Using Wavelets to Analyse the Dynamics of Inflation Processes

Mikhail Starichkov ()
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Mikhail Starichkov: Bank of Russia

Russian Journal of Money and Finance, 2025, vol. 84, issue 1, 105-128

Abstract: This paper proposes the use of wavelet analysis as an additional tool for studying inflation data. The corresponding mathematical apparatus is actively used in various fields and has proven effective for working with non-stationary signals due to its informativeness, clarity, and adaptability to the study of local features. Wavelets scan the observed series in a two-dimensional space in frequency and time, allowing to determine how significantly and at what specific moment certain groups of frequency components manifest themselves and when significant changes in data behaviour occur. This enables a multiscale analysis of the dynamics of the process under study. This is particularly relevant because, while jumps in data are usually very noticeable, interactions of events on small scales that develop into large-scale phenomena are much more difficult to detect. Conversely, focusing only on small details may result in missing phenomena occurring at the global level.

Keywords: wavelet; Mallat algorithm; detail and approximation coefficients; inflation; consumer price index; breakdown points (search for similar items in EconPapers)
JEL-codes: C02 C65 E31 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:84:y:2025:i:1:p:105-128

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