{"title":"Testing for the cointegration rank in threshold cointegrated systems with multiple cointegrating relationships","authors":"Jaya Krishnakumar, David Neto","doi":"10.1016/j.stamet.2015.04.001","DOIUrl":null,"url":null,"abstract":"<div><p>This paper is concerned with the estimation and inference for a threshold VECM with more than one cointegrating relation thus extending the literature in this context which has mostly considered only one cointegrating relationship so far. We then go on to develop an appropriate test for the number of cointegrating relationships in a threshold VECM. Asymptotic distributions of our test statistics are derived and tabulated. Finite sample performance of the proposed testing procedure is investigated.</p></div>","PeriodicalId":48877,"journal":{"name":"Statistical Methodology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.stamet.2015.04.001","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Methodology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1572312715000301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 4
Abstract
This paper is concerned with the estimation and inference for a threshold VECM with more than one cointegrating relation thus extending the literature in this context which has mostly considered only one cointegrating relationship so far. We then go on to develop an appropriate test for the number of cointegrating relationships in a threshold VECM. Asymptotic distributions of our test statistics are derived and tabulated. Finite sample performance of the proposed testing procedure is investigated.
期刊介绍：
Statistical Methodology aims to publish articles of high quality reflecting the varied facets of contemporary statistical theory as well as of significant applications. In addition to helping to stimulate research, the journal intends to bring about interactions among statisticians and scientists in other disciplines broadly interested in statistical methodology. The journal focuses on traditional areas such as statistical inference, multivariate analysis, design of experiments, sampling theory, regression analysis, re-sampling methods, time series, nonparametric statistics, etc., and also gives special emphasis to established as well as emerging applied areas.
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