{"title":"自动登记和自动供款升级对退休收入充足性的影响。","authors":"Jack VanDerhei","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The results in this paper demonstrate the profound influence of plan design variables, as well as assumptions of employee behavior in auto-enrollment 401(k) plans. Even with a relatively simple definition of \"success,\" large differences in success rates can be seen, depending on which plan design factors and employee behavior assumptions are used: The probability of success for the lowest-income quartile increases from the baseline probability of 45.7 percent to 79.2 percent when all four factors are applied. The impact on the highest-income quartile is even more impressive, with an increase in the probability of success from 27.0 percent to 64.0 percent. When viewed in isolation, it is clear that the impact of increasing the limit on employee contributions is much greater than any of the other three factors. However, the importance of including one or more additional factors, along with the increase in the limit on employee contributions, can more than double the impact of increasing the limit by itself. This suggests that additional analysis of the influence of plan design variables on optimizing employee results is warranted. The next step in this project will include development of a plan-specific simulation model that will allow additional plan design variables.</p>","PeriodicalId":79588,"journal":{"name":"EBRI issue brief","volume":" 349","pages":"1-11"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of auto-enrollment and automatic contribution escalation on retirement income adequacy.\",\"authors\":\"Jack VanDerhei\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The results in this paper demonstrate the profound influence of plan design variables, as well as assumptions of employee behavior in auto-enrollment 401(k) plans. Even with a relatively simple definition of \\\"success,\\\" large differences in success rates can be seen, depending on which plan design factors and employee behavior assumptions are used: The probability of success for the lowest-income quartile increases from the baseline probability of 45.7 percent to 79.2 percent when all four factors are applied. The impact on the highest-income quartile is even more impressive, with an increase in the probability of success from 27.0 percent to 64.0 percent. When viewed in isolation, it is clear that the impact of increasing the limit on employee contributions is much greater than any of the other three factors. However, the importance of including one or more additional factors, along with the increase in the limit on employee contributions, can more than double the impact of increasing the limit by itself. This suggests that additional analysis of the influence of plan design variables on optimizing employee results is warranted. The next step in this project will include development of a plan-specific simulation model that will allow additional plan design variables.</p>\",\"PeriodicalId\":79588,\"journal\":{\"name\":\"EBRI issue brief\",\"volume\":\" 349\",\"pages\":\"1-11\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EBRI issue brief\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EBRI issue brief","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The impact of auto-enrollment and automatic contribution escalation on retirement income adequacy.
The results in this paper demonstrate the profound influence of plan design variables, as well as assumptions of employee behavior in auto-enrollment 401(k) plans. Even with a relatively simple definition of "success," large differences in success rates can be seen, depending on which plan design factors and employee behavior assumptions are used: The probability of success for the lowest-income quartile increases from the baseline probability of 45.7 percent to 79.2 percent when all four factors are applied. The impact on the highest-income quartile is even more impressive, with an increase in the probability of success from 27.0 percent to 64.0 percent. When viewed in isolation, it is clear that the impact of increasing the limit on employee contributions is much greater than any of the other three factors. However, the importance of including one or more additional factors, along with the increase in the limit on employee contributions, can more than double the impact of increasing the limit by itself. This suggests that additional analysis of the influence of plan design variables on optimizing employee results is warranted. The next step in this project will include development of a plan-specific simulation model that will allow additional plan design variables.