


































African Journal of Agricultural Marketing Vol. 2 (1), pp. 082-090, January, 2014. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 
 
 
 

 

Full Length Research Paper 

 

Determinants of soybean market involvement by 
smallholder farmers in Zimbabwe 

 

Jackson Okemute
1
*, Bogos Sefas

1
, James Igari

2
 and Mary Oduma

3
 

 
1
International Centre for Tropical Agriculture, (CIAT), P.O. Box MP228 Mt Pleasant, Harare, Zimbabwe. 

2
Centre 

for Applied Social Sciences, University of Zimbabwe, P. O. Box MP167 Mt Pleasant, Harare, Zimbabwe. 
3
Department of Agricultural Economics and Extension, University of Zimbabwe, P. O. Box MP167, Mt Pleasant, 

                                                     Harare, Zimbabwe. *Corresponding author: jackson_okemute@gmail.com. 
 

Accepted 10 December, 2013 

 
This article examines the determinants of soybean market participation by smallholder farmers in 
Zimbabwe, with a view to identifying key policy entry points for increasing farmer incomes. Market 
linkages have been identified as key to the successful integration of grain legumes into the smallholder 
farming systems of southern Africa. Data for this article is derived from a baseline household survey in 
Guruve district of Zimbabwe. Using a sample of 187 smallholder farmers, we employed the Heckman’s 
Probit model with sample selection to firstly, identify the factors affecting a farmer’s decision to 
participate in soybean markets and secondly, evaluate the factors that affect the intensity of a farmer’s 
participation. Study findings show that the use of inoculants and improved soybean seed varieties are 
significantly correlated with participating in soybean markets. Results also show that ownership of 
radios has a positive effect on the household’s decision to participate in the soybean market. Further 
results show that male-headed households are less likely than female-headed households to participate 
in soybean markets because legumes are seen as women’s crops in Zimbabwe. We conclude that in 
order to leverage smallholder farmers’ market participation in soybean markets, it is important to 
improve access to inoculants and improved soybean seed varieties and improving access to market 
information. We recommend that authorities could improve access to market information to improve 
farmers’ decision making on soybeans market participation. 

 
Key words: Soybean, market participation, determinants, smallholder farmers, Zimbabwe. 

 
 
INTRODUCTION 
 
Market linkages have been identified as key to the 
successful integration of grain legumes into the 
smallholder farming systems of southern Africa (Chianu 
et al., 2009). Soybean (Glycine max) is a commodity with 
relatively higher prices and that has shown great potential 
to sustain production in smallholder farming systems due 
to its multiplicity of use. Soybean can be used as cash 
crop, as food and also as means of improving soil 

 
 
 

 
fertility through Biological Nitrogen Fixation (BNF). The 
net income benefits derived from soybean production 
depend on the extent to which farmers participate in 
output markets. According to IFAD (2003), market 
participation can be an effective route for rural small-
holder farmers to move out of abject poverty and increase 
income. Studies show that market participation by 
smallholder farmers in developing countries is very 



Jackson  et al.              082 
 
 

 
low (Barret, 2008). This scenario has slowed down 
agriculture driven economic growth and exacerbated 
poverty levels. As such farmers cannot benefit from the 
welfare gains and income growth associated with market 
participation. However, for agriculture to meaningfully 
contribute to economic growth, smallholder farmers have 
to commercialize their farming activities to produce 
marketable surpluses (Jagwe et al., 2010). The issue of 
why most smallholder farmers who happen to make the 
larger proportion of the poor in developing countries self 
select themselves out of the remunerative markets 
remains largely unanswered. It is therefore necessary to 
identify the key determinants of soybean market 
participation by smallholder farmers in order to be able to 
identify key entry points and interventions that can 
increase household income.  

The trade theory posits that if households participate in 
markets by selling surplus of what they produce on a 
comparative advantage, they are set to benefit not only 
from the direct welfare gains but also from opportunities 
that emerge from economies of large-scale production 
(Siziba et al., 2011; Barrett, 2008).  

