Estimating accruals models in Europe: industry-based approaches versus a data-driven approach
Journal Title: Economic Research-Ekonomska Istraživanja - Year 2018, Vol 31, Issue 1
Abstract
Accruals models have been estimated using a variety of approaches, but the industry-based cross-sectional approach currently seems to be the standard method. This estimation approach cannot be easily used in the vast majority of European countries where several industry groups do not have sufficient yearly observations. Using data from France, Germany, Italy and the UK, we artificially induce earnings manipulations to investigate how the ability to detect those manipulations through accruals models is affected by the use of different industry classifications. Moreover, we propose an alternative estimation approach based on a data-driven statistical procedure that provides an optimal choice of estimation samples. Our analyses show that enlarging the industry classification and/or pooling observations across years reduces the probability of discovering earnings manipulations but allows for the estimation of abnormal accruals (AA) for more firms. The data-driven approach, however, in most cases outperforms the industry-based estimation approaches without sample attrition. This result suggests that there is still ample room for improving the accruals model estimation process for capital markets of European countries. Furthermore, the analysis documents which accruals model outperforms the others in each of the four countries and the probabilities to detect earning management in a high variety of circumstances.
Authors and Affiliations
Antonio F. Di Narzo, Marzia Freo, Marco Maria Marco Maria Matteic
Keywords
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- EP ID EP507382
- DOI 10.1080/1331677X.2017.1421991
- Views 50
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