This research provides a status-based explanation for the high rates of female labor force non-participation (FLFNP) and the sustained increase in these rates over time that have been documented in many developing economies. This explanation is based on the idea that households or ethnic groups can signal their wealth, and thereby increase their social status, by withdrawing women from the labor force. If the value of social status or the willingness to bear the signaling cost is increasing with economic development, then this would explain the persistent increase in FLFNP. To provide empirical support for this argument, we utilize two independent sources of exogenous variation – across Indian districts in the cross-section and within districts over time – to establish that status considerations determine rural FLFNP. Our status-based model, which is used to derive the preceding tests, is able to match the high levels and the increase in rural Indian FLFNP that motivate our analysis. Counterfactual simulations of the estimated model indicate that conventional development policies, such as a reduction in the cost of female education, could raise FLFNP by increasing potential household incomes and, hence, the willingness to compete for social status. The steep increase in female education in recent decades could paradoxically have increased FLFNP in India even further.
This research connects two seemingly unrelated facts that have recently been documented in developing countries, with important consequences for global health: (i) the weak association between nutritional status and income, and (ii) the elevated risk of diabetes among normalweight individuals. The model that we develop to reconcile these facts is based on a set point for body size that is adapted to (low) pre-modern food supply, but subsequently fails to adjust to rapid economic change. During the process of development, some individuals thus remain at their low-BMI set point, despite the increase in their income (food consumption), while others who have escaped their set point (but are not necessarily overweight) are at increased risk of diabetes. The model is tested along different dimensions with multiple data sets. Our analysis indicates that many lean diabetics in developing country populations will be close to their individual-specific set point, suggesting a promising approach to diabetes control (reversal) that involves relatively little weight loss.