Rotating savings and credit associations (roscas) are informal financial organizations common in settings where communities have reduced access to formal financial institutions. In a rosca, a fixed group of participants regularly contribute sums of money to a pot. This pot is then allocated periodically using lottery, aftermarket, or auction mechanisms. Roscas are empirically well-studied in economics. They are, however, challenging to study theoretically due to their dynamic nature. Typical economic analyses of roscas stop at coarse ordinal welfare comparisons to other credit allocation mechanisms, leaving much of roscas' ubiquity unexplained. In this work, we take an algorithmic perspective on the study of roscas. Building on techniques from the price of anarchy literature, we present worst-case welfare approximation guarantees. We further experimentally compare the welfare of outcomes as key features of the environment vary. These cardinal welfare analyses further rationalize the prevalence of roscas. We conclude by discussing several other promising avenues.

Rotating Savings and Credit Associations (Roscas) are a widely documented informal financial organization that is often used in low-income communities with limited funding sources. Roscas have been shown to serve as a tool for economic empowerment and a way of mitigating adverse shocks to income for vulnerable communities. In this paper, I describe my contributions to a research project in which we study the allocative efficiency of different Rosca structures and formats in the presence of risk-averse agents.