{"title":"医疗成本指数组成部分的价格预测","authors":"D. Rosenbaum, Christopher Mann","doi":"10.5085/jfe-495","DOIUrl":null,"url":null,"abstract":"\n A new method is proposed to project future costs for medical components of a life care plan. The technique estimates the historical link between inflation in medical components of the CPI and overall inflation. This linkage for each component can then be applied to a CPI forecast to project inflation in that underlying component. Estimates are made for 17 separate medical cost components of the CPI. Root mean square errors show that our proposed method for forecasting component inflation performs better than more commonly used forecast methods. Our method incorporates the best parts of both historical and forecasting methods; it utilizes information from the financial markets and professional surveys to form the baseline inflation forecast, then adjusts the value using historical data, thereby leveraging both expert opinion and empirical observation.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":"139 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting Prices for Components of the Medical Cost Index\",\"authors\":\"D. Rosenbaum, Christopher Mann\",\"doi\":\"10.5085/jfe-495\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n A new method is proposed to project future costs for medical components of a life care plan. The technique estimates the historical link between inflation in medical components of the CPI and overall inflation. This linkage for each component can then be applied to a CPI forecast to project inflation in that underlying component. Estimates are made for 17 separate medical cost components of the CPI. Root mean square errors show that our proposed method for forecasting component inflation performs better than more commonly used forecast methods. Our method incorporates the best parts of both historical and forecasting methods; it utilizes information from the financial markets and professional surveys to form the baseline inflation forecast, then adjusts the value using historical data, thereby leveraging both expert opinion and empirical observation.\",\"PeriodicalId\":265321,\"journal\":{\"name\":\"Journal of Forensic Economics\",\"volume\":\"139 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forensic Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5085/jfe-495\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forensic Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5085/jfe-495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting Prices for Components of the Medical Cost Index
A new method is proposed to project future costs for medical components of a life care plan. The technique estimates the historical link between inflation in medical components of the CPI and overall inflation. This linkage for each component can then be applied to a CPI forecast to project inflation in that underlying component. Estimates are made for 17 separate medical cost components of the CPI. Root mean square errors show that our proposed method for forecasting component inflation performs better than more commonly used forecast methods. Our method incorporates the best parts of both historical and forecasting methods; it utilizes information from the financial markets and professional surveys to form the baseline inflation forecast, then adjusts the value using historical data, thereby leveraging both expert opinion and empirical observation.