Izvorni znanstveni članak
Estimating accruals models in Europe: industry-based approaches versus a data-driven approach
Antonio F. Di Narzo
; Antonio Di Narzo Consulting, Krakow, Poland
Marzia Freo
; Department of Statistics, University of Bologna, Bologna, Italy
Marco Maria Mattei
; Department of Management, University of Bologna, Bologna, Italy
Sažetak
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.
Ključne riječi
Earnings management; accruals models; abnormal accruals (AA); small capital markets; mixture model (MIX)
Hrčak ID:
200639
URI
Datum izdavanja:
3.12.2018.
Posjeta: 915 *