The market pricing of accruals quality

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Abstract

We investigate whether investors price accruals quality, our proxy for the information risk associated with earnings. Measuring accruals quality (AQ) as the standard deviation of residuals from regressions relating current accruals to cash flows, we find that poorer AQ is associated with larger costs of debt and equity. This result is consistent across several alternative specifications of the AQ metric. We also distinguish between accruals quality driven by economic fundamentals (innate AQ) versus management choices (discretionary AQ). Both components have significant cost of capital effects, but innate AQ effects are significantly larger than discretionary AQ effects.

Introduction

This study investigates the relation between accruals quality and the costs of debt and equity capital for a large sample of firms over the period 1970–2001. Our study is motivated by recent theoretical research that shows that information risk is a non-diversifiable risk factor (e.g., Easley and O’Hara, 2004; O’Hara, 2003; Leuz and Verrecchia, 2004). By information risk, we mean the likelihood that firm-specific information that is pertinent to investor pricing decisions is of poor quality. We assume that cash flow is the primitive element that investors price and identify accruals quality as the measure of information risk associated with a key accounting number—earnings. That is, accruals quality tells investors about the mapping of accounting earnings into cash flows. Relatively poor accruals quality weakens this mapping and, therefore, increases information risk.

Our paper makes two contributions. First, consistent with theories that demonstrate a role for information risk in asset pricing, we show that firms with poor accruals quality have higher costs of capital than do firms with good accruals quality. This result is consistent with the view that information risk (as proxied by accruals quality) is a priced risk factor. Second, we attempt to disentangle whether the components of accruals quality—accruals that reflect economic fundamentals (innate factors) and accruals that represent managerial choices (discretionary factors)—have different cost of capital effects. While theory does not distinguish among the sources of information risk, prior research on discretionary accruals (e.g., Guay et al., 1996; Subramanyam, 1996) provides a framework in which discretionary accruals quality and innate accruals quality will have distinct cost of capital effects. Briefly, this body of work suggests that, in broad samples, discretionary accrual choices are likely to reflect both opportunism (which exacerbates information risk) and performance measurement (which mitigates information risk); these conflicting effects will yield average cost of capital effects for discretionary accruals quality that are likely lower than the cost of capital effects for innate accruals quality. Consistent with this view, we find that innate accruals quality has larger cost of capital effects than does discretionary accruals quality.

The accruals quality (AQ) metric we use is based on Dechow and Dichev's (2002) model which posits a relation between current period working capital accruals and operating cash flows in the prior, current and future periods. Following McNichols (2002) discussion of this model, we also include the change in revenues and property, plant and equipment (PPE) as additional explanatory variables. In this framework, working capital accruals reflect managerial estimates of cash flows, and the extent to which those accruals do not map into cash flows, changes in revenues and PPE—due to intentional and unintentional estimation errors—is an inverse measure of accruals quality.

Our tests examine the relation between AQ and the costs of debt and equity capital. We find that firms with poorer AQ have higher ratios of interest expense to interest-bearing debt and lower debt ratings than firms with better AQ (all differences significant at the 0.001 level). Controlling for other variables known to affect debt costs (leverage, firm size, return on assets, interest coverage, and earnings volatility), the results suggest that firms with the best AQ enjoy a 126 basis point (bp) lower cost of debt relative to firms with the worst AQ. In terms of the cost of equity, tests focusing on earnings–price ratios show that firms with lower AQ have significantly (at the 0.001 level) larger earnings–price ratios relative to their industry peers; i.e., a dollar of earnings commands a lower-price multiple when the quality of the accruals component of those earnings is low. More direct tests show that CAPM betas increase monotonically across AQ quintiles, with a difference in betas between the lowest and highest quintiles of 0.35 (significantly different from zero at the 0.001 level). Assuming a 6% market risk premium, this difference implies a 210 bp higher cost of equity for firms with the worst AQ relative to firms with the best AQ. In asset-pricing regressions which include market returns and an accruals quality factor (AQfactor), we find that not only is there a significant (at the 0.001 level) positive loading on AQfactor, but also the coefficient on the market risk premium (i.e., the estimated beta) decreases in magnitude by nearly 20%. Extending this analysis to the three-factor asset-pricing regression, we find that AQfactor adds significantly to size and book to market (as well as the market risk premium) in explaining variation in expected returns. In these regressions, the largest change in coefficient estimates (relative to the model which excludes AQfactor) is noted for the size factor where the average loading declines by about 30% when AQfactor is included. We conclude that accruals quality not only influences the loadings on documented risk factors, but contributes significant incremental explanatory power over and above these factors.

