An Introduction to Multilevel Modeling for Insurance and Actuarial Applications

(copy)979-8-3503-3564-4/23/$31.00 ©2023 IEEEThis paper focuses on the statistical modeling of complex data using multilevel modeling. The purpose is to provide a simple yet reasonably comprehensive introduction to this advanced technique to encourage more usage of this technique by both researchers and practitioners. The paper starts by reviewing the usually familiar (single-level) general linear model theory. Then, it builds on it to the more advanced linear mixed model theory, and eventually the multilevel modeling approach. All the key terms are explained. The paper uses examples from actuarial and insurance applications to illustrate since these types of data are often encountered there. However, this technique can be also used for other business and management applications. As shown, multilevel modeling represents a powerful tool to handle complex data structures, including hierarchical and cross-classified datasets. Therefore, it can accommodate the complex nature of some insurance data, such as group insurance policies. Accordingly, it is recommended that this model is used more in future empirical studies and pricing group insurance contracts. The review of theories is designed to balance simplicity and comprehensive coverage to appeal to readers with different backgrounds including limited prior statistical background. It also bridges the gap between simple and more advanced techniques, whereas book coverage usually focuses only on one of these two aspects and takes a much longer time to grasp key ideas.