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Financial statement comparability and credit risk

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Abstract

Prior research shows that firms’ financial statement comparability improves the accuracy of market participants’ valuation judgments and thus may reduce firms’ costs of capital. Distinct from prior research focusing on the equity market, we develop measures of comparability relevant to debt market participants based on the within-industry variability of Moody’s adjustments to reported accounting numbers for the purposes of credit rating. We examine two sets of adjustments: (1) to the interest coverage ratio and (2) to non-recurring income items. We validate these comparability measures by providing evidence that greater comparability is associated with lower frequency and magnitude of split ratings by credit rating agencies. We predict and find that greater comparability is associated with (1) lower estimated bid-ask spreads for traded bonds, (2) lower credit spreads for both bonds and five-year credit default swaps, and (3) a steeper one- to five-year credit default swap term structure. Our results are consistent with financial statement comparability reducing debt market participants’ uncertainty about and pricing of firms’ credit risk.

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Notes

  1. For example, it is not particularly difficult for market participants to capitalize minimum lease payment disclosures for each of the first five years of operating leases required by FAS 13. Hence, if the calculated variability of Moody’s adjustments results solely from some firms having more operating leases with minimum lease payments in the first five year terms than others, then this variability will not indicate meaningful lack of comparability. However, it is more difficult to capitalize the disclosed lump sum of minimum lease payments beyond five years required by FAS 13. It is more difficult still to deal with lease contractual features that yield payments that are highly likely to occur but not deemed to be minimum lease payments, such as contingent lease payments and payments associated with the exercise of most renewal options, for which FAS 13 requires only descriptive, nonquantitative disclosures. Non-lease examples involving highly judgmental adjustments include securitizations with significant but not complete risk transfer and transitory income items with operating characteristics or that are in the same direction period after period.

  2. These papers are related to a large prior stream of literature that uses the strength of the contemporaneous relation between stock returns and accounting numbers or the magnitude or variability of valuation multiples as proxies for relative financial reporting quality, for example, of different accounting systems internationally (Joos and Lang 1994; Land and Lang 2002), or to identify peer firms (Bhojraj and Lee 2002).

  3. Prior research suggests that credit spreads in CDS markets are less affected by illiquidity than credit spreads in bond markets (Jorion and Zhang 2007; Longstaff et al. 2005).

  4. We conduct a robustness test where we drop days with positive covariances.

  5. In untabulated analyses, we control alternatively for Herfindahl indices that measure how well Moody’s industries map into Fama and French 30 and 48 industry classifications; these indices are strongly positively correlated with hhi_naics3 and yield similar results.

  6. Because we use Eq. (6) for construct validation purpose only, we omit compacctind because it is a competing comparability measure and bsmprob because average_rating_bond is a more relevant default measure for credit rating agencies.

  7. We conduct robustness tests where we recalculate the estimated bid-ask spread without any days with positive covariances and find that results are robust to this specification.

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Acknowledgments

We thank Brian Akins, Navneet Arora (the discussant), Karthik Balakrishnan, Anne Beatty, Gus De Franco, Mirko Heinle, Cathy Schrand, Minye Tang, Lakshmanan Shivakumar (the editor), and Rodrigo Verdi. We also thank participants at the RAST 2012 conference and at the CFEA 2012 conference, as well as workshop participants at the University of Missouri, the University of Pennsylvania, Tel Aviv University, New York University summer camp, and Quantitative Management Associates for constructive feedback, questions and suggestions. We gratefully acknowledge the financial support provided by NYU Stern School of Business and University of Pennsylvania Wharton School of Business. Kim gratefully acknowledges financial support from the Samsung Scholarship.

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Authors and Affiliations

  1. Stern School of Business, New York University, New York, NY, USA

    Seil Kim, Pepa Kraft & Stephen G. Ryan

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  1. Seil Kim
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Correspondence to Pepa Kraft.

Appendix

Appendix

Variable definitions

Variable

Explanation

Financial statement comparability, based on adjustments

cover_delta

Adjusted coverage minus reported coverage, winsorized at 1st and 99th percentile

nonrecurr_delta_sRev

Adjustment for non-recurring items divided by reported revenues, winsorized at 1st and 99th percentile

iqr_cover_delta

Interquartile range of cover_delta by peer-quarter multiplied by −1

iqr_nonrecurr_delta_sRev

Interquartile range of nonrecurr_delta_sRev by peer-quarter multiplied by −1

compacctind

Median pairwise comparability measure based on De Franco et al. (2011a) for all firms in the same 2-digit SIC industry

Outcome variables

split

Indicator equals one if any of Moody’s, S&P, or Fitch ratings differ

ms_split

Indicator equals one if Moody’s and S&P ratings differ

rating_range

Difference between maximum and minimum ratings by Moody’s, S&P, and Fitch (notches)

rating_ms_range

Difference between maximum and minimum ratings by Moody’s and S&P (notches)

bond_spread

Difference between average yield of bond and interpolated maturity-matched Treasury yield, winsorized at 0.5 and 99.5 percentile (bsp)

roll

Estimate of bid-ask spread based on Roll (1984), winsorized at 1st and 99th percentile

CDS5y

Five-year CDS spread (bsp)

CDS1y/CDS5y

One-year CDS spread divided by five-year CDS spread

Control variables for peer characteristics

cover_rep

Operating profit divided by interest expense (winsorized at 0 and 100), as reported

roa_rep

Operating profit divided by total assets, as reported

intanpro_rep

Goodwill and other intangibles divided by total assets, as reported

lever_rep

Long-term debt divided by total assets, as reported

size_rep

Revenues in USD thousands, as reported

median_[x]

Median of [x] by peer-quarter

iqr_[x]

Interquartile range of [x] by peer-quarter

hhi_naics3

Herfindahl index of 3-digit NAICS classification for Moody’s peer groups

busseg

Number of operating segments

geoseg

Number of geographical segments

sumseg

Total number of segments (busseg plus geoseg)

iqr_sumseg

Interquartile range of sumseg by peer-quarter

loss_peer

Proportion of negative net income firm-quarters within peer-quarter

audit_hhi

Auditor concentration Herfindahl index based on audit fees

Control variables for bond properties and credit risk

average_rating_bond

Average of Moody’s, S&P, and Fitch ratings for a given bond

average_rating_issuer

Average of Moody’s, S&P, and Fitch ratings for all bonds by the same issuer

bsmprob

Probability of default calculated using Black-Scholes-Merton formula following Hillegeist et al. (2004) and based on total debt

offering_amt

Par value of debt issued

timetillmat

Time from quarterly filing date to maturity (days)

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Kim, S., Kraft, P. & Ryan, S.G. Financial statement comparability and credit risk. Rev Account Stud 18, 783–823 (2013). https://doi.org/10.1007/s11142-013-9233-z

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