Indeed, they will also benefit from technological change 
effects from the improved flow of ideas from trade-based 
interactions (Barrett, 2008). Consequently, there will be 
improved factor productivity. Despite the stream of 
benefits that are inherent with market participation, 
evidence from studies in southern Africa shows that 
smallholder farmers’ participation in agricultural output 
markets is low due to high market transaction costs, 
information asymmetries, institutional constraints among 
other constraints. Barret (2008) argues that inducing 
market participation through trade and price based 
market interventions does not provide the sufficient 
conditions to induce improved participation. In addition to 
these policies, households need to have access to 
productive assets, adequate private and public 
investment, institutional and physical infrastructure to 
access remunerative markets (Siziba et al., 2011; Barret 
and Swallow, 2006). As noted by Barret (2008) such 
smallholder farmers with access to production, private 
and public sector goods, properly functioning institutions 
and well developed physical infrastructure actively 
participate in markets contrary to their counterparts.  

However, the general trend in most southern African 
countries is that most agricultural produce is lost soon 
after production largely because of poor post harvest 
handling and failure to access the formal markets (Phiri 
and Otieno, 2008). This trend is attributed to several 
factors and barriers in agricultural commodity marketing 
that discourage smallholder farmers from participating in 
formal markets. These factors range from household 
characteristics for instance low education levels, labor 
shortages, inadequate government services, high 
transaction costs and lack of physical infrastructure 
(Siziba et al., 2011, Jagwe et al., 2010; Pingali et al., 
2005). In response to these challenges, most 

 
 
 

 
governments in Sub Saharan Africa implemented marke 
liberalization policies in the 1980s and 1990s which 
sought to open new market led economic growth 
opportunities (Barrett, 2008). It involved the abolition of 
commodity boards, introduction of free markets and 
encouragement of private sector participation. According 
to Jayne and Jones (1997), although the overall aim of 
the liberalization was to improve the functioning and 
effectiveness of markets, it produced mixed results. In 
some cases, there was actual retreat to subsistence 
agriculture while in others there was increased market 
participation in more remunerative markets, technological 
progress and improvements in institutions and physical 
infrastructure.  

This study sets to establish factors affecting soybean 
market participation and the level of marketed surplus 
among smallholder farmers. The results of this study are 
essential in contributing to the existing body of knowledge 
on soybean market participation which is scant locally as 
most previous research concentrated on biophysical 
aspects of soybean production. Therefore, understanding 
smallholder marketing of soybean is vital for increased 
participation which may lead to increased farmer 
incomes, improved soil fertility and ultimately reduced 
poverty. Information from this study will be useful to 
agricultural policy makers to create or amend existing 
policies in an effort to develop the soybeans production 
and markets as well as motivate producers to access 
soybean commodity markets. 
 
 
Smallholder soybean production in Zimbabwe 
 
Historically, soybean production in Zimbabwe was highly 
mechanised and carried out by commercial farmers in 
high rainfall areas (Estehuizen, 2011). The commercial 
farmers had easy access to inputs, financial capital, 
irrigation services and well developed marketing channels 
(Madanzi et al., 2012). The output from commercial 
farmers accounted for 95% while smallholder farmers 
contributed only 5% of national soybean output 
(Estehuizen, 2011). Smallholder farmers used 
unimproved retained seeds and did not have access to 
Bradyrhizobium inoculant and this contributed to yields as 

low as 0.6 t ha-1 compared to 3 to 4 t ha
-1

 in the 
commercial sector (Mabika and Mariga, 1996). The 
smallholder farmers lacked general knowledge on good 
agronomic practices. Shumba-Munyulwa (1996) noted 
that agronomic research on soybean production was 
confined to the commercial sector and extension in 
smallholder farming sectors was limited. This implies that 
the recommendations from such agronomic studies could 
not be applied to smallholder farming.  

In 1996, the government formed the National Soybean 
Task Force (NSTF) whose mandate was to help increase 
the participation of smallholder farmers in soybean 
production and marketing (Madanzi et al., 2012). In 



 
 
 
 
 
 
 
 
 
 

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 Smallholder farmers 

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Figure 1. Soybean production in Zimbabwe in "000' metric tonnes. Source: Technoserve, 2011. 

 
 

 
particular the programme provided agricultural extension, 
access to cheap inputs and linkages to markets to 
smallholder farmers. When the programme started, it 
enrolled 55 smallholder farmers but by end of 2006 the 
programme had reached a total of 55,000 smallholder 
farmers who produced 40,000 t per annum (Chianu et al., 
2009). Complimentary efforts have been done by Africare 
and the N2Africa Project in Zimbabwe who are assisting 
the smallholder farmers with agronomic knowledge on 
soybean production in addition to market linkages. 
Despite these efforts, soybean producing smallholder 
farmers face challenges such as access to cheap inputs 
and rhizobium (Madanzi et al., 2012). Although the 
Rhizobium is produced by Zimbabwe’s Soil Productivity 
and Research Laboratory (SPRL) at a break-even price 
of $3.20 and distributed through Agricultural Technical 
and Extension services (AGRITEX) at a retail price of 
$5.00, some farmers claim that they access the inoculant 
at more than double the cost (Woomer et al., 2013). The 
seed houses are not producing sufficient quantities of 
soybean seed for the market as the smallholder farmers 
do not purchase the improved seed.  

