CHAPTER 4 DETERMINANTS OF COMMERCIALISATION IN SMALLHOLDER FARMERS
4.2 Research Methodology
(2008) found group membership to be positively associated with commercialisation. Kabiti et al (2016) found out that commercialisation of maize in smallholder farmers of Munyati area, Zimbabwe was positively affected by labour, age and off farm income. However, communal land holding was found to negatively influence commercialisation in the same study.
commercialised or non-commercialised since such discrete distinctions do not exist since farmers have diversified cropping patterns.
The Tobit model is estimated as follows: 𝑌𝑖∗ = 0 +Xi + ei Where
𝑌𝑖∗=is the latent variable of the dependant variable (HCI) 𝛽 =Vector of parameters to be estimated
Xi=set of explanatory variables ei = the disturbance term
The model errors ei are assumed to be independent, N (0, σ2) distributed, conditional on the Xi. The observed 𝑌𝑖∗ is defined as 1 if 𝑌𝑖∗ > 0 and 0 if 𝑌𝑖∗ ≤ 0.
The dependant variable
Following the work of Von Braun (1994), The Household Commercialisation Index (HCI) formula was given as:
HCI= Value of all crop sales
Total value of crops produced
This factor in all types of crops either food or cash crops. Many smallholders grow a diverse portfolio of crop mix with cash crops and food crops in one season, therefore, they practise both own food production and market production (Shumba and Whingwiri 2006). For one to analyse the extent of cash cropping the commercialisation index can be used as it gives the overall extend of market orientation by aggregating value of all crop sales as a ratio of total value of crops produced.
Independent Variables in the model
This study builds on empirical evidence of market participation decisions under transactions costs for specific crops as influenced by household characteristics, resource endowment and information (Ouma et al. 2013, Umar 2013, and Zamasiya et al. 2014). Household characteristics include variables such as the age of household head, gender, household size and labour. The household assets or resources include the number of cattle, off farm income, land and extension. The level of access to information is captured by group membership and market access. Table 4.1 gives a summary of the variables, which were likely to have an effect on commercialisation levels. It was expected that the higher the household size the greater the
chances of a household being involved in commercialisation due to increased labour supply which might be needed for cultivation of cash crops (Duve and Guveya 2016). The age of household head was expected to have a positive or negative effect. Age of farmer could be associated with more farming experience. As farmers become more experienced, they may have more access to marketing information thus age can be positively related to commercialisation decisions (Kiriti & Tisdell 2002, Kabiti et al. 2016). Gender of household head captures the variation between male headed and female-headed households in their market orientation. Male participants are expected to be more marketed oriented compared to the female participants (Kiriti & Tisdell 2002, Osman and Hassain 2015).
Table 4.1 List of variables expected to affect household commercialisation Description of variable Measurement Expected
relationship Gender of household head 1= Male 0 =female +
Age of household head Number of years -/+
Household size Number of people +
Number of cattle Number of cattle +
Total Off farm Income Annual off farm income in US$
- Access to market 1= access to market
0=otherwise
+
Communal tenure 1= communal 0=otherwise -
OR resettlement tenure 1= A1 resettlement 0=otherwise
+
Total arable land Hectares +
Total labour Number of family +hired
labour per season
+
Total land cultivated Hectares +
Group membership 1 =group member 0 =otherwise
+
Number of crops grown Continuous +
Access to finance 1 access to finance 0 otherwise
+ Access to draft power 1 access to draft power
0 otherwise
+ Access to extension 1 access to extension
0 otherwise
+
Ownership of physical assets such as cattle and total arable land would be expected to positively influence commercialisation. The availability of more land for cultivation allows farmers to grow more crops, generate surpluses, and hence increase chances for
commercialisation. Martey et al. (2012) and Ele et al. (2013) in separate studies found that the commercialisation level increased with increase in total arable land. Due to the heterogeneity of smallholder farmers in Zimbabwe, with some of the variations arising from land holdings, it can be expected that there would be differences in commercialisation between the communal farmers and resettled farmers. Communal farmers are less likely to commercialise than resettled farmers are. Mutami (2015) and Kabiti et al. (2016) have indicated that communal farmers have relatively less total arable land as compared to their resettled counterparts (A1 and OR) therefore, due to land constraints they are less likely to generate surplus for sale.
According to Martey et al. (2012), accessibility of credit is expected to link farmers with modern technology, ease liquidity and input supply constraint thereby increasing agricultural productivity and market participation. Therefore, farmers with greater access to finance are likely to commercialise than those failing to access credit.
Accessibility of both food and non-food crops markets is expected to positively influence commercialisation (Kiriti and Tisdell 2002, Goshu et al. 2012). Access to draft power and extension is expected to increase the productivity of cash crops thereby resulting in higher commercialisation (Govereh and Jayne 2003). Group membership may assist in providing marketing and production information, thus it is expected that farmers who belong to formal groups are likely to commercialise than non-members (Msongaleli et al. 2015, Bernard et al.
2016). Smallholder farmers usually grow a variety of crops in one season to minimise production and marketing risks. Number of crops is likely to reduce the marketing risks associated with specialisation in cash crops hence a positive association between the number of crops grown and commercialisation is expected (Mukherjee 2010).
4.3 Results and Discussion