IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/halshs-00679999.html
   My bibliography  Save this paper

De la qualité comptable : mesure et enjeux

Author

Listed:
  • Jean-François Casta

    () (DRM-Finance - DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique)

  • Hervé Stolowy

    () (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

Abstract

S'agissant de la qualité de l'information associée aux états financiers, le cadre conceptuel élaboré de 1978 à 1985 par le Financial Accounting Standards Board (FASB) a été le premier à apporter des réponses aux questions suivantes : quels doivent être les objectifs de la comptabilité ? Quelles doivent être les caractéristiques qualitatives de l'information comptable ? A cette fin, le Statement of Financial Accounting Concepts (SFAC) n°2 (FASB, 1980) a défini un ensemble cohérent de caractéristiques qualitatives requises de l'information comptable, structurées autour de l'utilité pour la prise de décision, comme la pertinence, la fiabilité et la comparabilité, mais aussi a focalisé l'identification des besoins de utilisateurs sur l'orientation " marché ". Ce choix n'est pas sans effet sur la définition sous-jacente du concept de qualité comptable. Thème de recherche récurrent en comptabilité financière, la qualité a suscité une abondante littérature, qui considère aussi bien la qualité des résultats (earnings quality), la qualité comptable (accounting quality), la qualité de l'information comptable (quality of accounting information) que la qualité de l'information financière (financial reporting quality). Paradoxalement, il apparaît que la définition du concept de qualité comptable est -- comme souvent en comptabilité financière -- assimilée à sa mesure. Il est dès lors paru opportun de mieux cerner ce construit social sous-jacent dans tout processus d'évaluation des normes comptables.

Suggested Citation

  • Jean-François Casta & Hervé Stolowy, 2012. "De la qualité comptable : mesure et enjeux," Working Papers halshs-00679999, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00679999 Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00679999
    as

    Download full text from publisher

    File URL: https://halshs.archives-ouvertes.fr/halshs-00679999/document
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nakajima, Kentaro & Saito, Yukiko Umeno & Uesugi, Iichiro, 2012. "Measuring economic localization: Evidence from Japanese firm-level data," Journal of the Japanese and International Economies, Elsevier, vol. 26(2), pages 201-220.
    2. Gilles Duranton & Henry G. Overman, 2008. "Exploring The Detailed Location Patterns Of U.K. Manufacturing Industries Using Microgeographic Data," Journal of Regional Science, Wiley Blackwell, vol. 48(1), pages 213-243.
    3. Ugo Fratesi, 2008. "Issues in the Measurement of Localization," Environment and Planning A, , vol. 40(3), pages 733-758, March.
    4. Dietrich Stoyan, 2000. "Improving Ratio Estimators of Second Order Point Process Characteristics," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 641-656.
    5. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    6. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2008. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Empirical Economics, Springer, vol. 34(1), pages 81-103, February.
    7. Gilles Duranton & Henry G. Overman, 2005. "Testing for Localization Using Micro-Geographic Data," Review of Economic Studies, Oxford University Press, vol. 72(4), pages 1077-1106.
    8. Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2010. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," American Economic Review, American Economic Association, vol. 100(3), pages 1195-1213, June.
    9. Pablo Jensen & Julien Michel, 2011. "Measuring spatial dispersion: exact results on the variance of random spatial distributions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(1), pages 81-110, August.
    10. Cutrini, Eleonora, 2009. "Using entropy measures to disentangle regional from national localization patterns," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 243-250, March.
    11. Paulo Guimarães & Octávio Figueiredo & Douglas Woodward, 2011. "Accounting For Neighboring Effects In Measures Of Spatial Concentration," Journal of Regional Science, Wiley Blackwell, vol. 51(4), pages 678-693, October.
    12. A. J. Baddeley, 2000. "Non- and semi-parametric estimation of interaction in inhomogeneous point patterns," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 54(3), pages 329-350.
    13. Giuseppe Espa & Diego Giuliani & Giuseppe Arbia, 2010. "Weighting Ripley�s K-function to account for the firm dimension in the analysis of spatial concentration," Department of Economics Working Papers 1012, Department of Economics, University of Trento, Italia.
    14. Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2011. "Spatial point pattern analysis and industry concentration," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(2), pages 311-328, October.
    15. Behrens, Kristian & Bougna, Théophile, 2015. "An anatomy of the geographical concentration of Canadian manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 47-69.
    16. Eric Marcon & Florence Puech, 2010. "Measures of the geographic concentration of industries: improving distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 10(5), pages 745-762, September.
    17. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
    18. Eric Marcon & Florence Puech, 2003. "Evaluating the geographic concentration of industries using distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 3(4), pages 409-428, October.
    19. Barlet, M. & Briant, A. & Crusson, L., 2013. "Location patterns of service industries in France: A distance-based approach," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 338-351.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Earnings quality; Accounting quality; Quality of accounting information; Financial reporting quality; qualité des résultats; qualité comptable; qualité de l'information comptable; qualité de l'information financière;

    JEL classification:

    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

    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:wpaper:halshs-00679999. See general information about how to correct material in RePEc.

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

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.