{"title":"奈特的不确定性假设:不可预见的变化和Muth的一致性约束","authors":"R. Frydman, S. Johansen, Anders Rahbek, M. Tabor","doi":"10.2139/ssrn.3341203","DOIUrl":null,"url":null,"abstract":"This paper proposes the Knightian Uncertainty Hypothesis (KUH), a new approach to macroeconomics and finance theory. KUH rests on a novel mathematical framework that characterizes both measurable and Knightian uncertainty about economic outcomes. Relying on this framework and Muthi?½s pathbreaking hypothesis, KUH represents participantsi?½ forecasts to be consistent with both uncertainties. KUH thus enables models of aggregate outcomes that 1) are premised on market participantsi?½ rationality, and 2) accord a role to both fundamental and psychological (and other non-fundamental) factors in driving outcomes. The paper also suggests how a KUH modeli?½s quantitative predictions can be confronted with time-series data.","PeriodicalId":299310,"journal":{"name":"Econometrics: Mathematical Methods & Programming eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"The Knightian Uncertainty Hypothesis: Unforeseeable Change and Muth’s Consistency Constraint in Modeling Aggregate Outcomes\",\"authors\":\"R. Frydman, S. Johansen, Anders Rahbek, M. Tabor\",\"doi\":\"10.2139/ssrn.3341203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes the Knightian Uncertainty Hypothesis (KUH), a new approach to macroeconomics and finance theory. KUH rests on a novel mathematical framework that characterizes both measurable and Knightian uncertainty about economic outcomes. Relying on this framework and Muthi?½s pathbreaking hypothesis, KUH represents participantsi?½ forecasts to be consistent with both uncertainties. KUH thus enables models of aggregate outcomes that 1) are premised on market participantsi?½ rationality, and 2) accord a role to both fundamental and psychological (and other non-fundamental) factors in driving outcomes. The paper also suggests how a KUH modeli?½s quantitative predictions can be confronted with time-series data.\",\"PeriodicalId\":299310,\"journal\":{\"name\":\"Econometrics: Mathematical Methods & Programming eJournal\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometrics: Mathematical Methods & Programming eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3341203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Mathematical Methods & Programming eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3341203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Knightian Uncertainty Hypothesis: Unforeseeable Change and Muth’s Consistency Constraint in Modeling Aggregate Outcomes
This paper proposes the Knightian Uncertainty Hypothesis (KUH), a new approach to macroeconomics and finance theory. KUH rests on a novel mathematical framework that characterizes both measurable and Knightian uncertainty about economic outcomes. Relying on this framework and Muthi?½s pathbreaking hypothesis, KUH represents participantsi?½ forecasts to be consistent with both uncertainties. KUH thus enables models of aggregate outcomes that 1) are premised on market participantsi?½ rationality, and 2) accord a role to both fundamental and psychological (and other non-fundamental) factors in driving outcomes. The paper also suggests how a KUH modeli?½s quantitative predictions can be confronted with time-series data.