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.
{"title":"Forecasting Prices for Components of the Medical Cost Index","authors":"D. Rosenbaum, Christopher Mann","doi":"10.5085/jfe-495","DOIUrl":"https://doi.org/10.5085/jfe-495","url":null,"abstract":"\u0000 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":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127460734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines medical inflation forecasting based on a two-step method proposed by Gilbert (2019), whereby the medical inflation rate is forecast via the sum of two terms: a broad inflation published forecast and a historical average of the inflation gap—this being the difference between medical inflation and broad inflation. In a simple forecasting experiment, the two-step method compares favorably to the one-step method of forecasting medical inflation based on its past values alone. Stationarity tests applied to the inflation gap mostly support stationarity, with a possible historical break. The econometric results generally support the use of the two-step method, with a limited historical window for inflation gap averaging, consistent with Gilbert (2019).
{"title":"Two-Step Medical Inflation Forecasts: Econometric Performance and Related Issues","authors":"Scott D. Gilbert, Gene A. Trevino","doi":"10.5085/jfe-492","DOIUrl":"https://doi.org/10.5085/jfe-492","url":null,"abstract":"\u0000 This paper examines medical inflation forecasting based on a two-step method proposed by Gilbert (2019), whereby the medical inflation rate is forecast via the sum of two terms: a broad inflation published forecast and a historical average of the inflation gap—this being the difference between medical inflation and broad inflation. In a simple forecasting experiment, the two-step method compares favorably to the one-step method of forecasting medical inflation based on its past values alone. Stationarity tests applied to the inflation gap mostly support stationarity, with a possible historical break. The econometric results generally support the use of the two-step method, with a limited historical window for inflation gap averaging, consistent with Gilbert (2019).","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124717402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This note contains graphs of worklife expectancies by quarters from 2012Q2 through 2022Q2. Graphs show Covid-19 pandemic-related downward movements in worklife expectancies were most prominent from 2020Q2 to 2021Q1. However, worklife expectances returned to their pre-pandemic levels starting in 2021Q2.
{"title":"Worklife Expectancies Two Plus Years after the Start of the Covid-19 Pandemic","authors":"K. Krueger, Gary R. Skoog, James E Ciecka","doi":"10.5085/jfe-496","DOIUrl":"https://doi.org/10.5085/jfe-496","url":null,"abstract":"\u0000 This note contains graphs of worklife expectancies by quarters from 2012Q2 through 2022Q2. Graphs show Covid-19 pandemic-related downward movements in worklife expectancies were most prominent from 2020Q2 to 2021Q1. However, worklife expectances returned to their pre-pandemic levels starting in 2021Q2.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115856968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum to “Use of Healthy Life Expectancy to Estimate Future Provision of Household and Personal Services”","authors":"Edward Foster","doi":"10.5085/jfe-493","DOIUrl":"https://doi.org/10.5085/jfe-493","url":null,"abstract":"","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121342203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Various studies estimate personal consumption expenditures from Consumer Expenditure (CEX) data. Early analysis relied on CEX data that was aggregated across expenditure categories and income groupings, while later studies used microdata containing disaggregated expenditures across individual items for each surveyed household. These newer studies allocated expenditures for each item to relevant household members, but analyzed results aggregated across income strata. We extend the microdata analysis by examining personal consumption expenditures at the household level. Our results indicate that at all but the lowest incomes, personal consumption rates generated using microdata-level observations differ only slightly from existing models using income-strata data. Forensic experts accounting for personal consumption may, thus, feel comfortable using either method of analysis.
