transaction costs and farm-to-market linkages: empirical...
TRANSCRIPT
Transaction Costs and Farm-to-Market Linkages: Empirical Evidence from China Apple
Producers
By Jianyun Hou Xuexi Huo*
Northwest Agriculture & Forestry University
This article estimates the impact of transaction costs on smallholders’ market
participation and integration, using the data collected in two apple production belts
of China. Based on an innovative measurement of the transaction costs, and a
disaggregated analysis on sales costs, information costs, negotiation costs and
monitoring costs. The study shows that levels of the farmers’ market participation
are mainly determined by the proportional transaction costs and price, while their
market integration depends on the fixed transaction costs and price. This suggests
that, in order to lower the transaction costs and enable specialization and market
participation, it is necessary to invest and construct the farming infrastructure,
update the rural information system, improve the structure of farmer households,
and subsidize the cooperative organizations.
Key words: market participation, market integration, transaction costs, China apple
producers.
* Respond author: [email protected]; +82-29-87081059
We are grateful to the China Natural Science Foundations (CNSF70973098 & CNSF71203181) and China
Agriculture Research System (CARS-28) for research funding.
1. Introduction
The development of agriculture continues to play a key role in the transformation of economies.
Practically, China agri-food markets are undergoing profound changes fueled by economic
development, increases in per capital income, changes in technology, and expansion of
urbanization. Higher income forces mean greater demand for high-value commodities (Pingali et
al., 2005). However, agricultural commercialization puts increased emphasis on specialization,
which is not confined to the production of high-value crops (like apple, the dominant type of
horticultural products in China). Often such transformation is accompanied by diversification of
smallholder farming toward high-value activities linked to modern markets (ADB, 2013). At the
same time, both commercialization and commercialization of smallholder agriculture in
developing markets faces challenges, which include information barriers, high transaction costs,
and high market fees. In addition, rapidly changing markets create new challenges for the sub-
sector. Already sanitary and phytosanitary standards in the global market have been tightened
while new standards are being applied to address previously unknown and unregulated risks,
especially in high value products markets. Meeting those standards represents potential barriers,
especially to small producers and their market intermediary organizations seeking to expand their
trade opportunities in the local or global markets. Policy interventions therefore require a clear
understanding of how smallholders are affected by transaction costs and what institutional
arrangements can enhance opportunities.
In China, supply chain integration is becoming a major strategy for guaranteeing fresh and
perishable products to urban market outlet (Ruben and Kruijssen, 2007).The local farmers use
different mechanisms and procedures for delivering agricultural products to markets, giving to a
wide variety of supply chain arrangements. Some retailers are developing preferred-supplier
arrangements with local growers, while others still purchase their products from dedicated
wholesalers at the local and regional market (LWM). The choice between these different
procurement strategies critically depends on differences in competitive relations and the consumer
demands which lead to a particular structure of transaction costs perceived in the local market
(Dorward, 2001; Pitelis, 1993).
On the production side, the apple producers in China can choose to sell all, a portion or none in
the farm-gate, local or global markets. To our knowledge, little work in economics has been done
on the factors affecting the selection of China’s farmers’ market integration (Yao and Qi, 2012).
One percussive explanation for an apple producers’ choice of marketing channel(s) may be the
transaction costs that alternative outlets impose on the sell. Many farmer households do not
participate in certain agricultural markets due to the existence of the transaction costs. Although
the literature clearly prove that high transaction costs can deter smallholder from entering more
specialized, but at the same time, more profitable agricultural markets, the literature has not
provide empirical evidence on how market integration may polarize a small farmer
economy(Escobal and Cavero, 2012). Moreover, the relationship between these costs and
marketing strategies has received little attention. Additionally, an important criticism of the
literature on transaction costs is that theoretical development has not been accompanied by
successful measurement of transaction costs. The objective of this research is to adopt a transaction
cost economics (TCE) framework and identify how smallholders are affected by transaction costs
and what institutional arrangements can enhance opportunities of the farm-to-market linkages in
China.
This article is divided into six sections, including the introduction. The second section presents
a brief overview of literature on transaction costs and institutional arrangements. The third section
reports the theoretical model and hypotheses to be tested. The fourth section discusses the
empirical results, followed by conclusions and policy applications.
2. Literature Review
According to the seminal work of Coase (1937) and Williamson (1979), transaction costs can
be defined as a trade-off between the costs of coordination within a transacting organization and
forming contracts in the market. Furthermore, the transaction costs economics (TCE) suggests that
agents make decisions on various types of transactions in a costly way because of transaction costs
associated with information, monitoring, coordination and enforcement of contracts. Those
intermediary firms economize on such costs, such as smallholders choosing which markets to sell
particular agricultural output. This depends not only on the price they expect to receive but also
on extra fees related to transacting in these markets.
Transaction costs have been divided into two categories, proportional costs and fixed costs (Key
et al., 2000). The proportional transaction costs include every-unit costs of participating markets
related to transportation costs, asymmetric information and bargaining power. The fixed
transactions costs are independent of the quantity of a transacted good. They include the costs of
information, bargaining, and monitoring costs. The information costs are incurred before the trade
takes place and consist of the cost of searching for higher prices and seeking potential buyers. The
negotiations costs occur during the trade, like the time of negotiating a contract, concluding an
agreement and making arrangements for settlement. Renos et al. (2003) suggest that to what extent
a farmer can lower these transaction costs usually is decided by individual characteristics
(education, skill, and gender), output attributes, and the relationship between agents participating
in the market. Finally, the costs of supervision are incurred to make sure that the trade conditions
are met.
