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FACTORS INFLUENCING PARTICIPATION OF SMALLHOLDER FARMERS IN

LIVESTOCK MARKETS IN MBULU AND BARIADI DISTRICTS, TANZANIA

Mayala Nyanjige Mbembela Department of Management,

Moshi Co-operative University, Box.474, Sokoine Road, Moshi – Tanzania.

Emails: [email protected]; [email protected]

ABSTRACT This paper explores the factors influencing livestock market participation decision of smallholder livestock farmers in Mbulu and Bariadi Districts, Tanzania. The objective of the study was to sort out the key factors that influence smallholder farmers’ decision to participate in the livestock market as it has been pointed out that smallholder farmers rarely participate in the markets. A Probit regression model was employed for the analysis. The study used primary data collected from 333 smallholder farmers of the two aforementioned Districts. It was found that herd size, family labour, income from livestock, market information, livestock income and farm income are the main factors that influence smallholder farmers’ decision to participate in the livestock markets. Findings also indicate that, smallholder farmers would participate more and more in the livestock market, if herd size, availability of labour, market information, farm income and income from livestock are increased as these factors were found to be significant at p<0.05. It is concluded that, smallholder farmers in the study area are influenced by a number of factors as aforementioned. The uniqueness of this paper is that it examines the phenomenon of smallholder farmers’ in the study area from the viewpoints of market participation, which may create an opportunity for further constructive debate. Furthermore, development of market infrastructure, provision of marketing incentives to smallholder livestock farmers and development of an institutionalized marketing information service are recommended to enhance commercialization of livestock in the study area.

Key words: Tanzania, livestock, market participation Paper type: Research paper Type of Review: Peer Review

1. INTRODUCTION

Markets for livestock and livestock products are an important and integral part of the livestock sector

development especially in the developing economies (Mayala et al., 2018). There have been indications around the

world that demand for livestock products are growing stemming from human population growth, increased

urbanization, and rising income (FAO, 2017). With this enlarged rate of consumption in most developing countries

(Jabbar, Baker, and Fadiga 2010), the livestock sector offers substantial chances for economic growth and poverty

reduction, especially among the rural farmers. However, despite the increasing opportunity offered by the rapid

growth of demand for livestock, smallholder livestock keepers are often characterized by low levels of

participation in the markets coupled with a very low market off-take rate (Negassa, Rashid, and Gebre medhin

2011). Understanding the motives for smallholder farmers in Tanzania not aggressively participating in livestock

markets may help policy makers come up with novelties to deal with the problem and help to improve lives

among smallholder farmers in the rural farm households.

A number of studies using household data have attempted to reveal the factors affecting smallholder

farmers’choices to join in livestock markets (Musemwa et al., 2010; Nkonde 2008; Ehui et al., 2003; Lapar, et al.,

2003). Physical limitations on marketing include low population densities in rural areas (Nkonde, 2008),

remoteness of livestock producers from the main urban market centres, and poor road infrastructure that results in

East African Journal of Social and Applied Sciences (EAJ-SAS) Vol.1, No.1 Publication Date: November. 20, 2019

ISSN: 0856-9681

The current issue and full text archive of this journal is available at: http//www.mocu.ac.tz

Cite this article as: Mayala, N. M. (2019). Factors Influencing Participation of Smallholder Farmers in Livestock Markets in Mbulu and Bariadi Districts, Tanzania, East African Journal of Social and Applied Sciences, 1(1), 31-39.

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Mayala, N.M., Factors Influencing the Participation of Smallholder Farmers in Livestock Markets in Mbulu and Bariadi Districts,

Tanzania.

East African Journal of Social and Applied Sciences [EAJ-SAS] Vol. 1, Issue 1, 2019 32

high transport costs are among the mentioned factors resulting into low smallholder livestock keepers to

participate in the markets (Gabre-Madhin, 2009). Improved road networks and marketing infrastructure such as

holding facilities may encourage farmers’ participation in livestock markets (Ouma, et al., 2003), though the effects

in some country studies are not significant (Ehui, Benin, and Paulos 2003). Sadoulet, and de Janvry (2000); and

Makhura et al., (2001) have mentioned high operation costs to be one of the main explanations for smallholder

farmers’ failure to partake in markets.

2. SMALLHOLDER FARMERS’ PARTICIPATION IN LIVESTOCK MARKETS

As the majority of the rural smallholder farmers in Africa originate in remote areas with poor road network and

market setup, operation costs rise not only due to high transport costs, but also due to the increased costs of

penetrating, screening, trading with, and monitoring distant exchange partners (Moyo, 2015). Increased

transaction costs also stem from failure to get market details such as grades and standards (Gabre-Madhin 2009).

