producers of fruits
mainly for the domestic market (n=11)
([WHQVLYHFRPPHUFLDOIDUPHUVFRPELQHDQLQGHSHQGHQWRUDTXDOL¿HGSHUPDQHQW
off-farm activity and managerial farm requiring numerous workers. They are well
equipped, with an operational irrigation system and a tractor. They have mostly
specialised in extensive mango production (low use of inputs and workforce).
Mangoes are usually harvested green to be delivered to local processors or sold
ripe to merchants, fresh produce markets or exporting agents. Some of them have
contracts (PDUNHWLQJ) which are usually verbally concluded.
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38
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
4.1.7 Intensive commercial producers of fruits and
vegetables for the domestic and export
markets (n=6)
The households of this last group are specialised in managerial farming. They
have developed an intensive (in terms of labour, capital and inputs) production of
fruits under irrigation. They own tractors, greenhouses, warehouses and a packing
unit to satisfy the requirements and standards of their buyers (local merchants,
processors, fresh produce markets and exporting agents) with whom half of
them have various types of contracts (mostly PDUNHWLQJ but also production-
PDQDJHPHQWFRQWUDFWV). Their activities are concentrated on large areas of private
land. They combine their production activities with extensive cattle breeding on
private pastures.
Table 2 also presents the distribution of the six types, based on a shorter survey
conducted among a larger number of farmers in the study area (n=239). The
resulting distribution differs from the one based on the long survey. The micro-
IDUPHUVVHHPWREHWKHODUJHVWJURXSIROORZHGE\VXEVLVWHQFHVPDOOVFDOH
IDUPHUV)URPWKHIDUPHUVLQWKHDQDO\VLVWKDWSDUWLFLSDWHGLQWKHORQJ
LQWHUYLHZ PHGLXPVFDOH IDUPHUV  HPHUJLQJ LQGXVWULDO FKLFNHQ SURGXFHUV
DQGLQWHQVLYHDQGH[WHQVLYHFRPPHUFLDOIDUPHUVVHHPWREH
overrepresented.
 ([WHQWDQGFKDUDFWHULVWLFVRIFRQWUDFWIDUPHUV
The extent of contract farming in the region remains limited with only 36 farmers
(34 per cent of the interviewees) having at least one contract, whether verbal or
LQZULWLQJ)ROORZLQJRXU¿QGLQJVLQWKHVKRUWVXUYH\FRQWUDFWIDUPHUVUHSUHVHQW
less than 1.2 per cent of the total number of farm households in the region. The
limited extent of contract farming can be explained by the fact that, as shown by
the typology analysis, the majority (54 per cent of the interviewees) are micro or
small-scale subsistence-oriented farmers. As they do not participate in markets
WKH\DUHDOVRH[FOXGHGIURPFRQWUDFWIDUPLQJDVFRQ¿UPHGLQ7DEOHZKLFKOLQNV
the farm household typology with participation in markets, contracts and the
destination of the agricultural produce.
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39
Demythifying contract farming: Evidence from rural South Africa
Table 3: Buyers, contracts, and types of households
7\SHVRI
EX\HUV
HDFK
W\SH
KDYHDW
OHDVWRQH
FRQWUDFW
7\SHVRIDJULFXOWXUDOFRQWUDFWV
Micro-farmers No sale 0 No contract
Subsistence small-scale No sale 0 No contract
Spot markets
Small-scale producers Spot markets 0 No contract
Local
merchants
Medium-scale producers Local
merchants
57 No contract
Fresh produce
markets
(FPM)
No contract
Restaurants Informal marketing agreements
Supermarkets No contract or formal organic
production-management contracts
Processors Informal marketing agreements or
formal production-management
contracts
Emerging farmers Local
merchants
100 No contract or informal
agreements
Road-side
stalls
Informal marketing agreements
FPM No contract or informal marketing
agreements
Supermarkets Formal organic production-
management contracts
Processors Informal agreements or formal
production-management contracts
Extensive commercial
farmers
Local
merchants
27 No contract
FPM No contract or informal marketing
agreements
Processors Informal gentlemen’s agreements
Exporting
agents
Formal market-speci±cation
contracts
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40
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
Intensive commercial
farmers
Local
merchants
50 No contract or informal
gentlemen’s agreements
FPM No contract or informal
gentlemen’s marketing agreements
Processors Informal agreements or formal
marketing or production-
management contracts
Exporting
agents
Marketing contracts
Tables 4 and 5 compare the mean values of the major characteristics of contract
IDUPHUV DQG QRQFRQWUDFW IDUPHUV 7KH WZR JURXSV GLIIHU VLJQL¿FDQWO\ LQ WKHLU
demographic characteristics, asset endowment and income structure. Contract
farmers seem to have smaller households (with fewer older members and more
children) and are led by younger heads (mostly male); they have better access
to land, mostly under private tenure or in land reform schemes and all of them
have access to irrigation (through various types of irrigation systems), with larger
cattle herds and higher agricultural incomes. Among the group of non-contracted
IDUPHUVZHFRXQWPRUHIHPDOHKHDGHGKRXVHKROGVZLWKVLJQL¿FDQWO\ORZHUOHYHOV
of education, less land (consisting mainly of gardens) and a greater dependency
on social grants.
