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Revisiting the Great Ratios Hypothesis

Author

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  • Alexander Chudik

    (Federal Reserve Bank of Dallas)

  • M. Hashem Pesaran

    (epartment of Economics, University of Southern California, USA and Trinity College, Cambridge, UK)

  • Ron P. Smith

    (Birkbeck, University of London)

Abstract

The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth, arbitrage or solvency, the empirical literature has tended to find little evidence for them. We argue that this outcome could be due to episodic failure of cointegration, possible two-way causality between the variables in the ratios, and cross-country error dependence due to latent factors. We propose a new system pooled mean group estimator (SPMG) to deal with these features. Using this new panel estimator and a dataset spanning almost one and half centuries and seventeen countries, we find support for five out of the seven great ratios that we consider. Extensive Monte Carlo experiments also show that the SPMG estimator with bootstrapped confidence intervals stands out as the only estimator with satisfactory small sample properties.

Suggested Citation

  • Alexander Chudik & M. Hashem Pesaran & Ron P. Smith, 2022. "Revisiting the Great Ratios Hypothesis," BCAM Working Papers 2203, Birkbeck Centre for Applied Macroeconomics.
  • Handle: RePEc:bbk:bbkcam:2203
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    References listed on IDEAS

    as
    1. Pesaran, M. Hashem, 2015. "Time Series and Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780198759980.
    2. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    3. Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
    4. Bailey, Natalia & Pesaran, M. Hashem & Smith, L. Vanessa, 2019. "A multiple testing approach to the regularisation of large sample correlation matrices," Journal of Econometrics, Elsevier, vol. 208(2), pages 507-534.
    5. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    6. Nelson C. Mark & Donggyu Sul, 2003. "Cointegration Vector Estimation by Panel DOLS and Long‐run Money Demand," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 655-680, December.
    7. Ulrich K. Müller & Mark W. Watson, 2018. "Long†Run Covariability," Econometrica, Econometric Society, vol. 86(3), pages 775-804, May.
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    Cited by:

    1. Alexander Chudik & M. Hashem Pesaran & Ron P. Smith, 2021. "Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels," Globalization Institute Working Papers 409, Federal Reserve Bank of Dallas, revised 08 Nov 2023.

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    More about this item

    JEL classification:

    • B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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