{"title":"非协整变量的误差修正模型与回归","authors":"Moawia Alghalith","doi":"10.2139/ssrn.3902889","DOIUrl":null,"url":null,"abstract":"We introduce valid regression models and valid error correction models for the non-cointegrated variables. These models are also valid for the cointegrated variables. Consequently, cointegration tests and analysis become needless. Furthermore, our approach overcomes the lag selection problem.","PeriodicalId":320844,"journal":{"name":"PSN: Econometrics","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Error Correction Models and Regressions for Non-Cointegrated Variables\",\"authors\":\"Moawia Alghalith\",\"doi\":\"10.2139/ssrn.3902889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce valid regression models and valid error correction models for the non-cointegrated variables. These models are also valid for the cointegrated variables. Consequently, cointegration tests and analysis become needless. Furthermore, our approach overcomes the lag selection problem.\",\"PeriodicalId\":320844,\"journal\":{\"name\":\"PSN: Econometrics\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PSN: Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3902889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PSN: Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3902889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Error Correction Models and Regressions for Non-Cointegrated Variables
We introduce valid regression models and valid error correction models for the non-cointegrated variables. These models are also valid for the cointegrated variables. Consequently, cointegration tests and analysis become needless. Furthermore, our approach overcomes the lag selection problem.
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