{"title":"宏观计量经济建模的普通业务:美联储-麻省理工学院-宾夕法尼亚大学模型的研究(1964-1974)","authors":"R. Backhouse, Béatrice Cherrier","doi":"10.2139/ssrn.3266559","DOIUrl":null,"url":null,"abstract":"The FMP model exemplifies the Keynesian models later criticized by Lucas, Sargent and others as conceptually flawed. For economists in the 1960s such models were “big science”, posing organizational as well as theoretical and empirical problems. It was part of an even larger industry in which the messiness for which such models were later criticized was endorsed as providing enabling modelers to be guided by data and as offering the flexibility needed to undertake policy analysis and to analyze the consequences of events. Practices that critics considered fatal weaknesses, such as intercept adjustments or fudging, were what clients were what clients paid for as the macroeconometric modeling industry went private.","PeriodicalId":330048,"journal":{"name":"Macroeconomics: Aggregative Models eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"The Ordinary Business of Macroeconometric Modeling: Working on the Fed-MIT-Penn Model (1964–1974)\",\"authors\":\"R. Backhouse, Béatrice Cherrier\",\"doi\":\"10.2139/ssrn.3266559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The FMP model exemplifies the Keynesian models later criticized by Lucas, Sargent and others as conceptually flawed. For economists in the 1960s such models were “big science”, posing organizational as well as theoretical and empirical problems. It was part of an even larger industry in which the messiness for which such models were later criticized was endorsed as providing enabling modelers to be guided by data and as offering the flexibility needed to undertake policy analysis and to analyze the consequences of events. Practices that critics considered fatal weaknesses, such as intercept adjustments or fudging, were what clients were what clients paid for as the macroeconometric modeling industry went private.\",\"PeriodicalId\":330048,\"journal\":{\"name\":\"Macroeconomics: Aggregative Models eJournal\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Macroeconomics: Aggregative Models eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3266559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Macroeconomics: Aggregative Models eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3266559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Ordinary Business of Macroeconometric Modeling: Working on the Fed-MIT-Penn Model (1964–1974)
The FMP model exemplifies the Keynesian models later criticized by Lucas, Sargent and others as conceptually flawed. For economists in the 1960s such models were “big science”, posing organizational as well as theoretical and empirical problems. It was part of an even larger industry in which the messiness for which such models were later criticized was endorsed as providing enabling modelers to be guided by data and as offering the flexibility needed to undertake policy analysis and to analyze the consequences of events. Practices that critics considered fatal weaknesses, such as intercept adjustments or fudging, were what clients were what clients paid for as the macroeconometric modeling industry went private.