Modeling Earnings Discontinuities: A Maximum Likelihood Approach

dc.contributor.author	Basu, Sudipta
dc.contributor.author	Byzalov, Dmitri
dc.date.accessioned	2017-12-21T21:11:54Z
dc.date.available	2017-12-21T21:11:54Z
dc.date.issued	2017-09-02
dc.description	Inquiries about this document can be made to <a href="mailto:HARC@hawaii.edu">HARC@hawaii.edu</a>
dc.description.abstract	We develop new distribution discontinuity tests for detecting earnings management and analyzing its determinants. We embed Burgstahler and Dichev’s (1997) intuition on benchmark-driven earnings management in a likelihood-based model that addresses important limitations of the existing distribution discontinuity tests. Our method offers large improvements in test performance relative to both histogram-based tests of the existence of earnings discontinuity and logit-based tests of the determinants of earnings discontinuity, and it changes some of the major findings in the earnings discontinuity literature. Future research on distribution discontinuities could benefit from adopting our likelihood-based tests.
dc.identifier.uri	http://hdl.handle.net/10125/51984
dc.subject	standardized difference test
dc.subject	zero benchmark
dc.subject	smooth distribution
dc.title	Modeling Earnings Discontinuities: A Maximum Likelihood Approach