Despite the government’s efforts in distributing land 
from the commercial farmers to landless peasants, 
Zimbabwe is still facing huge deficits in soybean 
production with demand far outstripping current 
production levels. Zimbabwe’s annual demand for 
soybean is 125,000 metric tonnes while production has 

 
 

 
been fluctuating far below the equilibrium quantity (Varia, 
2011). At present, the demand deficits have been filled by 
imported soybeans from South Africa, Zambia and 
Malawi. Zimbabwe is only producing 30% of its national 
demand of 125,000 metric tonnes and capacity utilization 
at the major soybean processors is only 16% 
(Technoserve, 2011). The huge demand deficit in 
soybean production offers an opportunity for smallholder 
farmers to produce large quantities of soybeans, 
participate in markets and improve household income. 
Since soybean is renowned for its high propensity to fix 
nitrogen, intensive market participation by smallholder 
farmers would also improve soil fertility and yields for 
subsequent crops such as maize if farmed on the same 
land in rotation. However, despite this market opportunity 
particularly from the booming livestock and poultry 
industries where soybean is used to produce animal feed, 
smallholder farmers are producing very low quantities of 
soybean for sale and market participation is very low as 
shown in Figure 1.  

Figure 1 shows the contribution of smallholder farmers 
to national output has remained very low between 2002 
and 2010. The observed trends in soybean production, 
presents an opportunity for smallholder farmers to exploit 
the market by increasing production of soybeans, as well 
as participating in its supply chain for income generation.  
However despite the income generation potential of 
soybean for smallholder farmers and the huge supply 

083      Afr. J. Agric. Mark. 



Jackson  et al.              084 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Figure 2. Map of study site: Zimbabwe’s Guruve district. 

 
 

 
deficit in Zimbabwe, research on soybean has largely 
focused on biophysical aspects such as yield 
enhancement, production practices and nutrient use 
efficiency. There is a lack of information on soybean 
market participation by smallholder farmers and in 
particular the factors that influence the level of 
marketable surplus. Smallholder farmers’ market 
participation is equally important if the full benefits from 
soybean production are to be realized. The studies on 
factors affecting smallholder market participation have not 
been fully exploited especially for soybeans. Most studies 
(Siziba et al., 2011; Okoyo et al., 2010; Jagwe et al., 
2010) conducted on factors influencing smallholder 
market participation have concentrated on staple crops, 
that is, maize, cassava and bananas.  

Since staple crop markets are very different from 
soybean markets, recommendations from such studies 
may not be applicable to soybean markets. Thus this 
study is an attempt to fill the knowledge gap on soybean 
market participation by smallholder farmers. To the best 
of our knowledge, this is the first such study in Zimbabwe, 
which seeks to identify factors influencing soybean 
market participation and the intensity of market 
participation by smallholder farmers. 
 
 
THE STUDY APPROACH 
 
Study site 
 
This study was conducted in Guruve district, which is in linked to 

 
 

 
Mashonaland west province of Zimbabwe (Figure 2). The district is 
linked to the main legume market, Harare, by a 151km tarred road. 
Although most of Guruve district lies in natural farming region IV, 
which is a semi-arid and marginal zone, the study sites lie in natural 
farming region II. The annual average rainfall is 600 mm while the 
annual average temperature is 26.5°C. This natural farming region 
is an agro-ecologically high potential zone suitable for growing 
soybeans, maize and common beans. The altitude range is 800 

to1500 m above sea level. The main livelihood activity is farming 
with maize being the dominant cereal crop while soybeans and 
common beans constitute the main legume cash crops. 
 

 
Sampling and data analysis 
 
This study uses cross sectional household data from the baseline 
survey collected using a questionnaire with semi structured and 
structured questions. A sample of 187 of actual greater than 128, 
an apriori power analysis computed using G Power. It therefore 
means that the sample provides acceptable statistical power (that is 
0.80) for moderate correlation r = 0.30, at two tailed 0.05 level of 
significant (Franzel et al., 2007). Random sampling was used to 
select the wards and the households for interviewing from the lists 
that were provided by resident agricultural extension officers. In the 
first place, 10 households per ward were randomly selected from 
six wards where the project is being implemented while the 127 all 
came from a counterfactual site.  

