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Discount Banking and Economic Cycles: A Wavelet Analysis of French Retrospective GNP Series

Author

Listed:
  • Patrice Baubeau

    (IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 Vincennes-Saint-Denis - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Bernard Cazelles

    (IRD [France-Nord] - Institut de Recherche pour le Développement, Laboratoire Ecologie et évolution - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - UPMC - Université Pierre et Marie Curie - Paris 6 - CNRS - Centre National de la Recherche Scientifique)

Abstract

Although 50 years of scientific work has been invested in building retrospective economic time series, their reliability is still debated, a good example being the two competing nineteenth century French GNP series. Instead of trying to bring up some new details to gauge their respective accuracy, we propose a different route, i.e. testing the intrinsic features of these two series, in absolute terms first, then by benchmarking them to a non-retrospective time series. In order to do that, we rely on new mathematical tools--wavelet spectrum analysis--developed in signal processing. This leads to a new approach, which separates the accuracy of a series between amplitude and time variations, and brings nuanced conclusions as to which of the two series tested is the best: indeed, since a trade-off is almost inescapable between the two criterions of accuracy, the statistical quality of one retrospective time series tends to linger either on one side (amplitude level) or the other (time variations). Our study also shows that variance distribution along the time axis is a good proxy for complex retrospective series accuracy.

Suggested Citation

  • Patrice Baubeau & Bernard Cazelles, 2009. "Discount Banking and Economic Cycles: A Wavelet Analysis of French Retrospective GNP Series," Post-Print halshs-00933197, HAL.
    • Handle: RePEc:hal:journl:halshs-00933197
    DOI: 10.1007/s11698-008-0033-9
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    Citations

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    Cited by:

    1. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
    2. 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.
    3. 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.
    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. 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.
    6. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.

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