{"title":"Unit-root tests for explosive behavior","authors":"Christopher F. Baum, Jesús Otero","doi":"10.1177/1536867X211063405","DOIUrl":null,"url":null,"abstract":"We present a new command, radf, that tests for explosive behavior in time series. The command computes the right-tail augmented Dickey and Fuller (1979, Journal of the American Statistical Association 74: 427–431) unitroot test and its further developments based on supremum statistics derived from augmented Dickey–Fuller-type regressions estimated using recursive windows (Phillips, Wu, and Yu, 2011, International Economic Review 52: 201–226) and recursive flexible windows (Phillips, Shi, and Yu, 2015, International Economic Review 56: 1043–1078). It allows for the lag length in the test regression and the width of rolling windows to be either specified by the user or determined using data-dependent procedures, and it performs the date-stamping procedures advocated by Phillips, Wu, and Yu (2011) and Phillips, Shi, and Yu (2015) to identify episodes of explosive behavior. It also implements the wild bootstrap proposed by Phillips and Shi (2020, Handbook of Statistics: Financial, Macro and Micro Econometrics Using R, Vol. 42, 61–80) to lessen the potential effects of unconditional heteroskedasticity and account for the multiplicity issue in recursive testing. The use of radf is illustrated with an empirical example.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"21 1","pages":"999 - 1020"},"PeriodicalIF":3.2000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X211063405","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 5
Abstract
We present a new command, radf, that tests for explosive behavior in time series. The command computes the right-tail augmented Dickey and Fuller (1979, Journal of the American Statistical Association 74: 427–431) unitroot test and its further developments based on supremum statistics derived from augmented Dickey–Fuller-type regressions estimated using recursive windows (Phillips, Wu, and Yu, 2011, International Economic Review 52: 201–226) and recursive flexible windows (Phillips, Shi, and Yu, 2015, International Economic Review 56: 1043–1078). It allows for the lag length in the test regression and the width of rolling windows to be either specified by the user or determined using data-dependent procedures, and it performs the date-stamping procedures advocated by Phillips, Wu, and Yu (2011) and Phillips, Shi, and Yu (2015) to identify episodes of explosive behavior. It also implements the wild bootstrap proposed by Phillips and Shi (2020, Handbook of Statistics: Financial, Macro and Micro Econometrics Using R, Vol. 42, 61–80) to lessen the potential effects of unconditional heteroskedasticity and account for the multiplicity issue in recursive testing. The use of radf is illustrated with an empirical example.
我们提出了一个新的命令,radf,用于测试时间序列的爆炸行为。该命令计算右尾增广Dickey和Fuller (1979, Journal of American Statistical Association, 74: 427-431)单位根检验及其进一步发展,该检验基于使用递归窗口(Phillips, Wu, and Yu, 2011, International Economic Review, 52: 201-226)和递归灵活窗口(Phillips, Shi, and Yu, 2015, International Economic Review, 56: 1043-1078)估计的增广Dickey - Fuller型回归得出的最大统计量。它允许测试回归的滞后长度和滚动窗口的宽度由用户指定或使用数据依赖程序确定,并且它执行Phillips, Wu, and Yu(2011)和Phillips, Shi, and Yu(2015)倡导的日期戳程序来识别爆炸行为的情节。它还实现了Phillips和Shi (2020, Handbook of Statistics: Financial, Macro and Micro Econometrics Using R, Vol. 42, 61-80)提出的野bootstrap,以减少无条件异方差的潜在影响,并解释递归检验中的多重性问题。通过一个实例说明了radf的应用。
期刊介绍:
The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.