A counter factual site is a site similar to the intervention 
(treatment) in agroecological and market conditions but did not 
receive a treatment (Binam et al., 2011). The 127 sampled 
households in the counterfactual site were randomly sampled from 
6 wards that did not participate in the project. The sampling 
approach followed by the project was meant to allow the use of 
propensity score matching approach in impact assessment. Data 
collection for this study was done in October 2011 through face- to- 



 
 
 

 
face administration of questionnaires. The survey collected 
information on household composition and characteristics, crop 
production, household market participation, access to infrastructure, 
household incomes, ownership of land and non land assets, 
livestock ownership and access to agricultural inputs on credit. 

 
The analytical approaches 
 
The data was entered, cleaned and then analyzed using STATA 
Version 11.2. The study uses the Heckman’s model with sample 
selection to identify the factors that affect smallholder farmers’ 
decision to participate in soybean markets and then to evaluate the 

factors that affect intensity of soybean market participation. This 
model is adopted on the basis that it models the market 
participation decision as a two step process that involves (1) the 
household deciding on whether or not to participate in the soybean 
market (2) the level of market participation. The factors influencing 
the farmers’ decision to participate are estimated using the Probit 
model (selection equation) while the level of participation is 
estimated using the Ordinary Least Squares approach (Outcome 
equation). Goetz (1992) and Huang et al. (1991) noted that the use 

of Heckman’s model with sample selection allows the interpretation 
of results by distinguishing between factors that affect the farmer’s 
decision to participate in the market and those that affect the level 
of market participation. 
 

According to Greene (2003), in instances where observed 
characteristics only occur in subsets, incidental truncation occurs. 
As such, this study uses this model as it corrects for sample 
selection bias and incidental truncation. The selection bias arises 
due to the observation of sales from a subset of households  
who participated in the soybean markets. The empirical   analysis 
in this study is premised   on three constructs namely household 
characteristics,   information and   assets. In   this   study,   the  
econometric analysis is based on these constructs to reflect the 
effect of transaction costs on farmer’s decision to participate in the 
market and also the level of market participation. Variables 
hypothesized  to explain smallholder  farmers’  soybean market 
participation and level   of participation were    identified based 
on    theoretical frameworkand    on    past empirical work  on  
market participation under transaction costs (Goetz, 1992; Holloway 
et al., 2000; Key et al., 2000; Alene et al.,2008; Jagwe et al., 2010; 
Siziba et al., 2011).  

This study builds on earlier studies on smallholder market 
participation under transaction costs by applying this to smallholder 
market participation in soybean markets. Based on these constructs 
as in Jagwe et al. (2010), in this study household head’s gender, 
head’s age, head’s age squared and household size are used as 
proxies for household characteristics. Livestock wealth or resource 
endowment is represented by number of cattle owned while 
information is represented by contact with extension, household 
head education, distance to nearest market, ownership of radio and 
ownership of a mobile phone. These constructs are used in the 
analysis to reflect the influence of transaction costs on the farmer’s 
decision to participate in a soybean market and to estimate the 
significant factors that influence the level of market participation. 

 
The outcome regression 
 
The outcome model is conditional on market participation and it is 
estimated using the Ordinary Least Squares (OLS). In the OLS 
equation, the dependent variable is amount of soybeans sold 
(continuous variable). In this paper we hypothesized that gender of 
household head, age of household head, size of the household, 
farming experience; ownership of cattle and distance to the market 

 

  
 
 

 
affect the intensity of a household’s participation in the soybean 
market—following Jagwe et al. (2010). 

 
Selection equation 
 
In the selection equation, that is the Probit model, the dependent 
variable is a dichotomous variable ‘participation in soybean market 
(represented as 1 when a household participates in the market and 
0 otherwise’). The independent variables that condition the 
participation of smallholder farmers as adapted from literature are 
gender of household head, age of household head, size of the 
household, farming experience; ownership of cattle, ownership of 

radio, ownership of cellphone, access to extension, use of rhizobial 
inoculants and use of improved soybean seed varieties (Table 1). 
Age may influence market participation through various channels 
such as experience, access to resources and risk preferences. The 
expected direction of the effect of age is thus ambiguous. The 
gender of a household head is likely to reveal the differences in 
market orientation between male and female household heads. 
Cunningham et al. (2008) argues that male household heads sell 
their produce when prices are high while  
female household heads keep  their produce  for  household  food 
self  sufficiency. W e thus expect the   sign to be positive 
meaningthat male-headed  households are more likely  to  
participate in soybean markets as compared to their female 
counterparts.  

