File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Anchoring and adjustment in probabilistic inference in auditing

TitleAnchoring and adjustment in probabilistic inference in auditing
Authors
Issue Date1981
Citation
Journal Of Accounting Research, 1981, v. 19 n. 1, p. 120-145 How to Cite?
AbstractAuditors are faced with the task of formulating opinions about the fairness of their clients' financial statements. In doing so, they use their professional judgment to determine the type and amount of information to collect, the timing and manner of collecting it, and the implications of the information collected. This information is rarely, if ever, perfectly reliable or perfectly predictive of the "true" state of a client's financial statements. Nevertheless, auditors may be held liable at common law or under the federal securities laws should the audited financial statements prove to be unrepresentative of this true state. Thus, it is important for auditors to have the ability to formulate appropriately judgments based on probabilistic data. In this paper, we describe the results of experiments designed to assess whether auditors formulate judgments in accordance' with normative principles of decision making or whether a particular alternative to the normative model of decision making under uncertainty 's employed. In the next section, we discuss several alternatives to normative decision models, focusing on the anchoring and adjustment heuristic which forms the basis for our experiments.
Persistent Identifierhttp://hdl.handle.net/10722/128996
ISSN
2015 Impact Factor: 2.243
2015 SCImago Journal Rankings: 5.733
SSRN
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorJoyce, EJen_US
dc.contributor.authorBiddle, GCen_US
dc.date.accessioned2010-12-09T03:05:31Z-
dc.date.available2010-12-09T03:05:31Z-
dc.date.issued1981en_US
dc.identifier.citationJournal Of Accounting Research, 1981, v. 19 n. 1, p. 120-145en_US
dc.identifier.issn0021-8456en_US
dc.identifier.urihttp://hdl.handle.net/10722/128996-
dc.description.abstractAuditors are faced with the task of formulating opinions about the fairness of their clients' financial statements. In doing so, they use their professional judgment to determine the type and amount of information to collect, the timing and manner of collecting it, and the implications of the information collected. This information is rarely, if ever, perfectly reliable or perfectly predictive of the "true" state of a client's financial statements. Nevertheless, auditors may be held liable at common law or under the federal securities laws should the audited financial statements prove to be unrepresentative of this true state. Thus, it is important for auditors to have the ability to formulate appropriately judgments based on probabilistic data. In this paper, we describe the results of experiments designed to assess whether auditors formulate judgments in accordance' with normative principles of decision making or whether a particular alternative to the normative model of decision making under uncertainty 's employed. In the next section, we discuss several alternatives to normative decision models, focusing on the anchoring and adjustment heuristic which forms the basis for our experiments.-
dc.languageengen_US
dc.relation.ispartofJournal Of Accounting Researchen_US
dc.titleAnchoring and adjustment in probabilistic inference in auditingen_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0021-8456&volume=19&spage=120&epage=&date=1981&atitle=ANCHORING+AND+ADJUSTMENT+IN+PROBABILISTIC+INFERENCE+IN+AUDITINGen_US
dc.identifier.emailBiddle, GC:biddle@hku.hken_US
dc.identifier.authorityBiddle, GC=rp00230en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.2307/2490965-
dc.relation.referenceshttp://apps.isiknowledge.com/CitedRefList.do?product=WOS&search_mode=CitedRefList&db_id=WOS&UT=A1981LX45200007en_US
dc.identifier.volume19en_US
dc.identifier.issue1en_US
dc.identifier.spage120en_US
dc.identifier.epage145en_US
dc.identifier.isiWOS:A1981LX45200007en_US
dc.identifier.ssrn1677224-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats