<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>Science and Education Publishing</publisher>
<journalTitle>American Journal of Applied Mathematics and Statistics</journalTitle>
<eissn>2328-7292</eissn>
<publicationDate>2018-07-19</publicationDate>
<volume>6</volume>
<issue>4</issue>
<startPage>121</startPage>
<endPage>125</endPage>
<doi>10.12691/ajams-6-4-1</doi>
<publisherRecordId>AJAMS2018641</publisherRecordId>
<documentType>article</documentType>
<title language="eng">Why Segregating Cointegration Test?</title>
<authors>
<author>
<name>Alayande Semiu Ayinla</name>
<email>alayandesa@run.edu.ng</email>
<affiliationId>1</affiliationId>
</author>
</authors>
<affiliationsList>
<affiliationName affiliationId="1">Department of Mathematical Sciences, College of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria</affiliationName>

</affiliationsList>
<abstract language="eng">This paper resolves the conflicts that exist between various cointegration tests for cases when different tests for cointegration provide different answers under the same data set. The tests considered are, Augumented Dickey Fuller (ADF) test, Hansen Lc test, Johansen's test, and Stock and Watson (SW) test. The Monte Carlo experiments conducted show that the Stock Watson and Johansen tests can be grouped together while ADF test significantly shows different performances from that of Hansen Lc test.</abstract>
<fullTextUrl format="pdf">http://pubs.sciepub.com/ajams/6/4/1/ajams-6-4-1.pdf</fullTextUrl>
<keywords language="eng"><keyword>unit root</keyword>
<keyword>cointegation</keyword>
</keywords>
</record>
</records>