{"title":"Estimating Personal Consumption Rates for Husbands and Wives: A Comparison of Income-Strata and Microdata Models","authors":"D. Rosenbaum, Kathleen G. Ellis","doi":"10.5085/jfe-466","DOIUrl":"https://doi.org/10.5085/jfe-466","url":null,"abstract":"\u0000 Various studies estimate personal consumption expenditures from Consumer Expenditure (CEX) data. Early analysis relied on CEX data that was aggregated across expenditure categories and income groupings, while later studies used microdata containing disaggregated expenditures across individual items for each surveyed household. These newer studies allocated expenditures for each item to relevant household members, but analyzed results aggregated across income strata. We extend the microdata analysis by examining personal consumption expenditures at the household level. Our results indicate that at all but the lowest incomes, personal consumption rates generated using microdata-level observations differ only slightly from existing models using income-strata data. Forensic experts accounting for personal consumption may, thus, feel comfortable using either method of analysis.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122705906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Event studies play a central role in class action securities fraud litigation. Event studies are used to assess market efficiency, price impact, loss causation, and damages, all of which are essential elements of a securities fraud claim. However, a substantial increase in market-wide volatility, such as what happened in 2020 with the Covid-19 pandemic, can render the standard event study methodology unreliable. In these periods, the usual distributional assumptions for t-tests of significance produce too many false positives. In this paper, we examine the extent of the problem and propose a solution that employs the empirical distribution of the t-statistic during the Covid period to adjust the critical test statistic value. We demonstrate this methodology with an application using the 19 constituents of the consumer durables index S5CODU in PreCovid and Covid period samples, and with an evaluation of earnings announcement effects on stock prices. We show the methodology restores correct test size, eliminating excess spurious significance, while preserving substantial test power to correctly identify significant events in the Covid period.
{"title":"Securities Litigation Event Studies in the Covid Volatility Regime","authors":"S. Feinstein, O. M. Villanueva","doi":"10.5085/jfe-480","DOIUrl":"https://doi.org/10.5085/jfe-480","url":null,"abstract":"\u0000 Event studies play a central role in class action securities fraud litigation. Event studies are used to assess market efficiency, price impact, loss causation, and damages, all of which are essential elements of a securities fraud claim. However, a substantial increase in market-wide volatility, such as what happened in 2020 with the Covid-19 pandemic, can render the standard event study methodology unreliable. In these periods, the usual distributional assumptions for t-tests of significance produce too many false positives. In this paper, we examine the extent of the problem and propose a solution that employs the empirical distribution of the t-statistic during the Covid period to adjust the critical test statistic value. We demonstrate this methodology with an application using the 19 constituents of the consumer durables index S5CODU in PreCovid and Covid period samples, and with an evaluation of earnings announcement effects on stock prices. We show the methodology restores correct test size, eliminating excess spurious significance, while preserving substantial test power to correctly identify significant events in the Covid period.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131103854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unlike for personal consumption of income, there is no literature for personal consumption of household services. Absent such a literature, some forensic economists use a variety of methods to estimate personal consumption of household services while others make no estimate. Using the American Time Use Survey (ATUS) data from 2003-2019, this study estimated the percentage of household services that are self-consumed based on the characteristics of the decedent and the decedent's household. The results show that the personal consumption percentage varies with the household size; number of household adults; age of the youngest child; and the decedent's sex, age, employment status, and (when applicable) the employment status of the decedent's spouse/partner. Generally, the personal consumption percentage is higher for men than women, decreases with the number of household children, increases with the age of the youngest child, is higher for respondents employed full-time compared to other employment statuses, and lower when the respondent's spouse/partner is employed full-time compared to other employment statuses. Note that in making these estimates, fungibility of time presents challenges when accounting for the contributions of various household members in the production of household services. These challenges are likely substantial between adults and minors in a household. To ignore the contribution of household members other than the decedent will underestimate the personal consumption of household services, just as ignoring fungibility issues by including the contributions of all household members will overestimate the personal consumption of household services. Accordingly, this study developed a model for the personal consumption of household services that considers only the contributions of household adults.
