to crop cutting. Focusing on sorghum, EACI collected data on 3,569 plots of which 1,098 were subject to crop cutting.

We start this part of the analysis by comparing the data from ERIVaS and EACI. This provides clues regarding the potential modifications, if any, in the parameter estimates for the relationships between yields and inputs when we extend our analysis to a nationally-representative survey. Table 10 shows summary statistics for pure stand sorghum plots on in ERIVaS and EACI samples.<sup>17</sup> We see that the measures of yields and inputs are statistically different between the two surveys. The mean value in EACI is often larger, and as can be observed on Figure A2 in the Appendix, the amplitude is often greater for the inputs. The latter finding reflects the fact that EACI covers the entire country and captures more heterogenous farming practices and outcomes. This may in turn be beneficial for the use of ML techniques to derive imputed CC yields, since these algorithms work best with more observations and are more adapted to handle potential heterogeneity across units of observations.

**Table 10:** Sample summary statistics of ERIVaS and EACI 2017.

|Variable|Sample|Mean|Std.Dev|Min|Median|Max|Obs.|
|---|---|---|---|---|---|---|---|
|SR Yields|ERIVaS|636.86|822.26|0.00|400.00|8139.45|577|
||EACI 2017|536.70<br>***|874.18|0.00|317.89|9523.81|3237|
|CC Yields|ERIVaS|500.68|380.06|0.00|423.44|2472.50|577|
||EACI 2017|760.19<br>***|482.30|0.00|720.00|3200.00|980|
|GPS measured area (ha)|ERIVaS|1.56|1.25|0.05|1.20|12.02|577|
||EACI 2017|2.65<br>***|2.49|0.02|1.94|17.83|3237|
|Quantity of Seeds used (kg/ha)|ERIVaS|8.30|5.90|0.56|6.56|51.02|577|
||EACI 2017|13.38<br>***|42.57|0.00|5.57|1300.00|3237|
|Household labor on plot (persons-days/ha)|ERIVaS|159.30|267.37|8.36|76.40|2711.45|577|
||EACI 2017|69.03<br>***|146.20|0.54|34.04|2700.00|3237|

_Notes:_ To ensure comparability of the variables, the EACI 2017 sample is limited to pure stand plots. The stars. below the sample mean values of the two surveys denote the statistical significance level for a t-test comparison of the means in the two samples. Significance levels: *p _<_ 0.1; **p _<_ 0.05; ***p _<_ 0.01 In terms of the non-classical measurement errors that were uncovered in the ERIVaS data, similar patterns emerge from the EACI sample. Table 11 shows the means of alternative yield and harvest measures for pure stand and intercropped sorghum plots. Similar to ERIVaS, the mean differences between SR and CC measures are statistically significant. However, in the nationally-representative sample, the sign of the difference is opposite and we find that the mean SR yields are underestimated vis-`a-vis CC yields (i.e., SR - CC _<_ 0). Figure 5 allows us to better understand why this is the case by showcasing the mean difference between SR and CC yields across quintiles of plot area, quantity of seeds per hectare and days of household labor per hectare. SR yields are overestimated vis-`a-vis CC yields in the first plot area quintile, while, in each of the remaining quintiles, SR yields are underestimated. On

- 17An expanded set of descriptive statistics computed with both samples can be found in Table A4.

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