On the other hand, our analysis further underscores the difficulty of estimating yields in the intercropped domain, even with objective measurement approaches. In MAPS II, we find that the average full-plot crop cutting yield on intercropped plots is 85 kilograms per hectare lower than its sub-plot crop cutting counterpart, and the difference is significant at the 5 percent level. This is in line with the expectation that the sub-plot crop cutting yield may not entirely reflect the true measure given the across-household variation in the types of crops intercropped with maize, and both across-household and intra-plot variation in maize seeding rate. And, if we can think of subplot crop cutting yield estimate in the intercropped domain as an upper bound for the true yield based on MAPS II data, we see that remote sensing overestimates plot-level maize production and yield in MAPS I by a significant margin – likely due to difficulties in attributing vegetation growth to maize production on intercropped plots.<sup>26</sup> Overall, the level and direction of discrepancy between farmer estimates of production and cropcutting observed in MAPS I and II run contrary to some previous works, synthesized by Fermont and Benson (2011). Specifically, while MAPS data reveal that maize yields based on farmerreported production are significantly over-reported relative to both sub-plot and full-plot crop cutting, Verma et al. (1988) assert that, on average, farmer estimates are in fact more accurate than sub-plot crop-cutting relative to full-plot harvests. There are, however, two concerns associated with this claim.

First, the small sample used by Verma et al. (1988) prohibited analysis at varying plot size levels. Yet, as presented below and in line with the findings of Desiere and Jolliffe (2017), the degree of error between farmer estimates and crop-cutting measures is systematic in nature, with production and yields more significantly over-estimated by the farmer on smaller plots. Ignoring distributional differences between farmer estimates and crop-cutting, therefore, can mask the true relationship between the two measures. Second, the plots analyzed by Vermal et al. (1988) were all subject to a full-plot harvest, which would likely contaminate farmer-reported production values. Full-plot harvests also eliminate the need for farmers to aggregate periodic harvests (such as early, green harvest with final, dry harvest), further contributing to the accuracy of farmer-reported production values in the presence of contamination.

Similarly, Fermont and Benson (2011) compile historical maize yield estimates in Uganda from a variety of sources, and report that the self-reported yield estimates are consistently lower than the estimates based on sub-plot crop cutting, in contrast with our findings. Yet, the assertion of Fermont and Benson (2011) is potentially misleading, since their reported estimates based on crop cutting originate from on-farm trials, where farmers may be positively selected and may receive technical assistance for optimal management practices, as opposed to standard household or farm

> 26 Since the MAPS II remote sensing work program was continuing at the time of the publication of the working paper version of this manuscript, we will refrain from making further concrete statements regarding the accuracy and feasibility of remote sensing for maize yield measurement in smallholder production systems, and will focus on this topic in a separate study.

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