Alene et al. (2008), posit that the household size is an indicator of 
the amount of family labor that is available for production activities.  

It also explains the consumption levels for a household. W e thus 

expect the sign to be positive when a household’s labor resources 
are efficient that is they produce far more output than what they 
require for household consumption. In such a case, there is high 
marketable surplus. However, if the sign is negative it is an indicator 
of household labor inefficiency that is, a larger household produces 
far less than what it needs for household consumption and thus less 
marketable surplus. According to Omiti et al. (2009), the distance to 
the market negatively influences both the household’s decision to 
participate in the market and the amount sold (intensity of 
participation). The further the distance to the market, the higher the 
transport costs and the lower the net benefit to the household. Key 
et al. (2000) note that farmers who stay in remote areas have low 
input use that is, they normally substitute high value commercial 
varieties with locally easily obtainable varieties. 
 

Consequently, this input substitution has adverse effects on 
productivity, market participation and marketable surplus. W e thus 
expect a negative relationship between distance to market and 
likelihood to participate in marketing. This implies that the higher the 
distance to the nearest selling points, the lower the likelihood of a 
household to participate in markets. However, Fafchamps and Hill 
(2005) observed that wealthy farmers can sell their produce to 
distant markets as they can afford the high transport costs 
compared to the poor farmers. This then implies that we expect the 
resource constrained farmers to participate in local markets while 
the resource endowed farmers participate in distant markets.  

Most economists argue that relative prices form critical incentives 
to induce market participation and increase the amount of 
marketable surplus (Alene et al., 2008; Fafchamps and Hill, 2005). 
Smallholder farmers in Zimbabwe access market information on 
prices of inputs and output through contact with extension agents, 
radios and phoning the buyers using cell phones. Knowledge of 
input prices enables farmers to make informed decisions on input 
use intensity and also the area to commit to soybeans. W e argue 
that access to price information positively influences the farmers’  
decision  to participate in soybean markets while the lack of it acts 
as  a  disincentive.  We therefore expect  a positive   relationship 

085      Afr. J. Agric. Mark. 



Jackson  et al.              086 
 
 
 
Table 1. Description of covariates used in the regression models. 
 
Variable Description Measurement Expected sign  
Household characteristics  
Age Age of household head 

 

Age squared Age of household squared 
 

Gender Gender of household head 
 

Household size Number of people in a household 
 

Farming experience Number of years household head has been farming 
 

as a household  

 
 

 
Number of years 

 
0=female; 1=male 

Number 
 
Number of years 

 
+  
+ 

 
+ 
 
+ 

 
Information 
 
Distance to market 
 
 
Household head’s 
education 
 
 
Access to extension 
 

 
Own cellphone 
 

 
Own radio 
 
 
Assets  
Number of Cattle Owned 

 
Average distance from household’s home to nearest 
point of sale 
 
 
Education level of household head 
 
 
Access to agricultural extension for crop production 
advice 
 
 
Ownership of a cellphone 
 

 
ownership of radio 
 
 
 
Number of cattle owned 

 
Km - 

 
0=no secondary education 

+/- 
1=has secondary education 

 
0=no access +/- 

 
0=does not own 

+/- 
1=owns a cellphone 
 
0=does not own 

+/- 
1=owns a radio 
 

 
Ratio + 

 
 

 
between a household’s decision to participate in the soybean 
market and its access to market information, ownership of a radio 
and or cellphone. By accessing extension agents, farmers get 
advice on good agronomic practices, improved technologies and 
market prices. W e therefore expect the sign to be positive when 
farmers have access to extension agents and negative otherwise. 
According to Zingore et al. (2007), ownership of cattle is a major 
determinant of the timeliness of agronomic operations. W e assume 
that the resource-endowed farmers may use their livestock for 