As transaction costs are an effective explanation for farmers’ choice of marketing channels or
type of contracting arrangements, a substantive volume of literature has been applied to
agricultural market (e.g. Traversac et al., 2011; Teece, 2010). The application of transaction costs
approach to inform action is not limited to crop choice, but also the choice of livestock marketing
channels (Hobbs, 1997). The study revealed that some transaction costs variables (such as grade
uncertainty, risk of not selling, time spent at the auction) were the significant factors affecting the
choice of either live-ring auction or direct-to packer sales. A similar study by Mathye et al. (2000)
addresses the choice of marketing channels for smallholders who produce bananas and mangoes
in northern province in Butundi. Various factors affect the choice of the market channel, but the
study found that problems of transport, searching for markets and education tend to influence more.
Using the same method, a few studies have discussed the effect of the transaction costs on output
markets (Omamo, 1998; Jagwe, 2011). A growing interest is shown in the research of the
transaction costs in the fields of apple, orange, banana, maize, cattle, vegetable, coffee, and milk
marketing (Qu and Huo, 2007; Hou and Huo, 2013; Woldie and Nuppenau, 2011; Staal et al., 1997;
Donovan and Poole, 2014; Holloway et al., 2000). Gabre-Madhin (2001) addressed another side
of the output markets by focusing on the transaction costs in the choice of market institutions such
as grain brokers in Ethiopia. In this case, traders first choose where to trade and then choose
whether to use a broker for searching on their behalf. The study indicates that high transaction
costs shown by traders’ individual rationality in selecting brokerage is linked to increased broker
use, while high social capital reduces the use of brokers. Fafchamps and Minten (2002) show that
social capital or networks play an important role in the resolution of dispute among traders, that is,
trust-based relationships are the dominant contract enforcement mechanism among traders.
Another line of research focuses on the relation between transaction costs and contract choice.
Dorward (2001) takes account of the socioeconomic characteristics of sellers and buyers,
economic and technical characteristics of the commodity, as well as the institutional environment.
He develops a non-linear programming model for individual firms’ supply chain decisions to
provide a framework for the application of the transaction cost economics to analyze policy
interventions in developing markets. Recently, there are some interesting studies focusing on
various contractual arrangements of cashew, tea, apple, and pear producers’ contract choices in
transition economies employing different frameworks (Cai and Han, 2011; Degla, 2012; Stifel et
al., 2003;Escobal et al., 2012).
In contrast to the latest work, we are interested in exploring the relations between price and
transaction costs on various marketing strategies in more profitable agricultural markets. This
study focuses on several determinants of farmer households, providing empirical evidence on what
circumstances market integration may function under with a database of 635 China apple
producers.
3. Apple Production in Chinese Agro-economy
As the dominant perennial horticultural crop, the apple plays a pivotal role in China farmers’
income increase and agriculture transition (Wang et al., 2012). It contributes to poverty reduction,
trade balance and raw materials for agro-industries. The locations of the apple planting areas are
shown in Figure 1. These districts are distributed in northern China and group into two broad belts,
named Bohai Rim (including the provinces Liaoning, Shandong and Hebei) and Loess Plateau
(including the provinces Henan, Shanxi, Shaanxi and Gansu). These provinces are endowed with
a generally favorable climate for apple production, but differ in the intensity and the orchard model
of apple produced, agro-ecological characteristics and accessibility. The regions contain different
agro-ecological zones that indicate the cultivation mode and type of apples that can be produced
in accordance with the local altitude and climate. The Bohai Rim Belt is located at a lower altitude
with rich rainfall and mainly produces for export market and up-market. Loess Plateau is located
at a higher attitude with less rainfall and mainly produces for domestic market and processed
market.
In terms of proximity to the harbor and mega-city clusters, the Bohai Rim is much closer to
Dalian-Beijing-Tianjin-Tangshan-Qingdao Urban Agglomeration and Shandong Peninsula Urban
Agglomeration, which offer a large up-market for domestically consumed apples owing to its large
and rapidly increasing higher income population. Furthermore, most apples for export are
packaged and shipped from the harbor of Tianjin and Qingdao.
Since 1978, the ratio of the apple planting area in China experienced four stages: 1978-1989,
1990-1997, 1998-present (See Figure 2). Especially in 1982-1989 and 1991-1996, apple
cultivation in both Bohai Rim and Loess Plateau maintained a rapid growth. After 2008, the apple
planting began to expand westward and northward. In 2014, China contributes over half of the
global apple production and is forecasted to 27.52 million MT. Overall apple planting area reached
2.31 million hectare. Ranked according to total production, Shaanxi accounts for 26.80% at 14.2
tons per ha., Shandong at 22.46% with 26 tons/ha, Henan at 9.81% with 20.4 tons/ha, Hebei at
9.69% with 10.8 tons/ha, Shanxi at 8.25% with 16.2 tons/ha, Gansu at 8.17% at 6.9 tons /ha and
finally Liaoning at 7.72% with 15.9 tons/ha. These two regions contribute 88.2% of the total apple
production in China (as shown in table 1). The smallholders predominantly produce apples, thus
this study focuses primarily on the apple production. About 98% of apples produced are consumed
in domestic market, while the remainder is exported. Despite its overall minority share of
production for export, the sub-sector earns the country tremendous amount of foreign exchange in
agriculture (See Figure 3).
