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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*