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Money growth and inflation in the euro area: a time-frequency view

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Cited by:

  1. Khalfaoui, Rabeh & Padhan, Hemachandra & Tiwari, Aviral Kumar & Hammoudeh, Shawkat, 2020. "Understanding the time-frequency dynamics of money demand, oil prices and macroeconomic variables: The case of India," Resources Policy, Elsevier, vol. 68(C).
  2. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
  3. Verona, Fabio, 2016. "Time–frequency characterization of the U.S. financial cycle," Economics Letters, Elsevier, vol. 144(C), pages 75-79.
  4. Turgut TURSOY & Muhammad MAR’I, 2020. "Lead-Lag And Relationship Between Money Growth And Inflation In Turkey: New Evidence From A Wavelet Analysis," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 11(1), pages 47-57.
  5. Patrick M. Crowley & David Hudgins, 2022. "Monetary policy objectives and economic outcomes: What can we learn from a wavelet‐based optimal control approach?," Manchester School, University of Manchester, vol. 90(2), pages 144-170, March.
  6. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
  7. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
  8. Jiang, Chun & Chang, Tsangyao & Li, Xiao-Lin, 2015. "Money growth and inflation in China: New evidence from a wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 249-261.
  9. Funashima, Yoshito, 2017. "Time-varying leads and lags across frequencies using a continuous wavelet transform approach," Economic Modelling, Elsevier, vol. 60(C), pages 24-28.
  10. 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.
  11. Funashima, Yoshito, 2016. "The Fed-induced political business cycle: Empirical evidence from a time–frequency view," Economic Modelling, Elsevier, vol. 54(C), pages 402-411.
  12. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
  13. Lin, Fu-Lai & Chen, Yu-Fen & Yang, Sheng-Yung, 2016. "Does the value of US dollar matter with the price of oil and gold? A dynamic analysis from time–frequency space," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 59-71.
  14. Funashima, Yoshito, 2015. "Automatic stabilizers in the Japanese tax system," Journal of Asian Economics, Elsevier, vol. 39(C), pages 86-93.
  15. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.
  16. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
  17. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
  18. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
  19. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
  20. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
  21. Funashima, Yoshito, 2016. "Governmentally amplified output volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 469-478.
  22. Yingying Xu & Zhixin Liu & Jichang Zhao & Chiwei Su, 2017. "Weibo sentiments and stock return: A time-frequency view," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-21, July.
  23. 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.
  24. Jun‐Hyung Ko & Yoshito Funashima, 2019. "On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 889-910, August.
  25. Crowley, Patrick M. & Hallett, Andrew Hughes, 2018. "What causes business cycles to elongate, or recessions to intensify?," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 338-349.
  26. Villa-Loaiza, Carlos & Taype-Huaman, Irvin & Benavides-Franco, Julián & Buenaventura-Vera, Guillermo & Carabalí-Mosquera, Jaime, 2023. "Does climate impact the relationship between the energy price and the stock market? The Colombian case," Applied Energy, Elsevier, vol. 336(C).
  27. repec:zbw:bofrdp:2019_001 is not listed on IDEAS
  28. Funashima, Yoshito, 2015. "The Fed-Induced Political Business Cycle," MPRA Paper 63654, University Library of Munich, Germany.
  29. Fathi Abid & Bilel Kaffel, 2018. "The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 561-590, February.
  30. Yoshito Funashima, 2018. "Macroeconomic policy coordination between Japanese central and local governments," Empirical Economics, Springer, vol. 54(4), pages 1631-1651, June.
  31. Thomas Conlon & Brian M. Lucey & Gazi Salah Uddin, 2018. "Is gold a hedge against inflation? A wavelet time-scale perspective," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 317-345, August.
  32. Funashima, Yoshito, 2014. "Macroeconomic policy coordination between Japanese central and local governments," MPRA Paper 59821, University Library of Munich, Germany.
  33. Alessandro Pietropaoli, 2025. "Income distribution and growth in France: a long-run time-frequency analysis," Temi di discussione (Economic working papers) 1483, Bank of Italy, Economic Research and International Relations Area.
  34. Xu, Yingying, 2020. "Will energy transitions impact financial systems?," Energy, Elsevier, vol. 194(C).
  35. Luís Aguiar-Conraria & Pedro Magalhães & Maria Soares, 2013. "The nationalization of electoral cycles in the United States: a wavelet analysis," Public Choice, Springer, vol. 156(3), pages 387-408, September.
  36. Maciej Ryczkowski, 2021. "Money and inflation in inflation-targeting regimes – new evidence from time–frequency analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 17-44, January.
  37. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
  38. Maciej Ryczkowski, 2020. "Money and credit during normal times and house price booms: evidence from time-frequency analysis," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 835-861, November.
  39. repec:zbw:bofrdp:2016_014 is not listed on IDEAS
  40. Caraiani, Petre, 2015. "Estimating DSGE models across time and frequency," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 33-49.
  41. Portugal, Pedro & Rua, António, 2020. "How the ins and outs shape differently the U.S. unemployment over time and across frequencies," European Economic Review, Elsevier, vol. 121(C).
  42. Berdiev, Aziz N. & Chang, Chun-Ping, 2015. "Business cycle synchronization in Asia-Pacific: New evidence from wavelet analysis," Journal of Asian Economics, Elsevier, vol. 37(C), pages 20-33.
  43. Verona, Fabio, 2016. "Time–frequency characterization of the U.S. financial cycle," Economics Letters, Elsevier, vol. 144(C), pages 75-79.
  44. Aissa Djedaiet & Hassan Guenichi & Hicham Ayad, 2024. "Do asymmetric oil shocks impact gold and Bitcoin returns symmetrically? A comparison between the COVID-19 pandemic and the Russo-Ukrainian war," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(4), pages 1187-1213, December.
  45. Gallegati, Marco & Ramsey, James B. & Semmler, Willi, 2014. "Interest rate spreads and output: A time scale decomposition analysis using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 283-290.
  46. Rai, Karan & Garg, Bhavesh, 2024. "Demographic transition and inflation," Economic Systems, Elsevier, vol. 48(4).
  47. Erdost Torun & Afife Duygu Ayhan Akdeniz & Erhan Demireli & Simon Grima, 2022. "Long-Term US Economic Growth and the Carbon Dioxide Emissions Nexus: A Wavelet-Based Approach," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
  48. Al Rababa’a, Abdel Razzaq & Alomari, Mohammad & McMillan, David, 2021. "Multiscale stock-bond correlation: Implications for risk management," Research in International Business and Finance, Elsevier, vol. 58(C).
  49. Funashima, Yoshito, 2015. "Wagner's law versus displacement effect," MPRA Paper 68390, University Library of Munich, Germany.
  50. Cheng-Feng Wu & Fangjhy Li & Hsin-Pei Hsueh & Chien-Ming Wang & Meng-Chen Lin & Tsangyao Chang, 2020. "A Dynamic Relationship between Environmental Degradation, Healthcare Expenditure and Economic Growth in Wavelet Analysis: Empirical Evidence from Taiwan," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
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