traction to till larger pieces of land and for transportation to the 
market. According to Alene et al. (2008) and Zingore et al. (2007) 
cattle ownership has a wealth effect, in that those households who 
own animals are more likely to use fertilizers than those without. 
The resource endowed households are also more likely to have 
cash resources to finance basal fertilizer purchases, inoculants and 
improved soybeans germplasm (Zingore et al., 2007). Varia (2011), 
notes that resource constrained smallholder farmers lack access to 
finance, give less priority to their non staple crops and use poor 
agronomic practices. The combined effect of these factors is very 
low yields and low market participation compared to the commercial 
farmers who have higher use of herbicides and fertilizers. We thus 
expect a positive relationship between wealth (resource 
endowment) and intensity of market participation as such 
households are more likely to have higher marketable surplus. 
According to Alene et al. (2008), access to agricultural extension 
services enhances market participation and marketable surplus as 
agents provide technical assistance and information on improved 
varieties and technologies. 

 
 

 
Extension agents are the information exchange platform between 
research and farmers; they decode information from researchers 
into a format understandable by farmers and also provide feedback 
to the researchers. These results were also observed by Siziba et 
al. (2011), who noted that access to extension services reduces 
farmers risk perceptions and thus improve market participation. W e 
thus expect a positive relationship between access to extension 
services and market participation in soybean markets. 
 
 
RESULTS AND DISCUSSION 
 
Sample characterization 
 
The household survey results in Table 2 show that only 
28.88% (54 out of 187 farmers) of the sampled 
households participated in the soybean market. The 
average marketable surplus for households that 
participated in the soybean market is 211.26 kg. These 
results are consistent with findings by Ojiem et al. (2007) 
and Giller et al. (2006) who note that soybean output is 
very low in smallholder farming communities largely 
because farmers apportion at most 5% of their land to 
legumes and do not fertilize them leading to low yields. 
The low levels of marketable surplus could also be a 



  
 
 
 
Table 2. Description of sample household and socioeconomic characteristics. 
 

Parameter Market participants Non market participants p-values 
Sample n (prop) 54 (28.88) 133 (71.12)  

Head age (years) 43.76(12.96) 50.43(16.60) 0.0089 
Household size 5.33(3.16) 5.18(2.77) 0.7433 
Head education (% prop with secondary) 59.26(0.50) 46.62(0.50) 0.1184 
Farming experience (no. of years) 15.13(11.94) 20.42(15.51) 0.0257 
Gender (%prop of male) 75.93(0.43) 79.7(0.40) 0.5709 
Own mobile phone (%prop) 68.52(0.47) 63.91(0.48) 0.5511 
Own Radio (% prop) 68.52(0.47) 52.63(0.50) 0.0469 
Number of cattle owned 2.35(3.46) 2.35(3.61) 0.0027 

 
 

 
result of low input usage and the substitution of 
commercial high value varieties with low yielding locally 
available varieties. The results show that the average 
household head for market participating households 
(43.76) is significantly lower with a standard deviation of 
19.96 than that of non-participating households (50.43) 
that has a standard deviation of 16.60 and this is 
significant at 1% level of significance. The probability of 
younger farmers to participate in soybean market is 
higher than that of older farmers. The results from the 
survey show that amongst the market participating 
households, 75.93% are male headed while 79.70% of 
the non-market participating households are male 
headed. Since the p-value is 0.5709, there is thus no 
statistically significant difference between the two groups 
of soybean farmers.  

Results for the average household sizes show that the 
mean household size for market participants is 5.33 with 
a standard deviation of 3.16 while that for non-market 
participants is 5.18 with a standard deviation of 2.77. 
Although the household sizes were slightly lower than the 
national average household size of six, the p-value of 
0.7433 indicates that there were no significant differences 
in household sizes between the market participating and 
non-market participating farmers. In terms of farming 
experience, there were statistically significant differences 
observed between soybean market participating 
households and the non-market participants at 5% level 
of significance. Households that participated in the 
soybean market on average had 15 years of farming 
experience compared to their counterparts with over 20 
years. The 2 sided t test results show that the difference 
in farming experience is statistically significant at 5% level 
of significance. This implies that the probability of less 
experienced to market soybean is very high.  

The results also show that 68.51% (standard deviation 
0.47) households who participated in the soybean market 
owned radios while 52.63% (standard deviation 0.50) 
amongst non-market participants owned radios. Since the 
p-value is 0.0469, we observed significant differences 
between the two groups at 5% level of significance. This 

 
 

 
means that ownership of radios is common among 
market participating households than non-market 
participating households. As such, owning a radio 
increases the probability of marketing soybeans.  

