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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