This paper offers a broad overview of the philanthropic goals of microinsurance — namely, to provide vulnerable populations with more self-sufficient and sustainable methods of coping with risk — and through this lens, analyses the applications of multiple linear regression in developing dynamic models for microinsurance. We explain the foundations of MLR (multiple linear regression), and then give two examples for how a simple multiple linear regression model can be adapted with a novel outcome variable (famine) and dependent variables (climate change related costs). Overall, a better understanding of MLR can lend to a better understanding of how microinsurance can scale its practices to new regions. Since this is an overview of the general practice of microinsurance, and not on any particular region or case study, we draw some insights on the practice of microinsurance modeling from some specific regions, such as the Bihar region of India, and illustrate generally how these insights can be used to improve microinsurance broadly
