The Association between Municipal Market Measures and Selected Financial Reporting Practices
An attempt has been made to identify the determinants of bond ratings in the corporate and municipal sectors through prior research. The research also attempted to assess whether the use of an internal auditor rather than an external auditor has an effect on interest rates. Results indicated that ac...
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Veröffentlicht in: | Journal of accounting research 1981-10, Vol.19 (2), p.502-520 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | An attempt has been made to identify the determinants of bond ratings in the corporate and municipal sectors through prior research. The research also attempted to assess whether the use of an internal auditor rather than an external auditor has an effect on interest rates. Results indicated that accounting measures and releases affect market measures. Presumably such reported numbers are perceived as more credible by lenders when produced from a particular type of accounting system and when subjected to an audit. Little effort has been directed toward the formal empirical verification of whether the quality of accounting information and detailed attributes of the auditor and auditee affect market measures. The accounting and auditing attributes of municipal bond issuers have been examined in a study to assess whether such attributes have a significant effect on borrowing costs and bond ratings. The study applied the probit model developed by McKelvey and Zavoina (1975) and regression analysis. Initial evidence has been provided by the study that interest costs reflect cross-sectional differences in accounting variables and bond ratings reflect cross-sectional differences in auditors and audit reports of municipalities. It is suggested that accounting variables have a significant association with net interest cost and auditing variables have a significant association with municipal bond ratings. Net interest cost and bond rating models which incorporate financial reporting practices lead to better predictions. Appendices. |
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ISSN: | 0021-8456 1475-679X |
DOI: | 10.2307/2490877 |