Lack of market information increases the transaction costs incurred by smallholder famers and thus inhibits

participation in markets (Costales et al. 2007; Nkhori 2004; Ehui et al., 2003; Lapar et al., 2003; Makhura et al., 2001).

The effect of information irregularity thus puts smallholder famers in a weak negotiating position when dealing

with larger buyers and reduces their attractiveness when dealing with supply chains that are becoming gradually

formalized and advanced.

The purpose of keeping livestock has also been identified to have an effect on the likelihood of participating in

livestock markets (Musemwa et al., 2010). Smallholder farmers in less developed economies have multiple goals

for their livestock enterprise. Apart from cash benefits, domestic animals are meticulously associated to the social

and traditional lives of smallholder farmers for whom livestock possession guarantees variable degrees of

household economic stability (Mayala et al., 2017; Felicia et al., 2013). For instance, cattle, goats and sheep are kept

for different purposes such as meat, milk, manure, draught power, and ceremonies such as rituals, baptism and

weddings apart from being a source of income (Felicia et al., 2013). Livestock are also considered a communal

means of signifying wealth, strengthening relationships through bride price payment, and a social link (Ouma et

al., 2014). Therefore, farmers who attach more value to non-cash benefits, tend not to commercialize their livestock

production.

The Tanzania Livestock policy of 2009 and the vision 2025 recognizes the importance of addressing livestock

marketing challenges as a way of ensuring food security, employment creation, and increased incomes (URT,

2017). However, the lack of knowledge about smallholder livestock market limitations, business dynamics, and

reasons influencing the movement towards and out of markets often lead to imprudent interventions that have

little impact on improving household welfare (Ouma, 2014). It is anticipated that, findings from this study will

provide significant information to identify policy options for improving market participation and addressing the

marketing concerns that surround the livestock sector in rural Tanzania.

3. METHODOLOGY 3.1 The study area

The study utilized data from the household surveys for the year 2016 conducted in Mbulu and Bariadi districts in

Tanzania. The choice of the districts was based on the concentration of the number of livestock in the research area

being among those with high number of livestock in the country (URT, 2017). A cross sectional research design

was employed in gathering information using a questionnaire and key informant interviews. The sample frame

was smallholder livestock farmers who have been keeping cattle, goats and sheep (animals of interest for the

study). A total of 333 smallholder farmers were randomly selected in Mbulu (158) and Bariadi (175) making a

response rate of 86.7% respondents from the original sample size of 384 calculated using a formula of Fisher et al.

(1991) for population greater than 10000 (Appendix I).

3.2 Livestock Market Participation Decision Model

Smallholder livestock farmers in the study area do practice subsistence farming. Farmers are characterized with

limited participation in the livestock markets and by-products due to subsistence nature of livestock production

and farming systems. In recent years, farmers are adopting modern technologies and their productivity has


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improved. Accordingly, this enables them to participate in the market through selling their livestock and livestock

by-product surpluses. A smallholder livestock farmer’s decision to take part in market is influenced by many

socio-economic and farm specific characteristics (Gebreselassie, Sharp, 2008; Gebreselassie, Ludi, 2008;

Gebremedhin, Jaleta, 2010b). As per the study of Egbetokun and Omonona (2012), a Probit model is used in this

study to identify such factors being this study involving choice made by the farmers. The relationship between

market participation decision and the factors that affect the decision can be formulated as follows:

Yi = f (Xi, Di)…………………………………………. (1)

Where,

Yi = Market participation decision by a livestock smallholder farmers’ household

Xi = Continuous factors of market participation decision

Di = Qualitative factors of market participation decision (dummy)

In this particular study, livestock market participation decision by smallholder farmers is estimated as Y = 1 if the

household participates in livestock markets and Y = 0 otherwise as done by Gebreselassie and Ludi (2008).

The nature of market participation level, farmers are said to be market participant if their proportion of value sold

is of substantial value otherwise they are not motivated to participate in marketing (Goletti, 2005; Ohen et al.,

2013). Therefore, the author defined the binary response variable as Y = 1 if the farmer’s livestock and other by-

products sales exceed a threshold or critical level of Y*(75%) and Y = 0 if Y ≤ Y*. Here, the proportion of livestock

out of the total production by the livestock smallholder farmers in the respective year was used as the proxy of

market participation during data collection period (Moyo, 2010).

Furthermore, off-farm income, ownership of farm equipment’s, and number of livestock owned are highly

substantial asset variables as observed by Siziba et al. (2011). Socio-economic characteristics such as age, education,

farm size, ownership of some assets and farm output were observed to have positive effect on market participation

of livestock and other agricultural commodities (Olwande, Mathenge, 2012; Omiti et al., 2009; Randela et al., 2008).

