{"title":"论间接噪声经济数据的计量经济信息恢复与推断","authors":"G. Judge","doi":"10.2139/ssrn.2122592","DOIUrl":null,"url":null,"abstract":"The focus of this paper is on starting a critical discussion on the state of econometrics. The problem of information recovery in economics is discussed, and information theoretic methods are suggested as an estimation and inference framework for analyzing questions of a causal nature and learning about hidden dynamic micro and macro processes and systems, that may not be in equilibrium.","PeriodicalId":163739,"journal":{"name":"ERN: Model Construction & Selection (Topic)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comment on Econometric Information Recovery and Inference from Indirect Noisy Economic Data\",\"authors\":\"G. Judge\",\"doi\":\"10.2139/ssrn.2122592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The focus of this paper is on starting a critical discussion on the state of econometrics. The problem of information recovery in economics is discussed, and information theoretic methods are suggested as an estimation and inference framework for analyzing questions of a causal nature and learning about hidden dynamic micro and macro processes and systems, that may not be in equilibrium.\",\"PeriodicalId\":163739,\"journal\":{\"name\":\"ERN: Model Construction & Selection (Topic)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Model Construction & Selection (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2122592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Model Construction & Selection (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2122592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comment on Econometric Information Recovery and Inference from Indirect Noisy Economic Data
The focus of this paper is on starting a critical discussion on the state of econometrics. The problem of information recovery in economics is discussed, and information theoretic methods are suggested as an estimation and inference framework for analyzing questions of a causal nature and learning about hidden dynamic micro and macro processes and systems, that may not be in equilibrium.