A note on the estimation of long-run relationships in panel equations with cross-section linkages

Francesca Di Iorio and Stefano Fachin

Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), 2012, vol. 6, No 2012-20, 18 pages

Abstract: The authors address the issue of estimation and inference in dependent non-stationary panels of small cross-section dimensions. The main conclusion is that the best results are obtained applying bootstrap inference to single-equation estimators, such as fully modified ordinary least squares and dynamic ordinary least squares. Seemingly unrelated regression estimators perform badly, or are even unfeasible, when the time dimension is not very large compared to the cross-section dimension.

Keywords: panel cointegration; fully modified ordinary least squares; fully modified seemingly unrelated regression; dynamic ordinary least squares; dynamic seemingly unrelated regression (search for similar items in EconPapers)
JEL-codes: C15 C23 C33 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://dx.doi.org/10.5018/economics-ejournal.ja.2012-20
https://www.econstor.eu/bitstream/10419/59035/1/717296768.pdf (application/pdf)

Related works:
Working Paper: A note on the estimation of long-run relationships in panel equations with cross-section linkages (2012)
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:zbw:ifweej:201220

DOI: 10.5018/economics-ejournal.ja.2012-20

Access Statistics for this article

Economics - The Open-Access, Open-Assessment E-Journal (2007-2020) is currently edited by Dennis J. Snower

More articles in Economics - The Open-Access, Open-Assessment E-Journal (2007-2020) from Kiel Institute for the World Economy (IfW Kiel) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().