4. Sampling Method and Statistical Description
4.1 Sampling Method
The current study involved a field survey that was conducted by China Agriculture Research
System (CARS) during the 2012/13 cropping season for project on Economic Impact Assessment
in Apple. The survey was purposefully conducted in the two apple planting belts, which are located
in Bohai Rim (Liaoning, Hebei and Shandong) and Loess Plateau (Henan, Shanxi, Shaanxi, and
Gansu). These selected provinces represent approximately 92% of the smallholders that produce
apples for domestic and outside markets. The geography location of sample provinces are shown
in Figure 1.
A multi-stage sampling procedure was used to select counties, sub-divisions and small scale
producers. The first stage was the deliberate selection of 122 counties in 7 provinces mentioned in
section 3. To ensure all apple producers were included in the sample, the Probability Proportional
to Size sampling method was used. Overall, 14 counties were randomly selected in the seven
provinces and 635 apple producer households were selected for interview (See Table 2). Via face-
to-face questionnaire interview, detailed information on apple production and transaction costs are
collected.
All sample households are net apple sellers that trade the majority of their production in the
three candidate markets. Household characters are shown in Table 3. Particularly, as one of the
important household characters, membership in an institution may help smallholders to facilitate
market integration and lower transaction cost. In table 3, we consider one membership, namely
“Producers' Cooperative Organization”; 40% of total households join a producers’ self-
organization, which provide them with technical training, information service, and input- factor
buying and apple selling helps.
4.2 Statistical Description
However, the smallholders (defined as farmers with land sizes≤1 ha.) dominate the apple
production in China (see Table 3). Smallholders have limited access to inputs, finance and new
technology. Inadequate infrastructure, high costs of storage and transportation and over-
competitive markets also militate against the production of marketable surplus. Their market
participation is therefore typically constrained choice, and such choice critically depends on their
ability and willingness to participate in input and output markets and on the functionality of those
markets that they are able to access. The smallholders, as sellers of apple, are likely to increase
their engagement in markets when well-functioning markets give them appropriate incentives; they
have access to, and the ability to use assets productively, and efficient infrastructure allow them to
transport their product to market at reasonable cost. As apple is a type of highly commercial crop,
producers have become more commercially oriented and facilitating participation in the processes
of value chain development, which may require support to assistant producers in meeting more
rigorous standards, or engaging in the more complex contractual arrangements.
The apple producers are able to choose to sell their output at farm gate market, or in local and
distant markets. The local markets usually situate in central town of high potential counties, and
the country’s central and the largest logistic and wholesale market is located in the biggest cities,
like Beijing, Shanghai, Guangzhou, Chongqing and Xi’an. In general, the apple producers will
receive higher prices but face more transportation difficulties at regional and distant markets (See
Table 4). The transportation distance varying from 0 to 1753km, transported by individual farmers
to reach the markets is diversified based on household specific.
5. Theoretical and Empirical Model
Following the research of Key et al. (2000), we incorporate the transaction costs into the farmer
household model framework. The farmers’ market participation can be specified as a choice model.
In addition to deciding how much of each output i to consume ( ic ), produce ( qi) and use of input
( xi ). The household also decides how much of each agricultural output to sell ( mi ). When the
farmer household sells the output, 0mi . When the household purchases such output , 0mi . If
we suppose that there were no transaction costs, the household problem would be maximize the
utility function（1）subject to （2）-（5）, which indicate the cash constraint, the resource
balance , production technology and non-negativity condition.
);(max zcuu u （1）
Subject to
01
Tmp i
N
i
m
i （2）
NicmAxq iiiii,,1,0 （3）
0);,( zxqG q （4）
0,, xqc iii （5）
Where pm
i the market price of output is i , Ai is endowment in good i , T is exogenous transfers and
other incomes, zu and zq are exogenous shifters in utility and production, respectively, and G
represents the production technology.
The cash constraint（2）states that expenditures on all purchases must not exceed revenues
from all sales and transfers. The resource balance（3）states that, for each of the N goods, the
amount consumed, used as input, and sold is equal to what is produced and bought plus the
endowment of the good. The production technology（4） relates inputs (e.g. land, labor and other
input-factors) to outputs. Proportional transaction costs (PTCs) raise the price paid by a buyer and
lower the price received by a seller and these costs may include transportation and marketing costs
(Key et al., 2000). However, the fixed transaction costs (FTCs) are invariant to the quantity
transacted; hence they are generally unobservable through factors zu and zq with coefficientssi
andbi , respectively, can explain these costs. Incorporating both the FTCs and the PTCs into the
cash constraint of farmer households, it can then be expressed as shown in equation（6）:
0))())()]))(())([(1
Tzfczfcmzvcpzvcp bi
bb
i
si
ss
ii
N
i
bi
bbi
m
i
si
ssi
m
i （6）
where the household pays the fixed transaction cost fcs
i and variable transaction costs vc
si if it sells
good i and pays fcb
iand vc
bi it buys good i. To solve for the household problem, a Lagrange
expression can be derived and first order conditions for the consumption goods obtained from
equations（1）-（6）.
