Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.8, No.8, 2017 1 Analysis of the Determinants of Sweet Potato Value Addition by Smallholder Farmers in Kenya Mary Orinda1* Job Lagat2 Patience Mshenga2 1.School of Agricultural and Food Sciences, Jaramogi Oginga Odinga University of Science and Technology, P.O. Box 210-40601, Bondo, Kenya 2.Faculty of Agriculture, Egerton University, P.O. Box 536-20115, Egerton, Kenya Abstract Sweet potato value addition is increasingly being popularized among producers due to its potential to reduce wastage, increase market access and fetch optimal prices. Despite these documented benefits, smallholder sweet potato producers in Kenya have not implemented value addition widely. This study analyzed the factorsinfluencing value addition and extent of value addition by smallholder sweet potato farmers of Rachuonyo South sub-county in western Kenya. Using a sample of 200 smallholder farmers, Heckman’s Probit model with sample selection was employed to firstly identify the factors affecting a farmer’s decision to adopt value addition, and secondly evaluate the factors that affect the extent of a farmer’s participation in sweet potato value addition. Study findings show that the probability of adoption was significantly influenced by household size, total quantity produced, credit access, land size and training. Further results show that the distance to the market, group membership, credit access and total quantity produced were found to greatly influence the extent of value addition by sweet potato farmers. In order to leverage smallholder farmers’ adoption of sweet potato value addition, it is important that county and national government policies should focus on encouraging farmers’ group formation, provision of cheap value addition loan packages, seminars, farmer field days and workshops to enable exchange of ideas among different farmers and further encourage farmers to produce more to benefit from economies of scale. In addition, proper marketing strategies such as linking farmers with supermarkets, adequate product development, proper packaging and labeling are challenges that require urgent attention. Keywords: Postharvest technologies, food security, Heckman two-stage selection model, sweet potato value chain, community based rural enterprise 1. Introduction Sweet potato (Ipomoea batatas Lam.) is a major staple food and a source of income in several regions of Kenya and elsewhere (Keller, 2012; Were et al., 2013). In Kenya, it is an important food crop for those who depend on cereals especially maize as their staple diet with an average per capita consumption of 24 kg per year, with higher proportions being consumed in the western parts of Kenya (Were et al., 2013). The agronomic traits of sweet potato to give satisfactory yields under adverse climatic and soil condition as well as under low or non-use of external inputs has also made sweet potato production gain popularity among many farmers in Kenya (Nungo et al., 2007). In addition, the flexibility of the crop in mixed farming systems and the ability to take short periods to mature, thus offering household food security, has made it an important livelihood strategy for small-scale farmers. Although grown by small-scale farmers for subsistence, importance of sweet potato production as an attractive income generator has been rising (Fuglie, 2007). This has been influenced by factors, such as new market outlets in urban centers, high cost of inputs for maize production, high cost of living which has forced people to consume cheaper foods (IDCCS, 2009; Were et al., 2013). This is evidenced by the steady increase inthe area planted. For example, in Kabondo and Kasipul divisions of Rachuonyo south district, farmers devoted approximately 75% of their land holdings to sweet potato production, where both white- and orange-fleshed sweet potatoes are grown by most households on smallholder farms(CEFA, 2010; DAO, 2008).This indicates the important role sweet potato production plays in reducing poverty and improving rural incomes in these areas.Unfortunately, rapid post-harvest spoilage due to perishability, poorly developed market chains coupled with inherent bulkiness of the crop leading to costly transport over long distances, contribute to lower net returns for smallholder sweet potato farmers. For sweet potato, postharvest losses of up to 20-30% have been reported (AGRA, 2013), with higher losses during periods of abundance. Consequently, initiatives that offer theopportunity to increase demand for the crop and create value added products, thereby expanding the incomes of smallholder producers, are critical for sustainability of production in these areas. 1.1 Sweet potato value addition Sweet potato value addition entails deliberate activity to change the form of the raw sweet potato into a more refined or usable form, thus increasing its value. For household and market purposes, sweet potato can be processed and utilized in various ways into beverages, soups, baby foods, ice cream, baked products, restructured fries, breakfast cereals, and various snack and dessert items (Ray and Tomlins, 2010; Nungo, 2004; brought to you by COREView metadata, citation and similar papers at core.ac.ukprovided by International Institute for Science, Technology and Education (IISTE): E-Journals
Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.8, No.8, 2017 2 Fawzia et al., 2000; Nxumalo, 1998). Initially, utilization of sweet potato in western Kenya was limited to boiling, roasting and chewing raw. However, this has been changing to value addition by processing the tubers into different products (Nungo et al., 2007; Fawzia et al., 2000). Contemporary studies and research point to the need of value addition of agricultural produce as it isperceived that farmers could maximize on their produce and also potentially increase their revenue in the process. Value addition in sweet potato has the potential to enhance the production of the crop and further play an important role in the food/nutritional security and income generation among the rural households and even urban markets (Nungo et al., 2007; Westby et al., 2003). In addition, processing of sweet potato into non-perishable products also addresses the farmer’s storage problems while ensuring food availability in time of scarcity (Westby et al., 2003). Therefore, this is a key strategy to commercialize farming for small holder farmers in Africa. According to a study by Lemaga (2005), the introduction of sweet potato based enterprises to poor and marginalized smallholder farmers increases their income as a result of sweet potato products sales and their knowledge on post-harvest technologies leading to improved food security. Indeed, research carried out by the International Potato Centre (CIP) on sweet potato productivity in developing countries found that value addition is an important post-harvest need (Fuglie, 2007). In Rachuonyo South sub-county, commercial processing of sweet potato into other more (non-traditional) commercial products have been promoted through farmer groups (FG), farmer field schools (FFS), non-governmental organizations (NGO) and community-based organizations (CBO) (IDCCS, 2009; Nungo et al.,2007). The promotion of on-farm processing of sweet potato in the district has been going on since 1995. In 2002, nearly 60% of the farmers in western Kenya were reported to be aware of utilization and processing technologies that aim at adding value and expanding sweet potato market potential (Odendo and Ndolo, 2002). Despite these documented initiatives and potential benefits of value addition, the majority of smallholder sweet potato farmers in Rachuonyo South sub-county have not embraced value addition widely. The factors that keep the sweet potato farmers from engaging in value addition are not clear and hence there is a need to investigate which factors determine their participation in the different value addition activities and the extent of value addition being undertaken. The result will be of interest to several development stakeholders, including relevant Government agencies (research, extension, policy and planning) and Non-Governmental Organizations (NGOs)to allow more informed decisions on how to promote value addition adoption and how to design appropriate policies to develop the sweet potato sub sector by the government. 1.2 Theoretical framework This study assumes that there is a potential for sweet potato value addition and that households who engage in value addition activity will increase their purchasing power due to increase in income and thus impacting positively on their livelihoods. The decision to engage in value addition is predicted by its perceived utility which is expected to be higher than without value addition. A profit maximization framework was used to examine the decision to add value or not.It is assumed that smallholder sweet potato producers will only add value if the expected net benefit from this option is significantly greater than it is the case without it. Suppose that iUand jUrepresent a household’s utility for two choices, then the model is specified as: inniUεβ+Χ=andjnnjUεβ+Χ= (1)where iU and jUare perceived utilities of value addition and non-value addition choices i and j, respectively,nΧis the vector of explanatory variables that influence the perceived attractiveness of each choice, βn are parameters to be estimated, iεand jε are error terms assumed to be independently distributed (Greene, 2002). In the case of sweet potato value addition, if a household decides to use optioni, then the expected utility from option iis greater than the utility from option j, which is defined as: ))(()(jnjnjininiUUεβεβ+Χ>+Χji≠ (2)The probability that a farmer adds value and chooses option iinstead of j, is then defined as: )()1(njniUUPYP>=Χ=)0''(Χ>+Χ−+ΧjnjiniPεβεβ(3))0''(Χ>−+Χ−ΧjinjniPεεββ))(0(nnFPΧ=Χ>+ΧΧ∗∗∗βε
Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.8, No.8, 2017 3 where P is a probability function, niU, njU represent a household’s utility for two choicesand nΧis the vector of explanatory variables that influence the perceived attractiveness of each choice, jiεεε−=*is a random disturbance term, )(''*jiiβββ−= is the net influence of the vector of independent variables influencing adoption of value addition, and )(*nFΧβis a cumulative distribution function of ε* evaluated at nΧ*β. The exact distribution of F depends on the distribution of the random disturbance term, ε*. Depending on the assumed distribution which underlies the random disturbance term, several qualitative choice models can be estimated (Greene, 2002). 2. Materials and Methods 2.1 Description of the study area The study was conducted in Rachuonyo South sub-county, which is located in Homabay County in western Kenya (Fig. 1). The region was selected because it is the leading sweet potato production area in Kenya. Rachuonyo South sub-county falls between longitude 34025’S 35oE and latitude 0o15’S 45’S, covering an area of 509.5 km2 with 196,210 inhabitants and 44660 small farm holdings as per the 2009 population census of Kenya (GoK, 2009). The altitude ranges from 1300 – 1770 m above sea level along the Lake Victoria shores to the upper areas bordering Kisii and Nyamira Districts. The district has an inland equatorial climate which is modified by the effect of altitude and proximity to the Lake Victoria with temperatures ranging from 17°C to 25°C. Rainfall is distributed bi-modal around the year and ranges from 800-1400 mm per annum. The crops grown include maize, sorghum, cotton, groundnuts, sweet potatoes, cassava, sunflower and beans. 