Impacts of climate-resilient push–pull technology on farmers’ income in selected counties in Kenya and Tanzania: propensity score matching approach

Table 3 Coefficient and standard errors in the probit regression of propensity score matching

Variables	Coefficients	Standard errors
Age of main farmer	0.0031	0.0071
Education level of main farmer	0.3799***	0.1079
Farming experience of main farmer	0.0036	0.0079
Household size	0.0495*	0.0284
Main occupation of the main farmer	− 0.0205	0.0636
Sex of the main farmer	0.0816	0.1587
Tropical Livestock Unit	0.0682***	0.0264
Group membership	0.3190*	0.1897
Number of extension services	0.0350	0.0426
County	− 0.0452	0.0299
Constant	− 1.2199***	0.4410
Number of observations	350
LR chi2(10)	41.46
Prob > Chi²	0.000
Pseudo-R²	0.088
Log-likelihood	− 215.226

ISSN: 2048-7010