Education Analysis Issues and Methodology

Although the terms “industry” and “global value chain” (GVC) are often used synonymously, they have different meanings, particularly when using data based on industrial classification systems. GVCs are composed of a series of activities that span multiple industries and economic sectors. For example, the apparel GVC spans all three sectors: agriculture, manufacturing, and services. “Inputs” come from agriculture (natural fibers such as cotton and wool). “Components” are part of the textile manufacturing industry, and “assembly” is part of the apparel manufacturing industry. Distribution, design, and branding are services carried out by wholesalers, retailers, and myriad other service sectors (Frederick 2019). In many manufacturing GVCs, downstream segments tend to be more labor intensive and upstream segments are more capital intensive.

To analyze labor market outcomes across industries and occupations, we use microlevel labor force survey (LFS) data (details in table A.2). The estimated statistics are generally consistent with those reported by the International Labour Organization or the World Bank. LFS data are linked to standardized classifications of industries and occupations. Some countries use the international systems (ISIC and ISCO) directly, while others use national systems that correlate to the international systems. These classification systems change over time, and time series analysis requires harmonization. Whenever possible, our analysis uses the version of ISIC and ISCO used in the original survey or as provided by the statistics agency to minimize harmonization impacts. We always use the national currency reported.

LFS data on education were converted to number of years and then standardized, to the extent possible, across countries. This enabled us to report education data based on number of years or by shares in education level groups. The available number of education levels varies significantly by country (from 7 to 25 options in the LFS); to standardize them, we had to determine the range of options available across countries and calculate to accommodate countries with fewer options (table A.9).2 Education groups are based on completion of education in that group; any reported values that fall below completion were moved to fewer years of education to facilitate harmonization across countries.

Like data in the previous chapters, education data were reviewed to determine accuracy and alignment with other reports using the same underlying data sources. Years of data determined to be unreliable are not used. In Bangladesh, for example, the education standardization was possible only for the last two rounds of the LFS for which we have data (2013 and 2016), but only the 2013 results are aligned with previous reports. We convert unstated, blank, or “don’t know” answers to missing values. In Bangladesh’s 2016 LFS, the latter issue accounts for 22 percent of total observations.