Although, we estimated that 68.5% of the soybean 
market participating households owned cellphones with a 
standard deviation of 0.47 compared to 65% with a 
standard deviation of 0.48 for non-participating 
households; the p-value of 0.5511 shows that there were 
no statistically significant differences in the proportions. 
This suggests that cellphone ownership is not a 
determinant of soybean market participation among the 
smallholder farmers. 
 
 
Econometric results 
 
The results from the econometric analysis for the market 
participation (Probit Model results) and intensity of market 
participation (OLS regression model) are presented here. 
Intensity of market participation is estimated conditional 
on the smallholder farmers’ market participation decision. 
 
 
Factors affecting soybean market participation 
 
Table 3 presents the OLS results for intensity of market 
participation and the Probit model results for smallholder 
farmers’ decision to participate in the soybean market. 
The OLS regression model estimates the factors affecting 
the intensity of participation in a soybean market while 
the Probit model estimates the determinants of the 
dichotomous soybean market participation variable. 
 
 
Selection model results (Probit model results) 
 
The results in Table 3 show that for the Probit model, 
gender of household head, ownership of a radio, access 
to agricultural extension services, use of inoculants and 
use of improved soybean seeds affect the farmers 

087      Afr. J. Agric. Mark. 



Jackson  et al.              088 
 
 

Table 3. OLS and Probit Estimates for soybean market participation and intensity of participation. 

 
  Probit (selection model) OLS (outcome) 

 

 
Dependent variable (soybean bean market 

(Amount of soybean sold)  

 
participation  

    
 

  β p-value β p-value 
 

 Gender -0.847 0.004*** 6.249 0.345 
 

 Head age -0.063 0.172 0.210 0.536 
 

 Head  age squared 0.000 0.488 0.004 0.490 
 

 Household size 0.045 0.511 -0.403 0.256 
 

 Farming experience -0.001 0.939 -0.367 0.183 
 

 Ownership of cattle 0.003 0.283 0.023 0.094* 
 

 Distance to market - - 3.921 0.014** 
 

 Own radio 0.672 0.0060***   
 

 Own cellphone 0.003 0.992   
 

 Access to extension 0.4185 0.086*   
 

 Used Inoculants 0.894 0.016**   
 

 Use improved seed varieties 0.684 0.041**   
  

*** Significant at 1% level; ** significant at 5% level; * significant at 10% level. 
 
 

 
decision to participate in the soybean market as a seller. 
The gender of the household head negatively influences 
the likelihood of smallholder farmers’ participation in the 
soybean output market, that is male headed households 
are less likely to participate in soybean markets than 
female headed households. The probable explanation is 
that in Guruve district as in other parts of Zimbabwe, 
most legumes are culturally viewed as women’s crops. 
These results are consistent with the findings of Alene et 
al. (2008) for Kenya but contrary to the findings of 
Cunningham et al. (2008) in a study on gender 
differences in marketing styles in western Oklahoma. 
Ownership of a radio, which represents access to a 
communication asset positively and significantly, 
influences a smallholder farmer’s likelihood of 
participating in the soybean market. It represents access 
to formal sources of market information that increases the 
likelihood of market participation. In Zimbabwe, radio 
stations frequently air broadcasts on rainfall patterns, 
crop varieties and input and out prices. Access to this 
information lowers the transaction costs and road 
accessibility to the market. According to Siziba et al. 
(2011) access to such information reduces smallholder 
farmers risk perceptions and improves the likelihood of 
participating in the soybean market. These results are 
consistent with the findings of Siziba et al. (2011) on 
cereal market participation in southern Africa. Access to 
agricultural extension agents positively influences the 
likelihood of participating in soybean markets. The results 
demonstrate the importance of improved technology and 
support services in promoting soybean market 
participation. The likely explanation for this is that 
agricultural extension workers are the bridge between 
research programmes and farmers. They 

 
 

 
provide information on good agronomic practices, 
production technologies, soybean varieties and market 
information. This interaction is likely to improve 
productivity, marketable surplus and enhance a 
smallholder farmer’s likelihood of participating in a 
market. These results are consistent with the findings of 
Alene et al. (2008).  

