Working Papers

Michael P Keane and Ramna Thakur

India has a high level of out-of-pocket (OOP) health care spending, and lacks well developed health insurance markets. As a result, official measures of poverty and inequality that treat medical spending symmetrically with consumption goods can be misleading. We argue that OOP medical costs should be treated as necessary expenses for the treatment of illness, not as part of consumption. Adopting this perspective, we construct poverty and inequality measures for India that account for impoverishment induced by OOP medical costs. For 2011/12 we estimate that 4.1% of the population, or 50 million people, are in a state of “hidden poverty” due to medical expenses. Furthermore, while poverty in India fell substantially from 1999/00 to 2011/12, the fraction of the remaining poverty that is due to medical costs has risen substantially. Economic growth appears less “pro-poor” if one accounts for OOP medical costs, especially since 2004/05, and especially in rural areas.

Jennifer Alonso-García, Hazel Bateman, Johan Bonekamp, and Ralph Stevens

Implied endorsement is considered, together with inertia, as an explanation for the stickiness of defaults. This paper explores whether implied endorsement can serve as an explanation for the stickiness of defaults in the retirement decumulation phase.

Robert Holzmann, Jennifer Alonso-García, Heloise Labit-Hardy, and Andrés M. Villegas

This paper explores five key mechanisms of compensation: individualized annuities; individualized contribution rates/account allocations; a two-tier contribution structure with socialized and individual rate structure; and two supplementary approaches under the two-tier approach to deal with the income distribution tails, and the distortions above a ceiling and below a floor.

Elena Capatina, Michael Keane, and Shiko Maruyama

In the US healthcare system, patients of different socio-economic status (SES) often receive disparate treatment for similar conditions. Prior work documents this phenomenon for particular treatments/conditions, but we take a system-wide view and examine socio-economic disparities in spending for all medical conditions at the 3-digit ICD-9 level.