First, the sample selectivity probit model is preferred to univariate probit models, since the results indicate the existence of sample selection bias if the second-stage equations were estimated alone.
Chen and Fan (2010) generalize four sources of endogeneity bias in quantitative studies of sociology: omitted variable bias, self-selection bias, sample selection bias, and simultaneity bias.
Thus sample selections bias should be stressed.
It is always difficult to measure turnout using survey questions due to the problems of over-reporting, sample selectivity, social desirability bias and the stimulus effects of pre-elections interviews (e.g. Aarts and Wessels, 2005; Bernstein et al., 2001; Karp and Brockington, 2005).
There are also a couple of caveats that ought to be considered when interpreting the findings of this research, particularly with respect to the issues of sample selectivity and self-report bias.
Taking a multi-crop approach, this paper fills the gap by investigating the key determinants of market participation decisions of smallholder farmers in Ghana using the sample selectivity probit model in order to account for potential endogeneity and selectivity bias and thus obtain unbiased estimates.
Verbeek and Nijman (1992) propose the latter as a simple means of both testing, and controlling, for the selectivity bias that might arise from the sample attrition that occurs during the course of a panel.
The sample selectivity probit model is adopted as it has an intrinsic ability to account for selectivity bias and make corrections simultaneously, as well as deal with endogeneity.
Moreover, longitudinal surveys are affected by sample attrition over time, though samples are usually refreshed as time goes on and remaining samples can possibly be calibrated in order to reduce potential selectivity bias.
