A sequential panel selection approach to cointegration analysis: An application to Wagner’s law for South Africa

Xolisa Vayi () and Andrew Phiri
Additional contact information
Xolisa Vayi: Department of Economics, Nelson Mandela University

No 1831, Working Papers from Department of Economics, Nelson Mandela University

Abstract: This study extends the recently introduced sequential panel selection method (SPSM) to a cointegration framework which is particularly used to investigate Wagner’s law for 9 South African provinces between 2001 and 2016. We note that when applying single country/region estimates we fail to find evidence of cointegration whereas within panel regressions, cointegration effects are present for the entire dataset. In further applying the SPSM we observed significant Wagner’s effects for panels inclusive of Gauteng, Eastern Cape and Kwazulu-Natal provinces and when these provinces are excluded from the panels, cointegration effects are unobserved.

Keywords: Sequential Panel selection method (SPSM); cointegration; Wagner’s law; Provincial analysis; South Africa. (search for similar items in EconPapers)
JEL-codes: C22 C23 C52 H70 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2018-09
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://repec.mandela.ac.za/RePEc/mnd/wpaper/paper.1831.pdf First version, 2018 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Internal Server Error

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mnd:wpaper:1831

Access Statistics for this paper

More papers in Working Papers from Department of Economics, Nelson Mandela University Contact information at EDIRC.
Bibliographic data for series maintained by Andrew Phiri ().