{"title":"Personal Consumption of Household Services","authors":"Eric W. Christensen","doi":"10.5085/jfe-475","DOIUrl":"https://doi.org/10.5085/jfe-475","url":null,"abstract":"\u0000 Unlike for personal consumption of income, there is no literature for personal consumption of household services. Absent such a literature, some forensic economists use a variety of methods to estimate personal consumption of household services while others make no estimate. Using the American Time Use Survey (ATUS) data from 2003-2019, this study estimated the percentage of household services that are self-consumed based on the characteristics of the decedent and the decedent's household. The results show that the personal consumption percentage varies with the household size; number of household adults; age of the youngest child; and the decedent's sex, age, employment status, and (when applicable) the employment status of the decedent's spouse/partner. Generally, the personal consumption percentage is higher for men than women, decreases with the number of household children, increases with the age of the youngest child, is higher for respondents employed full-time compared to other employment statuses, and lower when the respondent's spouse/partner is employed full-time compared to other employment statuses. Note that in making these estimates, fungibility of time presents challenges when accounting for the contributions of various household members in the production of household services. These challenges are likely substantial between adults and minors in a household. To ignore the contribution of household members other than the decedent will underestimate the personal consumption of household services, just as ignoring fungibility issues by including the contributions of all household members will overestimate the personal consumption of household services. Accordingly, this study developed a model for the personal consumption of household services that considers only the contributions of household adults.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131378120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper provides suggestions for future research by forensic economists, focused upon personal injury and wrongful death cases. The paper is particially based on questions from our 10 surveys of NAFE members over 25 years, in which members were directly asked to rank future areas of forensic economic research in importance. We discuss answers to important questions where there is little or no consensus among respondents, and where consensus is reasonably clear, as this may influence topics chosen for future research. We also discuss research topics by drawing on our own experience as forensic economists.
{"title":"An Agenda for Future Research in Forensic Economics: Topics from NAFE Surveys and Additional Proposals","authors":"M. Brookshire, Frank L. Slesnick","doi":"10.5085/jfe-481","DOIUrl":"https://doi.org/10.5085/jfe-481","url":null,"abstract":"\u0000 This paper provides suggestions for future research by forensic economists, focused upon personal injury and wrongful death cases. The paper is particially based on questions from our 10 surveys of NAFE members over 25 years, in which members were directly asked to rank future areas of forensic economic research in importance. We discuss answers to important questions where there is little or no consensus among respondents, and where consensus is reasonably clear, as this may influence topics chosen for future research. We also discuss research topics by drawing on our own experience as forensic economists.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128951713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite a large body of published research in forensic economics, there are still controversial topics that are lacking consensus. This paper presents an agenda for research on controversial topics in the hope that the results of such research will improve the reliability and validity of the work of forensic economists. Specifically, the paper presents suggestions for research on the choice of interest rates for discounting; interest rates, earnings growth and inflation; interest rates, growth in medical costs and inflation; how many years of earnings history is necessary to project base earnings and earnings history; alternative approaches to hedonic damages; and punitive damages.
{"title":"An Agenda for Future Research in Forensic Economics: New Approaches to Viewing Controversial Topics","authors":"Steven J. Shapiro","doi":"10.5085/jfe-487","DOIUrl":"https://doi.org/10.5085/jfe-487","url":null,"abstract":"\u0000 Despite a large body of published research in forensic economics, there are still controversial topics that are lacking consensus. This paper presents an agenda for research on controversial topics in the hope that the results of such research will improve the reliability and validity of the work of forensic economists. Specifically, the paper presents suggestions for research on the choice of interest rates for discounting; interest rates, earnings growth and inflation; interest rates, growth in medical costs and inflation; how many years of earnings history is necessary to project base earnings and earnings history; alternative approaches to hedonic damages; and punitive damages.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127527177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Do traditional two-state worklife estimates need adjustment for unemployment? To answer, an augmented three-state model classifies individuals as either 1) employed; 2) unemployed; or 3) inactive but not marginally attached. Periods of unemployment may reduce worklives; however, removal of those marginally attached or discouraged from the inactive state raises worklives. The three-state model results are compared to worklife estimates from the same initial data using the traditional two-state model. Results show that in many cases, the two-state model results are a good proxy for the three-state results that control for unemployment.
{"title":"Worklife and Unemployment: A New Consideration","authors":"D. Rosenbaum, K. Jayanetti","doi":"10.5085/jfe-473","DOIUrl":"https://doi.org/10.5085/jfe-473","url":null,"abstract":"\u0000 Do traditional two-state worklife estimates need adjustment for unemployment? To answer, an augmented three-state model classifies individuals as either 1) employed; 2) unemployed; or 3) inactive but not marginally attached. Periods of unemployment may reduce worklives; however, removal of those marginally attached or discouraged from the inactive state raises worklives. The three-state model results are compared to worklife estimates from the same initial data using the traditional two-state model. Results show that in many cases, the two-state model results are a good proxy for the three-state results that control for unemployment.","PeriodicalId":265321,"journal":{"name":"Journal of Forensic Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125840843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：