Tzfczfcmzvcpzvcp
zxqGcmAxqzcuL
bi
bb
i
si
ss
ii
N
i
bi
bbi
m
i
si
ssi
m
i
qiiiii
N
i
iu
))())()]))(())([(
);,()();(
1
1 （7）
where i, and are the Lagrangian multipliers of resource balance, cash constraint, production
technology. FOC of （7） can be written into:
}0|{,0
cii
c
uii
i
（8）
}0|{,0
qii
q
Gi
i
i （9）
}0|{,0
qii
q
Gi
i
i （10）
}0|{,0
xii
x
Gi
i
i （11）
}0|{,0]))(())([ miizvcpzvcp ibi
bbi
m
i
si
ssi
m
ii （12）
The decision price pi is thus defined as:
vcpp si
m
ii If 0mi
, for the selling household
vcpp bi
m
ii If 0mi , for buying household
iiipp ~ If 0mi , for self-sufficient household
The supply curve in absence of the transaction costs would be ),( zpq q
m. However, when the
transaction costs are incorporated, the supply curves for the producers are:
),( zfctcpqq q
ssm （13）
Most empirical analysis suppose that the supply function is linear and the detail expression is as
follows:
qqq zpzpq ),( （14）
This leads to linear expressions for supply by sellers as follows:
s
t
st
m
m
szzpq
*
（15）
where z t are exogenous characteristics that affect transaction costs when selling, zq are production
shifters, zc are consumption shifters and sq ,
sc are their coefficients, and
s
t, q
are coefficients
of zst and zq respectively.
The econometrical model of the farmer household market participation can be obtained as:
uzzpq qq
s
t
st
m
m
s *
（16）
where u is an error term.
The final decision for the household is on which market to sell its output q . We focus on the
farm-household who are net-suppliers. Then if there exists J available markets where farm-
households can sell qi, and the farm-household’s decision depends on three factors. Firstly, selling
in market j for a given transaction i is associated with variable transaction costs vcsij per unit of
product. These costs are a function of the market costs and the transportation costs. Secondly, the
household considers the expected price pij
to be received on each candidate market j .Finally,
selling on market j is associated with fixed transaction costs fcs
ijwhich are invariant to the costs
like searching for potential buyers and obtaining information about prices, markets, or types of
contractual agreements available at different markets.
Based on the above, given a transaction i , a farm-household chooses to sell qi in the market j
i
that yields the highest net profits among the available candidate markets. This can be written in
the semi-structural form as:
),,,(maxarg vcfcpqj sij
s
ijijiik
i （17）
where i is the net profit function. We specify the econometric model ofi as following:
ikkiikik W X* （18）
Let jidenote the market choice that maximizes profits for transaction i
Jkj ikk
i,,1,maxarg * （19）
Suppose that ik are distributed with typeⅠextreme value distribution, the choice of market j for
transaction i is given by:
J
k
kiik
jiik
iiki
W
WWjj
1
)exp(
)exp(),|Pr(
X
XX （20）
If we divide the markets J into three types: farm-gate market, regional market and distant market,
what should note here is that three types of markets are some ordered reaction to farmer-household.
As shown in Figure 5, comparing the farm gate market with the local market, there are more
barriers in the local market than in the farm gate market. For instance, these barriers include,
inefficient rural infrastructure, higher transaction costs, inequitable and uncompetitive market
relations, and a lack of innovative institutions (Kisamba-Mugerwa 2005). Similarly, the distant
market, like regional and/or national markets, require higher private grades, standards for food
quality and safety, and the adoption of contracts between buyers and sellers at various points along
the agri-food chain.
Considering barriers of entry into farm gate market, local market and distant market, we can
formulate a discrete choice variable taking values of 1, 2, 3, respectively. Scenario 3 has more
requirements for the smallholders than Scenario 2, which has more requirements than Scenario 1.
Therefore, when discrete choices have ordinal relevance, an Ordered Probit Model may be the
most appropriate specification (Sykuta 2008). The ordered probit probabilities of choice among
the farm gate market, the local market and the distant market are given by:
)()1Pr( 1 ixj （21）
)()()2Pr( 12 ii xxj （22）
)(1)3Pr( 2 ixj （23）
where is a threshold parameter that is estimated with . Mathematically, the marginal effects of
the Ordered Probit Model are given by:
)()1Pr(
1 ik
k
xx
j
（24）
)]()([)2Pr(
12 iik
k
xxx
j
（25）
)()3Pr(
2 ik
k
xx
j
（26）
Assuming is positive, increasing the value x while holding the parameters constant
effectively shifts the probability distribution to the right. In this research, the )1Pr( y must
decline and the )3Pr( y must increase as the probability distribution shifts to the right. Thus, a
positive value may be correctly interpreted as implying a positive relation between the variables
of interest and the probability of 3y (distant market). However, because the relative mass of the
distribution moving from 1y to 3y , the net effect on )2Pr( y is ambiguous and requires
more detailed examination. Thus, a statistically significant positive value for is not sufficient to
conclude the probability of all higher outcomes increases.
6. Econometric Results
6.1Variable Description
For the purpose of this study, we divide the transaction costs as two categories, namely the
proportional transaction costs and the fixed transaction costs. The proportional transaction costs
are represented by sale costs (which include the costs of storage, package and transportation),
information symmetry and bargaining power. The fixed transaction costs include information costs,
negotiation costs and enforcement costs. Information costs occurred before the trade while
attempting to obtain the information about price and buyer; negotiation costs are the costs of
concluding an agreement; and the enforcement costs are the costs to monitor the enforcement of
the transaction. Furthermore, the detailed descriptions are given as following (see Table 5).
