data at the person-plot level shows, farmers only perform 2.5 weeks of work on a given plot over the entire season, the possibility is large that their reporting as if they were working on every plot up to as often as they work on any plot—for instance, 12.8 plot-weeks at the person-level in weekly visit interviews—introduces errors in plot-person labor calculations. Accordingly, it appears as though farmers may report work that occurs across all plots as if it occurred on every plot, thereby inflating person-plot labor estimates.

# **Reporting on people and plots**

Unlike the case of work time, the direction of the bias in the reporting on people and plots active in agriculture means that forgetting is a plausible explanation for the observed gap between the weekly survey and the recall survey. Indeed, it may be a more plausible explanation in this case than mismeasurement because of poor inference because there is less gray area in reporting on the extensive margin of agricultural labor, that is, it is unlikely that a person would have to infer their participation or a plot’s engagement in agricultural work. What, then, drives certain plots and people to be forgotten? Here, as before, inconsistency plays a role, albeit perhaps a weaker one: where the associated work is rare or infrequent, people and plots are unlikely to be recalled as active in farming.

# _Reporting on plots_

First, we examine the possibility that, in recall surveys, households may have forgotten or otherwise failed to report plots that may have fallen out of the study over the course of the season for legitimate reasons. Put another way, we ask whether, in recall-surveyed households, the people and plots active in agriculture actually represent net end-of-season data, while, in the weekly surveyed household, they may represent cumulative or gross data.

Table 7, panel B shows a clear gap in the reporting on plots in the recalls, wherein roughly half the active agricultural plots are reported as in the weekly surveys. To track the addition and subtraction of plots over time, we turn to the weekly data. In the recall survey, plots are reported in the postharvest end line survey (July–September 2014), whereas weekly surveyed households first list plots in the baseline survey (January 2014). For these weekly surveyed households, the plot roster is then updated each week for the duration of the season. This allows for changes to the original plot listing, for instance, because it is necessary to add plots that were mistakenly forgotten at baseline, to add plots that are brought into cultivation after the previous weekly survey, or to drop plots that households planned to cultivate and, subsequently, decided not to cultivate. Figure 2 shows the increase over the course of the season in the cumulative number of plots reported by each group. Over the course of the weekly data collection, the number of plots per household in the weekly visit group grew from an average of 3.4 to 5.1 in the first 20 weeks of interviews.<sup>21</sup>

> 21 Part of the change in plots reported over the season could be the phrasing or context of the survey. In the baseline, households were asked “Please list all plots anyone in this household currently owns or cultivates.” Over the subsequent weeks, the survey was clearly (by default) referencing the 2014 long rainy season. In the end line survey, recall households were asked “please list all plots anyone in your household owned or cultivated during the 2014 long rainy season (masika season).” Nonetheless, because our standard for the inclusion of a plot in the data depends on whether labor was actually reported on the plot during the masika, misreporting based on a misunderstanding of the

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