Table 4: Comparison of means between contract and non-contract farmers
(standard deviation in brackets)
&RQWUDFWHGIDUPHUV
(n=36)
1RQFRQWUDFWHG
IDUPHUVQ 
7VWDW
Household size (nb) 2.56
(1.92)
5.17
(3.11)
5.338***
Share children in household (%) 14.41
(17.76)
6.88
(18.02)
2.049**
Age of household head (years) 50.42
(11.84)
57.41
(14.47)
2.500**
Available land (ha) 98.04
(106.43)
20.17
(63.60)
–4.035***
Cultivated land (ha) 36.58
(63.76)
10.69
(30.98)
–2.300***
Share cultivated (%) 41
(33)
92
(22)
8.197***
Number of cattle 19.03
(43.88)
4.26
(13.28)
–1.974*
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41
Demythifying contract farming: Evidence from rural South Africa
Agricultural income (R/year) 2,095,423
(3,122,966)
143,956
(600,139)
–3.714***
Remittances received (R/year) 2,666
(5,928)
4,670
(14,609)
0.789
Social grants received (R/year) 4,369
(6,991)
8,314
(7,714)
2.572**
Total income (R/year) 2,115,694
(3,115,194)
171,919
(601,174)
–3.708***
Share of income from off-farm
source (%)
16.5
(28.5)
63.7
(33.9)
7.568***
Note: *** signi±cant at 1%, ** signi±cant at 5%, * signi±cant at 10%
Table 5: Comparison of shares (%) of determinants between contracted and
non-contracted farmers
&RQWUDFWHGIDUPHUV
(n=36)
1RQFRQWUDFWHG
IDUPHUVQ 
&KLVTXDUH
stat
Gender household head (% male) 83 47 12.915***
Access to off-farm income (% yes) 56 89 14.795***
Education above primary level (% yes) 94 33 36.276***
Rain-fed production (% yes) 11 50 14.460***
Private land tenure (%) 50 17
Communal land tenure (%) 14 10
Gardens (%) 0 63
Land reform (%) 36 0
Garden + communal land (%) 0 10 60.893***
Note: *** signi±cant at 1%, ** signi±cant at 5%, * signi±cant at 10%
a Chi-square test for land reform versus contract farming
In the probit model we explain participation using several variables which are
expected to determine households’ ability to engage in contracts. The probit model
LVKLJKO\VLJQL¿FDQWDQGSUHGLFWVDOPRVWSHUFHQWRIWKHREVHUYHGHQJDJHPHQWLQ
contracts (Table 6). The model supports the conclusions of the typology analysis
DQG¿QGVWKDWODQGVL]HLQFUHDVHVWKHSUREDELOLW\WRHQJDJHLQFRQWUDFWVZKLOHWKH
share of off-farm income in the total income decreases this probability. The model
FRQ¿UPVWKDWIDUPHUV ZLWK ORZODQGHQGRZPHQWV PLFURVXEVLVWHQFH DQGVPDOO
scale farmers) are more likely to be excluded from contract farming.
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42
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
Table 6: Probit model of uptake of contracts (0: no contract; 1: contract)
&RHI±FLHQW 5REXVWVWGHUURU ]VWDW
Household size –0.247 0.086 –2.87***
Age of household head (yrs) 0.201 0.091 2.21**
Age squared (yrs²) –0.002 0.001 –2.40**
Gender of household head (1:male/2:female) –0.248 0.352 –0.70
Share off-farm income (%) –0.012 0.007 –1.68*
Log land size (log ha+1) 0.282 0.138 2.04**
Cattle (number of heads) 0.001 0.005 0.19
Constant –3.870 2.229 –1.74*
N= 106
Wald chi²=36.67
Pseudo R²= 0.519
Correctly classi±ed 87.5%
The combined quantitative and econometric analysis thus assists in classifying
WKHFRQWUDFWIDUPHUVLQWRWZRFDWHJRULHV7KH¿UVWJURXSRIKRXVHKROGVFRQVLVWVRI
large-scale commercial farmers. The analysis of their trajectories (see Figure 3)
shows that they access contracts as preferred suppliers of processors, supermarkets
and exporting agents as a result of a good asset endowment base (large cultivated
DUHDV RQ SULYDWH ODQG HI¿FLHQW LUULJDWLRQ V\VWHPV DQG HTXLSPHQW 7KH\ KDYH
succeeded in equipping the farm and becoming, relatively speaking, highly
productive due to the public support they received during apartheid (subsidised
interest rates, tax concessions and price support combined with strong institutional
arrangements with cooperatives). After liberalisation, the deregulation of markets
DQGWKHGLVPDQWOLQJRISDUDVWDWDOVRQO\WKHODUJHVWDQGWKHPRUHHI¿FLHQWIDUPHUV
in this group were able to meet the required volumes and quality (norms and safety
standards) and succeeded in remaining preferred suppliers.
