IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-01714256.html
   My bibliography  Save this paper

Why are philosophers more often right than others ? David Hume and general rules
[David Hume et les règles générales : Pourquoi les philosophes ont-ils plus raison que les autres ?]

Author

Listed:
  • André Lapidus

    (PHARE - Philosophie, Histoire et Analyse des Représentations Économiques - UP1 - Université Paris 1 Panthéon-Sorbonne)

Abstract

This paper supports the contention that the general rules introduced by Hume in the Treatise on Human Nature (THN 1.3.15) are a selection mechanism for inductive inferences, which rejects two sources of inefficiency: (i) from emotional origin, which would reduce the uneasiness coming from a possible failure in the uniformity of nature; (ii) from cognitive origin, which would tolerate the possible overflow of the imagination on judgment. A growing consensus in recent decades, which distinguishes between two kinds of rules – extensive and corrective – is at the basis of this device. Whereas the extensive rules allow us to go beyond a singular experience and derive a wider range of inferences, the corrective rules, whose command opposes the philosopher to the vulgar, control and rectify the effects of extensive rules alone, so as to eliminate emotional and cognitive inefficiencies, and to make inferences that, borrowing the expression to Peirce, we will designate as abductive.

Suggested Citation

  • André Lapidus, 2020. "Why are philosophers more often right than others ? David Hume and general rules [David Hume et les règles générales : Pourquoi les philosophes ont-ils plus raison que les autres ?]," Post-Print hal-01714256, HAL.
  • Handle: RePEc:hal:journl:hal-01714256
    DOI: 10.7202/1070256ar
    Note: View the original document on HAL open archive server: https://paris1.hal.science/hal-01714256v2
    as

    Download full text from publisher

    File URL: https://paris1.hal.science/hal-01714256v2/document
    Download Restriction: no

    File URL: https://libkey.io/10.7202/1070256ar?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Malinvaud, E., 1988. "Econometric Methodology at the Cowles Commission: Rise and Maturity," Econometric Theory, Cambridge University Press, vol. 4(2), pages 187-209, August.
    2. David Andrews, 1999. "Continuity and change in Keynes's thought: the importance of Hume," The European Journal of the History of Economic Thought, Taylor & Francis Journals, vol. 6(1), pages 1-21.
    3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    4. Jon Elster, 1998. "Emotions and Economic Theory," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 47-74, March.
    5. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, May.
    6. Bateman, Bradley W., 1987. "Keynes's Changing Conception of Probability," Economics and Philosophy, Cambridge University Press, vol. 3(1), pages 97-119, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. André Lapidus, 2018. "Why are philosophers more often right than others ? David Hume and general rules [Pourquoi les philosophes ont-ils plus raison que les autres ? David Hume et les règles générales]," Working Papers hal-01714256, HAL.
    2. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
    3. Wallace E. Huffman & James R. Lothian, 1984. "The Gold Standard and the Transmission of Business Cycles, 1833-1932," NBER Chapters, in: A Retrospective on the Classical Gold Standard, 1821-1931, pages 455-512, National Bureau of Economic Research, Inc.
    4. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412.
    5. Michaelides, Panayotis G. & Papageorgiou, Theofanis, 2012. "On the transmission of economic fluctuations from the USA to EU-15 (1960–2011)," Journal of Economics and Business, Elsevier, vol. 64(6), pages 427-438.
    6. Christopher L. Gilbert & Duo Qin, 2005. "The First Fifty Years of Modern Econometrics," Working Papers 544, Queen Mary University of London, School of Economics and Finance.
    7. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    8. Christopher L. Gilbert & Duo Qin, 2007. "Representation in Econometrics: A Historical Perspective," Working Papers 583, Queen Mary University of London, School of Economics and Finance.
    9. Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
    10. Julia Campos & Neil R. Ericsson & David F. Hendry, 2005. "General-to-specific modeling: an overview and selected bibliography," International Finance Discussion Papers 838, Board of Governors of the Federal Reserve System (U.S.).
    11. Pacheco Jiménez, J.F., 2001. "Business cycles in small open economies: the case of Costa Rica," ISS Working Papers - General Series 19075, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    12. Uebele, Martin & Ritschl, Albrecht, 2009. "Stock markets and business cycle comovement in Germany before World War I: Evidence from spectral analysis," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 35-57, March.
    13. Ubilava, David, 2019. "On The Relationship Between Financial Instability And Economic Performance: Stressing The Business Of Nonlinear Modeling," Macroeconomic Dynamics, Cambridge University Press, vol. 23(1), pages 80-100, January.
    14. Campos, Julia & Ericsson, Neil R. & Hendry, David F., 1990. "An analogue model of phase-averaging procedures," Journal of Econometrics, Elsevier, vol. 43(3), pages 275-292, March.
    15. Yao, Vincent W. & Solboda, Brian, 2005. "Forecasting Cycles in the Transportation Sector," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208159, Transportation Research Forum.
    16. Harm Bandholz, 2005. "New Composite Leading Indicators for Hungary and Poland," ifo Working Paper Series 3, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Ritabrata Bose & Ashima Goyal, 2020. "Disaggregated Indian industrial cycles: A Spectral analysis," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-033, Indira Gandhi Institute of Development Research, Mumbai, India.
    18. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412, April.
    19. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2017. "Technology and Business Cycles: A Schumpeterian Investigation for the USA," MPRA Paper 80636, University Library of Munich, Germany.
    20. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-01714256. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.