We extend these analyses by investigating whether the pricing of accruals quality differs depending on whether the source of accruals quality is innate, i.e., driven by the firm's business model and operating environment, or discretionary, i.e., subject to management interventions. Following Dechow and Dichev, we identify several summary indicators of the firm's operating environment or business model: firm size, standard deviation of cash flows, standard deviation of revenues, length of operating cycle, and frequency of negative earnings realizations. Our first analysis uses the fitted values from annual regressions of AQ on these summary indicators as the measure of the innate portion of accrual quality; the residual is used as the measure of discretionary accruals quality. Our second analysis of innate versus discretionary components includes these summary indicators as additional control variables in the cost of capital tests. Controlling for these variables allows us to interpret the coefficient on (total) AQ as capturing the pricing effects associated with the discretionary piece of accruals quality—i.e., the piece that is incremental to the innate factors. Regardless of the approach used to isolate the components of AQ, we find that the cost of capital effect of a unit of discretionary AQ is smaller both in magnitude and statistical significance than the cost of capital effect of a unit of innate AQ.

Overall, we interpret our results as documenting cost of capital effects that are consistent with a rational asset-pricing framework in which accruals quality captures an information risk factor that cannot be diversified away. The findings concerning innate and discretionary accruals quality are consistent with information risk having larger pricing effects when it is driven by firm-specific operating and environmental characteristics than when it is associated with discretionary decisions.

We believe these results have implications for assessments of reporting quality. First, we provide systematic evidence that reporting quality as captured by accruals quality is salient for investors; i.e., we provide evidence that reporting quality matters. Second, our results contradict an implicit assumption in some policy-oriented discussions (e.g., Levitt, 1998) that reporting quality is largely determined by management's short-term reporting choices; our results suggest that in broad samples, over long periods, reporting quality is substantially more affected by management's long-term strategic decisions that affect intrinsic factors. For those who believe that financial reporting should reflect economic conditions more than management implementation decisions, this result suggests that accrual accounting is performing as intended. Third, research which has assessed the relative importance of reporting standards versus implementation decisions using a cross-jurisdictional design (e.g., Ball et al., 2003) has concluded that the reporting standards are less important than the incentives which drive implementation decisions in determining differences in earnings quality across jurisdictions. Our results suggest that this analysis should be further conditioned on innate factors that capture jurisdiction-specific features of business models and operating environments.

In addition to research pertaining to the pricing of information risk, our results relate to other streams of accounting research. The first stream investigates the capital market effects of financial reporting, as documented by adverse capital market consequences (in the form of shareholder losses) when earnings are of such low quality as to attract regulatory or legal attention. For example, previous research has documented severe economic consequences for earnings of sufficiently low quality as to attract SEC enforcement actions (Feroz et al., 1991; Dechow et al., 1996; Beneish, 1999), shareholder lawsuits (Kellogg, 1984; Francis et al., 1994), or restatements (Palmrose et al., 2004). The financial press also provides ample anecdotal evidence of catastrophic shareholder losses associated with the (arguably) lowest quality accruals, those resulting from financial fraud. However, research on severely low earnings quality firms does not establish a general relation between reporting quality and capital market consequences. Our results show that the quality of one component of earnings—accruals—has economically meaningful consequences for broad samples of firms, unconditional on external indicators of extremely poor quality.

A second stream of related research explores a different, and explicitly anomalous, form of capital market effects of accruals. By anomalous effects we mean systematic patterns in average returns not explained by the CAPM (Fama and French, 1996). Specifically, this research shows that firms with relatively (high) low magnitudes of signed accruals, or signed abnormal accruals, earn (negative) positive risk-adjusted returns (e.g., Sloan, 1996; Xie, 2001; Chan et al., 2001). While both anomaly research and our investigation are concerned with the relation between accruals-based measures and returns, the perspectives differ. Whereas anomaly research views the abnormal returns associated with observable firm attributes as arising from slow or biased investor responses to information, we view observable firm characteristics as proxies for underlying, priced risk factors. Consistent with this view, our tests are based on unsigned measures. That is, we predict that larger magnitudes of AQ are associated with larger required returns because a larger magnitude of AQ indicates greater information risk, for which investors require compensation in the form of larger expected returns. In contrast, anomaly research rests on signed accruals measures; this research predicts positive returns to firms with the largest negative accruals and negative returns to firms with the largest positive accruals. While the anomaly research perspective and our perspective imply the same predictions about large negative accruals, the perspectives imply the opposite predictions for large positive accruals. Consistent with this argument, we find that while the profitability of the accruals trading strategy is marginally reduced by the inclusion of accruals quality as a control (risk) factor, the abnormal returns remain reliably positive. We conclude that the accruals quality pricing effects that we document are distinct from the accruals anomaly.

