The omission of any consumption is a major cause of bias in the standard recall modules (except the usual month). While the 7-day long list module comes closest in the estimate of mean household food consumption (see table 2), the incidence of consumption is significantly lower than the benchmark for most food groups. The same finding holds for the other 7-day recall designs (modules 3 and 4) and also, to a lesser degree, for the 14-day long list.

While consumption incidence is largely downward biased in the 7-day recall, the reported values, conditional on positive consumption, exhibit a large degree of upward bias for most food groups, whether commonly consumed (e.g. Cereals) or not (e.g. Dairy). The relative equality in mean consumption of the 7-day recall and the benchmark individual diary may therefore derive from the happenstance of offsetting errors: negative errors in incidence multiplied by positive errors in value. This approximately equal offsetting error magnitude may not translate to other settings, thus raising questions about a characterization of the 7-day recall as the most accurate recall design. The 7-day subset list recall module (module 3) also exhibits an extensive degree of overreporting of value. We conclude that value overreporting (because of telescoping or rule of thumb) is most pronounced in the short 7-day window. On the other hand, the 14-day recall module also exhibits positive value errors for some food groups, but to a lesser degree than the 7-day period. The 14-day recall also exhibits net negative error for other, mostly perishable food groups. Clearly, the recall period that yields the greatest accuracy will vary with the nature of the good in question, an issue to which we return below.

This simple decomposition exercise, which raises some stark patterns in differential response according to recall module, suggests that methods to improve the accuracy of recall surveys should consider a dual-track approach: (1) efforts related to the prompting of households to report any positive consumption because recall modules underreport the consumption incidence associated with almost any food group and (2) efforts aimed at improving the accuracy of consumption value reporting, conditional on the household reporting any consumption.

Regarding efforts to improve the accuracy of consumption incidence data, note that the absolute magnitude of recall error is particularly high for foods that are not commonly consumed. Further prompting in the interview and perhaps the use of locally salient images to aid the memory of survey respondents may therefore represent avenues of exploration, especially for less common food items.

Regarding efforts to improve the accuracy of consumption value reports, note that overreporting of value is a particularly prominent error for short recall periods such as seven days. Unlike the incidence error, we do not have a strong lead on what causes the misreports. If telescoping of high-value consumption items is the driver, then one approach sporadically discussed in the literature is to bracket the recall period with a surveyor visit at the start of the relevant period as a reference for the respondent during the second visit when the recall is reported. The initial visit from a survey team may help delineate the exact period of recall and improve accuracy. However, this approach would need to be validated before being taken up more broadly. It also has consequences for fieldwork structure and cost (in cases where mobile teams rather than resident enumerators are used).

We have extended the basic analytic framework with respect to how food reporting errors across modules interact with the key socioeconomic characteristics of households and with food characteristics such as perishability or the prevalence of home production. With respect to interactions with household characteristics, the bias in consumption incidence is most pronounced among disadvantaged households 16