The Proportional transaction costs are parts of the transaction costs that change according to the
amount of output traded and represented by the sales costs, information symmetry and bargaining
power. In this context, the apple producers are asked with three questions, namely “How much the
sale costs that you paid for the transaction, for instance, the cost of storage, package and
transportation?”, “Do you know the sale price at the other two markets?” ( the scale of 1-3), and
“Do you think it’s a fair price that you received?” (the scale of 1-3).
Information of the transaction can be costly and difficult to obtain. Therefore, the apple
producers are asked “How much do you pay the broker for searching buyers”, “Number of
enquiring price”. Time spent on negotiation for an agreement and the form of sale contract are
used to represent the negotiation costs. Finally, we consider the monitoring and enforcement costs.
A monitoring cost is incurred by the problem of payment delays and default. The frequencies of
payment delay and default, both of which take the value of 1-3, and the methods of payment are
used to represent the costs of monitoring and enforcement.
6.2Market Participation Function Estimation
To test hypothesis one, we firstly estimate the effect of transaction costs on apple producers’
quantity sold with a semi-log model. The specific model of the smallholders’ market participation
function is as following:
iAREAAREAAREAAREA
AREAAREAYEARMEMBERLABOREDU
AGEPLOTSIZEPRICEDEFAULTPAYMENT
CLEARFORMCONTRACTINTIMESBARGATIMESPRICE
BROKERFEEFAIRPRICEEMARKETPRICSALECOSTQ
7654
32
23222120
191817161514
131211109
8765
43210
（27）
The independent variable of this model contains three parts, proportional transaction costs and
fixed transaction costs, market price, household characters and dummy variable of smallholders’
living area. The OLS estimation results are presented in Table 6. From the analysis, the household
market decision is a trade-off between transaction costs and price. Specifically, the quantity sold
in the market is mainly determined by the proportional transaction costs and the farmer household
demographics. The fixed transaction costs have little effect on the dependent variable.
The results indicate that the quantity sold in market has positive reciprocal causal relationship
with sale cost (SALECOST) at the 5% level, and is influenced positively by the accuracy of other
markets price (MARKETPRICE), negatively by the fairness of market price (FAIRPRICE).
Market price is found to be significant at the 1% level to explaining a higher quantity sold. In
regard to the households’ characters, total land coverage dedicated to the apple production
(PLOTSIZE), the amount of household labor working on the apple production(LABOR),
membership of the cooperatives (MEMBER), as well as years of professional experience have the
positive effect on the quantity sold. Age of head of household (AGE) has a negative effect. In
general, education level does not have much of an impact on the market participation.
6.3 Market Integration Estimation
According to the results of section 3, we consider Farm gate, Local and Distant Markets as
degrees of entering barriers. Therefore, the Ordered Probit Model is applied to estimate the effects
of the transaction costs on the apple producers’ market integration. The specific function of the
Ordered Probit Model is:
ξPRICEαDEFAULTαPAYMENTα
CLEARFORMαCONTRACTαNTIMEBARGAIαTIMESPRICEα
BROKERFEEαFAIRPRICEαEMARKETPRICαSALECOSTααY
++++
+++
+++=
11109
8765
4321+0
（28）
Formula (28) is usually estimated by Maximum Likelihood function and the likelihood function
can be written as:
))-(-)-(ln(=
)|=Pr(ln=ln
′1-′
1= 1=
1= 1=
∑∑
βxμFβxμF
xjyL
ijij
n
i
J
jij
ii
n
i
J
jij
y
y
∑∑
（29）
Table 7 and 8 present the regression results estimated by STATA 12.0 and the relative marginal
effects of model (14). The results show that the market integration is mainly determined by the
fixed transaction costs and the apple price. Negotiation costs, namely times of bargaining
(TIMEBARGAIN) and form of sale contract (CONTRACT) have significant effect on market
integration, which indicate that the closer from market to apple producers, the lower transaction
costs and market price received. In regard of enforcement and monitoring costs, if the apple
producers could not be paid in time and buyer postponed payment or owed, they prefer to closer
markets.
7. Conclusions and Policy Implications
Since Chinese government launched the reform of the agricultural system in 1978, China has
established a market-oriented agricultural system. But China's agricultural market is still lacking
of effectiveness and efficiency because of the lagging reform of the farming-land property right
system, the slow development of the specialization and scale farmers, the weak service functions
of the farmer-self organizations (like cooperatives), the poor rural and farming infrastructure, and
the inefficient regulation system for agricultural market. Therefore, the agri-chain arrangements
of China are suffering serious challenges, namely high transaction costs and the market risk. The
majority of the famer households face significant market uncertainties without reasonable risk-
sharing techniques and mechanism, which induce new institutional arrangement and
organizational innovation. Empirical evidence suggests that the smallholder’s market integration
is a trade-off between the transaction costs and price. Specifically, the levels of the farmers’ market
participation are mainly determined by the proportional transaction costs and price, and their
market integration depends on the fixed transaction costs and price.
