similar pattern in the self-reporting of past health, whereby smaller illness events are ignored or forgotten as the recall period increases. They also find heterogeneity in these effects by income, driven by the normalization by the poor of what would otherwise—that is, for richer people—be salient illness events worthy of medical treatment. In our context, if asked to report on labor in the last week, a farmer may interpret the question differently compared with someone who is asked to report on several months’ worth of labor at the end of the season. Our results suggest that even seemingly straightforward questions, such as how many plots the farmer has cultivated, or who has worked on them, are affected by the recall period.

Beyond the length of the recall period, there are aspects of the cognitive and communicative processes that affect survey responses. Menon (1993) shows that, for infrequent and salient events, respondents are likely to recall and count individual events because they are stored episodically and remain in memory for a longer time. In the absence of episodic event information that is easily retrieved, respondents will rely on other strategies. For regular events, such as “I visit my grandmother every Saturday,” respondents are not likely to use the recall-andcount strategy, relying instead on the information they have stored about the event’s periodicity. Such rate-based estimations may be adjusted by memories of nonoccurrence (“except when I’m on holiday”) or more frequent occurrence (“also on her birthday if that doesn’t fall on a Saturday”). Menon (1993) notes that counting the occurrence of events that are neither salient nor regular requires much more cognitive effort on the part of the respondent. Thus, where work is neither salient nor regular, as may be the case for the labor of smallholder farmers over an agricultural season, respondents are unable to use rate-based or recall-and-count strategies and, so, are likely to yield erroneous reports of labor.

In the absence of episodic or rate-based information, respondents may revert to their general assumptions about the state of the world in their search for answers to survey questions. These assumptions then form a benchmark that is used to infer previous behavior. Indeed, the spuriously high recall-surveyed labor we find in our study can stem from this sort of inference (see below). Schwarz and Oyserman (2001) cite evidence that retrospective estimates of income and of tobacco, marijuana, and alcohol consumption are unduly influenced by people’s income and consumption habits at the time of the interview. Thus, they infer their previous behavior based on their current or recent behavior. Similarly, de Nicola and Giné (2014) show that survey responses on income from small-scale boat owners in coastal India rely more on inference and less on true recollection as the recall period increases. The authors show that, while this bias has little influence on the mean (because, in their case, fishermen base their inferences on average earnings), it does lead to an underestimation of income variability as the recall period increases. The information and assumptions held by respondents are also important if people report on the behavior of others, a common practice in the collection of labor data in household surveys (Bardasi et al. 2011; de Nicola and Giné 2014).

Respondents may also be suggestible and base their inferences on what they believe _should_ have occurred. Ross and Conway (1986) allowed students to participate in a skills-training program that did not, in fact, influence their skills. After participating in the study, the students 6