Consolidation

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International Review of Financial Analysis 16 (2007) 496–507

Proportionate consolidation versus the equity method:Additional evidence on the association with

bond ratings☆

Mark P. Bauman ⁎

College of Business Administration, University of Northern Iowa, Cedar Falls, IA 50614, United States

Available online 23 June 2007

Abstract

From a financial analysis perspective, proportionate consolidation of significant influence equityinvestments is often presumed to provide more useful information than equity method accounting.Surprisingly, Kothavala [Kothavala, K., 2003, Proportional consolidation versus the equity method: A riskmeasurement perspective on reporting interests in joint ventures, Journal of Accounting and Public Policy22, 517–538.] finds that financial statement measures based on the equity method are more relevant forbond ratings than are similar measures based on proportionate consolidation. This study provides additionalevidence regarding this issue. Using a sample of manufacturing firms with significant influence equityinvestments accounted for under U.S. GAAP, the results indicate that pro forma proportionatelyconsolidated financial statements have greater relevance than equity method statements for explaining bondratings.© 2007 Elsevier Inc. All rights reserved.

JEL classification: G10; M41Keywords: Bond ratings; Accounting methods

1. Introduction

The accounting for significant influence equity investments is interesting due to the diver-sity observed in practice. For example, while the IASB recommends and Canada requires

☆ I thank Chris Bauman, Ken Shaw, an anonymous reviewer, and the editor for their helpful comments and suggestions.I also thank Donald Cram for generously providing SAS code for a logit-based likelihood ratio test.⁎ Tel.: +1 319 273 4323; fax: +1 319 273 2922.

E-mail address: [email protected].

1057-5219/$ - see front matter © 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.irfa.2007.06.005

mailto:mark.bauman@uni.�edu

http://dx.doi.org/10.1016/j.irfa.2007.06.005

497M.P. Bauman / International Review of Financial Analysis 16 (2007) 496–507

proportionate consolidation for joint venture investments, U.S. GAAP requires the equity methodof accounting.1

Under the equity method, a significant influence equity investment is reflected in the investor'sfinancial statements as single lines in the balance sheet and income statement. This presentation ofnet amounts is criticized as a means of facilitating off-balance sheet activities and potentiallyhindering effective financial analysis (e.g., Penman, 2004; Stickney & Brown, 1999; White,Sondhi, & Fried, 2003). Under proportionate consolidation, the investor combines on a line-by-line basis its accounts with its pro rata share of the investee's accounts. Accordingly, propor-tionate consolidation provides a more comprehensive view of the investor's operations andfinancial condition.

Research has examined various aspects of credit analysis (e.g., Carleton, Dragun, & Lazear,1993; Laitinen, 1999) and the differences between financial statements prepared under propor-tionate consolidation versus the equity method (see Kothavala (2003) for a detailed summary).Bierman (1992) argues that proportionate consolidation is superior and should be used for allmaterial equity investments, even majority-owned subsidiaries. Davis and Largay (1999,p. 281) find “no substantive justification for continued use of the equity method…due to themethod's intrinsically limited informational characteristics.” Graham, King, and Morrill (2003)find that financial statements prepared under proportionate consolidation provide betterpredictions of future profitability than pro forma statements prepared under the equity method.Not all studies find in favor of proportionate consolidation. Using a sample of Canadian firms,Kothavala (2003) finds that equity method statements are more relevant for bond ratings thanare proportionately consolidated statements. Stoltzfus and Epps (2005) find that financialstatements prepared under proportionate consolidation are more strongly associated with bondrisk premiums than equity method statements only for firms that guarantee the debt of jointventure investments.

In the current study, I use a sample of U.S. manufacturing firms to examine further the relativeinformation content of proportionately consolidated versus equity method financial statementamounts for explaining bond ratings. In contrast to Kothavala (2003), the results indicate thatproportionately consolidated financial statements have greater relevance than equity methodstatements for explaining bond ratings. These differing results are most likely due to homogeneityof the sample firms in the present study. Unlike Stoltzfus and Epps (2005), the results are notaltered when guarantees of investee obligations are considered. Overall, these results add to theongoing debate regarding the usefulness of financial statements prepared under alternativemethods of accounting for significant influence equity investments.

