{"title":"一个统一的单位根测试不管截距","authors":"Bingduo Yang, Xiaohui Liu, Wei Long, Liang Peng","doi":"10.1080/07474938.2023.2217077","DOIUrl":null,"url":null,"abstract":"Abstract Using the augmented Dickey-Fuller test to verify the existence of a unit root in an autoregressive process often requires the correctly specified intercept, since the test statistics can be distinctive under different model specifications and lead to contradictory results at times. In this article, we develop a unified inference that not only unifies the specifications of the intercept but also accommodates different degrees of persistence of the underlying process and heteroscedastic errors. A simulation study shows that the resulting unified unit root test exhibits excellent size control and reasonably good power. In an empirical application, we implement the proposed test to re-examine the presence of unit roots within eleven widely used variables in stock return predictability.","PeriodicalId":11438,"journal":{"name":"Econometric Reviews","volume":"42 1","pages":"540 - 555"},"PeriodicalIF":0.8000,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A unified unit root test regardless of intercept\",\"authors\":\"Bingduo Yang, Xiaohui Liu, Wei Long, Liang Peng\",\"doi\":\"10.1080/07474938.2023.2217077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Using the augmented Dickey-Fuller test to verify the existence of a unit root in an autoregressive process often requires the correctly specified intercept, since the test statistics can be distinctive under different model specifications and lead to contradictory results at times. In this article, we develop a unified inference that not only unifies the specifications of the intercept but also accommodates different degrees of persistence of the underlying process and heteroscedastic errors. A simulation study shows that the resulting unified unit root test exhibits excellent size control and reasonably good power. In an empirical application, we implement the proposed test to re-examine the presence of unit roots within eleven widely used variables in stock return predictability.\",\"PeriodicalId\":11438,\"journal\":{\"name\":\"Econometric Reviews\",\"volume\":\"42 1\",\"pages\":\"540 - 555\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometric Reviews\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/07474938.2023.2217077\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometric Reviews","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/07474938.2023.2217077","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
Abstract Using the augmented Dickey-Fuller test to verify the existence of a unit root in an autoregressive process often requires the correctly specified intercept, since the test statistics can be distinctive under different model specifications and lead to contradictory results at times. In this article, we develop a unified inference that not only unifies the specifications of the intercept but also accommodates different degrees of persistence of the underlying process and heteroscedastic errors. A simulation study shows that the resulting unified unit root test exhibits excellent size control and reasonably good power. In an empirical application, we implement the proposed test to re-examine the presence of unit roots within eleven widely used variables in stock return predictability.
期刊介绍:
Econometric Reviews is widely regarded as one of the top 5 core journals in econometrics. It probes the limits of econometric knowledge, featuring regular, state-of-the-art single blind refereed articles and book reviews. ER has been consistently the leader and innovator in its acclaimed retrospective and critical surveys and interchanges on current or developing topics. Special issues of the journal are developed by a world-renowned editorial board. These bring together leading experts from econometrics and beyond. Reviews of books and software are also within the scope of the journal. Its content is expressly intended to reach beyond econometrics and advanced empirical economics, to statistics and other social sciences.