Testing Growth Convergence with Time Series Data— a non-parametric approach

Mikael Linden

International Review of Applied Economics, 2000, vol. 14, issue 3, 361-370

Abstract: A non-parametric time series testing is suggested to analyse the convergence of international output per-capita gaps. Non-parametric tests are based on signs and ranks of time series properties of output differences. The methods are applied to logs of USA percapita income differences for 16 OECD countries from 1900-97. In contrast to the results obtained by Bernard & Durlauf (1995) for the period 1900-87, convergence of output gaps was evident for the majority of countries. However, the trends in 1970-97 and 1987-97 are noticeably more complicated than the homogeneous convergence found in the pre-1970 period. The results indicate that widening USA gaps are now more likely to emerge than steady-state or narrowing gaps.

Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02692170050084088 (text/html)
Access to full text is restricted to subscribers.

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:taf:irapec:v:14:y:2000:i:3:p:361-370

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CIRA20

DOI: 10.1080/02692170050084088

Access Statistics for this article

International Review of Applied Economics is currently edited by Professor Malcolm Sawyer

More articles in International Review of Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().