more detailed questioning to better capture this work. This mechanism helps to explain the results in Figure 3 showing that the IHS4 non-proxy sample reports lower non-farm enterprise and wage employment. Recent cognitive studies conducted by the ILO across countries, for example, have found that many respondents in highly informal and agricultural contexts can have difficulty — without detailed contextual and follow-up questions — on identifying their work in an enterprise or casual wage work (Benes and Walsh, 2018b).

Table 5 aims to better understand whether this mechanism is at work for non-farm enterprise activity, where underreporting under the business-as-usual approach is more systematic across the wealth distribution and for both men and women. Specifically, Table 5 compares the enterpriserelated outcomes above that come from the labor module, with the same outcomes from a separate household enterprise module that was also part of each survey. The enterprise module in each survey creates a roster of all enterprises that household members are involved in, and for each enterprise, one person (almost always the owner/manager, discussed below) reported on roles across household members on owners, managers, as well as those in supporting roles.

We find that the IHPS individual-interview approach tends to result in lower discrepancies between the labor module and non-farm enterprise module for the overall sample (although there is a significant difference, albeit small in magnitude, for the share of women working in a supporting role). For the IHS4, on the other hand, a significantly greater number of men and women are captured by the enterprise module as owners/managers, as well as supporting workers. Within the sample of households with an enterprise, there are significant differences in both the IHPS and IHS4, where the nonfarm enterprise module captures a greater share of men and women owners/managers as compared to the labor module. The discrepancy, however, is much greater under the business-as-usual approach, and also relatively greater for women (an increase from 37 to 51 percent in women’s ownership/management moving from the labor module to the nonfarm enterprise module, or a 14-percentage point increase) as compared to men (a 12-percentage point increase).

In addition, there were cases of proxy respondents in the enterprise module (those that neither owned/managed or worked in the enterprise), although for the sample of individuals used in the analysis, the share of proxy response was lower in the IHPS (6.7 percent, or 64 individuals) compared to the IHS4 (10.4 percent).<sup>17</sup> The last two columns of Table 5 show that proxy response in the non-farm enterprise module has a greater effect on reporting of ownership/management in the IHS4, particularly for men — where own-reporting tended to be lower than the overall (proxy plus own-reporting) sample. There was, otherwise, no effect of proxy response in the IHPS non-

> 17 The enterprise module provides a closer look at the types of enterprises that had a proxy respondent — nearly all (99 percent) of these enterprises had only one owner/manager, with most (about 80 percent) having no other supporting workers. These tended to be enterprises owned by the husband, with the spouse reporting. Among those enterprises with the owner/manager not reporting and which had workers, however nearly all (20 out of 25) of IHPS respondents were working in that enterprise, compared to 69 percent in the IHS4 (66 out of 96 enterprises).

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