회계이익과 과세소득의 차이가 회사채 신용등급에 미치는 효과에 대한 재검토 및 새로운 증거

Prior research suggests that differences between book and taxable incomes reflect firms’ underlying economic fundamentals and their opportunistic earnings management activities. A number of recent studies investigate whether differences between book income and taxable income are a source of information useful to financial report users, and several key findings have emerged, including: book-tax differences (BTDs) are useful in detecting certain types of earnings and tax management (e.g., Phillips at el. 2003); large magnitude positive and negative BTDs reflect differences in earnings persistence (Hanlon 2005); the ratio of taxable income to book income is useful in predicting earnings growth and explaining security returns (Lev and Nissim 2004); and taxable income provides information about a firm’s performance and its value incremental to book income, and vice versa (Hanlon et al. 2008). Overall, previous research suggests that BTDs arises (i) from differences in book and tax reporting requirements that reflect aspects of firms’ underlying fundamentals not reflected in either income measure by itself, and (ii) from firms’ earnings and tax management activities. That is, firm value depends on both financial reporting and tax reporting decisions, and BTDs combine the effects of these decisions. Thus, we note that with regard to the quality of accounting information, BTDs can reflect firms’ earnings management as well as their tax management strategies. Therefore, we extend this literature by investigating the relation between BTDs and credit ratings to gain a deeper understanding of the information reflected in the differences between these two earnings measures and its impact on rating agencies. Meanwhile, credit ratings are determined by rating agencies’ assessments of the probability distribution of future cash flows to bondholders, which in turn, depends on the future cash flows to the firm. A firm’s creditworthiness is determined by assessing the likelihood that its future cash flows will be sufficient to cover debt service costs and principal payments. A credit rating implications include signaling, maintaining relationships with third parties such as suppliers and customers, and maintaining firms’ credit ratings in line with competitors. A credit rating represents a signal of overall quality in the capital market. So, rating agencies may face fewer incentives to detect earnings management by issuers. Hence, this study investigates the effects of firms’ BTDs on bond’s credit ratings using firms listed on KOSPI and KOSDAQ. Especially, we are trying to differentiate this study from previous studies by focusing on two aspects. One is to examine how different measures of BTDs (measured in various way) affect the relation between BTDs and credit ratings. The other is to examine whether this relation between two variables varies with the methods for sampling partition, which may represent a conditional situation. As these issues have not been well-studied, this paper is expected to give additional information to the emerging literatures on the BTDs. As in the previous studies, we anticipate that firms would report higher pre-tax book income than taxable income when managers manipulate earnings upward. In this case, credit analysts may interpret positive BTDs (i.e. where book income is more than taxable income) as a signal of decreased earnings quality, which results in less favorable credit ratings. To test this hypothesis, we use credit ratings as a dependent variable and measure of BTDs, a variable of interest, following Jeon and Kim (2008). We use 1,929 firm-year observations for the period of 2001-2010. The empirical results are as follows. First, in the tests using clustering-adjusted ordered probit regression to consider ranked order attribute of credit ratings, the negative relation between BTDs and credit ratings exhibits more evidently when we measure BTDs based on the fractional ranking of the values of variables rather than continuous values. Second, this negative relation does not change where measuring BTDs as a indicator variable. This result suggests that credit analysts consider firms with positive BTDs have higher credit risk than firms with negative BTDs. Third, these findings show a difference across the listed market. Specifically, the negative relation between BTDs and credit ratings is more pronounced for KOSPI firms than for KOSDAQ firms. Also, for KOSPI firms it is revealed that BTDs provide incremental information content beyond discretionary accruals, while we get the opposite result from KOSDAQ firms. Fourth, the above results are mostly observed in firms with positive taxable income, not in firms with negative taxable income. Fifth, when we partition full sample into sub-samples based on earnings quality or audit quality, the negative relation between two variables are more noticeable for firms with positive discretionary accruals or for firms audited by non-BIG4 auditors. These results mean that credit analysts negatively much more reflect BTDs into the bond’s credit ratings for firms with low earnings quality or low audit quality. Finally, in the additional tests, we divide the samples into deciles and examine in which decile the negative relation between two variables. We find that the negative relation exhibits just one decile of many, but also only firms from the lowest negative BTDs, irrespective of listed market. The findings of this study have contributions in that they suggest the negative relation between BTDs and credit ratings may be affected by measures of BTDs, sample partition, earnings quality, audit quality and market characteristics, while previous studies focus on investigating the relation between two variables on average. Above empirical results of this study are expected to make additional contribution to studies on the BTDs as a new evidence. Therefore, understanding the credit ratings consequences of BTDs is important and interesting in its own merit. Our findings will thus be of interest to academicians as well as managers, credit rating agencies, bondholders, and regulators alike.