employment we detect in the household enterprise modules (4%-19%) can be explained by the use of a longer reference period rather than a different way of detecting employment.

Our results highlight some issues of under-detection of employment that are common in LMICs, but employment detection issues may vary across contexts. Our results may be more applicable to situations where women’s economic activities are carried out within the context of the home or the family farm and where a clear separation between domestic roles (in unpaid care work) and economic roles does not exist. Countries with a larger share of the population in non-wage work, living in rural areas, or engaged in agriculture may be particularly at risk for underdetection of employment. For instance, in Sudan, a country with a primarily rural population, disproportionately engaged in informal, non-wage, and agricultural work, the employment rate rises from 12% to 25% for women when moving from standard individual questions to measures that incorporate participation in household enterprises (Krafft et al. 2023).

# **_6.3 Implications for data collection and research_**

As noted in Section 2, efforts to improve the measurement of female participation in economic activity have a long history in LMICs such as Egypt. These efforts were often difficult to sustain and resulted in considerable instability in the measured rates. The 19<sup>th</sup> ICLS made substantial progress in distinguishing between the concept of employment (or work for pay or profit) and other kinds of work. Given the informality of much employment in LMICs (La Porta and Shleifer 2014), administrative data are not sufficient to assess employment rates, requiring reliance on household surveys. However, operationalizing these definitions in Labor Force Surveys has been fairly difficult and has been applied inconsistently across countries and even in the same country over time.

The main difficulty with measuring women’s employment has been with self-employment and unpaid family work that women undertake in the context of household enterprises and farms. Our work suggests that information about such work can best be obtained by asking about the household’s involvement in specific activities such as crop production, livestock rearing, other agricultural processes, and non-agricultural activities and then inquiring in detail about who among household members is involved in either running or managing these activities or in support roles. Distinguishing between employment and other forms of work would then depend on whether these activities are carried out at least in part for purposes of market exchange.

Clearly, an individual approach to inquiring about employment is also necessary, but that approach should be supplemented by this enterprise-based methodology to obtain a fuller picture of women’s and potentially children’s involvement in economic activity in LMICs. Accurate data on women’s employment is critically important for informing policies and programs to support women’s employment and economic development. For instance, common surveys in Sub-Saharan Africa that differentially sample and survey women-owned businesses yield different policy implications for supporting such businesses (Hardy, Kagy, and Jimi 2022).

Future research should revisit the relationship between women’s employment and other outcomes with better measures of employment. For instance, the additional employment captured with different measures could have a differential relationship with women’s 24