{"title":"回顾美国税收改革的立法滞后","authors":"P. Adämmer, T. Dybowski","doi":"10.2139/ssrn.3075049","DOIUrl":null,"url":null,"abstract":"We apply an unsupervised machine learning algorithm to revisit legislative lags of U.S. tax reforms and show that at least two lags have been longer than previously identified. Our approach offers an alternative way to approximate U.S. tax foresight, given that the relationship between tax exempt municipal bonds and taxable U.S. Treasury securities has broken down in 2007.","PeriodicalId":330166,"journal":{"name":"Law & Society: Public Law - Tax eJournal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Revisiting Legislative Lags of U.S. Tax Reforms\",\"authors\":\"P. Adämmer, T. Dybowski\",\"doi\":\"10.2139/ssrn.3075049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We apply an unsupervised machine learning algorithm to revisit legislative lags of U.S. tax reforms and show that at least two lags have been longer than previously identified. Our approach offers an alternative way to approximate U.S. tax foresight, given that the relationship between tax exempt municipal bonds and taxable U.S. Treasury securities has broken down in 2007.\",\"PeriodicalId\":330166,\"journal\":{\"name\":\"Law & Society: Public Law - Tax eJournal\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Law & Society: Public Law - Tax eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3075049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Law & Society: Public Law - Tax eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3075049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We apply an unsupervised machine learning algorithm to revisit legislative lags of U.S. tax reforms and show that at least two lags have been longer than previously identified. Our approach offers an alternative way to approximate U.S. tax foresight, given that the relationship between tax exempt municipal bonds and taxable U.S. Treasury securities has broken down in 2007.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
