Table 8.
The impact of training on wheat and maize productivity and households’ income (Kernel based matching algorithm, bandwidth = 0.06).
| Outcome variables | Sample | Trainees | Non-trainees | Difference | S.E | T-stat | Average treatment effect with bootstrap standard error |
|||
|---|---|---|---|---|---|---|---|---|---|---|
| ATT | Bootstrap S.E |
Z | P>|z| | |||||||
| WY (kg ha-1) | Unmatched | 4096.88 | 3180 | 916.88 | 112.95 | 8.12 | - | - | - | - |
| ATT | 4086.49 | 3226.33 | 860.16 | 120.45 | 7.14∗∗∗ | 860.16 | 138.83 | 6.20 | 0.000∗∗∗ | |
| NWI (birr ha-1 year-1in ‘000) | Unmatched | 45.85 | 37.43 | 8.42 | 1.726 | 4.88 | - | - | - | - |
| ATT | 45.63 | 38.14 | 7.49 | 1.867 | 4.01∗∗∗ | 7.49 | 2.045 | 3.66 | 0.000∗∗∗ | |
| MY (kg ha-1) | Unmatched | 3286.54 | 3050.14 | 236.41 | 99.28 | 2.38 | - | - | - | - |
| ATT | 3285.95 | 2984.39 | 301.56 | 108.32 | 2.78∗∗∗ | 301.56 | 109.03 | 2.77 | 0.006∗∗∗ | |
| NMI (birr ha-1 year-1 in ‘000) | Unmatched | 23.33 | 22.15 | 1.18 | .874 | 1.35 | - | - | - | - |
| ATT | 23.31 | 21.75 | 1.56 | .946 | 1.65∗ | 1.56 | .893 | 1.75 | 0.080∗ | |
WY = wheat yield; NWI = net wheat income; MY = maize yield; NMI = net maize income.
∗∗∗p < 0.01; ∗∗p < 0.05; ∗p < 0.1.
Source: Field survey result, 2020.