Faculty
Statistical and Acturaial Sciences / Arts and Humanities
Supervisor Name
Ricardas Zitikis
Keywords
microinsurance, sustainable development, weather index insurance
Description
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.
Acknowledgements
I owe the existence of this research paper to Dr. Ricardas Zitikis, who has been unrelenting in his support of my research interests since our first correspondence. Coming from an unconventional background into statistical research has certainly come with its own set of hurdles, but thanks to my supervisor being a supportive and firm believer in interdisciplinary research, I have never doubted that I have something unique to contribute in my work.
I would also like to give a special thank you to the School for Advanced Studies in the Arts and Humanities, and Dr. Barbara Bruce, experiential learning coordinator at SASAH, who read through my reflections and offered me emotional support throughout the process of producing this paper as well. I am exceptionally grateful to be a part of such an encouraging community as a part of my undergraduate experience.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Document Type
Poster
Included in
Applied Mathematics Commons, Arts and Humanities Commons, Growth and Development Commons
Modeling Weather Vulnerability Dynamically: Applications of Multiple Linear Regression to Weather Index Microinsurance
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.