A Nonparametric Measure of Convergence Toward Purchasing Power Parity

Mototsugu Shintani

No 219, Vanderbilt University Department of Economics Working Papers from Vanderbilt University Department of Economics

Abstract: It has been claimed that the deviations from purchasing power parity are highly persistent and have quite long half-lives under the assumption of a linear adjustment of real exchange rates. However, inspired by trade cost models, nonlinear adjustment has been widely employed in recent empirical studies. This paper proposes a simple nonparametric procedure for evaluating the speed of adjustment in the presence of nonlinearity, using the largest Lyapunov exponent of the time series. The empirical result suggests that the speed of convergence to a long-run price level is indeed faster than what was found in previous studies with linear restrictions.

Keywords: Mean reversion, nonlinear time series, nonparametric regression, purchasing power parity puzzle; Real exchange rates (search for similar items in EconPapers)
JEL-codes: C14 C22 F31 (search for similar items in EconPapers)
Date: 2002-08, Revised 2004-07
New Economics Papers: this item is included in nep-ecm and nep-ifn
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.accessecon.com/pubs/VUECON/vu02-w19R.pdf Revised version, 2004 (application/pdf)

Related works:
Journal Article: A nonparametric measure of convergence towards purchasing power parity (2006)
Working Paper: A Nonparametric Measure of Convergence Toward Purchasing Power Parity (2003)
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:van:wpaper:0219

Access Statistics for this paper

More papers in Vanderbilt University Department of Economics Working Papers from Vanderbilt University Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by John P. Conley ().