(hypothesis 2), nor once they are in the labor force and have to make a trade‐off between monetary and non‐monetary benefits (hypothesis 1), but during the transition to the labor market. This scenario would require a different set of policies.

To test this hypothesis, we check whether women are more likely than men to be working outside their field of study. We carry out a matching exercise between field of study and occupation to identify whether a worker is working within their field of study or working outside of their field of study. Specifically, we estimate: where �������� is a dummy variable that takes the value of 1 when person � works outside their field of study, and 0 otherwise. A positive ��� would support the hypothesis that women find it more difficult than men to find jobs within their field of study. �� here only includes a control for age.

# 4. Data

We use three data sets to implement the strategy described above. First, we use data on wage workers in Vietnam from the Labor Force Surveys (LFS) carried out by the General Statistics Office (GSO) of Vietnam between 2011 and 2014. The LFS includes information on occupation, industry of employment and highest level of educational attainment for all respondents. Occupations are classified using the international standard classification of occupations (ISCO‐08) and industries using the International standard classification of Industry (ISIC‐08), with both available at the 4‐digit level (corresponding to more than 400 occupations and industries), providing a sufficiently granular level of information on occupational and industry choice. A worker’s highest level of education is classified using a system that is based on the international standard classification of education (ICSED‐08). Vietnam has an extensive system of vocational education, so we simplify the educational classification for ease of presentation<sup>4</sup> (see Appendix III).

The LFS data permits us to estimate equations 1 ‐ 3 – i.e. to estimate the size of the gender wage gap in Vietnam, the role that differences in educational attainment and occupation‐industry sorting play in explaining the size of the gender wage gap. Given the sample design of the LFS, these estimates likely provide a good picture of the overall state of the labor market in Vietnam.

Second, we use data from the Vietnam Young Lives project. Young Lives is an international longitudinal cohort study of childhood poverty which has been following 12,000 children in four countries (Ethiopia, Peru, Vietnam and India) over a period of 15 years. Each country has two cohorts, one consisting of 2,000 children born in 2001‐2002 and another consisting of 1,000 children born in 1994‐1995. The survey consists of three main elements: (1) a household questionnaire, (2) a child questionnaire and (3) a community questionnaire.

The first of four rounds of data collection under Young Lives (YL) took place in 2002. It used a sampling strategy designed to ensure over‐sampling of poor communities. An equal number of eligible children

> 4 We originally ran the analysis on the fully extended system of educational levels. The results are robust to the choice of classification system.

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