The second group, which is the target group of the project, consists of smaller-
scale farmers located on both private (redistributed) land and communal areas.
The analysis of their trajectories shows convergent trends. Most of them accessed
support measures as a result of social networks established before the end of
apartheid (for example, access to land and support as public workers or as decision
PDNHUV LQ WKH KRPHODQGV 2WKHUV EHQH¿WWHG IURP UHFHQW SXEOLF VXSSRUW LQ WKH
context of Broad-Based Black Economic Empowerment for Agriculture and other
DI¿UPDWLYHDFWLRQSURJUDPPHV
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43
Demythifying contract farming: Evidence from rural South Africa
Figure 3: Trajectories of households per types of farming systems
Source: Authors
The trajectories of the emerging vegetable and broiler producers are good examples
of how some small-scale farmers succeeded in concluding contracts in the study
area (Figure 3). Seven individual farmers received productive farmland in 2002
through the Land Reform’s Settlement Land and Acquisition Grant programme,
complemented with loans from the Land Bank. After acquisition their farms
collapsed due to, amongst other factors, inadequate experience or institutional
support. In 2005, the Limpopo Department of Agriculture intervened with a
multi-million rand poultry project as part of the agri-BEE drive, including the
construction of environmentally controlled houses with a carrying capacity each
of 40 000 broilers per 32 day cycle (Anjuère & Boche, 2009; Business Report,
2QHRIWKHFRQGLWLRQVIRUWKHIDUPHUVWREHQH¿WIURPWKHLQIUDVWUXFWXUHZDV
WKHFRQFOXVLRQRID¿YH\HDUUHVRXUFHSURYLGLQJFRQWUDFW which the Department of
Agriculture signed with the processor, Bushvalley. Broiler production effectively
started in 2007. The contract terms include the following: Bushvalley is to provide
farmers with all the required inputs (poultry equipment, one-day-old healthy
broiler-type chicks from a local hatchery, high quality balanced foodstuffs, poultry
litter, disease prevention/control medicines, etc.) and a strict monitoring plan for
feeding and managing the chickens. All costs (input, transport and processing) are
to be deducted from the amount producers are paid; the price is not pre-established
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44
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
and depends on the weight of the chickens. In addition to the provision of technical
assistance, quality and hygiene inspections are to be conducted to ensure the
highest quality of the products delivered (Anjuère & Boche, 2009; Limpopo
3URYLQFLDO*RYHUQPHQW7KHSURMHFWOHDGHUVDOVREHQH¿WWHGIURPLQWHQVLYH
training regarding poultry production in environmentally controlled facilities,
provided through the DoA’s comprehensive agricultural support programmes.
 'HWHUPLQDQWVRIDJULFXOWXUDOLQFRPH
A Heckman model was used in order to test whether contracts could improve
OLYHOLKRRGV 7KH ¿UVW VWHS RI WKH PRGHO 7DEOH  LV D SURELW PRGHO RI WKH
determinants of the likelihood that the farmers commercialise their produce or not.
Indeed, it is obvious that if a farmer is not able to generate marketable output, he
will not be able to participate in any arrangement; testing if contract farming is a
GHWHUPLQDQWRIWKHIDUPLQFRPHLVLQWKDWFDVHLUUHOHYDQW7KH¿UVWVWHSRIWKHPRGHO
thus shows that an education above primary level is an important determinant of
commercialisation. Furthermore, households that receive larger social grants and
do not have access to irrigation infrastructure are less likely to commercialise any
agricultural produce, which also corresponds with the results of the qualitative
analysis.