The remainder of the paper proceeds as follows. Section 2 presents the research design.Section 3 describes the data and results. Section 4 concludes.

2. Research design

The empirical analysis proceeds in three steps. First, I estimate the models employed byKothavala (2003), using the same variable definitions. In particular, financial statement measures

1 As described in Accounting Principles Board (APB) Opinion No. 18 (APB, 1971), investors must use the equitymethod for investments in common stock that provide “significant influence over operating and financial policies of aninvestee even though the investor holds 50% or less of the voting stock” (APB 18, ¶17). There is a presumption thatsignificant influence exists with ownership interests of 20% or more.

498 M.P. Bauman / International Review of Financial Analysis 16 (2007) 496–507

based on amounts determined under equity method (E) and proportionate consolidation (P)accounting are separately regressed against bond ratings:

ðEÞ RATINGit ¼ a0 þ a1TAEit þ a2LEVEit þ a3ROAEit þ a4SRAEit þ a5PMEit

þ a6VREit þ eit ð1Þ

ðPÞ RATINGit ¼ b0 þ b1TAPit þ b2LEVPit þ b3ROAPit þ b4SRAPit þ b5PMPit

þ b6VRPit þ eit; ð2Þwhere RATING is the Standard & Poor's long-term issuer credit rating. A rating of “AAA” isassigned a value of 1 and a rating of “D” is assigned a value of 22.2 The independent variables aremeasured as follows: TA is the natural logarithm of total assets, LEV is total liabilities divided bythe book value of common equity, ROA is return on assets (calculated as net income divided byending total assets), SRA is the standard deviation of ROA, PM is profit margin (net incomedivided by total revenues), and VR is revenue volatility (calculated as the standard deviation oftotal revenues scaled by the book value of common equity).

The coefficients on TA and ROA are expected to be negative, as credit risk should bedecreasing in firm size and profitability. Conversely, as credit risk is increasing in leverage andvolatility, the coefficients on LEV, SRA, and VR are expected to be positive. With respect to profitmargin, Kothavala (2003) states that the coefficient on PM should be negative (i.e., profit margininversely related to risk). However, one must recognize that the ROA term is equal to the productof PM and asset turnover (ATO, where ATO=total revenues÷ total assets). Given ROA representsthe interaction between PM and ATO, the marginal effect of PM on RATING is appropriatelymeasured as α3·ATO+α5 and β3·ATO+β5 in Eqs. (1) and (2), respectively. While the marginaleffect of PM on RATING should be negative, there is no clear prediction for the coefficient on thePM term itself.

Eqs. (1) and (2) are estimated via OLS regression, and the test of relative information contentfrom Biddle, Seow, and Siegel (1995) (“BBS”) is used to compare the two competing, non-nestedmodels. Thus, the focus is on relative explanatory power of financial statement measures based onthe equity method versus proportionate consolidation.

The next step of the empirical analysis involves two modifications to Eqs. (1) and (2). First, Isubstitute the market value of equity for book value of equity in the VR term. As VR is designedto measure the volatility of (scaled) revenues, the coefficient should be positive. However, thecoefficient estimates in Kothavala (2003) are negative. A likely cause of this unexpected result isa small denominator problem associated with scaling by book value of equity. For consistency,the market value of equity is also substituted for book value of equity in the leverage term (LEV).Second, the models do not include guarantees of investee obligations made by investors. Asacknowledged by Kothavala (2003), it is unlikely that bond raters ignore these contingentliabilities; however, specific details on guarantees are often not available in financial statements.Further, Stoltzfus and Epps (2005) find that the existence of guarantees affects the relativeexplanatory power (for bond risk premiums) of proportionately consolidated versus equitymethod statements. Thus, Kothavala's finding that equity method statements are more relevantfor bond ratings than are proportionately consolidated statements may be due to her sample notincluding many firms that provide such guarantees. In the current study, many sample firms

