We combine several nationwide micro data sets. First, we rely on the 2002 and 2018 national censuses to quantify and analyze changes in FLFP over this period. The censuses capture information on FLFP together with individual and household socioeconomic characteristics and local labor markets including age, education, ethnicity, marital status, household composition, labor market status of household members, and household infrastructure characteristics. Second, we compute municipality and department level variables from the 2017-2018 Census of Human Resources of the Central Government (INE), 2017 Crime statistics (INE), and 2017 Latinobarómetro survey to create measures of social norms and attitudes towards women. These variables capture the extent to which women participate in household decision making, the share of females among high-wage public sector employees (as a proxy of public visibility), rates of intrafamily violence against women, and the share of individuals endorsing gender parity in parliament or in the judicial system. Finally, we rely on subnational information on social public policy produced by INE, the Foundation for the Development of Guatemala (FUNDESA in its Spanish acronym), and the Central American Institute of Fiscal Studies (ICEFI in its Spanish acronym) to assess its impact on the women’s incentives to participate in the labor market. These policy variables include the number of preprimary centers in each municipality, public spending in education and health at the department level, and a measure of municipal road accessibility (all measured in 2017).

Our main sample is composed of women in the active age of 25 to 49 years-old living in households where they or their spouses are household heads (see Berlinski and Galiani, 2007). We start by assessing changes in FLFP between 2002 and 2018. We assume the probability of FLFP in each year can be represented by a linear probability model. We explore the Oaxaca-Blinder decomposition (Blinder, 1973; Oaxaca, 1973) using individual and household characteristics and local labor market variables as possible drivers of this change. Our decomposition results point to significant unexplained differences in FLFP over time.

We consider a simple reduced-form model to estimate the impact of a more extended set of local drivers on FLFP in 2018. We follow the literature and measure FLFP with the ILO definition.<sup>5</sup> This reduced form model faces at least two challenges. First, despite our efforts, there could be still non-observable drivers of FLFP that are simultaneously correlated with the individual, household, or municipality-level variables that we include in the reduced-form model. This could bias the least squares estimates for the impacts of the variables considered or their power to explain within-country differences. Take for instance the role of women’s unobserved personality traits, such as individual self-confidence. This could be correlated both with the participation of women in household decision making and with their decision to participate in the labor market. Second, it

> 5 The ILO definition of FLFP does not differentiate between formal or informal work.

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