We have shown what factors are most relevant to the smallholders’ decisions to enter the agri-
industrial markets. It is the markets that can absorb increasing quantities of the apple providing
higher returns to the producers to overcome the transaction costs. Moreover, their farming land
scale, labor size, and the degree of systematization have positive effect on the quantity sold in
markets. Therefore, the key constraint factors effecting on farm-to-market linkages from the small-
land scale, the low level degree of systematization and the high transaction costs need to be
overcome.
As Escobal and Cavero (2012) indicate that, with the help of an external actor that helps to
develop coordination between the small farmers and reduces the transaction costs to advance the
farmers specialization. If the government wants to truly level the economic playing field they may
need to improve market context and reduce the transaction costs smallholders face, in addition to
investing and constructing the rural and farm infrastructure, updating the rural information system,
and other policies aimed to improve their connections to integrated markets. Also, the governments
should pay more attention to perfect the laws and policies to improve the structure of farmer
households. Furthermore, functions of the cooperatives and other farmer self- organization need
to be improved, which will not only make more likely that the less endowed smallholders enhance
their opportunities to access integrated markets but also increase their net incomes once.
Appendix
Figure 1. Apple Planting Belts of China
Source: The Ministry of Agriculture of the People's Republic of China
Figure 2 .Trends of Apple Planting Areas By Growth Rate
Source: China Agriculture Statistical Yearbook (1982-2014)
Table 1. China’s Apple Production in 2012-2014
Source: The Ministry of Agriculture of the People's Republic of China, http://www.gov.cn
Figure 3. Apple Yields per Hectare of Seven Main Provinces (2009-2014)
Source: China Agriculture Statistical Yearbook
Region
2012 2013 2014（F）
Yield Percentage Yield Percentage Yield Percentage
（million ton） （%） （million ton） （%） （million ton） （%）
China 33.70 100.00 31.70 100.00 27.52 100.00
Shaanxi 9.10 27.40 8.20 25.80 7.37 26.80
Shandong 7.40 22.30 6.88 21.70 5.90 21.46
Henan 2.97 8.90 2.86 9.00 2.70 9.81
Hebei 3.10 8.40 2.90 9.20 2.66 9.69
Shanxi 2.60 7.80 2.30 7.30 2.27 8.25
Gansu 2.50 7.50 2.30 7.30 2.25 8.17
Liaoning 240.00 7.20 250.00 7.90 212.46 7.72
Figure 4. Trends of Apple Exports
Source: FAO (2014)
Table 2 .Sample Distribution
Source: Field Survey
Province Henan Shandong Liaoning Hebei Shaanxi Gansu Shanxi
Sample Size 91 90 91 91 91 89 92
Percentage（%） 14.33 14.17 14.33 14.33 14.33 14.01 14.49
Table 3. Apple Producer Household Characteristics
Variable Variable Description Measurement Frequency Percentage (%)
PLOTSIZE Total land size for apple production
≤0.5ha. 350 55
0.5～1ha. 216 34
＞1 ha. 69 11
AGE Average age of householder
≤40 years 69 10.87
40～60 years 445 70.08
＞60 years 121 19.06
EDU Final education level of householder
None 14 2.2
Initial 113 17.8
Primary 353 55.59
Secondary 150 23.62
Higher 5 0.79
LABOR Size of adults engaged in farming
≤2 46 7.24
2～4 547 86.14
＞4 42 6.61
MEMBER Join the rural cooperative organization or not Yes=1 254 40
YEAR Experienced years of apple production
≤10 49 7.72
10～20 309 48.66
＞15 277 43.62
Source: Field Survey
Table 4. Market Price, Quantity and Transportation
Market Farm-gate Market Regional Market Distant Market
Number of household transactions 387 220 28
Average Price(yuan/kg)
Premium Grade 5.16 5.46 6.4
First Grade 4.32 4.36 4.5
Second Grade 2.52 2.8 3.6
Average Market distance(km) 0.85 7.58 118
Average Levels of transportation Difficulties
(1=very easy~5=very difficult) 1.01 1.18 3.71
Source: Field Survey
Figure 5 .Three Scenarios of Apple Producers’ Market Choices
Table5. Transaction Costs Related Variables
Variable Name Variable Description Measurement Variable
Property
SALECOST Sale cost How much did you pay for store, package and transportation Ration variable
MARKETPRICE Accuracy of markets
price
Do you know the sale price at another two markets
Unclear
Not so clear
Very clear
Ordinal variable
1
2
3
FAIRPRICE Fair price or not Do you think the price you received is fair or not Ordinal variable
Very fair 1
Not so fair 2
Very unfair 3
BROKERFEE Fee paid brokers How much money you paid brokers for searching buyers Ration variable