Table 7: Probit model of commercialising agricultural produce (0: no sales; 1: sales)
6WHSRI+HFNPDQPRGHO &RHI±FLHQW 6WGHUURU ]VWDW
Household size 0.052 0.063 0.83
Age of household head (yrs) 0.062 0.144 0.43
Age squared (yrs²) –0.0005 –0.001 –0.39
Gender of household head (1:male/2:female) –0.638 0.556 –1.15
Secondary education or more (1:yes) 1.615 0.537 3.00***
Log social grants (R) –0.293 0.168 –1.74*
Log remittances (R) 0.044 0.050 0.87
Rain-fed production (1:yes) –0.926 0.459 –2.01**
Constant 1.524 4.138 0.37
The second step of the model is a regression of the determinants of farm income
7DEOH 7KH ODWWHUVHHPVWREHSRVLWLYHO\LQÀXHQFHGE\WKHQXPEHURIDFWLYH
members on the farm, the level of specialisation in agriculture, the size of the
cultivated land, and whether this land was acquired under private tenure or land
UHIRUP7KHVHGHWHUPLQDQWVDUHDOO³FODVVLF´VWUXFWXUDOYDULDEOHVLQÀXHQFLQJIDUP
income, as widely commented on in the literature. Further literature (Eaton &
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45
Demythifying contract farming: Evidence from rural South Africa
Shepherd, 2001; FAO, 2005; IFAD, 2003; Little & Watts, 1994; World Bank,
FRQ¿UPVWKDWFRQWUDFWVSRVLWLYHO\LQÀXHQFHIDUPLQFRPH
Table 8: Regression results for determinants of agricultural income
(dependent variable: log of income from agriculture)
6WHSRI+HFNPDQPRGHO &RHI±FLHQW 5REXVWVWGHUURU ]VWDW
Household members active on farm 0.607 0.222 2.73***
Age of household head (yrs) –0.012 0.013 –0.94
Gender of household head (1:male/2:female) 0.482 0.402 1.20
Probability of contract 2.016 0.881 2.29**
Log land size cultivated (log ha+1) 0.535 0.176 3.04***
Private land tenure (1:yes) 1.141 0.638 1.79*
Land reform bene±ciaries (1:yes) 1.796 0.615 2.92***
Rain-fed production (1:yes) –0.203 0.500 –0.41
Constant 7.623 1.000 7.62***
Inverse mills – Lambda –0.597 0.560 –1.07
n= 106
Censored obs = 31
Uncensored obs = 75
Wald ch²=130.65
Rho=-0.443
Sigma= 1.348
7KHDQDO\VLVRI WKH +HFNPDQ PRGHOFRQ¿UPVWKDWIDUPHUV ZKR JHQHUDWHKLJKHU
farm incomes are also better endowed with regard to capital and production factors
(land, private tenure, equipment, etc.). The qualitative analysis (Figure 3 and Table
3) suggests that these farmers engage in contracts for different reasons: (i) they are
PRUHFRQFHUQHGZLWKHQVXULQJVWDELOLW\LQWKHÀRZRISURGXFHWRVSHFL¿HGPDUNHWV
rather than with accessing production factors, credit and other inputs as they
DOUHDG\KDYHDFFHVVWRWKHVHWKLVLVVSHFL¿FDOO\WKHFDVHIRUFRPPHUFLDOIDUPHUV
who participate in either informal agreements or formal PDUNHWLQJ FRQWUDFWV;
or (ii) contract farming is ‘part of the deal’ for gaining access to development
programmes (agri-BEE, public-private partnerships, land reform programmes,
other public programmes for rural development, small-scale enterprises and
agriculture, etc.), as illustrated by the emerging farmers. In this case, contract
farming is a sine qua non condition for the farming system which is largely based
on public support.
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46
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
5 CONCLUSION
The objective of this paper was to contribute to the ongoing debate about whether
and how contract farming can provide viable market opportunities for small-scale
farmers in South Africa.
The results show, however, that contract farming is not a panacea for small-
scale farmers. They highlight that contracts mostly involve the already well-
RIIZKR DUH HLWKHU ODUJHVFDOHPDQDJHULDOFRPPHUFLDO IDUPHUV KDYLQJ EHQH¿WHG
from public support during apartheid and which enabled them to become highly
productive, well-equipped and well-inserted in output markets, or medium-scale
IDUPHUVZKR KDYHEHQH¿WHGIURPFDVHVSHFL¿FSXEOLF SURJUDPPHVDQGRUVRFLDO
RU SROLWLFDO FRQQHFWLRQV %RWK WKH TXDOLWDWLYH DQG TXDQWLWDWLYH DQDO\VHV FRQ¿UP
the existence of entry barriers for small-scale farmers in concluding contracts
(production and commercialisation scales, education and asset endowments such
DV DFFHVV WR ODQG DQG LUULJDWLRQ $V VXFK DOWKRXJK VLJQL¿FDQW FKDQJHV KDYH
occurred in South African agriculture, small-scale farmers with limited access to
DVVHWVDQGZKRUHO\PDLQO\RQGLYHUVL¿HGLQFRPHVSDUWWLPHZRUNVRFLDOJUDQWV
etc.) to sustain their livelihoods, remain excluded and thus often marginalised.
Hence, the results support the concerns around the inclusivity of contract farming
posed elsewhere in the literature (Losch et al., 2010; Poulton et al., 2010; Vorley
et al., 2007, amongst others).
