This stands in contrast to the 2.8 plots per household reported by recall NPS and recall ALT households. This is only slightly larger than the number of plots reported in the three waves of the NPS (reporting plots in the 2008, 2010, and 2012 long rainy seasons) for rural farm households in the Mara or bordering regions, where the mean number of plots per household is 2.2. However, it is much smaller than even the smallest-ever number of plots reported by households in the weekly surveys.

The main reason households offer for making changes on the plot list obtained in the baseline is that some plots have been erroneously forgotten (table 8). Far fewer plots (91) in the weekly visit group are dropped over the course of the season; the chief reason given is that the plots were originally listed in error. The number of plots dropped over the course of the season is not sufficiently high to account for the discrepancy between the plots reported by recall and the plots reported in weekly interviews. Furthermore, households are more likely to add plots over the season than drop them. Even if we restrict the number of plots per household to those that faced no change over the season, that is, plots that were never dropped early or added late, on the premise that, perhaps, recall households only tended to remember to report those plots that were consistently present to be reported on, the weekly-recall plot gap remains (not reported).

Plot traits might reveal which plots are likelier to have been forgotten. We perform this reckoning by comparing the proportion of plots by characteristic across the four arms of the study. In table 9, we show, however, that, except perhaps for an overrepresentation of nearby plots in the recall surveys, plot characteristics are similar, suggesting that recall farmers do not systematically forget certain types of plots.<sup>22</sup> Instead, it may be possible that the plots that are forgotten are the prime responsibility or exclusive domain of people who are themselves likely to have gone unreported. If this were the case, then the omission of a person (say, one who worked little or infrequently) from the household reporting may also result in the omission of her or his plot. To test this, we look for significant differences in the average number of plots worked per person and the average number of people working per plot. These data are presented in table 7. They suggest both that many different people work on a given plot (an average of 3.2 people in weekly visit households) and that a given person will work on many different plots (an average of 3.6 plots). Thus, it is unlikely that the omission of a single household member would necessarily result in the omission in their plots.

# _Reporting on people_

We now perform a similar analysis of which household workers may be likelier to be forgotten in recall-based reporting and why.

First, as above, we examine the entry and exit of people from the household using weekly data. In the baseline survey, households reported on household members who were working on each of the household plots. Figure 3 shows that, in this earliest survey, an average of 2.1 people per weekly visit household were reported as engaged in agricultural work. This number grew

> baseline question’s intent is unlikely to have driven the weekly recall gap in the number of plots.

> 22 The large and significant differences by ownership status are driven by technical difficulties in the collection of ownership information among some weekly surveyed households.

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