variability in work across weeks). Table 3 shows that agricultural labor does not take place every day, nor does it even necessarily take place every week. However, these facts alone need not undermine the success of inference if there is a regular cycle or pattern to the work that respondents can use as a relatively accurate rule of thumb.

To uncover what, if any, labor patterns exist during the season, we examine the weekly data.<sup>18</sup> First, we calculate the modal days spent farming during those weeks in which there was any farm work. In table 4, for each mode of days worked, we show the distribution of days worked. The distribution of workdays is essentially bimodal: many people generally work in agriculture once a week (24 percent), while another group works six times a week (29 percent). Even though farming is the predominant activity in the region, the farming workweek is short, and the majority of people farm little each week.<sup>19</sup> There is also substantial deviation from the modal work pattern. For example, of those with a modal farm workweek of six days, fewer than half (42 percent) of their weeks entailed six days of work. For these people, 15 percent of their working weeks consist of five working days, and 9 percent entail only one working day. The proportion of all workweeks conforming to the people’s modal workday (represented by the diagonal in bold in the table) usually represent under half of the weeks, except for mode 1 persons, who work one day a week in 56 percent of their working weeks. The proportion of weeks not conforming to the modal work pattern are relatively evenly spread from one to seven working days. From these data, it is clear that even a person’s typical workweek is not that typical and that their work patterns in an atypical week vary widely.

The case with respect to hours, however, is somewhat different. In table 5, we present the modal number of hours worked per day in farming. Two patterns emerge. First, in contrast to the bimodal days-per-week patterns above, nearly half of farming workdays consist of four hours of work. Second, a larger share of a person’s days is spent working the same number of hours as their modal hours. Thus, a larger share of the days worked are on the bolded diagonal here relative to table 4. There is less variation in the number of hours worked per day than in the number of days worked per week. Inferences based on a typical workday are therefore likely to be more accurate than those based on a typical workweek.

Together, these results suggest there may be no real typical work pattern to which farmers can reliably refer in constructing their survey responses. Furthermore, we find that the spacing of workdays or working weeks is not consistent over the season and that the variation in days per week or hours per day observed in tables 4 and 5 is not driven by seasonality (not reported), meaning that any mental shortcuts or rules of thumb used in inference (for example, “I may not

> 18 For simplicity’s sake, these statistics are calculated at the person level (that is, summed across all plots on which each person worked), rather than the person-plot level. If anything, this will understate the degree of irregularity in person-plot working patterns because there is considerable irregularity in the work on a specific plot (see below in this subsection).

> 19 This reality has implications for the traditional calculation methodology on labor and labor productivity in agriculture, which tends to assume full-time engagement in farming. Even the recall-based weeks worked and hours worked per day, which we posit are overestimates, are not sufficiently high to support these standard assumptions.

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