2.2 Study design and data The study uses both primary and secondary sources of data. Primary data was collected using questionnaires which were administered to the sampled households. During sampling process, a two-stage sampling procedure was used to select sample farmers that were included in the study. In the first stage, out of the total 18 locations of the Rachuonyo South sub-county four locationswere selected purposively based on their sweet potato production. In the second stage, from the selected locations, systematic random sampling technique was adopted to randomly select respondents based on probability proportional to size of households of each location. As a result, two hundred farmers were chosen for the study. Primary data were collected from the selected farmers through a well-structured questionnaire which was randomly administered to farmers. Secondary data wascollected from the District Agricultural Reports, NGO’s such as CEFA, IDCCS and C-MAD and Government databases. Data collected included marketing outlets, various value addition activities and various sweet potato value added products. Descriptive statistics involving mean, percentage and standard deviations were used to assess the household characteristics and institutional factors affecting farmers’ response to adoption of value addition technologies. Both Pearson Chi square analysis and t-test were used to compare the qualitative determinants affecting the decision of both non-value adders and value adders. These analyses were performed using SPSS version 17.5 (IBM, NY, USA). 2.3 Empirical approach and model specification In this study both descriptive statistics and econometric models were utilized to assess the relationship between explanatory and dependent variables. For the econometrics model, the Heckman two stage selection model was used to assess the factors influencing sweet potato value addition. It included various variables such as household characteristics, institutional characteristics and marketing characteristics. It is hypothesized that the farmers’ behavior is driven by the need to derive or maximize the utility associated with the practice. Depending on the farmers’ perception on the utility choice is made, either to add value or not. This farmers’ behavior that leads to a particular choice is modeled in a logical sequence, starting with the decision to add value, and then followed by a decision on the extent of the value addition. Since the farmers’ utility maximization behavior cannot be observed, the choice made by the farmer is assumed torepresent the farmers’ utility maximization behavior. Based on the nature of these decisions, it is justified to use the Heckman two-stage selection model, in which estimations involves two stages. In the first stage, the decision to add or not to add value was assessed using a probit model. The choice of this model is based on the fact that the decision to add value is discrete; it is either one adds value or not. Furthermore, the study assumes that the error term is normally distributed hence the choice of the probit model. The reasoning behind the two stage approach is that the decision on the extent of sweet potato value addition (the number of 90 kilogram bags used for value addition) is usually preceded by a decision to engage in the process of value addition. The probit model
Journal of Economics and Sustainable Development www.iiste.orgISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.8, No.8, 2017 4 used in the first stage is as specified in Equation 4 below: 1 (4) where Y is an indicator variable equal to unity of households that add value, φ is the standard normal distribution function, s are the parameters to be estimated and s are the determinants of the choice. When the utility that household j derives from value addition is greater than 0, takes a value equal to 1 and 0 otherwise. It follows therefore, that: (5) where ∗ is the latent level of utility the household gets from value addition and ∼ 0,1. Given this assumption, it follows that: 1 if ∗% 0 and 0 if ∗) 0 (6) Empirically, the model can be represented as follows: * (7) where Y is the probability of a household adding value given farm, farmer and market and institutionalcharacteristics andthe error term*. In the second step the Inverse Mills Ratio (IMR) is added as a regressor in the extent of value addition equation to correct for potential selection bias. It was expected that the extent of value addition is self-selected in the sense that only some farmers choose to add value, hence the decision of the extent of value addition is preceded by the decision to add value. Consequently, this raises an empirical problem of self-selection. To reconcile this problem, the decision to add value is treated endogenously in this study to control for the potential sample selection problem. Therefore, first the determinants of the decision to add value are estimated, then the IMR from the selected equation is used as an independent variable in the target equation, that is used to assess the determinants of the extent of value addition. EZ Y 1 -x yλ1 μ (8) where E is the expectation operator, Zis the (continuous) extent of value addition measured by the proportion of value added sweet potato output, xis a vector of independent variables influencing the extent of value addition and is a vector of the corresponding coefficients to be estimated, λ1 is the estimated IMR. So Zcan be expressed as follows: 3∗ yλ1 μ (9) where 3∗ is only observed if the farmer is undertaking value addition (Y=1), hence Z 3∗. Empirically, this can be represented as: 3 yλ1 μ (10) where 3 is the extent of value addition given the farm and farmer characteristics , the Inverse Mills Ratio λ1estimated in step one of the Heckman model and the error term μ. Equation (7) and (10) were then jointly estimated using the Heckman two stage procedure in STATA 9 (StataCorp LP, Texas, USA). The explanatory variables used in the two stage Heckman selection included age of respondent, gender household head, access to extension services, household size, accessibility to credit, training, education level, quantity of potato harvested, off-farm employment, distance to the nearest local market and farmer group membership (Table 1). The a priori expectation of the survey was that age, gender of the household head, distance to the market and household size would influence value addition either positively or negatively, while total quantity produced, education level, credit access, group membership, training and land size werehypothesized to positively influence uptake of value addition technologies.