Abstract:
Against the backdrop of the 2030 UN Agenda for Sustainable Development, this paper analyzes the measurement issues in gender-based indices constructed by the United Nations Development Programme (UNDP) and suggests alternatives for choice of variables, functional form, and weights. While the UNDP Gender Inequality Index (GII) conceptually reflects the loss in achievement due to inequality between men and women in three dimensions-health, empowerment, and labor force participation-we argue that the assumptions and the choice of variables to capture these dimensions remain inadequate and erroneous, resulting in only the partial capture of gender inequalities. Since the dimensions used for the GII are different from those in the UNDP's Human Development Index (HDI), we cannot say that a higher value in the GII represents a loss in the HDI due to gender inequalities. The technical obscurity remains how to interpret GII by combining women-specific indicators with indicators that are disaggregated for both men and women. The GII is a partial construct, as it does not capture many significant dimensions of gender inequality. Though this requires a data revolution, we tried to reconstruct the GII in the context of Asia-Pacific using three scenarios: (1) improving the set of variables incorporating unpaid care work, pay gaps, intrahousehold decision making, exposure to knowledge networks, and feminization of governance at local levels; (2) constructing a decomposed index to specify the direction of gender gaps; and (3) compiling an alternative index using Principal Components Index for assigning weights. The choice of countries under the three scenarios is constrained by data paucity. The results reveal that the UNDP GII overestimates the gap between the two genders, and that using women-specific indicators leads to a fallacious estimation of gender inequality. The estimates are illustrative. The implication of the results broadly suggests a return to the UNDP Gender Development Index for capturing gender development, with an improvised set of choices and variables.