|(8)<br>Total<br>(Std. Index)<br>-0.62**<br>(0.20)<br>3.69***<br>(0.16)<br>-0.03<br>(0.16)<br>548<br>0.56<br>0.00<br>1.00<br>_αc_+_εit_ , where_i_corre-<br>of the outcome variable<br>m to fertilize at sowing.<br>achinery were advised<br>d 45 days after sowing.<br>g sessions each farmer<br>following season. The<br>was visited by the our<br>the outcome in column<br>1, ** p_<_0.05, * p_<_0.1.|
|---|
|(7)<br>Total<br>(0-9)<br>-0.76**<br>(0.31)<br>4.83***<br>(0.26)<br>0.12<br>(0.24)<br>548<br>0.48<br>2.34<br>2.11<br>_i_+_βFFlexiblei_+ <br>andard deviation<br>ovided by our tea<br>use the sowing m<br>t should be applie<br>number of trainin<br>reparation for the<br>y times the farmer<br>dardized index of<br>ntheses. *** p_<_0.0|
|(6)<br># AEW<br> <br>visits (0-3)<br>-0.29**<br>(0.12)<br>1.23***<br>(0.13)<br>0.01<br>(0.09)<br>548<br>0.30<br>1.40<br>1.28<br>_ndRecommi_+_βGGrant_<br>ort the mean and the st<br>precision machinery pr<br>y. Farmers who did not<br>of YARA fertilizers, tha<br>ent variable counts the<br>ement, as well as soil p<br>iable counts how man<br>ndent variable is a stan<br>Standard errors in pare|
|(1)<br>(2)<br>(3)<br>(4)<br>(5)<br>Precision<br>1_st_ Package<br>2_nd_ Package<br>Out-of-pocket<br># training<br>drill (1=Yes)<br>(1=Yes)<br>(1=Yes)<br>(Mex$/ha)<br>sessions (0-3)<br>Individual recommendation (1=Yes)<br>-0.09*<br>-0.09**<br>-0.21***<br>2.90<br>-0.08<br>(0.05)<br>(0.04)<br>(0.05)<br>(39.34)<br>(0.11)<br>Grant (1=Yes)<br>0.76***<br>0.83***<br>0.74***<br>315.68***<br>1.27***<br>(0.04)<br>(0.03)<br>(0.04)<br>(22.42)<br>(0.11)<br>Flexible (1=Yes)<br>-0.12**<br>0.07**<br>-0.02<br>-103.96***<br>0.20**<br>(0.05)<br>(0.03)<br>(0.05)<br>(28.51)<br>(0.09)<br>Observations<br>548<br>548<br>548<br>548<br>548<br>R-squared<br>0.43<br>0.63<br>0.42<br>0.27<br>0.35<br>Mean dep. var. T4<br>0.08<br>0.07<br>0.04<br>0.00<br>0.76<br>SD dep. var. T4<br>0.27<br>0.25<br>0.19<br>0.00<br>0.95<br>Note: this table reports results on the take-up of our proposed treatment by farmers in our sample. Using only the set of 548 treated farmers, we run the following regression: _Yit_ = _β_0+_βI I_<br>sponds to a farmer,_Y_is the outcome of interest and_t_is the time period. We include randomization strata fxed effects and compute robust standard errors. At the bottom of the table, we rep<br>for the group of farmers who did not receive the grant (T4), the omitted category in our regression. In column 1, the dependent variable is a dummy that takes value 1 if the farmer used the<br>In column 2, the dependent variable is a dummy that takes value 1 if the farmer took up the frst package of YARA fertilizers, that should be applied at sowing using the precision machiner<br>to use this package 30-60 days after sowing depending on how their crop grew. In column 3, the dependent variable is a dummy that takes value 1 if the farmer took up the second package<br>In column 4, the dependent variable is the amount that each farmer had to pay for the packages of fertilizers, on top of the QFD subsidies, if they received them. In column 5, the depend<br>attended, out of 3 our team organized. The frst training session introduced farmers on how to fertilize at sowing. The second one aimed at on harvesting and preparations for yield measur<br>third training session covered the importance of using quality fertilizers and herbicides, as well as on the right timing to fertilize during plant development. In column 6, the dependent var<br>team to be provided with technical assistance (out of 3 scheduled visits). In column 7, the dependent variable is the sum of columns 1, 2, 3, 5 and 6, varying from 0 to 9. In column 8, the depe<br>8, computed by standardizing each variable individually, adding them all and standardizing the sum. We use the mean and standard deviation of T4 as reference for the standardized index.|

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