How Often Do Managers Withhold Information?
Ivan Marinovic
Additional contact information
Ivan Marinovic: Stanford University
Research Papers from Stanford University, Graduate School of Business
Abstract:
We estimate and test a model of voluntary disclosure in which a manager's information set is uncertain (Dye 1985; Jung and Kwon 1988). In this model, a manager makes his disclosure decision to maximize the market price, but sometimes, for exogenous reasons, he cannot or is not willing to disclose. We offer a flexible framework to measure the prevalence of unobservable disclosure frictions and the quality of managers' private information. More broadly, the method can be used to test for voluntary disclosure in datasets featuring an option to withhold. We also develop theory-based tests for detecting whether a firm is reporting strategically. At the firm level, we reject strategic reporting for between 1/3 to 2/3 of the sample of firms. Finally, estimating the model with quarterly management guidance, we document that firms face a disclosure friction between 30% to 46% of the time. Conditional on not facing a friction, firms strategically withhold between 4.3% to 20.7% of the time. To aid policymakers, these estimates predict that the level of voluntary forecasts will increase by 2.6% to 13.5% in a counter-factual world without strategic information withholding.
JEL-codes: D72 D82 D83 G20 (search for similar items in EconPapers)
Date: 2015-12
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/407336
Our link check indicates that this URL is bad, the error code is: 404 Not Found (http://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/407336 [301 Moved Permanently]--> https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/407336)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:3377
Access Statistics for this paper
More papers in Research Papers from Stanford University, Graduate School of Business Contact information at EDIRC.
Bibliographic data for series maintained by ().