judgment about women who do not work. Our enumerators were all Jordanians, which may have gone some way toward mitigating social desirability bias. In addition, we incentivized responses to some questions by offering rewards if they were able to estimate correctly the number of respondents who expressed certain beliefs or behaved in certain ways. Incentivizing accuracy should have mitigated social desirability bias. The pre-test also made clear the importance of examining the expectations couples had of each other. The final questionnaire focused on the mutual expectations of male-female couples in order to explore whether a) social norms are enforced primarily in households, rather than through generalized disapproval, gossip, or harassment; and b) intra-household power dynamics, or interpersonal expectations within the household, could constrain women’s economic participation even independently of social norms.

Two additional findings from the pre-test were of interest. First, it became clear that social norms regarding women working in the private sector, though important in the minds of policy makers, did not appear to be prominent to respondents, who did not know enough women working in the private sector to be able to adequately distinguish between jobs in the public and private sectors. Accordingly, the final questionnaire dropped a set of questions regarding social norms of women working in the public vs. private sectors. Second, there appeared to be some continuity between normative and empirical expectations questions. For instance, the harassment of women working is both a circumstance that affects the empirical likelihood a Jordanian woman works (like having young children) and an expression of normative disapproval in Jordan society. But rather than deciding in advance whether questions like this were to be understood as social empirical or social normative expectations, we decided to examine this in the exploratory factor analysis after the data were collected.

Approximately two weeks after the completion of the main survey, a follow-up survey was conducted with 1,000 respondents. The follow-up survey included selected questions from each of the themes from each social norms module. It was conducted over the phone with a random subset of respondents who agreed to share their phone numbers for the short follow-up survey. The purpose of this survey was to assess if responses to social norms and beliefs related questions stayed consistent over time.

# **Sample and Data Collection**

The main survey was conducted with a sample of 2,007 respondents from low to middle-income families, in urban and peri-urban areas of Amman, Zarqa, and Mafraq, between March and April 2018. Given the low rate of female labor force participation in Jordan, working women were oversampled at each location to obtain a sufficiently large sample size for comparison and analysis. Targeting at least 30% working women, the sampling methodology was a stratified cluster sample based off an enumeration exercise. With Amman comprising of 70% of the sampling frame, the governorate was under-sampled by 15 clusters, which were transferred to the Mafraq stratum. Localities within each governorate served as the primary sampling unit; grids within each locality as the secondary sampling unit; and within each randomly selected grid, census blocks acted as the tertiary sampling unit. Census blocks were enumerated to locate working women, and priority of selection was given to working women within each household. Lastly, a stratified (by work status and gender) simple random sample was drawn from eligible households (fourth sampling unit).

Quantitative data from the pre-test, quantitative survey, and follow-up survey were collected using tablets. Enumerators were trained extensively by research team members and the local data firm, and the survey was pre-tested to check for comprehension, proper administration, and survey fatigue. Enumeration data were used to pre-assign respondents to enumerators, and replacement households were also assigned to minimize enumerator discretion in the field. Data were analyzed using Stata to generate descriptive tables and figures and to conduct validity, reliability and regression analysis, and Python for narrative analysis.

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