The use of rhizobial inoculants in the production of 
soybeans by smallholder farmers in Guruve district is 
significantly positive and increases likelihood of 
participating in the soybean market. The likely 
explanation for this is that rhizobial inoculants increase 
average yield and total soybean production with lower 
costs than using inorganic fertilizers (Chanaseni and 
Kongngoen, 1992). Thus the results show that 
smallholder farmers who used rhizobial inoculants for 
soybeans had a higher likelihood of participating in 
soybean markets than their counterparts. Similarly, the 
use of improved soybean seed varieties has a 
significantly positive influence on soybean market 
participation by smallholder farmers. The likely 
explanation is that improved seed varieties (germplasm) 
have high yield potential and are disease and pest 
resistant thus improve productivity and marketable 
surplus (Technoserve, 2011). 
 
 
OLS regression model results 
 
The results for the OLS regression model are shown in 
Table 3. Livestock wealth (cattle owned) and average 
distance to the market explained the intensity (amount of 
soybean sold) of smallholder farmers’ participation in 
soybean market. Number of cattle owned had a positive 



089      Afr. J. Agric. Mark. 
 
 

 
and significant influence on the intensity of market 
participation conditional on market participation. The 
probable explanation is that resource endowed 
households have more cattle which they can use for 
traction and transportation, a development which reduces 
production and market related transaction costs. The 
resource endowed households are likely to have finances 
from which they are able to hire labor, purchase 
inoculants, buy improved soybean germplasm and thus 
can grow soybeans on bigger pieces of land compared to 
the resource constrained smallholder farmers. 
Furthermore, households who own cattle are more likely 
to use good agronomic practices to produce their 
soybean. Resultantly, this will increase yield and 
marketable surplus. These results are consistent with the 
results of Alene et al. (2008). Zingore et al. (2007) noted 
that resource endowed farmers had higher yields in their 
fields compared to resource constrained farmers.  

Distance to the market positively and significantly 
influences the intensity of soybean market participation 
by smallholder farmers. This means that as distance to 
the market increases, the amount of soybean sold by 
smallholder farmers also increases. These results are in 
contrast to findings from studies on staple crops in which 
distance negatively influences smallholder farmers’ 
intensity of market participation (Siziba et al., 2011; Alene 
et al., 2008, Makhura et al., 2001; Key et al., 2000). A 
common finding in all these studies is that as distance 
from the market increases, variable transport costs 
increase and this discourages resource constrained 
smallholder farmers from selling high volumes. However, 
a possible explanation for the Zimbabwean case is that, 
local buyers offer very low prices compared to well 
established distant buyers. This is so because 
established soybean buyers are based in Harare, which 
lies over 151 km from the study sites. As such most 
farmers are set to benefit from price differentials between 
local prices and prices in distant markets. 
 

 
Conclusion 

 
This article did set out to identify through empirical 
evidence the determinants of soybean market 
participation and further evaluate the factors that affect 
intensity of market participation by smallholder farmers in 
Guruve district of Zimbabwe. This study used cross 
sectional household data of 187 randomly selected 
smallholder farmers in Guruve district in Zimbabwe. 
Econometric analysis was done using the Heckman 
model with sample selection, which corrects for selection 
bias at market participation decision by smallholder 
farmers. Choice of covariates for the OLS and Probit was 
guided by economic theory, literature and in some cases 
intuition. Descriptive results from the survey show that 
only 28.88% of the survey households participate in 
soybean market. The market participating households 

 

  
 

 
averagely sold 211.26 kg of soybean. Most of the market 
participating households owned communication 
equipment such as radios (68.52%) and had bigger land 
sizes (3.52 ha) compared to the non-participating 
households. The econometric analysis results from this 
study show that for the OLS model, livestock wealth or 
resource endowment and distance to the market have 
positive influence on marketed surplus. However, for the 
Probit model, only gender negatively influences the 
smallholder farmers’ decision to participate in soybean 
market while household ownership of a radio, access to 
agricultural extension, use of rhizobial inoculants and use 
of improved soybean varieties have a positive influence 
on household’s likelihood to participate in the soybean 
market.  

Based on these findings from the analysis of the factors 
affecting soybean market participation by smallholder 
farmers in Guruve district, we recommend that policy 
makers can improve farmer to extension worker ratio as 
this will improve access to technical information and 
support services on improved technologies such as use 
of inoculants, biological nitrogen fixation and knowledge 
on improved soybean seed varieties. Furthermore, policy 
makers could improve the dissemination of market 
information as it is currently available through radio 
broadcasts. Access to market information would improve 
farmers’ knowledge of markets and aid in decision 
making on market participation as well as the level of 
marketed surplus. This will lead to increased productivity, 
high marketable surplus and enhances the likelihood of 
participating in the soybean market. 
 

 
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