Table 2 presents the summary results of the consumption survey experiment. It reports the difference in the log per capita consumption measure of each design relative to the benchmark individual diary.<sup>7</sup> The estimates in table 2 derive from regressions of the natural logarithm of food, nonfood, and total consumption on binary indicators for module assignment (whereby the benchmark personal diary is the left out category). Because the survey experiment was randomized, the regressions include no covariate controls except for the survey cluster (the village or urban area sampling unit within which households were randomized to the various survey designs). The regressions in table 2 show that, with the exception of 7-day recall with the long list, the modules record between 8 percent and 33 percent less food consumption compared with the personal diary (column 3). The impact on total consumption is at a similar magnitude (column 2). In the diary approach to food consumption, the use of only one respondent to complete the diary for an entire household is associated with significantly lower food consumption, by 13–20 percent, most likely because some share of unobservable personal consumption of the other household members is omitted (not captured) by the respondent maintaining the diary. Differences in frequent nonfood consumption are also observed, especially in the diaries, again suggesting the importance of accurately recording personal consumption.<sup>8</sup> Regarding the recall survey approach, all mean food expenditures are lower than the benchmark. The mean of the 7-day long list lies nearest to the benchmark value, while modules with longer recall periods (14 days or the usual month) or more aggregated consumption categories (the collapsed list) record food consumption that is 17 percent to 33 percent lower. Even though the 7-day long list comes closest to the mean benchmark food consumption value in this experiment, it is difficult to extrapolate definitively that the 7-day long list will be the most accurate of the recall designs if it is applied in different settings. Because the net deviation of each module from the benchmark is the product of the contrasting influence of various types of reporting error, different settings may present differing magnitudes of underlying error types. The error decomposition analysis below is a first attempt to disentangle the relative influence of these types of reporting errors.

Beegle et al. (2012) also investigate the possible effect of salient and easily observed household characteristics—those assumed to determine actual consumption levels—on the accuracy of consumption reporting. The characteristics investigated include the following: (1) household size: it was determined that recall modules underreport consumption even more as the size of the household increases; (2) urban

> 7 While the experiment focused on food consumption measurement, each survey also recorded nonfood consumption. For less frequently purchased items, such as durable goods, clothes, and health care, all surveys and diaries employed a one-month or 12-month recall design (whereby households assigned to diaries were administered a nonfood consumption survey at the end of a two-week study period). For more frequently purchased nonfood items such as soap or transport, the consumption was either asked in recall form in the recall modules 1–5 (in which the period of recall corresponded to that for food) or recorded as diary entries for households assigned a diary.

> 8 Because the questionnaire wording and structure for the nonfrequent nonfood consumption section were identical across the eight modules, it is perhaps surprising to see significantly negative coefficients for modules 1, 4, and 7 relative to the benchmark. Such differences can result from three sources: respondent fatigue as the recalled items in these modules come after the lengthy food recall sections in modules 1–5 or after a two-week diary; cognitive framing; and variations in the ability to capture personal nonfrequent nonfood consumption outside the purview of the main respondent. Contrary to concerns of respondent fatigue, module 4, with the collapsed food categories and shorter interview time, yielded significantly less (by 14 percent) nonfrequent nonfood consumption. Possibly the lack of follow-up during the diary period made the module 7 respondents less diligent in the nonfrequent nonfood section of the final interview.

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