TIMESPRICE Times of searching price How many times was the price to be enquired Ration variable
TIMEBARGAIN Times of bargaining Do you spend long time on bargaining Ordinal variable
Very long 1
Not so long 2
Very short 3
CONTRACT Form of sale contract Do you sign a formal contract with buyer
Yes
No
Dummy variable
1
0
CLEARFORM Clearing form Form of clearing transaction Ordinal variable
Buyer paid all Cash 1
Buyer paid cash partly 2
Buyer owed 3
PAYMENT Time to get paid How long time you get paid Ordinal variable
After transaction 1
One week after transaction 2
Default 3
DEFAULT Frequency of default How often buyers are in default Ordinal variable
Never 1
Occasionally 2
Sometime 3
Table 6. OLS Regression of Household Market Participation Function
Dependent Variable Quantity sold in market(log of quantity)
Independent Variable Coefficient Standard Error T value P>|T|
Proportional transaction costs
SALECOST 0.0001** 0.0001 2.27 0.024
MARKETPRICE 0.0840*** 0.0303 2.77 0.006
FAIRPRICE -0.1219* 0.0631 -1.93 0.054
Fixed transaction costs
BROKERFEE 0.0004** 0.0001 2.78 0.006
TIMESPRICE 0.0089 0.0057 1.57 0.116
TIMEBARGAIN 0.1289** 0.0594 2.17 0.030
CONTRACT 0.1228 0.0884 1.39 0.165
CLEARFORM -0.1047 0.0794 -1.32 0.188
PAYMENT 0.0737 0.0523 1.41 0.159
DEFAULT -0.0034 0.0692 -0.05 0.961
Market Price
PRICE 0.3867*** 0.0444 8.72 0.000
Household Characters
PLOTSIZE 0.0768*** 0.0066 11.66 0.000
AGE -0.0076** 0.0029 -2.6 0.010
EDU 0.0273 0.0377 0.72 0.469
LABOR 0.1010** 0.0427 2.36 0.018
MEMBER 0.1549** 0.0616 2.51 0.012
YEAR 0.0172*** 0.0043 3.96 0.000
Zone Dummy
AREA2 -0.3284*** 0.1133 -2.9 0.004
AREA3 0.3413*** 0.1207 2.83 0.005
AREA4 -0.0767 0.1132 -0.68 0.499
AREA5 0.0025 0.1144 0.02 0.983
AREA6 -0.3981*** 0.1173 -3.39 0.001
AREA7 -0.4914*** 0.1153 -4.26 0.000
Constant 8.4249*** 0.3427 24.59 0.000
F test 32.95
Prob>F 0.000
R-square 0.5481
Sample size: 607.
*Significant at the 10%. ** Significant at the 5%. ***Significant at the 1%.
Table 7. MLE Regression of Transaction Costs and Apple Producers Integration
Dependent Variable Ordinal Choice of Farm gate, Local and Distant Markets
Independent Variable Coefficient Standard Error Z-value P>|Z|
Proportional transaction costs
SALECOST 0.0001 0.0001 1.26 0.208
MARKETPRICE 0.0116 0.0570 0.2 0.839
FAIRPRICE -0.1707 0.1172 -1.46 0.145
Fixed transaction costs
BROKERFEE 0.0001 0.0003 0.54 0.591
TIMESPRICE 0.0101 0.0108 0.93 0.353
TIMEBARGAIN 0.2742** 0.1109 2.47 0.013
CONTRACT 0.3929** 0.1744 2.25 0.024
CLEARFORM -0.5461*** 0.1422 -3.84 0.000
PAYMENT 0.3324*** 0.0947 3.51 0.000
DEFAULT -0.2085* 0.1261 -1.65 0.098
Market Price
PRICE -0.1959*** 0.0678 -2.89 0.004
Number of obs 607
LR Chi2(11) 59.74
Prob>Chi2 0.000
Log likelihood -458.50
Pseudo R2 0.061
Sample size: 607.
*Significant at the 10%. ** Significant at the 5%. ***Significant at the 1%.
Table 8. Marginal Effects of Transaction Costs and Market Integration from Ordered
Probit Model
Variable dy/dx Standard Error Z-value P>|Z|
Proportional transaction costs
SALECOST 0.0000 0.0000 1.24 0.217
MARKETPRICE 0.0009 0.0044 0.2 0.839
FAIRPRICE -0.0130 0.0091 -1.43 0.154
Fixed transaction costs
BROKERFEE 0.0000 0.0000 0.54 0.592
TIMESPRICE 0.0008 0.0008 0.92 0.357
TIMEBARGAIN 0.0209** 0.0090 2.33 0.020
CONTRACT 0.0300** 0.0139 2.16 0.031
CLEARFORM -0.0417*** 0.0123 -3.39 0.001
PAYMENT 0.0254*** 0.0081 3.15 0.002
DEFAULT -0.0159 0.0099 -1.61 0.108
Market Price
PRICE -0.0150*** 0.0056 -2.67 0.008
*Significant at the 10%. ** Significant at the 5%. ***Significant at the 1%
References
Cai Rong, Han Hongyun. 2011. Effect of Transaction Costs on Famers Market Integration:
Evidence from Apple Producers in Shandong Province. Finance & Trade Economics, 7, 103-109.
Coase R.H.1937.The Nature of the Firm. Economica, 4(16), 386-405.
David J. Teece. 2010. Forward Integration and Innovation: Transaction Costs and Beyond. Journal
of Retailing, 86(3), 277-283.
David Stifel, Bart Minten, and Paul Dorosh. 2003. Transactions Costs and Agricultural
Productivity: Implications of Isolation for Rural Poverty in Madagascar. International Food Policy
Research Institute MSSD DISCUSSION PAPER NO. 56.
Dorward, A. 2001. The Effects of Transaction Costs, Power and Risk on Contractual
Arrangements: A Conceptual Framework for Quantitative Analysis. Journal of Agricultural
Economics, 52(2), 59-73.
Eleni Z. Gabre-Madhin.2001. Market Institutions, Transaction Costs and Social Capital in the
Ethiopian Grain Market. International Food Policy Research Institute Research Report.
