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Table 5 Subsidy simulations

From: Predicting minimum tillage adoption among smallholder farmers using micro-level and policy variables

Predicted probability of CA adoption by sample
SER level Whole sample Ethiopia Kenya Malawi Tanzania
Base Level (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 subsidy expenditure as a percentage of agricultural budgets spent on farm input subsidies (SER). Set SER at Malawi’s level
 At Malawian mean (C) 0.319***
(0.67)
0.572***
(0.126)
0.140***
(0.057)
NA 0.143**
(0.019)
  Chi-square tests A = B 5.12** 6.38** 3.11* NA 5.62**
  Elasticities of adoption with respect to SER A to B 1.194 0.261 1.233 NA 1.585
Panel II: effect of low subsidy with full credit availability: for each country set SER at Ethiopia’s level and credit constraint at 0
 At Ethiopia’s SER and no credit constraint (C) 0.109***
(0.024)
0.285***
(0.010)
0.033***
(0.006)
0.119***
(0.062)
0.031***
(0.017)
  Chi-square tests A = C 6.15** 19.3*** 2.54 11.83*** 17.93***
Panel III: effect of high subsidy with no credit available: for each country set credit constraint at 1 and SER = at Malawi’s level
 At Malawi’s SER and no credit available (D) 0.292***
(0.064)
0.547***
(0.126)
0.124***
(0.052)
0.312***
(0.010)
0.120***
(0.017)
  Chi-square tests A = D 3.80* 5.34* 2.61 20.96*** 1.63