As an additional robustness check, we assess the relationship between recall length and the quantity of maize sold and maize in storage (results not shown). The rationale is as follows: Absent measurement error, the quantity of maize harvested should not be correlated with the timing of the interview. In contrast, as the time between harvest and interview increases, the expectation is that households deplete their storage of harvested maize, while selling more of it. Thus, there should be a negative correlation between the time passed since harvest and maize in storage and a positive correlation with maize sold. Finding that this is not the case may point to some other underlying dynamic and cast doubt on the results. We thus test this hypothesis in the data. The data indeed reflect a negative relationship between time elapsed since harvest – that is, recall length – and the quantity of maize in storage. We also find a positive relationship between time elapsed since harvest and the quantity of maize households report they have sold.

In light of the finding that reported harvest quantity increases with the recall period, the question of interest is whether this implies that harvest quantity is being increasingly over-reported the longer the recall period becomes. The logic of recall decay would suggest this is the case: farmers likely remember the amount harvested if the harvest has only just finished. But absent written records, they need to rely on inference or reconstruction more often if the harvest is many months in the past. If this logic holds, interviews conducted just after the harvest, with a short recall length, produce the most reliable estimates. Whether or not this logic holds is of course predicated on respondents having accurate knowledge of how much they harvested in the first place. Existing evidence shows that other factors, such as land area or respondent characteristics, are correlated with harvest mis-reporting, so even in cases of short recall periods self-reported harvest quantities may well be inaccurate.

Resolving this question systematically would require comparing farmer-reported harvest quantities to more objective benchmark estimates, for example based on crop cutting. Crop cutting is not available in the three main data sets used for this analysis. As an ancillary analysis, we use the MAPSII data set to benchmark the farmer self-reported harvest against the more objective full-plot crop cuts. We replicate the main specification for the effect of recall length on farmer-reported harvest in the sample of plots for which a full-plot crop cut is available. Then, we quantify the reporting error (farmer-reported harvest quantity minus full plot crop cut quantity) and assess the effect of the recall length on the reporting error. We find a significant effect of the recall length on self-reported harvest as well as on reporting error (Figure 7). This suggests that farmers are indeed increasingly over-reporting harvest with longer recall periods, at least in this sample.

# Labor

Reported farm labor per plot increases significantly with recall length. The effect size is similar in Tanzania NPS 2012/13 and Malawi IHS4 at 1.6 (2.3 percent) and 1.2 person-days (2.8 percent) per plot per month of recall length, respectively (Figure 8, Figure 9, Table A.9, Table A.10, Table A.11).<sup>9</sup> A quadratic rather than linear specification for recall length suggests no mis-specification by the linear model, and the BIC’ analysis shows the linear model provides a better fit in both data sets (results not shown).

> 9 The comparison with the Malawi IHS4 panel is omitted because in that survey labor inputs are collected partially in the first visit (labor used for land preparation and planting, ridging and fertilizing) and partially in the second visit (harvest and post-harvest labor). Thus, there is no one unique recall period against which to evaluate total labor input, rendering the comparison meaningless.

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