Farm and Household Characteristics

Farm and household characteristics are shown in Table 4.1. We differentiate between HVM and TM suppliers. The majority of the farmers in HVM supply vegetables to supermarkets. This involves verbal agreements on quantity, price, and time of delivery. A few HVM farmers also sell their vegetables to companies and institutions (e.g., hotel chains). As the agreements between farmers and these companies and institutions are similar to the agreements with supermarkets, including both in the same HVM category is justified.

While the supply channel of farmers may change over time, the distinction between HVM and TM suppliers in any particular year is clear-cut. All TM suppliers sell their vegetables only in traditional markets. Most HVM suppliers sell their vegetables primarily to HVM; only when the harvested amount at a particular date unexpectedly exceeds the agreement with supermarkets or other institutions, the surplus is sold in TM.

HVM suppliers tend to specialize on one HVM channel. That is, in 80% of the cases, the HVM supplier sells to only one particular supermarket, company, or institution.

Sample households are typical smallholders with an average farm size of 1-2 acres. Some of the variables shown in Table 4.1 deserve further explanation. Personal characteristics of the farmer are captured in terms of age, gender, and education. This refers to the person in the household responsible for vegetable cultivation and marketing, which may or may not be the household head. Wealth and capital endowment are captured in terms of ownership of assets, such as land, livestock, and a vehicle (means of transportation), among others. Furthermore, we look at access to certain types of infrastructure, such as piped water and electricity. Household size and off-farm employment of the farmer are proxies for labor availability and the opportunity cost of

8 Of the 66 farmers that could not be interviewed again in 2012, 18 were supplying supermarkets and 48 traditional markets in 2008. In order to test for attrition bias we followed an approach similar to Wooldridge (2002 p. 582), using the full sample from the first round and estimating the probability that a household is also interviewed during the second round with a probit model. Based on this model, we estimated the inverse mills ratio, which was included in a first-differenced income equation for the reduced sample used in our analysis. The inverse mills ratio was insignificant in this income equation. We conclude that attrition

when credit markets fail (Oseni and Winters 2009).

Table 4.1.Sample descriptive statistics

HVM 2008 TM 2008 HVM 2012 TM 2012

Age of farmer (years) 47.24^* (12.94) Education of farmer (years of

schooling) Number of HVM neighbors 2.90^***

(1.65) Per capita income (Ksh per

year) Access to credit for buying

production assets ^a

0.78^***

(0.42)

0.53 (0.50)

Number of observations 115 221 77 259

Notes: ^*** p<0.01; ^** p<0.05; ^* p<0.1. HVM, suppliers to high-value markets; TM, suppliers to traditional markets. Mean values are shown with standard deviations in parentheses. Monetary values for 2012 were deflated to 2008. Mean values between HVM and TM in the same year were tested for statistically significant differences. ^a This variable was measured in different ways in the two survey rounds, hence only the 2012 values are included.

Chapter 4. Following Up on Smallholder Farmers and Supermarkets in Kenya

In the conceptual framework we discussed the possible role of social capital to facilitate farmers’ access to HVM. We proxy social capital with a variable measuring the number of farmers supplying HVM among the five nearest neighbors in terms of geographic proximity. The five nearest neighbors refer to other farmers in the sample and are derived from GPS coordinates measured at the farmers’ homestead. Coordination between nearby farmers may reduce the cost of supplying HVM. In principle, clustering of HVM farmers could also be the result of supermarkets preferring to transact with farmers located in proximity to one another and therefore, as such, is not conclusive evidence that social capital matters. However, in this case the transaction costs are primarily borne by the HVM farmers themselves, as supermarkets require farmers to deliver their vegetables directly to the stores in Nairobi. Indeed, previous research in Kiambu showed that collective action among HVM farmers from the same neighborhood helps to reduce transport and transaction costs (Rao and Qaim 2011).

We also discussed the possible role of NGOs to facilitate HVM access. In the study area, an international NGO had implemented a project since the mid-2000s aiming at linking farmers to supermarkets (Ngugi, Gitau, and Nyoro 2007). This NGO promoted collective action and trained farmers to meet the supermarket standards in terms of quality, consistency, and post-harvest handling of vegetables. The NGO also helped farmers to negotiate supply conditions and provided financial assistance to bridge the time between vegetable delivery and payment by the supermarkets. These support measures seemed to be effective in linking smallholders to supermarket channels in the early period (Rao and Qaim 2011). However, farmer participation in this NGO project decreased significantly between 2008 and 2012. The reason is that the NGO had phased out most of its activities in the region by 2012.

The descriptive statistics in Table 4.1 show that farmers supplying HVM own more land, are better educated, and have better access to transportation and off-farm employment than TM farmers. HVM suppliers also have more neighbors supplying HVM and higher household incomes. The possibility to obtain credit for buying production assets such as irrigation infrastructure is significantly higher for farmers supplying HVM (around 80%) than for farmers supplying TM (around 50%). Household incomes, expressed in Kenyan shillings (Ksh), were calculated by including all farm enterprises and off-farm economic activities over a 12-months period. In the survey, output from crop cultivation was covered separately for the two seasons of the year (long rains and

Costs for inputs and hired labor were subtracted. Off-farm earnings of all household members were reported for the entire 12-months period. All monetary values for 2012 were deflated to 2008.¹⁰