2 RATING ranges from 1 to 27 in Kothavala (2003). This difference is due to the lack of +/− modifiers in Compustatfor bond ratings of CC and C. However, there are no firms with ratings below CCC in the current sample.


disclose guarantees related to investee obligations. Although the precise dollar amount of somecommitments (e.g., formal guarantee of a credit facility) can be identified, others (e.g., deficiencyagreements, take-or-pay contracts, etc.) cannot be accurately quantified. Accordingly, theexistence of guarantees enters the revised models in the form of an indicator variable, GUAR, setequal to 1 if the firm discloses some form of guarantee (and equal to 0 otherwise):

ðEÞ RATINGit ¼ a0 þ a1TAEit þ a2LEVMEit þ a3ROAEit þ a4SRAEit þ a5PMEit

þ a6VRMEit þ a7GUARþ eit ð10Þ

ðPÞ RATINGit ¼ b0 þ b1TAPit þ b2LEVMPit þ b3ROAPit þ b4SRAPit þ b5PMPit

þ b6VRMPit þ b7GUARþ eit; ð20Þwhere LEVM is total liabilities divided by the market value of common equity, VRM is thestandard deviation of total revenues scaled by the market value of common equity, and all othervariables are as defined above. As the existence of guarantees increases the level of risk, it isexpected that GUAR will have a positive coefficient.3 If the inclusion of GUAR increases theinformation content of one model relative to the other, any difference in explanatory power fromestimating Eqs. (1′) and (2′) may be affected.

Finally, there is a problem using the OLS estimator with bond ratings as the dependentvariable. OLS assumes that bond ratings are measured on an interval scale, such that the ratingsrepresent equal intervals on a scale of creditworthiness. However, bond ratings convey ordinalinformation (Kaplan & Urwitz, 1979; Kennedy, 1998). To address the possibility of misspeci-fication, Eqs. (1′) and (2′) are estimated using an ordered logit model. The logit-based test ofrelative information content from Hillegeist et al. (1995) is then used to compare the twocompeting models.4

3. Data and results

3.1. Data and descriptive statistics

To be included in the sample, a firm must (1) be a calendar year-end U.S. manufacturing firm(SIC code between 2000 and 3999), (2) have non-missing, non-zero amounts for “Equity inEarnings” (Compustat item #55), (3) have Standard & Poor's issuer debt ratings reported onCompustat (item #280), and (4) provide footnote disclosures in sufficient detail to permit proforma proportionate consolidation of equity method investees.5 An example of pro formaproportionate consolidation of an equity method investee is provided in the Appendix.

Limiting the sample to manufacturers increases the degree of homogeneity among firms,allowing for more valid comparisons of ratio values. After deleting observations with negativebook values, the final sample consists of 39 firms and 173 firm-year observations from 1997–2001. The sample is similar in size to that used by Kothavala (2003) — 40 firms and 156 firm-year observations from 1995–2000.

3 Recall that GUAR represents guarantees made by the investor company with respect to obligations of the investee.Thus, the credit risk of the investor is increasing in the presence of such guarantees.4 The test is a logit-based version of the Vuong (1989) test, designed to statistically compare the log likelihood statistics

of non-nested models.5 SEC regulations require detailed footnote disclosure only when one of three specific materiality thresholds is met.

