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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