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Temporal Aggregation and Purchasing Power Parity Persistence

Yamin Ahmad and William Craighead

No 2011-001, Wesleyan Economics Working Papers from Wesleyan University, Department of Economics

Abstract: This paper uses a unique new monthly US-UK real exchange rate series for the January 1794 – December 2009 period to reexamine the academic debate over purchasing power parity (PPP). The consensus view described by Rogoff (1996) is that PPP holds in the long-run, but short run deviations are very persistent, with half-lives ranging from 3-5 years. Most of the literature using long time series relies on the annual data developed by Lee (1976) and Lothian and Taylor (1996), which were both constructed from underlying higher-frequency data sources. Estimates of purchasing power parity persistence using these series may therefore be subject to temporal aggregation bias. We find evidence of aggregation bias which indicates the half-life of PPP deviations has been overestimated in much of the previous literature. We also find that estimates of the half-lives under temporal aggregation are further reduced once we account for the Harrod (1933)-Balassa (1964) - Samuelson (1964) effect. The result of aggregation bias appears to be robust even when considering the case that real exchange rates exhibit nonlinear dynamics.

Keywords: Temporal Aggregation; Real Exchange Rates; Purchasing Power Parity; Exchange Rate Persistence; Half-Lives (search for similar items in EconPapers)
JEL-codes: F31 C22 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2011-02
New Economics Papers: this item is included in nep-cba and nep-opm
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Citations: View citations in EconPapers (18) Track citations by RSS feed

Published in the Journal of International Money and Finance, 30:5 (September 2011), 817-830

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http://dx.doi.org/10.1016/j.jimonfin.2011.05.008
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Journal Article: Temporal aggregation and purchasing power parity persistence (2011) Downloads
Working Paper: Temporal Aggregation and Purchasing Power Parity Persistence (2011) Downloads
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