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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
  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*