Table 1Descriptive statistics (N=173)

Variable Mean Median S.D. Wilcoxon

RATING 9.271 9.000 4.07TAE 8.542 8.374 1.32 b0.01TAP 8.650 8.417 1.33LEVE 3.853 1.889 8.53 b0.01LEVP 4.514 2.269 9.68LEVME 1.307 0.878 1.29 b0.01LEVMP 1.528 0.967 1.55ROAE 0.036 0.043 0.07 b0.01ROAP 0.033 0.039 0.06SRAE 0.045 0.033 0.04 b0.01SRAP 0.038 0.030 0.03PME 0.040 0.051 0.08 b0.01PMP 0.033 0.045 0.07VRE 1.619 0.405 4.54 b0.01VRP 1.869 0.464 5.23VRME 0.614 0.272 0.75 b0.01VRMP 0.698 0.309 0.79GUAR 0.301 0 0.46

RATING is the S&P long-term issuer credit rating (a rating of “AAA” is assigned a value of 1 and a rating of “D” isassigned a value of 22), LEV is total liabilities divided by the book value of common equity, LEVM is total liabilitiesdivided by the market value of common equity, ROA is return on assets (calculated as net income divided by ending totalassets), SRA is the standard deviation of ROA, PM is profit margin (calculated as net income divided by total revenues),VR is revenue volatility (calculated as the standard deviation of total revenues scaled by book value of common equity),VRM is the standard deviation of total revenues scaled by market value of common equity, and GUAR=1 if a guarantee ofinvestee obligations is disclosed (=0 otherwise).


Table 1 presents descriptive statistics for the variables appearing in the models.6 For allvariables, the amounts based on the equity method are significantly different from those based onproportionate consolidation. Under the equity method, a firm reports its investment in a sig-nificant influence investee as a single line item in the balance sheet, thereby netting its share of theinvestee's assets against its share of liabilities. In contrast, under proportionate consolidation, theinvestor's share of each of the investee's financial statement elements is combined on a line-by-line basis with that of the investor. Accordingly, total assets (TA) and leverage (LEV) are greaterunder proportionate consolidation due the suppression of asset and liability amounts under theequity method. The suppression of total assets also results in significantly higher ROA under theequity method. Under the equity method, the investor's income statement contains its propor-tionate share of the investee's net income (loss) as a single line item. Accordingly, the suppressionof investee sales amounts under the equity method results in greater reported profit margin (PM).Finally, the standard deviation for LEVM (VRM) is much smaller than that for LEV (VR),indicating that the substitution of market value of equity for book value is effective in addressingthe small denominator problem.

Table 2 presents a correlation matrix including all model variables. The correlations betweenbond rating (RATING) and each of the independent variables have the expected signs and aresignificantly different from zero, except for the Pearson correlations with LEV and volatility of

6 Consistent with Kothavala (2003), the extreme one percentiles of independent variable observations are winsorized tomitigate their influence.

Table 2Correlations between bond ratings and equity method and proportionate consolidation amounts; Spearman (Pearson) correlations in upper (lower) triangle (N=173)

