Table 4 Extension simulations
From: Predicting minimum tillage adoption among smallholder farmers using micro-level and policy variables
Predicted probability of CA adoption by sample | |||||
|---|---|---|---|---|---|
| Â | Whole sample | Ethiopia | Kenya | Malawi | Tanzania |
Base case (A) | 0.168*** (0.004) | 0.258*** (0.008) | 0.039*** (0.004) | 0.338*** (0.009) | 0.099*** (0.008) |
Panel I: effect of changing Extension-Staff-to-Farmer-Ratio (EFR): for each country set EFR at Ethiopian level | |||||
 EFR at Ethiopian mean (B) | 0.214*** (0.019) | NA | 0.065*** (0.013) | 0.498*** (0.067) | 0.214*** (0.057) |
  Chi-square tests A = B | 5.47*** | NA | 4.47** | 5.91** | 4.10** |
  Elasticities of adoption with respect to EFR A to B | 0.795 | NA | 1.111 | 0.284 | 0.387 |
Panel II: effect of low EFR and high subsidy (SER): for each country set EFR Tanzania’s level and SER at Malawi’s level | |||||
 At Tanzania’s EFR and Malawi’s SER (C) | 0.213*** (0.023) | 0.301*** (0.037) | 0.092*** (0.029) | 0.308*** (0.014) | 0.142*** (0.019) |
  Chi-square tests A = C | 3.85* | 1.31 | 3.60* | 6.50* | 5.62* |
Panel III: effect of high EFR with low SER (keeping both EFR and SER at Ethiopia’s level) | |||||
 At Ethiopia’s EFR and Ethiopia’s SER (D) | 0.129*** (0.015) | NA | 0.048*** (0.006) | 0.201*** (0.047) | 0.080*** (0.015) |
  Chi-square tests A = D | 7.22** | 1.31 | 3.61* | 7.89* | 2.35 |
Panel IV: effect of high extension with complete absence of credit: for each country set credit constraint at 1 and EFR at Ethiopia’s level | |||||
  No credit available and EFR at Ethiopia’s level (E) | 0.192*** (0.019) | 0.179*** (0.022) | 0.056*** (0.011) | 0.469*** (0.067) | 0.184*** (0.051) |
  Chi-square tests A = E | 1.75 | 12.16*** | 2.33 | 4.04* | 2.73* |