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Reassessing the dependence between economic growth and financial conditions since 1973

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  • Tony Chernis
  • Patrick J. Coe
  • Shaun P. Vahey

Abstract

Adrian, Boyarchenko and Giannone (2019, ABG) adapt Quantile Regression (QR) methods to examine the relationship between U.S. economic growth and financial conditions. We confirm their empirical findings, using their methodology and their pre-2016 sample. Mindful of the importance of the Covid-19 pandemic, we extend the sample to 2021:3 and find attenuation of the key estimated coefficients using ABG’s empirical methods. Given the pandemic observations, we provide robust QR analysis of dependence based on ranked data, and explain the relationship with extant copula modelling methods.

Suggested Citation

  • Tony Chernis & Patrick J. Coe & Shaun P. Vahey, 2022. "Reassessing the dependence between economic growth and financial conditions since 1973," CAMA Working Papers 2022-30, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2022-30
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2022-04/30_2022_chernis_coe_vahey.pdf
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    References listed on IDEAS

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    1. Ozer Karagedikli & Shaun P. Vahey & Elizabeth C. Wakerly, 2019. "Improved methods for combining point forecasts for an asymmetrically distributed variable," CAMA Working Papers 2019-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Dante Amengual & Enrique Sentana & Zhanyuan Tian, 2022. "Gaussian Rank Correlation and Regression," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 269-306, Emerald Group Publishing Limited.
    3. Smith, Michael Stanley, 2015. "Copula modelling of dependence in multivariate time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 815-833.
    4. Reichlin, Lucrezia & Ricco, Giovanni & Hasenzagl, Thomas, 2020. "Financial variables as predictors of real growth vulnerability," Discussion Papers 05/2020, Deutsche Bundesbank.
    5. Mateo Velásquez‐Giraldo & Gustavo Canavire‐Bacarreza & Kim P. Huynh & David T. Jacho‐Chavez, 2018. "Flexible Estimation of Demand Systems: A Copula Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1109-1116, November.
    6. Ryan Niladri Banerjee & Juan Contreras & Aaron Mehrotra & Fabrizio Zampolli, 2020. "Inflation at risk in advanced and emerging economies," BIS Working Papers 883, Bank for International Settlements.
    7. Sulkhan Chavleishvili & Simone Manganelli, 2024. "Forecasting and stress testing with quantile vector autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 66-85, January.
    8. Jianqing Fan & Lingzhou Xue & Hui Zou, 2016. "Multitask Quantile Regression Under the Transnormal Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1726-1735, October.
    9. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    10. Gianni De Nicolò & Marcella Lucchetta, 2017. "Forecasting Tail Risks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 159-170, January.
    11. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    12. repec:hal:spmain:info:hdl:2441/4nn4ojjkth8qe9ci5b0hpu7ala is not listed on IDEAS
    13. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    14. Machado, Jose A. F. & Silva, J. M. C. Santos, 2000. "Glejser's test revisited," Journal of Econometrics, Elsevier, vol. 97(1), pages 189-202, July.
    15. Patrick J. Coe & Shaun P. Vahey, 2020. "Financial conditions and the risks to economic growth in the United States since 1875," CAMA Working Papers 2020-36, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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    Cited by:

    1. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    2. Aaron Amburgey & Michael W. McCracken, 2023. "Growth-at-Risk is Investment-at-Risk," Working Papers 2023-020, Federal Reserve Bank of St. Louis, revised 16 Aug 2024.

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    Keywords

    Vulnerable Growth; Quantile Regression; Copula Modelling;
    All these keywords.

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