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Table 3 Estimation of propensity score through probit regression model

From: Does adaptation to climate change and variability provide household food security? Evidence from Muger sub-basin of the upper Blue-Nile, Ethiopia

Adoption Coef. Std. Err z-value Sig.
Agroecology .31019 .20626 1.50 0.133
Gender of HH 1.9498 .24496 7.96 0.000
Age of the HH − .00252 .00876 − 0.29 0.774
Education − .03589 .03203 − 1.12 0.263
Family size .16198 .05581 2.90 0.004
Social capital .14003 .10045 1.39 0.163
Total land size .32195 .10689 3.01 0.003
Access to extension service 1.3541 .22822 5.93 0.000
Access to credit .31800 .24587 1.29 0.196
Market distance − .15333 .11874 − 1.29 0.197
livestock − .07169 .03354 − 2.14 0.033
Early warning information .09858 .05041 1.96 0.051
_cons − 3.2501 .69312 − 4.69 0.000
  1. Probit regression
  2. Number of observation = 442
  3. LR chi2 (12) = 231.61
  4. Prob>chi2 = 0.000
  5. Pseudo R2 = 05425
  6. Log likelihood = − 97.676355