Rating TAE TAP LEVE LEVP LEVME LEVMP ROAE ROAP SRAE SRAP PME PMP VRE VRP VRME VRMP GUAR

Rating – −0.58 −0.57 0.28 0.27 0.66 0.67 −0.62 −0.63 0.31 0.34 −0.58 −0.60 0.28 0.23 0.74 0.73 0.15TAE −0.65 – 0.99 −0.14 −0.10 −0.33 −0.33 0.36 0.35 −0.04 −0.11 0.39 0.37 −0.16 −0.13 −0.51 −0.47 0.11TAP −0.64 0.99 – −0.14 −0.07 −0.33 −0.32 0.37 0.34 −0.00 −0.08 0.39 0.37 −0.14 −0.11 −0.50 −0.45 0.12LEVE 0.02 −0.25 −0.24 – 0.93 0.64 0.63 −0.36 −0.37 −0.10 −0.08 −0.31 −0.32 0.60 0.58 0.34 0.32 0.09LEVP 0.04 −0.25 −0.23 0.99 – 0.55 0.58 −0.30 −0.34 0.03 −0.00 −0.25 −0.29 0.62 0.63 0.30 0.31 0.07LEVME 0.55 −0.32 −0.31 0.25 0.27 – 0.99 −0.62 −0.61 −0.04 −0.02 −0.58 −0.59 0.35 0.30 0.76 0.75 0.20LEVMP 0.54 −0.31 −0.29 0.25 0.28 0.97 – −0.62 −0.62 −0.01 −0.01 −0.58 −0.60 0.37 0.33 0.77 0.78 0.21ROAE −0.53 0.36 0.36 −0.14 −0.16 −0.48 −0.51 – 0.99 −0.15 −0.17 0.95 0.95 −0.33 −0.28 −0.56 −0.55 −0.11ROAP −0.58 0.37 0.35 −0.14 −0.16 −0.51 −0.53 0.97 – −0.19 −0.20 0.94 0.95 −0.36 −0.31 −0.56 −0.56 −0.13SRAE 0.30 −0.08 −0.03 −0.10 −0.06 −0.02 0.06 −0.28 −0.31 – 0.97 −0.08 −0.14 0.19 0.20 0.03 0.09 0.26SRAP 0.31 −0.09 −0.06 −0.14 −0.11 −0.06 −0.03 −0.26 −0.28 0.96 – −0.10 −0.13 0.17 0.16 0.03 0.07 0.25PME −0.51 0.34 0.34 −0.13 −0.15 −0.44 −0.47 0.96 0.95 −0.26 −0.24 – 0.98 −0.30 −0.25 −0.60 −0.59 −0.09PMP −0.50 0.33 0.31 −0.13 −0.16 −0.44 −0.48 0.95 0.95 −0.31 −0.27 0.98 – −0.33 −0.30 −0.61 −0.65 −0.14VRE −0.01 −0.32 −0.31 0.84 0.83 0.11 0.11 −0.20 −0.21 0.01 −0.01 −0.19 −0.19 – 0.97 0.36 0.37 0.13VRP −0.02 −0.31 −0.30 0.84 0.83 0.10 0.11 −0.19 −0.20 0.01 −0.01 −0.18 −0.18 0.99 – 0.32 0.35 0.12VRME 0.60 −0.50 −0.50 0.06 0.06 0.61 0.57 −0.41 −0.42 0.02 0.01 −0.40 −0.40 0.06 0.05 – 0.98 0.13VRMP 0.64 −0.50 −0.49 0.07 0.08 0.67 0.65 −0.41 −0.44 0.05 0.01 −0.41 −0.42 0.06 0.05 0.98 – 0.21GUAR 0.15 0.10 0.10 −0.09 −0.09 0.14 0.16 −0.03 −0.05 0.05 0.04 −0.02 −0.02 −0.15 −0.15 0.04 0.13 –

Correlation coefficients significantly different from zero at p-values less than 0.05 are in boldface type.All variables are as defined in Table 1.

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revenue (VR). Substituting the market value of equity for book value in the leverage and revenuevolatility variables strengthens their relation with RATING. For the Pearson correlations, there isno significant relation between RATING and either LEVor VR. However, these correlations arestrongly positive for LEVM and VRM (ranging between 0.54 and 0.64). While the Spearmancorrelations between RATING and both LEV and VR are significantly positive (ranging from0.23 to 0.28), the correlations are much greater for LEVM and VRM (ranging from 0.66 to 0.74).The correlations between the independent variables are generally moderate. A notable exceptionis the correlation between ROA and PM, which ranges between 0.94 and 0.96. As the numeratorsfor these measures (i.e., net income) are the same, this reflects the high correlation between salesand total assets for manufacturing firms. Despite this high degree of correlation, collinearity is nota serious concern. Specifically, the condition indices for the regression models are less than 8,well below the rule-of-thumb critical value of 30 (Belsley, Kuh, & Welsch, 1980).

3.2. Results from regression analysis

The results from estimating models (1) and (2) via OLS regression are presented in the thirdand fourth columns of Table 3, respectively. As the model is estimated on a pooled basis,statistical significance is assessed using Huber–White robust standard errors (Huber, 1967;White, 1980). The robust estimator relaxes the assumption of independence of the observations.Further, clustering observations by firm produces correct standard errors even if the observationsare correlated and heteroscedastic (Rogers, 1993). One-sided hypothesis tests are performed forthose coefficients expected to have directional relations.

