Market Participation Among Kenyan Smallholder Sweet Potato Farmers
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Published: Mon, 5 Dec 2016
Market participation has a potential to increase farmers rural incomes and employment opportunities. With the maize shortages in Vihiga district which is synonymous to food insecurity majority of farmers have resorted to consuming and producing sweet potatoes. Only a few participate in output markets leaving a majority of the farmers with a low purchasing power despite the increasing demand in many markets. The aim of this paper is therefore to evaluate the determinants of market participation of the sweet potato based farmers so as to advise policy on what could be done to increase participation. Primary data will be collected using structured questionnaires while secondary data through government publications, journals and district statistical offices. A sample of 120 farmers will be selected using multi-stage stratified sampling procedure. The paper will use descriptive statistics to characterize the sweet potato based farmers and the marketing channels that they use and a Multi-nomial logit will be used to analyse the determinants of market participation. Socio-economic factors at the farm and farmer level, institutional like extension services and membership to farmer groups, cultural like farming methods and standard norms and values and infrastructural factors like road conditions and storage facilities will be expected to be the major determinants of sweet potato market participation.
TABLE OF CONTENTS
Statement of the Problem
Justification of the study
Limitations and scope of the study
Definition of terms
2.1 Empirical literature review
2.2 Theoretical framework
2.3 Conceptual framework
3.1 Study area
3.2 Sampling procedure
3.3 Data types and Sources
3.4 Analytical techniques
Over the recent years increased marketing of agricultural crops has increased participation in output markets for the smallholder farmers. In Sub-Saharan Africa most farmers produce for subsistence rather than market purposes. Majority of crops that are marketed include high value crops and cash crops which have a high return. Traditional crops like the sweet potato are normally for subsistence use especially when staple foods are in short supply (FAO, 2002).
Majority of households in Kenya are smallholder farmers who depend on agriculture for their livelihoods and most of them live in rural areas. Vihiga is one of the poorest and densely populated districts of Kenya with an average household land size of 0.4 hectares. (GOK, 2004). This has been attributed to limited land, high poverty levels, and limited off-farm incomes. The main food crop cultivated is maize, recording a yield of 20 bags/hectare, (GoK, 2001). Maize is the staple food for the residents of Vihiga thus its insufficiency is synonymous to food insecurity.
Over the decade (1997-2006), the district’s demand for maize outpaced the production level, worsening the already bad food situation, (Nyangweso et al., (2007). Because of this food insufficiency, smallholder farming households have resorted to production of drought tolerant resistant crops which require low inputs like the sweet potato.
Sweet potato (Ipomoea Batatas) is an important secondary food crop for many farming households of Kenya whose staple diet is based on cereals, particularly maize (Gakonyo, 1993). These act as a source of food especially when maize is in short supply. Over the decade (1998-2007) sweet potato output had been on an upward trend as shown in the figure below, and this trend could be attributed to government efforts to promote the production of the crop through distribution of 4.3 million sweet potato vines to farmers (MOA, 2009), and the yield of the crop which has been slightly increasing.
Figure 2: Sweet potato production and trends
Source: FAOSTAT 2010
In addition, the ability of sweet potato to establish ground cover very fast enables suppression of weeds such as striga, control of soil erosion and maintenance of soil fertility. Therefore it is an attractive crop for Kenya’s farming systems.
In Kenya sweet potato growing is mainly concentrated in western Kenya (including Kakamega, Bungoma, Busia former Homa Bay, Rachuonyo and Kisii districts). It is also grown to a small extent at the coast and in Central Province.
In nutritional terms, sweet potato, particularly the yellow fleshed varieties are good sources of vitamins A (300 micrograms/100 grams, fresh weight) (Woolfe 1992). A comparison with other food crops shows that it yields more calories per unit area than either maize or potato and nearly as much as cassava, while its protein yields is far higher than the latter (table 1).
Table 1: Nutritive value of maize compared to root and tuber crops
Yield, t/ha (average of 88 to 96)
Energy, KJ per 100 g fresh matter
Crude protein, g per 100 g fresh matter
Energy, MJ per ha
Crude protein, kg per ha
Source: Rehm and Espig (1991), FAO (1997)
1.2 Statement of the Problem
Unavailability of food to rural dwellers in easily accessible markets for consumers has increased food insecurity to the rural populations of Vihiga district and Kenya generally, despite increased sweet potato farming amongst majority of smallholder farmers and increased demand for sweet potatoes amongst rural and urban consumers in Vihiga district. Increased market participation by majority of the sweet potato farmers could increase their incomes and thus reduce their food insecurity situation through their improved purchasing power.