The results lead us to emphasise the need for disaggregated analyses of farm-
ing systems, of their different structures, their diverse roles and, subsequently, of
their different needs, policy measures and support systems. They also question
the effectiveness of contract farming as a “mythic” tool to integrate small-scale
farmers into restructured markets and modern value-chains and to reduce rural
poverty and inequality. The heavy support and subsidised measures necessary
to make contract farming work for the poor cast further doubt on the viability
of these instruments. Rethinking instruments is a must in order to support the
different types and roles of agriculture in the context of social dependency and
exclusion of productive income-generating activities affecting the rural poor.
This is particularly the case in South Africa, marked by its agrarian history. It
applies, however, also to other developing countries where the majority of farmers
are engaged in agriculture solely for subsistence, within a complex and strongly
GLYHUVL¿HGOLYHOLKRRGV\VWHP
NOTES
1 Poverty rate indices for South Africa vary according to sources and methodologies: the
World Bank (2011) estimates that 22 per cent of the population lives on less than R524 per
month whereas the National Planning Commission (2010) estimates that 49 per cent of the
population lives on less than R283 per month.
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47
Demythifying contract farming: Evidence from rural South Africa
2 Limpopo Province is located in the north of South Africa. It is a typical developing area,
characterised by the export of primary products and the import of manufactured goods and
services. It is one of the poorest regions of South Africa.
3 Mainly citrus and subtropical fruits are produced in the area for both domestic and export
markets. The area is also known for its tomatoes (constituting approximately 60 per cent of
tomato production in South Africa).
4 We assume that off-farm income is exogenous to farm income at household level because it
FRQVLVWVPDLQO\RIZHOIDUHJUDQWVDQGUHPLWWDQFHV,QWKHFDVHRIFURVV¿QDQFLQJOLYHOLKRRG
GLYHUVL¿FDWLRQ LQFUHDVLQJ WKH VKDUH RI RIIIDUP LQFRPH LQ WRWDO LQFRPH PD\ LQFUHDVH
agricultural income. It is equally possible, however, that farm income may decrease as the
VKDUHRI RIIIDUPLQFRPH LQFUHDVHVLQ WKRVHLQVWDQFHV ZKHUHWKH RIIIDUPLQFRPH VDWLV¿HV
the household’s utility levels.
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country/south-africa
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50
S. Freguin-Gresh, M. d’Haese and W. Anseeuw
$33(1',;'(6&5,37,212)7+(+(&.0$102'(/
7KHHPSLULFDO VSHFL¿FDWLRQRIPDUNHW SDUWLFLSDWLRQDQGLQFRPH IURPDJULFXOWXUH
problem takes the following form:
iiii MXY
HGE
(1)
where Yi is agricultural income, Xi denotes the explanatory variables that
LQÀXHQFHDJULFXOWXUDOLQFRPHDQGMi is the dummy variable indicating the market
participation decision (binary choice). In case of self-selection, the least square
estimator dwill be biased, i.e. overestimating the effect of market participation.
The solution lies in incorporating a standard treatment effects model, which
extends the programme participation model (1) with (Greene, 2000; Maddala,
1983):
.0otherwise,0if1 *
*
!
iii
iii
MMM
u:M
J
(2)
In reality, Mi
* is unobservable, whereas Mi is the dichotomous parameter of
PDUNHWSDUWLFLSDWLRQLQÀXHQFHGE\WKHVHWRIH[SODQDWRU\YDULDEOHV:i) as directly
measured in the survey. Hence, the probability of market participation (2) can be
GH¿QHGDV

)(-1)0(Proband
)()(Prob0Prob)1(Prob *
ii
iiiii
:M
::uMM
J
JJ
)
) ! ! (3)
wherein ) is a cumulative probability distribution for u (Maddala, 1983). The
distributional form of ) can either be a normal or logistic distribution. Since the
issue of which probability distribution to use is unresolved (Greene, 2000), we
assumed the distributional form of ) as the cumulative normal (with f representing
the standard normal pdf) and as such the problem can be solved as a probit model.
