The Bangladesh gender gap in education : biased intra-household educational expenditures

By investigating the educational expenditure of children over the ten years (2000 to 2010), we evaluate whether there exists any gender specific discrepancy at the household level and the trend of such discrepancy over the years. Using three rounds of nationally representative Household Income & Expenditure Surveys this study reveals that households spend less on education for their school-going girls compared to boys. By disaggregating the total expenditure into fixed and variable components, we find persistent gender imbalance in educational expenditure where households provide better quality of education for boys. Moreover, we find that gender based discrepancy has a very persistent trend and does not show any significant sign of narrowing the gap over the years. Cohort wise difference-in-difference estimation also reveals that the gap has initially widened and later converged but has not diminished beyond the initial level of discrepancy, which may warrant targeted policy intervention.

Measuring smile curves in global value chains

The concept and logic of the "smile curve" in the context of global value chains has been widely used and discussed at the individual firm level, but rarely identified and investigated at the country and industry levels by using real data. This paper proposes an idea, based on an inter-country input-output model, to consistently measure both the strength and length of linkages between producers and consumers along global value chains. This idea allows for better identification and mapping of smile curves for countries and industries according to their positions and degrees of participation in a given conceptual value chain. Using the 1995-2011 World Input-Output Tables, several conceptual value chains are investigated, including exports of electrical and optical equipment from China and Mexico and exports of automobiles from Japan and Germany. The identified smile curves provide a very intuitive and visual image, which can significantly improve our understanding of the roles played by different countries and industries in global value chains. Further, the smile curves help identify the benefits gained by these countries and industries through their participation in global trade.