All the advantages of sweet potato farming like provision of early maturing varieties to curb food insecurity when maize, the staple food crop is in short supply, low prices to consumers as compared to other foods and high prices for farmers especially in urban markets, nutritional benefits like high calorie content, use in brewing industries and others that can be achieved given the stable sufficient production of sweet potatoes currently existing in Vihiga district, have not been realized because smallholder sweet potato farmers’ participation in markets is minimal due to unknown factors, thus the need for this research to close that knowledge gap by helping identify determinants of market participation for smallholder sweet potato farmers in Vihiga district and to inform policy such that impediments to market participation are cleared.
1.3 Objectives of the study
The main objective of the study will be to evaluate factors that affect sweet potato farmers’ market participation in Vihiga district. Specifically, the study will attempt;
To describe the socio-economic characteristics of sweet potato farmers in Vihiga district
To characterize (identify, describe and level of participation by farmers) the marketing outlets/channels available to the sweet potato farmers.
To analyse the factors that influence market participation of sweet potato farmers
1.4 Research Questions
What are the socio-characteristics of smallholder sweet potato farmers that influence market participation?
What are the characteristics of the marketing channels available to the farmers?
What factors mainly determine market participation of the sweet potato farmers?
Food insecurity the world over, where ever it exists brings about instability and loss of lives thus food security is a critical issue in every area, Vihiga district not excludable. Therefore ways of improving farmers’ incomes and employment opportunities through generating information on market participation becomes necessary especially about crops that majority of the farmers grow in this case taking prime interest in sweet potatoes.
Furthermore, climate changes, population pressure and high costs of production have decreased the production of the staple food, maize, in this area thus the need to focus on commercialization of a crop such as the sweet potato which is grown by majority of the smallholder farmers as a food security crop, high yielding given the small land sizes, its adaptability to harsh weather conditions and low input requirements.
Evidence on perishable crop (such as sweet potato) market participation is needed as literature in Sub-saharan Africa focuses on grain and high valued cash crops for example maize, vegetables and cotton. Drivers of marketing decisions may differ based on crop perishability For example, there could be a high portion of net sellers among growers as storage options are limited, and seasonal conditions could result in large supply variations. Moreover, price could have a limited impact on the decision making of perishable-crop sellers as these crops cannot be stored for long periods and once consumption needs have been met ( Komarek, 2010).
1.6 Limitation and Scope of the study
This study will take into consideration all the varieties of sweet potato produced by smallholder farmers in Vihiga district. Any farmer who grows sweet potatoes will be considered a possible target for this study.
Because sweet potato is a low input requirement crop, the study will limit itself to analysis of the output markets only.
The study will cover all the original six divisions of the district, using twenty farmers from each division to make a total of 120 respondents.
Cross-sectional data only will be used for the study.
1.7 Definition of key terms
2.1 Empirical literature review
2.2 Theoretical framework
2.3 Conceptual framework
Determinants of Market Participation: Socio-economic factors (gender, age, education level ), institutional factors ( credit, land tenure system), cultural factors and infrastructural factors.The figure below provides a sequence of relationship that the researcher conceptualized in relation to how determinants of market participation will influence the sweet potato farmers activities.
Markets: village retail level, local town, transshipment and final destination markets
Sweet potato farmers; Participators and non-participators in markets
Level of farmers’ income
Figure 1: A Conceptual framework showing factors affecting Market Participation and its effect on farm incomes.
Source: Researcher’s own
Socio-economic factors affecting market participation of farmers like gender of farmer, age, education level, household size, farm size, off-farm income of the household and credit access; cultural factors like farming methods, taboos and standard norms and values; institutional factors like membership to a group, access to extension services and land tenure system and infrastructural actors like road conditions and storage facilities will determine whether sweet potato farmers will participate in markets. The class of the level of participation of these sweet potato in markets will determine characteristics of markets like size (in terms of numbers of consumers and producers), type (value added or not) and distance location that these farmers participate, at village level retail, local town, transshipment or final destination markets. These market characteristics will in turn dictate the amount of returns (incomes) to these sweet potato farmers that could be used by farmers to influence the factors affecting their market participation to the directions of the farmers’ interest.
3.1 Study Area
Vihiga county formerly, district, Western Province, occupying an area of 563 km2, is among the smallest districts in Kenya (GoK 2002). It is sub-divided into six administrative divisions: Luanda, Emuhaya, Sabatia, Tiriki East, Tiriki West and Vihiga. Table 1 below shows the administrative divisions, their areas and populations and the number of administrative locations.
