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Using wavelets to decompose the time–frequency effects of monetary policy

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  • Aguiar-Conraria, Luís
  • Azevedo, Nuno
  • Soares, Maria Joana

Abstract

Central banks have different objectives in the short and long run. Governments operate simultaneously at different timescales. Many economic processes are the result of the actions of several agents, who have different term objectives. Therefore, a macroeconomic time series is a combination of components operating on different frequencies. Several questions about economic time series are connected to the understanding of the behavior of key variables at different frequencies over time, but this type of information is difficult to uncover using pure time-domain or pure frequency-domain methods.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 387 (2008)
Issue (Month): 12 ()
Pages: 2863-2878

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Handle: RePEc:eee:phsmap:v:387:y:2008:i:12:p:2863-2878

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Monetary policy; Time–frequency analysis; Non-stationary time series; Wavelets; Cross-wavelets; Wavelet coherency;

References

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Citations

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Cited by:
  1. Arif Dar & Amaresh Samantaraya & Firdous Shah, 2014. "The predictive power of yield spread: evidence from wavelet analysis," Empirical Economics, Springer, vol. 46(3), pages 887-901, May.
  2. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu, 2013. "The influence of the international oil prices on the real effective exchange rate in Romania in a wavelet transform framework," Energy Economics, Elsevier, vol. 40(C), pages 714-733.
  3. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2010. "The yield curve and the macro-economy across time and frequencies," CEF.UP Working Papers 1004, Universidade do Porto, Faculdade de Economia do Porto.
  4. Fernández-Macho, Javier, 2012. "Wavelet multiple correlation and cross-correlation: A multiscale analysis of Eurozone stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1097-1104.
  5. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.
  6. Lukas Vacha & Jozef Barunik, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Papers 1201.4776, arXiv.org.
  7. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2011. "Synchronization of Economic Sentiment Cycles in the Euro Area: a time-frequency analysis," CEF.UP Working Papers 1105, Universidade do Porto, Faculdade de Economia do Porto.
  8. Yung-hsiang Ying & Koyin Chang & Ginny ju-ann Yang & Chen-hsun Lee, 2014. "Measuring co-movement of globalization and democratization in the time–frequency space," Economics Bulletin, AccessEcon, vol. 34(1), pages 206-219.
  9. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.
  10. Aviral Kumar Tiwari & Suresh K.G. & Mohamed Arouri & Frédéric Teulon, 2014. "Causality between consumer price and producer price: Evidence from Mexico," Working Papers 2014-292, Department of Research, Ipag Business School.
  11. Alvarez-Ramirez, J. & Rodriguez, E. & Espinosa-Paredes, G., 2012. "A partisan effect in the efficiency of the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4923-4932.
  12. Zied Ftiti & Aviral Tiwari & Amél Belanès, 2014. "Tests of Financial Market Contagion- Evolutionary Cospectral Analysis V.S. Wavelet Analysis," Working Papers 2014-062, Department of Research, Ipag Business School.
  13. Tiwari, Aviral Kumar & Oros, Cornel & Albulescu, Claudiu Tiberiu, 2014. "Revisiting the inflation–output gap relationship for France using a wavelet transform approach," Economic Modelling, Elsevier, vol. 37(C), pages 464-475.
  14. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
  15. Jozef BARUNÍK & Lukáš VÁCHA, 2013. "Contagion among Central and Eastern European Stock Markets during the Financial Crisis," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 443-453, November.

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