Garth Holloway, Charles Nicholson, Chris Delgado. 2000. “Agro-industrialization through
Institutional Innovation: Transaction Costs, Cooperatives and Milk-Market Development in the
Ethiopian Highlands. Agricultural Economics, 23, 279-288.
Getachew A. Woldie, E.A. Nuppenau. 2011. A Contribution to Transaction Costs: Evidence from
Banana Markets in Ethiopia. Agribusiness, 27(4), 493-508.
Javier A. Escobal, Denice Cavero. 2012. Transaction Costs, Institutional Arrangements and
Inequality Outcomes: Potato Marketing by Small Producers in Rural Peru. World Development,
40(2), 329-341.
Hou Jianyun, Huoxuexi.2013. Transaction Costs and Farmers’ Choice of Marketing Channels in
China: Empirical Evidence from apple planters of 7 Provinces 124 villages.” Journal of Shanxi
Finance and Economics University, 7, 57-67.
J.N. Jagwe* & C. Machethe. 2011. Effects of Transaction Costs on Choice of Selling Point: A
Case of Smallholder Banana Growers in the Great Lakes Region of Central Africa. Agrekon, 50(3),
207-219.
Jason Donovan, Nigel Poole. 2014. Changing Asset Endowments and Smallholder Participation
in Higher Value Markets: Evidence from Certified Coffee Producers in Nicaragua. Food Policy,
44, 1-13.
Jean-Baptiste Traversac, Sylvain Rousset, Philippe Perries-Cornet. 2011. Farm Resources,
Transaction Costs and Forward Integration in Agriculture: Evidence from French Wine Producers.
Food Policy, 36, 839-847.
Jill E. Hobbs. 1997. Measuring the Importance of Transaction Costs in Cattle Marketing. American
Journal of Agricultural Economics, 79(4), 1-15.
Jing Wang, Xuexi Huo , Assem Abu Hatab, Md. Shajahan Kabir. 2012. Non-neutral technology,
farmer income and poverty reduction: Evidence from high-value agricultural household in China.
Journal of Food, Agriculture & Environment, 10 (3&4), 582 - 589.
Marcel Fafchamps, Bart Minten. 2002. Returns to Social Network Capital among Traders. Oxford
Economic Papers, 54,173-206.
Mathye MM, Makhura MT, Kirsten JF. 2000. Transaction Cost in the Marketing of Bananas:
Explaining Market Participation of Small Holders in the Northern Province. Paper Presented at the
38th Annual AEASA Conference Held in Sun City, 27-29 September 2000.
Michael E. Sykuta. 2008. New Institutional Econometrics: The Case of Research on Contracting
and Organization. In Éric Brousseau, Jean-Michel Glachant eds, New Institutional Economics: A
Guidebook. Cambridge University Press.
Nigel Key, Elisabeth Sadoulet, Alain de Janvry. 2000. Transaction Costs and Agricultural
Household Supply Response. American Journal of Agricultural Economics, 82,245-259.
Oliver E. Williamson. 1979. Transaction-Cost Economics: The Governance of Contractual
Relations. Journal of Law and Economics, 22(2), 233-261.
Pamphile Kokou Degla. 2012. Transaction Costs in the Trading System of Cashew Nuts in the
North of Benin: A Field Study. American Journal of Economics and Sociology, 7(2), 277-296.
Pitelis, Christos. 1993 .Transaction costs, markets and hierarchies. Blackwell Oxford, UK and
Cambridge, Mass.
Prabhu Pingali, Yasmeen Khwaja, Madelon Meijer. 2005. Commercializing Small Farms:
Reducing Transaction Costs. Selected Paper at the Research Workshop the Future of Small Farm
at Wye, UK 26-26 June 2005.
Qu Xiaobo, Huo Xuexi.2007. Effect of Transaction costs on Farmer Households Agricultural
Output Sale: Evidence from Apple Producers in 27 villages of 6 Counties from Shaanxi Province.
China Rural Economy, 8, 35-46.
Ruerd Ruben, Dave Boselie, Hualiang Lu. 2007. Vegetables Procurement by Asian Supermarkets:
A Transaction Cost Approach. Supply Chain Management: An International Journal, 12(1), 60-68.
S. J. Staal, Christopther Delgado, Charles Nicholoson. 1997. Smallholder Dairying under
Transaction Costs in East Africa. World Development, 25(5), 779-794.
Steven Were Omamo. 1998. Farm-to-market Transaction Costs and Specialization in Small-Scale
Agriculture: Explorations with a Non-separable Household Model. Journal of Development
Studies, 35(2), 152-163.
Vakis Renos, Elisabeth Sadoulet, Alain de Janvry. 2003. Measuring Transaction Costs from
Observed Behavior: Market Choice in Peru. Discussion Paper of UC Berkeley, 1-19.
Wiberforce Kisamba-Mugerwa. 2005. The Politics of and Policies for Smallholder Agriculture.
Selected Paper at the Research Workshop the Future of Small Farm at Wye, UK 26-26 June 2005.
Yao Wen, Qi Chunjie. 2011. Measuring the Effect of Transaction Costs on Tea Producers Vertical
Integration: Evidence from 1394 Farmer Households in 29 Counties of 9 Provinces. Journal of
China Survey, 2, 52-66.