Table 1: Administrative Units, Area and Population
Source: Vihiga District strategic plan 2005-2010
The average density is estimated at 975 persons per square kilometre, making it the third most densely populated district in the country after Nairobi and Mombasa districts (CBS 2000). The high density has led to serious fragmentation of agricultural land into uneconomical units. Agriculture and livestock production are the key livelihood activities, providing for nearly 80% of incomes generated. Nevertheless, the sector is beset by several constraints such as inadequate credit facilities, poor crop varieties, landlessness, poor access to markets and outdated traditions and culture (GoK 2001). Poverty is widespread throughout the district. According to the District development plan 2005-2010, about 62% of the population in Vihiga District lives in absolute poverty and about 60% of the population is food poor. This means that half of the population is in some state of poverty. The district’s contribution to national poverty is 3%. Areas of high concentration of poverty are found in Luanda, Emuhaya, Tiriki East and West and Vihiga Divisions. A summary of the socio-economic indicators of the district are presented in table 2 below
Table 2: Socio-Economic Indicators, 2001
Total number of households
Average household size
Number of female headed households
Absolute poverty (Rural and Urban)
Income from Agriculture
Income from self employment
Source: Adapted from the Vihiga District Strategic plan 2005-2010
The target population for the study will be sweet potato producing farmers participating in the output markets. The study will apply multi-stage stratified sampling procedure where it will purposively select three divisions in the district that is Luanda, Sabatia and Vihiga divisions because they are densely populated and the incidence of poverty is high therefore sweet potato commercialization efforts will be justified. Simple random sampling technique will then be used to select the required sample because the target population is large and majorly homogenous that is they grow sweet potatoes on small scale. The source list/sampling frame will be obtained from the district statistical offices in Mbale. The study will purposively select a sample of 20 households from the six divisions making a sample size of 120 households which is justified because it has surpassed the recommended sample of 30 for representative results. The table of random numbers will be used to come up with the required sample.
Data types and sources
Primary data for this study will be collected using a structured interview schedule administered to the sampled households because a majority of them are illiterate and data analysis will be made easy. Secondary data will be collected from Government publications, district statistical offices and various data bases.
To analyse objective one, descriptive statistics will be used i.e. mean, variance, standard deviations, and proportion. Characterization of sweet potato farmers will involve establishing the following parameters; land ownership and size, area of land under sweet potatoes vis a vis other crops, age of the farmer, gender, non-farm income, and reason for sweet potato production i.e. food security, sale or leisure, contact with extension agents and availability of credit facilities.
To analyse objective two, descriptive statistics will also be used. The marketing channels available in the locality will be identified and the choice made by majority identified. Mean and mode will be used to analyse the data. The level of market participation of the different market channels will also be analysed using percentages and pie charts. Variables to be looked at will include the number of participants in sweet potato markets, number of participants in sweet potato markets as a percentage of the total number of farmers to be sampled, gender of farmer, age, household size, quantity of sweet potato produced the last cropping season (Kg), quantity of sweet potato sold last year (kg), quantity of sweet potato consumed by the household, credit facilities available to the household, access to adequate road infrastructure, access to adequate storage facility and access to reliable information/ markets.
To analyse objective three which is to determine the factors affecting market participation among the sweet potato farmers, a multinomial logit model will be used. whereby the dependent variable ( market participation which will be the single decision) will have various options (village level retail markets, local town markets, transshipment, final destination markets among others) while the independent will have the same variables which will then be regressed on each market option to see which variable is most significant.
According to Greene (2002), the model has a single decision among two or more alternatives. Unordered choice models can be motivated by a random utility model. For the ith farmer faced with j choices, suppose that the utility of choice j is
If farmer makes choice j in particular, then we assume that Uij is the maximum among the j utilities. Hence the standard model will be driven by the probability that choice j is made which is
Probability (Uij>Uik) for all other k≠j………………………….Equation 2
Let Yi be a random variable that indicates the choice made. Mc Fadden (1973) showed that if the j disturbances are independent and identically distributed then
which leads to a conditional logit model. Utility will depend on Xij which will include aspects specific to the individual as well as to the choices. Assuming Zij = (Xij, wi), then Xij will vary across the choices and possibly across individuals as well. The components of Xij will be attributes of the choices but wi will contain the characteristics of the individual and thus same for all choices. If this is incorporated in equation 3 then
For each sample, the data for each of the individual in the sample will consist of the following:
Market options/channels: 0=village retail level markets; 1=local town markets; 2=transshipment markets; 3=final destination markets
Regressors: constant and independent variables
For each farmer who participates in the market, there is a single decision among two or more alternatives. For the ith farmer faced with j choices suppose that the utility of choice j is
The model for market choice is as below:
The estimated equations will provide for a set of probabilities for the j+1 choices for a decision maker with characteristics Xi.
Variables for the multinomial logit are shown in table 5 below. Factors that negatively influence the dependent variable are those that reduce market participation while those with a positive influence increase the same.
Table 5: Variables used in the Multinomial Logit Model.
Unit of measurement
Farmer participates in market ( options)
0= village retail level, 1= local town, 2=transshipment, 3=final destination
Gender of farmer
Age of the farmer
Level of household education
No of males/females
Off farm income
Access to credit
Land tenure system
Dummy(0=no storage,1=local storage,2 modern)
Distance to the nearest market
If member of a group
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