Finally, the estimation of the linear regression model (1) will be:
>
@
>
@

iiiiiii :XMEXMyE
JOUVGEHGE
H
and11
>@


»
¼
º
«
¬
ª
)
i
i
iii :
:
XMyE
J
JI
UVE
H
1
0(4)
The factor (LQVHUWIRUPXODKHUHLVGH¿QHGDVWKHLQYHUVH0LOOV¶UDWLRODPEGD$V
previously indicated, the estimation of this inverse Mills’ ratio provides an answer
Downloaded by [Cirad-Dist Bib Lavalette] at 08:46 01 February 2013
51
Demythifying contract farming: Evidence from rural South Africa
to the issue of self-selection bias or whether the estimator of market participation
in the linear regression is biased. This is shown by the expected difference in
agricultural income between market participants and non-participants derived
from (4) as:
>@>@

»
¼
º
«
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ª
))
ii
i
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01
I
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(5)
Downloaded by [Cirad-Dist Bib Lavalette] at 08:46 01 February 2013
... Poverty is common among smallholder farmers in low-income countries (Meemken and Bellemare 2020; Lu et al. 2021) and contract farming is claimed as a tool that may change this, through increased farmer participation in global agricultural markets and subsequently improved household welfare. Numerous studies (e.g., Sharma 2008;Miyata et al. 2009;Wang et al. 2011;Bardhan et al. 2012;Barret et al. 2012;Freguin-Gresh et al. 2012;Bellemare 2012;Swain 2012;Ndoro et al. 2015;Payal and Rishikanta 2015;Kiwanuka and Machethe 2016;Chamboko et al. 2017;Masasi and Ng"ombe 2019;Belay 2020;Kiwanuka et al. 2021) have examined farmers" participation in contract farming, which is essential given the growing policy support. Most of these studies have concentrated on the crop sector with few focusing on dairy contract farming (e.g. ...
... exploitation (Freguin-Gresh et al. 2012). Bijman et al. (2020) and Ruml and Qaim (2021) contend that mistrust and lack of transparency leading to side-selling is common in contract farming which could be one of the reasons for these determining factors behind these corner solution outcomes. ...
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Smallholder farmers’ preferences for participation in contract farming may take the form of proportional data – whereby farmers only sell some proportions or fractions of output to contractors. We analyze determinants for preferences for zero (potential corner solution) and proportional amounts of milk that farmers sell through contract farming using dairy farmers’ data from Zambia. Bayesian linear, linear probability, and hurdle models are compared with a Bayesian zero-one-inflated beta regression. Monte Carlo simulations show that alternative models are biased. Meanwhile, empirical findings suggest gender and marital status of the household head, household size, and delayed payment significantly drive preferences for proportional milk sales in contract farming. Additionally, household size, experience selling through milk collection centers, total livestock units, access to dairy marketing information, and a buyer's milk price among others, tend to affect zero-inflated outcomes. We recommend a Bayesian zero-one-inflated beta regression model for proportional data and also provide strategies to overcome farmer-engagement barriers in contract farming.
... Poverty is common among smallholder farmers in low-income countries (Meemken and Bellemare 2020; Lu et al. 2021) and contract farming is claimed as a tool that may change this, through increased farmer participation in global agricultural markets and subsequently improved household welfare. Numerous studies (e.g., Sharma 2008;Miyata et al. 2009;Wang et al. 2011;Bardhan et al. 2012;Barret et al. 2012;Freguin-Gresh et al. 2012;Bellemare 2012;Swain 2012;Ndoro et al. 2015;Payal and Rishikanta 2015;Kiwanuka and Machethe 2016;Chamboko et al. 2017;Masasi and Ng"ombe 2019;Belay 2020;Kiwanuka et al. 2021) have examined farmers" participation in contract farming, which is essential given the growing policy support. Most of these studies have concentrated on the crop sector with few focusing on dairy contract farming (e.g. ...
... exploitation (Freguin-Gresh et al. 2012). Bijman et al. (2020) and Ruml and Qaim (2021) contend that mistrust and lack of transparency leading to side-selling is common in contract farming which could be one of the reasons for these determining factors behind these corner solution outcomes. ...
Article
Full-text available
Smallholder farmers' preferences for participation in contract farming may take the form of proportional data-whereby farmers only sell some proportions or fractions of output to contractors. We analyze determinants for preferences for zero (potential corner solution) and proportional amounts of milk that farmers sell through contract farming using dairy farmers' data from Zambia. Bayesian linear, linear probability, and hurdle models are compared with a Bayesian zero-one-inflated beta regression. Monte Carlo simulations show that alternative models are biased. Meanwhile, empirical findings suggest gender and marital status of the household head, household size, and delayed payment significantly drive preferences for proportional milk sales in contract farming. Additionally, household size, experience selling through milk collection centers, total livestock units, access to dairy marketing information, and buyer's milk price among others, tend to affect zero-inflated outcomes. We recommend a Bayesian zero-one-inflated beta regression model for proportional data and also provide strategies to overcome farmer-engagement barriers in contract farming.
... In Vietnam, Saenger, Qaim, Torero, and Viceisza (2013) found that even under adverse climatic conditions, well-designed contract farming with incentives enabled farmers to produce high-quality milk products, especially where bonus payments were also extended. Freguin-Gresh, d'Haese, and Anseeuw (2012) found that in South Africa, contract farming improved agricultural output and incomes through offering farmers better access to resources and services while at the same time creating opportunities for farmers to participate in markets. In India, Ramaswami, Birthal, and Joshi (2009), found that contracting offered a win-win situation for both broiler growers and poultry integrators. ...
