Spectral Analysis of Time Series with Rhythmic Structure

1999 ◽  
Vol 31 (1-3) ◽  
pp. 100-107
Author(s):  
I. N. Yavorskiy ◽  
I. Yu. Isaev
2016 ◽  
Vol 95 ◽  
pp. 99-104 ◽  
Author(s):  
Eulogio Pardo-Igúzquiza ◽  
Francisco J. Rodríguez-Tovar ◽  
Javier Dorador

2017 ◽  
Vol 2 (1) ◽  
pp. 32-42
Author(s):  
Vasile-Aurel Caus ◽  
Daniel Badulescu ◽  
Mircea Cristian Gherman

In the last decades, more and more approaches of economic issues have used mathematical tools, and among the most recent ones, spectral and wavelet methods are to be distinguished. If in the case of spectral analysis the approaches and results are sufficiently clear, while the use of wavelet decomposition, especially in the analysis of time series, is not fully valorized. The purpose of this paper is to emphasize how these methods are useful for time series analysis. After theoretical considerations on Fourier transforms versus wavelet transforms, we have presented the methodology we have used and the results obtained by using wavelets in the analysis of wage-price relation, based on some empirical data. The data we have used is concerning the Romanian economy - the inflation and the average nominal wage denominated in US dollars, between January 1991 and May 2016, highlighting that the relation between nominal salary and prices can be revealed more accurately by use of wavelets


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