This study uses a double-hurdle (DH) model to examine the key factors influencing market
participation decisions among maize-producing households in the former homelands of
South Africa. In the first stage of the double-hurdle model, using data on South African rural
maize growers, the decision whether or not to participate (binary variable) is used to
estimate the maximum likelihood estimation (MLE), which is assumed to follow a probit
model. In the second stage, the conditional quantity sold (continuous variable) is assumed
to follow a truncated normal regression model, whereby the MLE is estimated by fitting a
truncated normal regression into the quantity sold.
The results of the double-hurdle regression point specifically to five key factors that were
found to have a positive statistical effect on rural smallholders’ market participation
decisions, and on the conditional quantity of maize they traded (viz. household size, land
size, access to credit and government transfers for the first stage, which was estimated
using the probit model, and age, education and employment status of the household head,
use of tractor when cultivating, government transfers, quantity produced, market price, and
own transport to the market for the second stage which was estimated using truncated
normal regression).