in areas such as poverty, food security, labor market performance, demography, education, health, gender equality, housing, and agriculture.

Finally, in Bangladesh we complement data from the Household Income and Expenditure Survey (HIES, rounds 2005, 2010, and 2016) and the Quarterly Labour Force Survey (QLFS, rounds 2002, 2003, 2005, 2006, 2010, 2013, 2015, and 2016). The QLFS is a standard labor survey focused on labor market indicators such as employment, participation rates, wages, while the HIES focuses on socio-economic household characteristics.

Careful examination of these surveys and censuses questionnaires shows that labor indicators differ in subtle but important ways, including differing definitions of “employment”. The implications of these inconsistencies increase in economies where self-employment and casual work are pervasive: it is easy to recognize a standard “nine-to-five” job with a written contract and benefits attached to it, but relatively few jobs match this description in South Asia. Therefore, it is often difficult to tell whether people are working, unemployed, or inactive, and survey answers vary depending on the statistical instrument. The difficulty of measuring employment for women is exacerbated by the fact that women tend to engage more than men in activities falling in the grey areas between work, unemployment, and inactivity.

One way the definition of employment differs across statistical instruments is what constitutes the main activity of the individual. In the Bangladesh HIES, for example, each respondent lists a number of activities he or she was engaged in, and only the activity accounting for the most time determines the person’s job type, sector of activity, or institutional sector. The Indian NSS makes distinction between “usual” status and “principal” status, and only retains the “usual” status. And in the Nepal Living Standards Survey (LSS), household activities—such as fetching water, collecting firewood and dung, and making mats—are counted as work; but to remain consistent with other data sources, we did not include such types of “extended work “as employment. We categorized each respondent as employed, unemployed, or out of the labor force based on standard definitions, matched as closely as possible to the questionnaire of each census or survey.

Another key definitional difference between statistical instruments is the reference or recall period to which the questions pertain. For example, the Pakistan LFS uses a recall period of “one week” as well as “one year” when asking respondents whether they are employed, but the HIES in the same country has a recall period of “one month” in some years and “one week” in others. In Sri Lanka, the HIES in earlier years did not specify a concrete recall period when inquiring about employment, instead asking whether the respondent is “usually” engaged in an economic activity. The LFS in Sri Lanka, on the other hand, focuses on a “one week” reference period. The Indian NSS considers a weekly and a yearly status: the first one is constructed based on questions about time use over-half days; the second one is identified based on a specific question to the respondent.

Because of these differences, comparing employment figures across sources without standardizing them can be misleading, and relying on published data alone is potentially confusing. Therefore, we aimed to standardize labor indicators to allow for valid comparisons. Given the breadth of data available, we use 8