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Money growth and consumer price inflation in the euro area: A wavelet analysis

Citations

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Cited by:

  1. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," NIPE Working Papers 04/2019, NIPE - Universidade do Minho.
  2. Alexander Jung, 2018. "Have money and credit data releases helped markets to predict the interest rate decisions of the European Central Bank?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(1), pages 39-67, February.
  3. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2020. "Okun’s Law across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
  4. Yaqi Wu & Chen Zhang & Po Yun & Dandan Zhu & Wei Cao & Zulfiqar Ali Wagan, 2021. "Time–frequency analysis of the interaction mechanism between European carbon and crude oil markets," Energy & Environment, , vol. 32(7), pages 1331-1357, November.
  5. Gallegati, Marco & Giri, Federico & Fratianni, Michele, 2019. "Money growth and inflation: International historical evidence on high inflation episodes for developed countries," Bank of Finland Research Discussion Papers 1/2019, Bank of Finland.
  6. Antony, Jürgen & Klarl, Torben, 2020. "Estimating the income inequality-health relationship for the United States between 1941 and 2015: Will the relevant frequencies please stand up?," The Journal of the Economics of Ageing, Elsevier, vol. 17(C).
  7. Aguiar-Conraria, Luis & Martins, Manuel M.F. & Soares, Maria Joana, 2018. "Estimating the Taylor rule in the time-frequency domain," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 122-137.
  8. repec:zbw:bofrdp:2019_012 is not listed on IDEAS
  9. Ramin Khochiani & Younes Nademi, 2020. "Energy consumption, CO2 emissions, and economic growth in the United States, China, and India: A wavelet coherence approach," Energy & Environment, , vol. 31(5), pages 886-902, August.
  10. Scharnagl, Michael & Mandler, Martin, 2015. "The relationship of simple sum and Divisia monetary aggregates with real GDP and inflation: a wavelet analysis for the US," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112879, Verein für Socialpolitik / German Economic Association.
  11. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.
  12. Ha, Le Thanh, 2024. "Dynamic spill-over influences of FinTech innovation development on renewable energy volatility during the time of war in pandemic: A novel insight from a wavelet model," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 515-529.
  13. Bašta, Milan & Molnár, Peter, 2018. "Oil market volatility and stock market volatility," Finance Research Letters, Elsevier, vol. 26(C), pages 204-214.
  14. Patrick M. Crowley & Andrew Hughes Hallett, 2021. "The Evolution of US and UK Real GDP Components in the Time-Frequency Domain: A Continuous Wavelet Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 233-261, December.
  15. Luís Aguiar-Conraria & Maria Joana Soares & Rita Sousa, 2017. "California´s Carbon Market and Energy Prices: A Wavelet Analysis," NIPE Working Papers 13/2017, NIPE - Universidade do Minho.
  16. Fratianni, Michele & Gallegati, Marco & Giri, Federico, 2022. "The medium-run Phillips curve: A time–frequency investigation for the UK," Journal of Macroeconomics, Elsevier, vol. 73(C).
  17. Xie, Henglang & Bui, Wency Kher Thinng, 2024. "Impact of globalization and energy consumption on CO2 emissions in China: Implications for energy transition," Finance Research Letters, Elsevier, vol. 67(PB).
  18. Flor, Michael A. & Klarl, Torben, 2017. "On the cyclicity of regional house prices: New evidence for U.S. metropolitan statistical areas," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 134-156.
  19. repec:zbw:bofrdp:2019_001 is not listed on IDEAS
  20. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2023. "The Phillips curve at 65: Time for time and frequency," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
  21. Jung, Alexander, 2016. "Have monetary data releases helped markets to predict the interest rate decisions of the European Central Bank?," Working Paper Series 1926, European Central Bank.
  22. Amine Ben Amar & Jean‐Étienne Carlotti, 2021. "Who drives the dance? Further insights from a time‐frequency wavelet analysis of the interrelationship between stock markets and uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1623-1636, January.
  23. Rünstler, Gerhard & Balfoussia, Hiona & Burlon, Lorenzo & Buss, Ginters & Comunale, Mariarosaria & De Backer, Bruno & Dewachter, Hans & Guarda, Paolo & Haavio, Markus & Hindrayanto, Irma & Iskrev, Nik, 2018. "Real and financial cycles in EU countries - Stylised facts and modelling implications," Occasional Paper Series 205, European Central Bank.
  24. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," CEF.UP Working Papers 1902, Universidade do Porto, Faculdade de Economia do Porto.
  25. Andreani, Michele & Giri, Federico, 2024. "Mortgages, house prices, and business cycle dynamic: A medium-run exploration using the continuous wavelet transform," International Review of Economics & Finance, Elsevier, vol. 94(C).
  26. Marcin Koltuniak, 2016. "Examination of the directions of spillover effects between the real estate and stock prices in Poland using wavelet analysis," Bank i Kredyt, Narodowy Bank Polski, vol. 47(3), pages 251-266.
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