Community assets have also been found to have positive relationship with market participation especially with

respect to access to credit and insurance (Cadot et al., 2006; Stephens, Barrett, 2011) and input use and access to

extension services (Alene et al., 2008). Additionally, Siziba et al. (2011) noted that extension training and

participation in research have positive effects on market participation. Following these studies, age, sex and

education of household head and that of the spouse were treated as socio-demographic aspects while farm size,

household labour, non-farm income earnings, access to credit, market information, on-farm income, income from

livestock, and non-farm income are used in Probit model as independent variables. Therefore, the specified Probit

regression model for detecting the factors that influence livestock market participation decision of smallholder

farmers is expressed as follows:

Yi = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 + β6X6 + β7X7 + β8X8 + β9X9 + β10X10 + β11X11 + ui…………… (2)

Where,

Yi refers to market participation decision by a household (Y=1, if farmers participate in the market and Y=0,

otherwise); X1, X2,…......, X8 are explanatory variables that affect the market participation decision; β0,………,β11

are parameters to be estimated; and is the stochastic error term. The Probit regression model adds the condition of

normally distributed variables that can be expressed as:

Where,

Ii = β0 + β1X1 + …………+ β11X11 = utility index (latent variable); P (Y=1/ X) = the probabilityof market

participation; Z = the standard normal variable, and F = the standard normal CDF. Gujarati (2003) explains the

behaviour of a dichotomous dependent variable as we need to use a suitable CDF (cumulative distribution

function). CDF is a function, which can be used in the regression model where the dependent variable is

dichotomous taking the values of 0 or 1. Which is say, CDF of a random variable X is merely the likelihood that

takes a value less than or equal to X0, where X0 is some definite arithmetical value of X. The approximation model


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that occurs from the normal CDF is generally known as the Probit model. In the selection equation (2), that is, the

Probit model, the dependent variable is a dichotomous variable ‘participation decision in the livestock market

(represented as 1 when a household participates in the market and 0 otherwise’). The independent variables that

condition the participation of smallholder livestock farmers as adapted from literature are farm size, household

labour, non-farm activities, use of credit, market information; income from livestock, non-farm income and farm

income. These explanatory variables are specified in Table 1 with their predictable sign assumed.

Table1: Definition of Hypothesized Effects of Explanatory Variables on Market Participation

Variable Variable

Type

Variable definition and measurement Hypothesized Effect

on Market

Participation

Herd Size Continuous Number of animals held by the household +

Family Labour Continuous Number of family members involved in taking care

of the livestock (aged 15-60 years)

+

Off-farm Activities Dummy 1 if participated, 0 if otherwise -

Use of Credit

schemes

Dummy 1 if took credit for livestock management, 0 if

otherwise

+

Market Information Dummy 1 if accessible to market information, 0 if not +

Income from

Livestock

Continuous Total value of livestock and by-products sold in the

year (Tanzania Shillings)

+

Non-Farm income Continuous Total value of income from non-farm (Tanzania

Shillings)

+

Farm Income Continuous Total value of income from farm sold produce

(Tanzania Shillings)

+

4. FINDINGS AND DISCUSSION 4.1 Socio-demographic Characteristics of Smallholder farmers in the study areas

Data was collected from 333 smallholder farmers and analyzed to describe the appropriate socio-demographic

characteristics associated with livestock keeping. The key features of the variables used in the study are as shown

in Table 2.

Table 2: Socio-demographic characteristics of respondents related to livestock investment

Variables Min Max Range Medn Mean Mode Std.

Dev.

Var.

Age 24 102 78 49 50.82 42 11.783 138.834

Education level HH 0 14 14 7 7.07 7 2.336 5.456

Education level of Spouse 0 12 12 7 6.62 7 2.661 7.079

Cattle 1 462 461 50 64.13 20 66.510 4423.634

Goats 2 500 498 22.5 47.13 10 62.011 3845.355

Sheep 1 280 279 20 30.27 10 33.735 1138.072

As indicated in Table 2, it was found that the average age of the household head is 50. 82 years with maximum of

102 years and minimum of 24 years. This shows that, livestock keeping in the study area is undertaken mostly by

aged people. That being the case, decision to participate in livestock markets may be to the lower side as elders in

African context may concentrate more on the social benefit of animals like keeping herds for inheritance of the

future generations, meeting socio-cultural obligations like bride price, rituals and ceremonies as found out by

Felicia et al, (2013). The average education level of head of household is 7.07 while that of the spouse is 6.62 in

number of years spent at formal schooling. This may be an indication that smallholder farmers and their spouse

have primary, secondary or tertiary education. This may mean that, smallholder farmers with regards to market


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participation may be placed at a level where they are not able to have the skills to search for market information or

understand some marketing message contents as found by Osmani and Hossain (2013) in Bangladesh. It is

however evident from the statistics point of view that most farmers have a good experience in livestock keeping i.e

the number of years they have been keeping animals of interest in this study (cattle, goats and sheep). However,

the question will be on their participation in the livestock market. This is because, in the study areas, the tradition

is to keep livestock for the social reasons rather than the commercial reasons.