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Full-text available
The literature on contract farming and climate change in Zimbabwe has blind spots in relation to the study of contract farming as a climate change response. While the literature on contract farming and climate change abounds, such literature is lacking when it comes to the exploration of how contract farming can facilitate climate change coping and adaptation strategies by smallholder farmers. This paper fills this gap. It draws on in-depth interviews with 10 contracted and 10 non-contract farmers who were engaged through face-to-face in-depth interviews in the Chipinge South Constituency. It found that contract farming does not only boost productivity, but it also enables farmers to positively respond to the ravages of climate change, and therefore, it should be supported and encouraged. Future research should explore more viable and sustainable way through which the state, instead of private sector actors, should be at the centre of contract farming.
... On the other hand, Freguin-Gresh., et al. suggested that contract farming derived benefits such as improved agricultural production and increased incomes for contract farmers, allowing better access to services and resources, and provided new opportunities to participate in markets. However, they concluded that contract farming did not have an effective way of reducing poverty or a systemic mechanism for improving rural livelihoods on its own [4]. ...
... Vulnerable groups may opt out voluntary due to resource constraints or risk aversion, but may also be ineligible to participate due to corporate discrimination against smaller, less resource endowed, producers (Bellemare, 2012). When contract farming schemes are not fully inclusive, especially of more marginalised groups, they risk exacerbating rural inequalities (Freguin-Gresh, d'Haese, & Anseeuw, 2012). These risks are perceptible under many oil palm contract farming schemes since participation is, due to oil palm's high labour demands, generally restricted to households with adequate labour reserves (Brandão & Schoneveld, 2015). ...
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The Government of Brazil established their Sustainable Palm Oil Production Programme (SPOPP) in 2010, which sought to enhance the sustainability and inclusiveness of oil palm development in the Amazon. This paper evaluates how well oil palm contract farming promoted by SPOPP has delivered on its inclusive development objectives. Drawing on cross-section data collected in Northeast Pará, it analyses two recurrent SPOPP themes, namely (1) equitable participation and (2) labour allocation to plantation management. Our analysis demonstrates that household availability of land and labour resources strongly shapes patterns of inclusion and exclusion. Moreover, findings reveal that labour time allocation is influenced by hiring of external labourers, which increases when households are labour and land poor. These results give reason to question the utility of labour-oriented contract farming eligibility criteria, revealing important inclusive business and value chain development dilemmas.
... Contracts solve several constraints smallholders face in producing and marketing their output. However, several studies criticize contract farming as it creates income inequality, which in turn creates inequality in the community (Minot, 2011;Freguin-Gresh et al., 2012), or excludes smallholders, as traders prefer to contract with medium and large farmers due to characteristics of the crops that make them particularly unsuited to smallholders (Nankumba and Kalua, 1989;Saenger et al., 2012). Some studies show that contract farming can strengthen value chain relations (Schipmann and Qaim, 2011) and improve smallholders' access to better technology, improve seed varieties and other inputs, increase income, and reduce transaction costs (Minten et al., 2009;Barrett et al., 2012;Abebe et al., 2013). ...
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To document indigenous knowledge and farmers’ know-how related to the leafy vegetables Launaea taraxacifolia, Bidens pilosa and Alternanthera sessilis, an ethnobotanical investigation using participatory approach research methods and tools, was conducted in 19 villages randomly selected across ethnic and agro-morphological zones of southern and central Benin. The geographical distribution of the three species was established and the southern area appeared suitable for an in situ conservation programme of genetic diversity of these leafy vegetables. Respectively, 11.11%, 55.56% and 90% of the respondents reported that Launaea taraxacifolia Bidens pilosa and Alternanthera sessilis are still harvested from the wild (level 0 of domestication) while 22.22% and 16.67% of respondents reported that L. taraxacifolia and B. pilosa are being cultivated (level 4 of domestication). Uprooting and cutting plant stems were the most common harvesting methods. The study revealed the existence of morphotypes resulting in the identification of different varieties of L. araxacifolia (three varieties), B. pilosa and A. sessilis (two). The frequency of consumption of each of the leafy vegetables and its consumption method varied according to the ethnic group. Regarding methods of preparation, sauce made from fresh leaves was reported only for L. taraxacifolia while precooked leaves were otherwise used. The respondents also reported that these leafy vegetables possessed, in addition to their culinary value, several medicinal virtues. L. taraxacifolia was the most valued medicinally and is used for the prevention or healing of 21 diseases with 16 possible pharmacological functions. Further research is required on the biochemical and phytochemical characterization of the genetic diversity of these species as well as the effects of processing methods on their nutritional value.
