Neural Networks: Is it hermeneutic?
AbstractThis paper proposes a synoptic methodology to evaluate the determinants of audit fees by utilising Neural Networks. First, a brief discussion is presented to highlight the significant application of Neural Network in the areas of financial management; second the framework of proposed methodology has been outlined to examine the implication of audit fees on target sample. The underlying rational of this paper is to establish NNs as a diagnostic tool to assess the effect of audit fees on firms, which indeed warrants further empirical investigation. The importance of NNs emerges from the fact that if external and internal audit fees can be disseminated by employing this methodology which is perceived more significantly robust than other econometric models, then accounting standards can be improved.
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Bibliographic InfoPaper provided by EconWPA in its series Experimental with number 0403003.
Length: 10 pages
Date of creation: 19 Mar 2004
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Note: Type of Document - pdf; pages: 10
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Neural Networks and Audit Fee;
Find related papers by JEL classification:
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-03-22 (All new papers)
- NEP-CMP-2004-03-22 (Computational Economics)
- NEP-DEV-2004-03-22 (Development)
- NEP-HPE-2004-03-22 (History & Philosophy of Economics)
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