{"title":"损失率动力学","authors":"Martin F. Grace","doi":"10.1111/rmir.12247","DOIUrl":null,"url":null,"abstract":"Abstract Many studies of the insurance profit cycle use industry‐level annual data and focus on the existence of an AR(2) process. We take a different approach by adopting the idea of possible hard and soft markets, but they are not necessarily cyclical in the classic sense. In addition to aggregated data, we use quarterly firm‐level data to examine loss ratio behavior over time. This approach allows one to assess the firm‐level heterogeneity in the insurance market. We further use a Markov switching model to assess the heterogeneity of response to economic variables. Using a K‐means cluster approach, we examine the different clusters of firms and their different behavior over 2001q1−2020q4.","PeriodicalId":35338,"journal":{"name":"Risk Management and Insurance Review","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Loss ratio dynamics\",\"authors\":\"Martin F. Grace\",\"doi\":\"10.1111/rmir.12247\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Many studies of the insurance profit cycle use industry‐level annual data and focus on the existence of an AR(2) process. We take a different approach by adopting the idea of possible hard and soft markets, but they are not necessarily cyclical in the classic sense. In addition to aggregated data, we use quarterly firm‐level data to examine loss ratio behavior over time. This approach allows one to assess the firm‐level heterogeneity in the insurance market. We further use a Markov switching model to assess the heterogeneity of response to economic variables. Using a K‐means cluster approach, we examine the different clusters of firms and their different behavior over 2001q1−2020q4.\",\"PeriodicalId\":35338,\"journal\":{\"name\":\"Risk Management and Insurance Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Risk Management and Insurance Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/rmir.12247\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Management and Insurance Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/rmir.12247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Abstract Many studies of the insurance profit cycle use industry‐level annual data and focus on the existence of an AR(2) process. We take a different approach by adopting the idea of possible hard and soft markets, but they are not necessarily cyclical in the classic sense. In addition to aggregated data, we use quarterly firm‐level data to examine loss ratio behavior over time. This approach allows one to assess the firm‐level heterogeneity in the insurance market. We further use a Markov switching model to assess the heterogeneity of response to economic variables. Using a K‐means cluster approach, we examine the different clusters of firms and their different behavior over 2001q1−2020q4.
期刊介绍:
Risk Management and Insurance Review publishes respected, accessible, and high-quality applied research, and well-reasoned opinion and discussion in the field of risk and insurance. The Review"s "Feature Articles" section includes original research involving applications and applied techniques. The "Perspectives" section contains articles providing new insights on the research literature, business practice, and public policy. The "Educational Insights" section provides a repository of high-caliber model lectures in risk and insurance, along with articles discussing and evaluating instructional techniques.