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Cited by 199

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Convergence of Prices and Rates of Inflation*

Busetti, Fabio, Fabiani, Silvia, Harvey, Andrew·2006·Oxford Bulletin of Economics and Statistics

Abstract

We consider how unit‐root and stationarity tests can be used to study the convergence of prices and rates of inflation. We show how the joint use of these tests in levels and first differences allows the researcher to distinguish between series that are converging and series that have already converged, and we set out a strategy to establish whether convergence occurs in relative prices or just in rates of inflation. Special attention is paid to the issue of whether a mean should be extracted in carrying out tests in first differences and whether there is an advantage to adopting a (Dickey–Fuller) unit‐root test based on deviations from the last observation. The asymptotic distribution of this last test statistic is given and Monte Carlo simulation experiments show that the test yields considerable power gains for highly persistent autoregressive processes with ‘relatively large’ initial conditions. The tests are applied to the monthly series of the consumer price index in the Italian regional capitals over the period 1970–2003.

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Metadata

Authors
Busetti, F., Fabiani, S., & Harvey, A.
Venue
Oxford Bulletin of Economics and Statistics
Publisher
Wiley
Published
2006-11-23
Volume
68
Issue
s1
Pages
863-877
ISSN
  • 0305-9049 (ISSN-L)
  • 1468-0084
OpenAlex
W3122518303
Cited by
199
References
2
FWCI
83.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Convergence of Prices and Rates of Inflation*. https://app.cochat.ai/papers/10.1111/j.1468-0084.2006.00460.x
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Busetti, F., Fabiani, S., & Harvey, A. (2006). Convergence of Prices and Rates of Inflation*. Oxford Bulletin of Economics and Statistics. https://doi.org/10.1111/j.1468-0084.2006.00460.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.