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Erschienen in: Review of Accounting Studies 1/2011

01.03.2011

Analyst forecast characteristics and the cost of debt

verfasst von: Sattar A. Mansi, William F. Maxwell, Darius P. Miller

Erschienen in: Review of Accounting Studies | Ausgabe 1/2011

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Abstract

We examine the relation between analyst forecast characteristics and the cost of debt financing. Consistent with the view that the information contained in analysts’ forecasts is economically significant across asset classes, we find that analyst activity reduces bond yield spreads. We also find that the economic impact of analysts is most pronounced when uncertainty about firm value is highest (that is, when firms have high idiosyncratic risk). Our findings are robust to controls for private information in equity prices and level of corporate disclosures. Overall, the results indicate that the information contained in analyst forecasts is valued outside the equity market and provide an additional channel in which better information is associated with a lower cost of capital.

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Fußnoten
1
Campello et al. (2008) argue that bond yields can also be used to construct ex ante equity risk premiums.
 
2
There are two approaches to corporate bond pricing: structural and reduced form models. The structural models (e.g., Merton 1974) provide a theoretical construct for pricing corporate bonds but often produce outputs that underestimate observed default spreads. In contrast, the reduced form models allow for illiquidity and systematic credit risk to be priced and tend to fit the observed default premia better than structural models (Campbell and Taksler 2003). Our empirical models control for factors that proxy for the underlying factors that drive the pricing in either the structural or reduced form models.
 
3
The theoretical motivation for these studies is generally taken from models of estimation risk (Barry and Brown 1985; Coles et al. 1995) and incomplete information (Merton 1987). More general evidence on disclosure and the cost of capital exists using microstructure data (Welker 1995; Leuz and Verrechia 2000; Easley et al. 2002; Botosan et al. 2004).
 
4
Bushman et al. (2004) argue that analysts’ information production results from investor demand.
 
5
Gu and Wu (2003) have found that using the median forecast consensus rather than the mean provides the most accurate forecast.
 
6
Though not reported, we also estimate the basic models using the month of fiscal year-end and find similar results.
 
7
The underlying assumption in the regression models is that there are uniform differences between the ordinal credit ratings. To ensure this assumption is not driving our results, we also estimate credit ratings using ordered probit models, which captures the information in the ordering of the ordinal variable (rating) but does not impose a uniform relation among the ratings categories. Though not reported, we find similar results to the reported OLS results.
 
8
Francis et al. (2008) also provide data on one additional disclosure variable, the firm-initiated press releases. However, due to the high correlation between that variable and the already collected conference calls activity (about 50%), we do not report the results for the firm-initiated press releases variable.
 
9
Our finding that AIMR scores are insignificant differs from Yu (2005). However, we use a different sampling method. We sample once a year to coincide with our financial controls rather than monthly, which induces serial correlation in the AIMR variable, which does not change on a monthly basis. We also include additional information control variables and apply stricter econometric estimation techniques.
 
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Metadaten
Titel
Analyst forecast characteristics and the cost of debt
verfasst von
Sattar A. Mansi
William F. Maxwell
Darius P. Miller
Publikationsdatum
01.03.2011
Verlag
Springer US
Erschienen in
Review of Accounting Studies / Ausgabe 1/2011
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-010-9127-2

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