... However, it has limitations when it comes to taking into account non-numerical factors, and when using such a methodology is employed there are often difficulties with the inclusion within the analysis of the pre-existing gap between participants and non-participants. Overcoming the gap is 6 7 important since several studies suggest that the positive or better impacts of CF might derive from the exclusion of smallholders from CF (Freguin-Gresh, D'Haese, and Anseeuw 2012;Ito, Bao, and Su 2012;Neven et al. 2009). These studies suggest that participants tend to be better-off than non-participants before participating into CF because the transaction costs can be lower if the buyer deals with a few larger-holders rather than many smallholders. ...
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This review challenges two major presumptions made by previous studies: (1) that contract farming can be understood only in a polarized term, as an agricultural model that is either inclusive or exploitative (2) that Sub-Saharan smallholders must be somewhat ambiguously viewed as being “passive receivers of aid” who need to be “helped out of poverty.” Although more recent studies have placed greater focus on diverse pictures, an absence of concepts that reflect reality on the ground, is causing them to continue to adopt unrealistic representations of contract farming and smallholders. By contrast, this review works to overcome the limitations of previous studies of contract farming by focusing on context-specific pictures, including embedded inter-and intra-household relationships such as kinship, lineage, and gender. For this reason, this review draws upon a broad spectrum of discussions regarding peasants, including those that took place in peasant studies, anthropology, sociology, and moral economy from the 1950s onwards. Moreover, it also takes into consideration context-specific research on large-scale land deals, and provides original means of conceptualizing the unexpected research findings.
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Determining an effective approach to replacing chemical fertilizer with organic fertilizer is a difficult challenge for the Chinese government. This paper constructs a dynamic analysis framework with broader application than previous statistical and case studies by theoretically deriving the impact of farmers' participation in contract farming on their organic fertilizer application behavior. The framework analyzes farmers' intertemporal organic fertilizer application behavior under the two scenarios of participation and nonparticipation in contract farming. Participation in contract farming positively impacts organic fertilizer application behavior in both the short and long terms. Survey data from 473 vegetable farmers in Shandong province of China were used to conduct an empirical analysis, and the endogenous switching probit model was used to solve the endogeneity problem of farmers' participation in contract farming. The empirical analysis supports the above results: farmers' participation in contract farming increases their probability of applying organic fertilizer by 50.7%. Robustness tests conducted using the recursive bivariate probit model and replacing the dependent variable (the intensity with which farmers replace chemical fertilizer with organic fertilizer) confirm the research results. Further heterogeneity analysis shows that farmers' participation in contract farming has a more obvious promoting effect on organic fertilizer application behavior in the older group, the group with an education level of primary school or below and the small-scale farming group. Therefore, the government should promote participation in contract farming, especially among elderly, low-education and small-scale farmers, to improve the adoption level of organic fertilizer in China.
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The main objective of this article is to review the research by agricultural economists over the past decade on linking smallholder farmers to agri-food supply chains in Southern Africa, and to consider international and local urban trends in the development of such supply chains. The research reviewed covers the constraints placed by transaction costs on access by smallholder farmers to input and product markets; the potential role of contracting in linking smallholders to agribusiness firms; linking smallholders to supermarkets; equity-share schemes; the role of trust in a business relationship; promoting investment in smallholder agriculture by developing rental markets in communal areas; and the role of collective action (e.g., the formation of cooperatives, investor-owned firms or trusts) in promoting access to input and product markets. The development of alternative food networks in urban areas, which face a growing influx of poor people, could provide opportunities for smallholders, as individuals or groups, to supply the communities with the products and services they desire.
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Conservation agriculture (CA) is often perceived to provide "win-win" outcomes for farmers leading to reduced erosion and off-site sedimentation, as well as improved soil fertility and productivity. However, adoption rates for CA in many regions of the world remain below expected levels. This article looks at the effects of participation in organic markets and farmers' organizations on the adoption of soil conservation practices. Based on original survey data from 241 small-scale farm households in Honduras, we find that both participation in organic markets and farmer-based groups have positive effects on the number of soil conservation practices adopted. The results indicate that besides supply-oriented policy measures, such as the provision of technical assistance and extension, demand-related factors are likely to play an important role in sustainable soil management. Demand-oriented policy measures include support for labeling initiatives and consumer education to facilitate value-added product differentiation and market segmentation. Copyright (c) 2010 International Association of Agricultural Economists.
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The expansion of contract farming in Africa has elicited considerable debate. This article examines the impact of a new contract farming scheme on small farmers in KwaZulu-Natal. Scheme participants and the company which established the project both extol the virtues of the Dakadaka irrigated sugar cane scheme and there is a keen interest among nearby farmers in joining it. However, despite many positive features of the scheme, the dependence on sugar cane is a major potential problem. Company control of irrigation water and the employment of children at low rates of pay are further issues of concern.