Document Type
Article
Publication Date
7-2021
Publisher
Emerald Insights
Source Publication
Journal of Public Budgeting, Accounting & Financial Management
Source ISSN
1096-3367
Abstract
Purpose
As the management discussion and analysis (MD&A) section contains discretionary narrative disclosures regarding a government's yearly financial changes and status, the authors investigate several municipal debt market consequences of linguistic tone within these disclosures.
Design/methodology/approach
The authors textually analyze municipal MD&As with Linguistic Inquiry and Word Count (LIWC) software and develop narrative tone measures based on existing financial-specific dictionaries. Using a final sample of 446 municipal bond issuances from 2012 to 2016, the authors modify the current bond regression models to examine the association between MD&A disclosure tone and future bond interest costs or rating disagreements.
Findings
This study’s empirical analysis suggests that more negative MD&A tone is associated with higher future debt costs and greater future disagreements among bond rating agencies.
Practical implications
Overall, the evidence implies that municipal bond stakeholders use the information in narrative disclosures when evaluating risk, but that the qualitative nature can introduce differences in interpretation between users. Furthermore, additional training in MD&A writing and further standard guidance in MD&A disclosures could improve the MD&A's informativeness for bond market decision-making and state-level monitoring.
Originality/value
This study is first to incorporate narrative tone measures into bond models in a governmental context.
Recommended Citation
Rich, Kevin T.; Roberts, Brent L.; and Zhang, Jean X., "Linguistic Tone of Management Discussion and Analysis Disclosures and the Municipal Debt Market" (2021). Accounting Faculty Research and Publications. 141.
https://epublications.marquette.edu/account_fac/141
Comments
Published version. Journal of Public Budgeting, Accounting & Financial Management, Vol. 33, No. 4 (July 2021): 427-446. DOI. © 2021 Emerald Insight. Used with permission.