The results indicate that proportionately consolidated financial statements have greaterrelevance for explaining bond ratings, as the BBS test of relative information content rejectsequality for explaining RATING with a p-value of 0.001. The proportionate consolidation modelhas an adjusted R-squared of 0.672, while the equity method model has an adjusted R-squared of0.631. This result is contrary to Kothavala (2003), who finds that amounts based on equity

Table 3Summary statistics from OLS regression of bond ratings on equity method and proportionate consolidation accountingamounts and ratios (robust t-statistics in parentheses; N=173)

Variable Predictedsign

Models (1) and (2) Models (1′) and (2′)

(E) (P) (E) (P)

TA(E,P) − −1.90⁎⁎⁎ (−7.52) −1.76⁎⁎⁎ (−8.02) −1.36⁎⁎⁎ (−4.36) −1.23⁎⁎⁎ (−4.11)LEV(E,P) + 0.14⁎⁎⁎ (4.43) 0.13⁎⁎⁎ (3.44) – –LEVM(E,P) + – – 0.75⁎⁎⁎ (2.65) 0.43⁎⁎ (2.18)ROA(E,P) − −17.35⁎ (−1.56) −50.71⁎⁎⁎ (−5.19) −1.64 (−0.16) −30.29⁎⁎ (−2.29)SRA(E,P) + 20.26⁎⁎ (2.32) 26.71⁎⁎ (2.11) 23.10⁎⁎⁎ (3.64) 30.67⁎⁎⁎ (2.89)PM(E,P) ? −0.61 (−0.08) 20.43⁎⁎⁎ (2.95) −4.37 (−0.60) 15.28⁎ (1.70)VR(E,P) + −0.47⁎⁎⁎ (−6.66) −0.41⁎⁎⁎ (−5.38) – –VRM(E,P) + – – 0.97⁎⁎ (2.30) 1.24⁎⁎⁎ (2.93)GUAR + – – 1.18⁎ (1.33) 0.91 (1.06)BBS p-value EbP 0.001 EbP 0.045Adj R2 0.631 0.672 0.661 0.684

Coefficient estimates significantly different from zero at p-values less than 0.01 (⁎⁎⁎), 0.05 (⁎⁎), or 0.10 (⁎), based onHuber–White robust standard errors, are in boldface type. One-sided hypothesis tests are performed for those coefficientsexpected to have directional relations.The BBS p-value is from the test of relative information content in Biddle et al. (1995).All variables are as defined in Table 1.


method accounting (adjusted R-squared=0.32) have significantly greater explanatory power thanamounts based on proportionate consolidation (0.22).

Other than the BBS test results, the most notable difference across the studies is the relativeexplanatory power of the models. For the proportionate consolidation (equity method) model, theadjusted R-squared is 205% (97%) higher in the current study. This increase in explanatory powercould be due to differences in (a) U.S. and Canadian GAAP, (b) bond rating methodologies, and/or(c) sample composition. With respect to accounting methods, differences in GAAP are not a likelycause given the overall similarity between U.S. and Canadian accounting standards (Doupnik &Salter, 1993). In addition, Webster and Thornton (2004) find no evidence of significant differencesin accrual quality over the period 1990–2002 between Canadian firms reporting under CanadianGAAP and U.S. firms reporting under U.S. GAAP. Further, Leuz, Nanda, and Wysocki (2003)document low earnings management ‘scores’ in both the U.S. and Canada. With respect to the bondrating process, a review of the methodologies and criteria as described on the Standard and Poor'sand Dominion Bond Rating Service web sites reveals no substantive differences. With respect tosample composition, the current sample consists exclusively of manufacturing firms. WhileKothavala (2003) does not provide data regarding industry membership, her sample appears to bemore heterogeneous as the primary sample selection criterion is the existence of detailed data forjoint venture investments. Based on the above, sample composition is the most likely cause of thediffering BBS test results.7

With respect to individual coefficients, the estimates for all variables have the predicted sign,except for VR. Of the estimates with the expected sign, the coefficients on TA, LEV, ROA, andSRA all are significantly different from zero, as in Kothavala (2003). Based on the sample meanvalues of asset turnover (ATO), the marginal effect of PM on RATING has the expected negativesign under both the equity method (−17.35⁎0.906−0.61=−16.33) and proportionate con-solidation (−50.71⁎0.935+20.43=−26.98). The unexpected negative coefficient estimates forthe VR terms are consistent with Kothavala (2003); however, her estimates for the VR terms arenot significantly different from zero.

