by people working on a given plot: while in the weekly visit group, the person-plot average of total season hours was 39.5, this number jumped to 121.3 and 146.3 in recall NPS and recall ALT, respectively. Total hours worked per person-plot are 3.0 and 3.7 times higher in the recall surveys than in our preferred benchmark, the weekly visit estimates.<sup>17</sup> These results show considerable recall bias in seasonwide person-plot hours, driven primarily by error in the least granular time unit reported (days in the case of the recall NPS and weeks in the case of the recall ALT).

# **Aggregation of hours and the competing sources of recall bias**

Does the stark difference in reported hours we find by person-plot persist at all levels? Aggregating from the labor at the person-plot level to that at the household level entails introducing data on both the number of household members working in agriculture and the number of household plots on which farming takes place. If both of these new components are recorded with the same accuracy in the recall data as in the weekly data, then the degree of overreporting in hours per person-plot (presented in table 3, panel A) and in hours aggregated by household will be roughly the same. Table 3, panels B–D show this aggregation, presenting statistics on the person level (that is, all labor performed by a given person on any plot; panel B), the plot level (that is, all labor performed on a given plot by any person; panel C), and the household level (panel D). The large difference between the weekly and recall surveys virtually disappears in aggregation.

This arises because of considerable underreporting by recall households of the number of plots cultivated and the number of people farming. Table 7 shows that an average of 1.5 (or roughly 33 percent) fewer household members report they worked in farming in the recall NPS and the recall ALT than in the weekly visit group. The number of plots in recall is underestimated by roughly 35 percent, or 1.6 plots. As was the case in hours, the number of people and plots reported as active in agricultural labor is essentially identical between the two weekly survey designs and between the two recall designs. In section 4.2, we investigate which people and which plots may be systematically underreported in recall surveys and why.

Returning to table 3, we can see that the significant difference in the number of active workers between recall-surveyed and weekly surveyed households plays out in an important way in aggregating labor at each stage. If hours are aggregated to either the person or the plot, the total season hours remain higher in recall than in the weekly surveys, but the gap in person-plot hours 17 Additional comparisons can be made with our survey experiment data and the data from the three waves of the Tanzanian NPS. This is a national panel survey in which sampled households are interviewed once during each survey wave (randomly across 12 months). We can compare the NPS with our weekly data because, in each NPS interview, members were asked if they worked in agriculture, livestock, or fisheries in the previous seven days. This is a broader set of activities than the set here, which is restricted to time spent on the plot. For the NPS subsample of rural households in or near the Mara Region, both participation and hours are significantly higher in the NPS than in our weekly data (results not reported). Hours conditional on working are closer: approximately 26 to 20 hours for the NPS and our weekly data, respectively. This suggests that the respondents in the NPS are interpreting the question not literally about hours in the previous seven days, but perhaps are reporting a typical number of hours working. In comparing NPS estimates with estimates obtained in our end-of-season recall modules, we find that both the total days worked on plots and the average hours per working day on plots are roughly the same as in the NPS: 26 days and 4.9 hours per working day in the NPS, compared with 29 days and 4.6 and 4.8 hours in the two recall designs if analysis is conducted conditional on realized person-plot combinations (not reported).

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