4.2 Regression Results of Market Participation Decision In order to attain the objective of the study, a number of socio-economic variables which are thought and

established from the literature to have an influence on smallholder farmers’ decision to participate in the livestock

markets are included in the Probit regression. The estimation results are presented in Table 3.

Table 3: Determinants of Market Participation by Smallholder Farmers

Variable Coefficient Std. Error Z-value P>|z|

Herd Size 1.03*** 0.01 3.17 0.029

Family Labour 1.04*** 0.02 2.67 0.299

Off-farm activities -0.52 0.60 -0.90 0.564

Use of credit schemes -0.31 0.71 -0.70 0.011

Market information 0.02*** 0.03 -0.70 0.463

Income from livestock 0.022*** 0.01 -2.62 0.067

Non-farm income 0.018*** 0.02 -0.82 0.067

Farm income 0.037*** 0.03 1.90 0.076

Constant 3.72 2.51 -1.92 0.071

Log likelihood = -22.082217; LR chi2 (8) = 82.03;

Prob. > chi2 = 0.0000; Pseudo R2 = 0.6670

Note: *** 5% significance level

Table 3 shows that, the likelihood ratio statistics as indicated by chi-square statistics are highly significant (P

<0.0000), suggesting that the model has a robust expounding power. The Pseudo R2 is 0.6670, indicating that the

condition fits well the variables included in the model explaining 67% inconsistency in the decision of smallholder

farmers for livestock market participation. the table also indicates that the estimated coefficients of the Probit

regression show that the explanatory variables age, herd size, family labour, income from livestock, income from

non-farm activities and farm income significantly influence the smallholder farmers’ decision to participate in the

livestock markets as they turned out to be positively significant at (p< 0.05).

Findings indicate that herd size is statistically significant at (p< 0.05) level and has positive influence on the

decision for households’ market participation. As the herd size increases, the probability of decision for

commercialization increases. This finding is in line with Okezie et al. (2012), Goshu et al. (2012) and Gebreselassie

and Sharp (2008). The explanation of the findings could be due to the role of herd size in boosting total production

level in terms of number of milk litres, cattle, sheep and goats head counts for sales of surplus by-products like

milk, hides and ghee. Again, farm households with large herd size have a large flexibility to sale as the number of

animals and by-products cumulatively results in large proportion of the same as compared with households with

less number of animals. Felicia et al. (2015) had opined that herd size influences the level of livestock

commercialization in a study in Ghana. This study substantiates their result.

Furthermore, the variable family labour has shown a positive influence, at a significance level of (p<0.5) on the

decision of smallholder farmers to participate in the livestock market. The coefficient indicates that, if a household

has one more active family labour, its probability to taking decision of participating in the livestock market

increases. Rural household rarely use hired than family labour to take care of the animals. Girls do better in

cleaning, milking and taking care of the calves as found out my Moyo (2015) and Ciamara et al, (2017) while boys

do better in sending herds for feeds and search for water. This finding is consistent with Gebre edhin and Jaleta


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(2010b). In that case, it appears rational since households with a large number of active household labour can

decrease their cost of production and produce surplus for them to be market-oriented.

Moreover, the coefficient of income from livestock is found to be statistically significant at (p< 0.05) showing

positive influence on the probability of households to participate in the livestock markets. Findings indicate that as

income from livestock of the smallholder farmer’s increases, the probability of farmers’ orientation towards

commercialization in the study area increases. Thus, farmers with high degree of participation in the livestock

market may be highly efficient in enhancing their productivity; consequently farmers have a more chance of

achieving surplus production for sale.

Furthermore, farm income as another important variable has resulted into being significantly positive impacting

on the decision of smallholder farmers to participate in the livestock market. At (p < 0.5) it has shown that,

households with high level of farm production (crops) tend to participate in the market than those with lower

production level. This means that farmers’ decision on livestock market entry is significantly related to the amount

of farm production levels. This may be due to the fact that households with higher number of animals and

products has much more chance to sell higher proportion of their animals and produce and thus, increase the

probability to participate in market due to the surpluses they have. This finding is comparable to the finding of

Moyo (2013), as well as Felicia et al. (2015).