The results from estimating models (1′) and (2′) are presented in the last two columns of Table 3.The coefficient estimates for VRM are statistically significant with the expected positive sign underboth the equity method (0.97, t=2.30) and proportionate consolidation (1.24, t=2.93). This changein results is attributed to the substitution of market value of equity for book value of equity. Withrespect to guarantees, the coefficient estimate on GUAR for the equity method regression (1.18,t=1.33) is positive and marginally significant at the 0.095 level. While the estimate forproportionate consolidation (0.91, t=1.06) has the expected positive sign, it is not significant. Thisdifference is attributed to the explicit recognition of investee liabilities under proportionateconsolidation. While the inclusion of GUAR reduces the difference between adjusted R-squared forthe equity method (0.661) versus proportionate consolidation (0.684) regressions, the BBS test ofrelative information content indicates that the difference continues to be significant (at the 0.045level). Thus, the model modifications do not affect the inference that proportionately consolidatedfinancial statements have greater relevance for explaining bond ratings.

To assess the robustness of the results from models (1′) and (2′), several additional analyses areconducted (results not tabulated). First, yearly indicators are added to the model to control for

7 Another sample-related possibility is that a fundamental difference exists in the nature of investments investigated. Inthe present study, significant-influence equity investments encompass associates, joint ventures, partnerships, etc.whereas Kothavala (2003) focuses exclusively on joint ventures. If these investments are characteristically different, itmay explain some of the differences in results.

Table 4Summary statistics from ordered logit regression of bond ratings on equity method and proportionate consolidationaccounting amounts and ratios in models (1′) and (2′) (robust t-statistics in parentheses; N=173)

Variable Predictedsign

Coefficient (z-statistic)

(E) (P)

TA(E,P) − −1.15⁎⁎⁎ (−3.45) −1.10⁎⁎⁎ (−3.51)LEVM(E,P) + 0.61⁎⁎⁎ (2.54) 0.31⁎⁎ (1.93)ROA(E,P) − −7.99 (−0.75) −40.21⁎⁎⁎ (−3.21)SRA(E,P) + 16.04⁎⁎⁎ (3.05) 20.67⁎⁎ (2.30)PM(E,P) ? 1.58 (0.21) 22.91⁎⁎⁎ (2.50)VRM(E,P) + 0.69⁎⁎ (1.92) 1.02⁎⁎⁎ (2.57)GUAR + 0.62 (0.85) 0.42 (0.54)LR test p-value EbP 0.001Log likelihood −355.9 −345.9Psuedo adj. R2 0.215 0.237

Coefficient estimates significantly different from zero at p-values less than 0.01 (⁎⁎⁎), 0.05 (⁎⁎), or 0.10 (⁎), based onHuber–White robust standard errors, are in boldface type. One-sided hypothesis tests are performed for those coefficientsexpected to have directional relations.The LR test p-value is from the logit-based Vuong likelihood ratio test from Hillegeist et al. (2004).All variables are as defined in Table 1.


time effects. Second, net income is adjusted for non-recurring items by removing special items(Compustat item #17), adjusted for income taxes by multiplying by 1 minus the statutory tax rateof 0.35. Third, both LEV and VR are log transformed due to skewness. Fourth, the 2 firms (7observations) with negative book value are included in the estimation. Finally, an alternative towinsorization as a means to handle influential observations is utilized. Specifically, thoseobservations with studentized residuals having absolute values in excess of 3 are deleted from thesample (Belsley et al., 1980). In each of these estimations, proportionately consolidated financialstatements have significantly greater relevance for explaining bond ratings, based on the BBS testof relative information content.

