Accounting Complexity and Misreporting: Manipulation or Mistake?

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dc.contributor.author Peterson, Kyle en_US
dc.date.accessioned 2008-08-25T20:56:53Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2008-08-25T20:56:53Z
dc.date.issued 2008 en_US
dc.date.submitted en_US
dc.identifier.uri http://hdl.handle.net/2027.42/60842
dc.description.abstract I explore the effect of accounting complexity on misreporting using a setting of revenue restatements. I measure revenue recognition complexity using a factor score based on the number of words and revenue recognition methods from the revenue recognition disclosure in the 10-K just prior to the restatement announcement. Results are consistent with revenue recognition complexity increasing the probability of revenue restatements, after controlling for other determinants of misreporting revenue. These results are significant both statistically and economically and are robust to a number of different specifications. I also test whether misreporting for complex revenue recognition firms is the result of mistakes or manipulation. My tests provide no evidence consistent with complex revenue recognition being associated with manipulating revenue. However, there is evidence that firms that restate revenue and have more complex revenue recognition are less likely to receive an AAER from the SEC and have less negative restatement announcement returns than firms with less complex revenue recognition, suggesting mistakes are more likely for more complex firms. en_US
dc.format.extent 339047 bytes
dc.format.extent 1373 bytes
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso en_US en_US
dc.subject Misreporting en_US
dc.subject Restatement en_US
dc.subject Accounting en_US
dc.subject Complexity en_US
dc.subject Revenue Recognition en_US
dc.title Accounting Complexity and Misreporting: Manipulation or Mistake? en_US
dc.type Thesis en_US
dc.description.thesisdegreename Ph.D. en_US
dc.description.thesisdegreediscipline Business Administration en_US
dc.description.thesisdegreegrantor University of Michigan, Horace H. Rackham School of Graduate Studies en_US
dc.contributor.committeemember Hanlon, Michelle Lee en_US
dc.contributor.committeemember Dichev, Ilia D. en_US
dc.contributor.committeemember Lee, Yoonseok en_US
dc.contributor.committeemember Lundholm, Russell James en_US
dc.contributor.committeemember Muir, Dana M. en_US
dc.subject.hlbsecondlevel Economics en_US
dc.subject.hlbtoplevel Business en_US
dc.description.bitstreamurl http://deepblue.lib.umich.edu/bitstream/2027.42/60842/1/kylepete_1.pdf
dc.owningcollname Dissertations and Theses (Ph.D. and Master's)
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