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Interactions between financial stress and economic activity for the U.S.: A time- and frequency-varying analysis using wavelets

Author

Listed:
  • Ferrer, Román
  • Jammazi, Rania
  • Bolós, Vicente J.
  • Benítez, Rafael

Abstract

This paper examines the interactions between the main U.S. financial stress indices and several measures of economic activity in the time–frequency domain using a number of continuous cross-wavelet tools, including the usual wavelet squared coherence and phase difference as well as two new summary wavelet-based measures. The empirical results show that the relationship between financial stress and the U.S. real economy varies considerably over time and depending on the time horizon considered. A significant adverse effect of financial stress on U.S. economic activity is observed since the onset of the subprime mortgage crisis in the summer of 2007, indicating that the impact of financial market stress on the real economy is particularly severe during periods of major financial turmoil. Furthermore, the significant linkage between financial stress and the economic environment is mostly concentrated at time horizons from one to four years, demonstrating that the effect of financial stress on economic activity is especially visible in the long-run.

Suggested Citation

  • Ferrer, Román & Jammazi, Rania & Bolós, Vicente J. & Benítez, Rafael, 2018. "Interactions between financial stress and economic activity for the U.S.: A time- and frequency-varying analysis using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 446-462.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:446-462
    DOI: 10.1016/j.physa.2017.10.044
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    Cited by:

    1. Armah, Mohammed & Amewu, Godfred, 2024. "Quantile dependence and asymmetric connectedness between global financial market stress and REIT returns: Evidence from the COVID-19 pandemic," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    2. Jareño, Francisco & González, María de la O & Tolentino, Marta & Sierra, Karen, 2020. "Bitcoin and gold price returns: A quantile regression and NARDL analysis," Resources Policy, Elsevier, vol. 67(C).
    3. Václav Brož & Lukáš Pfeifer, 2021. "Are risk weights of banks in the Czech Republic procyclical? Evidence from wavelet analysis," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(1), pages 113-139.
    4. María del Carmen Valls Martínez & Pedro Antonio Martín Cervantes, 2021. "Testing the Resilience of CSR Stocks during the COVID-19 Crisis: A Transcontinental Analysis," Mathematics, MDPI, vol. 9(5), pages 1-24, March.
    5. Mpoha, Salifya & Bonga-Bonga, Lumengo, 2021. "Spillover effects from China and the US to global emerging markets: a dynamic analysis," MPRA Paper 109349, University Library of Munich, Germany.
    6. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    7. Baneng Naape & Bekithemba Qeqe, 2022. "How Does Financial Market Stress Respond to Shocks in Global Economic Activity and Exchange Rate Stability? A Structural VAR Approach," Eurasian Journal of Social Sciences, Eurasian Publications, vol. 10(1), pages 25-36.
    8. Bonga-Bonga, Lumengo & Mpoha, Salifya, 2024. "Spillover effects from China and the United States to Key Regional Emerging Markets: A dynamic analysis," International Review of Financial Analysis, Elsevier, vol. 91(C).
    9. Choi, Sun-Yong, 2022. "Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    10. Zhang, Hongwei & Wang, Peijin, 2021. "Does Bitcoin or gold react to financial stress alike? Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 629-648.
    11. Gaies, Brahim & Chaâbane, Najeh & Bouzouita, Nesrine, 2024. "Navigating the storm: Time-frequency quantile dependence and non-linear causality between crypto-currency market volatility and financial instability," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 43-70.
    12. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2021. "How do Artificial Intelligence and Robotics Stocks co-move with traditional and alternative assets in the age of the 4th industrial revolution? Implications and Insights for the COVID-19 period," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    13. Kang, Sang Hoon & Lahmiri, Salim & Uddin, Gazi Salah & Arreola Hernandez, Jose & Yoon, Seong-Min, 2020. "Inflation cycle synchronization in ASEAN countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

    More about this item

    Keywords

    Financial stress; Financial stress index; Real economy; Wavelets; Wavelet squared coherence;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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