{"title":"A Panel Unit-Root Test with Smooth Breaks and Cross-Sectional Dependence","authors":"Chingnun Lee, Jyh‐Lin Wu","doi":"10.2139/ssrn.2039620","DOIUrl":null,"url":null,"abstract":"This paper develops a simple panel unit-root test that accommodates cross-sectional dependence among variables and smooth structural changes in deterministic components. The proposed test is the simple average of the individual statistics constructed from the breaks and cross-sectional dependence augmented Dickey-Fuller (BCADF) regression. Applying the sequential limit approach, this paper shows that the asymptotic distribution of the BCADF statistic is free of nuisance parameters as N, T go to infinity. We also extend our analysis to the case where shocks are serially correlated. The limiting distribution of the average BCADF statistic is shown to exist and its critical values are tabulated. Monte-Carlo experiments point out that the size and power of the average BCADF statistic are generally good as long as T is greater than fifty. The test is then applied to examine the validity of long-run purchasing power parity.","PeriodicalId":425229,"journal":{"name":"ERN: Hypothesis Testing (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Hypothesis Testing (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2039620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper develops a simple panel unit-root test that accommodates cross-sectional dependence among variables and smooth structural changes in deterministic components. The proposed test is the simple average of the individual statistics constructed from the breaks and cross-sectional dependence augmented Dickey-Fuller (BCADF) regression. Applying the sequential limit approach, this paper shows that the asymptotic distribution of the BCADF statistic is free of nuisance parameters as N, T go to infinity. We also extend our analysis to the case where shocks are serially correlated. The limiting distribution of the average BCADF statistic is shown to exist and its critical values are tabulated. Monte-Carlo experiments point out that the size and power of the average BCADF statistic are generally good as long as T is greater than fifty. The test is then applied to examine the validity of long-run purchasing power parity.