The approximation of findings presented in Table 4, is also presented as the marginal effects of the variables

predicted probability of households’ market participation, evaluated at the means of the explanatory variables,

presented in Table 4. The marginal effects present the Probit regression providing the probability that a farm

household will participate in livestock markets. Table 4 provides the probability estimation for the likelihood of

market participation of a farm household given the statistically significant variables: herd size, family labour;

income from livestock, non-farm income and farm income. The marginal effect report of the Probit regression in

Table 4 shows that there is a probability of 11% that a smallholder farmer participates in the livestock market if his

herd size increases at mean value by one unit. Further, the marginal effect shows that there is a probability of

approximately 17% that a smallholder farmer participates in the livestock market if he/she succeeds to have a

mean of one additional active family labour. Likewise, the probability that a smallholder farmer will participate in

livestock market as a result of a one shilling increase, at mean value, if the farm income is given by 0.0001%. This

means that, if the farm income of a farmer increases by Shilling 1000, at mean value, then the likelihood of

participation in the market increases by 0.1%.

Table 4: Marginal Effect of the Explanatory Variable

Variable Coefficient Std. Error Z-value P>|z| x-bar

Herd Size 0.011*** 0.04 2.98 0.001 3.99

Labour 0.167** 0.08 2.20 0.023 1.19

Off-farm activities -0.112 0.13 -0.91 0.311 0.47

Use of credit schemes -0.070 0.10 -0.61 0.497 0.39

Market information 0.079*** 0.15 0.59 0.511 0.71

Income from livestock 0.006*** 0.00003 1.98 0.013 197.11

Non-farm income 0.0002*** 0.00002 -0.69 0.391 298.56

Farm income 0.00001* 0.00006 1.57 0.067 10344

Observed probability 0.4

Predicted probability 0.1075557

Log likelihood = -22.082217; Number of observation = 333; LR chi2 (8) = 82.03;

Prob. > chi2 = 0.0000; Pseudo R2 = 0.6670

Additionally, the marginal effect results of the Probit regression in Table 4 indicates that, if a smallholder farmers’

income from livestock increases by one Shilling, then there are 0.0006% likelihoods that he/she would take part in

the livestock market since the coefficient of this variable is positive to indicate the direction of the influence.


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5. CONCLUSION AND RECOMMENDATIONS

From the findings of the study, it seems that smallholder farmers are influenced by a number of factors in livestock

marketing making for them to fully commercialize. Smallholder farmers in the study area are likely to contribute

to economic growth and development if they participate in the livestock markets. Findings indicate that among the

eight tested factors, six turned to be positively significant influencing the decisions of smallholder farmers to

participate in the livestock markets. As herd size was found to be a significant factor, the study concludes that, for

small holder farmers to have surpluses to sale coming out of the economies of scale by having an adequate number

of the animals in question. On the other hand, family labour was also found to be a significant factor influencing

smallholder farmers to participate in livestock market. It is concluded that, indeed, rural household depend on

family labour than hired labour as it is a practice from urban and large scale livestock keepers. It is also concluded

that, market information is crucial for smallholder farmers about their decision to participate in the livestock

markets. Findings shows that information is an important aspect for them to participate as income from livestock,

non-farm income and farm income has turned out to be positive and significant factors. Which means that, farmers

are in need of the income from all the three mentioned economic activities, hence information is important.

It is recommended that efforts should be made at family level to balance the need of family labour and other

important social aspect functions. As it has been found in the socio-demographic findings, the number of years

spent at school for the head of households and spouses is less; it could translate into children not being sent to

school as it is the case for most pastoralist communities around the world. More awareness campaigns on the

balance of the two aspects should be provided to smallholder in the study area. Furthermore, the government

should ensure that more information about price, business opportunities, networks with other livestock business

operators are built to support the smallholder farmers in the study area. Provision of marketing incentives to

smallholder livestock farmers and development of an institutionalized marketing information service are also

recommended to enhance commercialization of livestock in the study area.

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APPENDIX 1: Calculation of Sample Size

The sample size was 384 determined using the formula of Fisher et al (1991): for population greater than 10000

n = Z2 pq

d 2

Where-:

n - The desired sample size

Z - The standard normal deviation, set at 1.96, which corresponds to 95% confidence level

p – Skewness level estimated at 50 percent

q = 1.0 – p

d = the degree of accuracy desired, here set at 0.05 corresponding to the 1.96.

In substitution, n= 1.962 x 0.5 x (1-0.5) = 384

0.052

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http://www.worldbank.org/en/news/

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