The results from estimating models (1′) and (2′) via ordered logit are presented in Table 4.These results are consistent with the OLS results in Table 3, with one exception— the coefficientestimate for GUAR in the equity method regression (0.62, t=0.85) is no longer significantlygreater than zero. Both the log likelihood and pseudo R-squared for the proportionate con-solidation model (−345.9 and 0.237, respectively) exceed that for the equity method model(−355.9, 0.215). Most important, the likelihood ratio test utilized in Hillegeist, Keating, Cram,and Lundstedt (2004) rejects equality of information content in favor of proportionatelyconsolidated financial statements at the 0.001 level.

To assess the robustness of the ordered logit results, the battery of sensitivity tests describedabove is performed (results not tabulated). In each of these alternative specifications, propor-tionately consolidated financial statements continue to have significantly greater relevance forexplaining bond ratings.

4. Summary and concluding remarks

This study provides additional evidence regarding the association between bond ratings andfinancial statement amounts under proportionate consolidation versus the equity method.Utilizing a sample of Canadian firms, Kothavala (2003) surprisingly finds that equity method


statements are more relevant for bond ratings than are proportionately consolidated statements.The present study examines the same issue, using a sample of U.S. manufacturing firms. Incontrast to Kothavala (2003), the results indicate that proportionately consolidated financialstatements have greater relevance than equity method statements for explaining bond ratings. Thisresult is attributed to greater sample homogeneity. This result is not altered when guarantees ofinvestee obligations are included in the model. These findings add to the ongoing debateregarding the usefulness of financial statements prepared under alternative methods of accountingfor significant influence equity investments.

Appendix A

The following example illustrates how footnote disclosures for a sample firm are used toproportionately consolidate, on a pro forma basis, a significant influence investee. See Bauman(2003) for a more complete discussion of issues associated with proportionate consolidationbased on footnote data. At December 31, 2001, Coca Cola Bottling Co. Consolidated (“CokeBottling”) reports one material equity method investment — a 50% interest in Piedmont Coca-Cola Bottling Partnership (“Piedmont”). Financial data follow:

Coke Bottling ($ millions)

Balance sheet (equity method)
Investment in Piedmont $ 60.2 Other assets 1004.3 Total liabilities 1047.4 Shareholders' equity 17.1
Income statement (equity method)
Revenues 1022.7 Expenses 1013.2 Net income 9.5
Summarized financial statement information for Piedmont disclosed in footnotes of Coke Bottling
Total assets $ 365.5 Total liabilities 245.1 Partners' equity 120.4
Revenues
296.9 Net income 0.8
With respect to the balance sheet, pro forma proportionate consolidation involves removal of theinvestment account ($60.2) and substitution of the investor's share of investee assets and liabilities[(0.5)($365.5−245.1)=$60.2]. Although not applicable to this example, goodwill is recorded incases where the balance in the investment account exceeds the proportionate share of the investee'snet assets. With respect to the income statement, net income reported under proportionateconsolidation is equal to that reported under the equity method. When sales of inventory are madebetween investor and investee, realization does not occur until the inventory is consumed inoperations or resold to an unrelated party. Accordingly, the amount of revenues reported under proforma proportionate consolidation should be adjusted for unrealized intercompany sales. Since theinformation necessary to make this adjustment is not disclosed, no adjustment is made.


Amounts for Coke Bottling under proportionate consolidation are computed as follows:

Balance sheet (proportionate consolidation)
Investment in Piedmont 60.2−60.2=0.0 Other assets 1004.3+(0.5)(365.5)=1187.1 Total liabilities 1047.4+(0.5)(245.1)=1170.0 Shareholders' equity 17.1
Income statement (proportionate consolidation)
Revenues 1022.7+(0.5)(296.9)=1171.2 Net income 9.5
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