A third stream of related research assesses the relation between costs of capital and measures of either the quantity of information communicated to investors, or some mixture of quality/quantity attributes of that information. For example, Botosan (1997) finds evidence of higher costs of equity for firms with low analyst following and relatively low disclosure scores, where the scores capture information quantity. Research has also found a relation between both the cost of equity (Botosan and Plumlee, 2002) and the cost of debt (Sengupta, 1998) and analyst-based (AIMR) evaluations of aggregate disclosure efforts, where the evaluations take into account annual and quarterly reports, proxy statements, other published information and direct communications to analysts. Our analysis adds to this work by providing evidence on the link between the costs of debt and equity capital and measures of the quality of accruals information.

Finally, while our perspective on the relation between accruals quality and costs of capital is that accruals quality—whether innate or discretionary—has the potential to influence costs of capital, recent related work by Cohen (2003) explores whether exogenous variables explain both reporting quality and its economic consequences. Cohen first estimates the probability that reporting quality for a given firm is above the industry median and then tests for an association between this binary indicator of reporting quality and proxies for economic consequences. He finds reporting quality is associated with bid-ask spreads and analyst forecast dispersion, but not with his implied estimates of the cost of equity capital. While both Cohen's and our studies are complementary in identifying firm-specific variables that are intended to capture intrinsic influences on reporting outcomes, they differ considerably in terms of sample period, data, variable selection and measurement, and research design, so results are not comparable.1

In the next section, we develop hypotheses and describe the proxy for accruals quality used to test these hypotheses. Section 3 describes the sample and provides descriptive information on the test and control variables. Section 4 reports tests of whether (total) accruals quality is related to the cost of capital and Section 5 extends these tests by examining whether the innate and discretionary components of accruals quality are separately and differentially priced. Section 6 reports the results of robustness checks and additional tests. Section 7 concludes.

Section snippets

Theories of the pricing of information risk

Our paper builds on theoretical research investigating how the supply of information affects the cost of capital. Easley and O’Hara (2004) develop a multi-asset rational expectations model in which the private versus public composition of information affects required returns and thus the cost of capital. In their model, relatively more private information increases uninformed investors’ risk of holding the stock, because the privately informed investors are better able to shift their portfolio

Sample and description of accruals quality proxies

We calculate values of AQj,t=σ(υj)t for all firms with available data for the 32-year period t=1970-2001. To be included in any of the market-based tests, we require that each firm-year observation has data on AQ and the necessary market measures. Because σ(υj)t is based on five annual residuals, our sample is restricted to firms with at least 7 years of data (recall that Eq. (1) includes both lead and lag cash flows). This restriction likely biases our sample to surviving firms which tend to

Accruals quality and the costs of debt and equity capital

Our first set of tests examines the association between accruals quality and proxies for costs of capital: cost of debt (Section 4.1) and cost of equity, as captured by industry-adjusted earnings–price ratios (Section 4.2) and factor loadings in conventional one-factor and three-factor asset-pricing models (Section 4.3). For each test, we merge the sample described in Section 3 with all observations with the market and accounting data dictated by that test. Of the 91,280 firm-year observations

The pricing of innate versus discretionary accruals quality

The results in Table 2, Table 3 demonstrate that total accruals quality is priced by the market. In this section we test Hypothesis 2, which considers differential pricing effects for the innate versus discretionary components of accruals quality. Our tests use the two approaches described in Section 2.3.2 to distinguish the innate and discretionary components of accruals quality.

Additional tests

In this section, we summarize the results of several sensitivity tests (Section 6.1), and we describe two supplemental tests. The first supplemental test investigates whether changes in accruals quality are predictably associated with changes in the proxies for costs of capital (Section 6.2); the second examines the relation between our findings and the accruals anomaly (Section 6.3).

Conclusions

We find that investors price securities in a manner that reflects their awareness of accruals quality: lower-quality accruals are associated with higher costs of debt, smaller price multiples on earnings, and larger equity betas. Moreover, accruals quality loads as a separate factor in explaining variation in excess returns when added to both one- and three-factor asset-pricing regressions. Our results are consistent across securities (debt and common equity), estimation procedures (pooled

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    This research was supported by the Fuqua School of Business, Duke University and the University of Wisconsin. The views expressed in the paper are those of the authors’ and do not represent positions of the Financial Accounting Standards Board. Positions of the Financial Accounting Standards Board are arrived at only after extensive due process and deliberation. We appreciate comments from Ross Watts (the editor) and Charles Wasley (the referee); from workshop participants at the Boston Area Research Colloquium, Duke, Missouri, Northwestern, Rochester, University of Southern California, the Southeast Accounting Research Conference 2002 and the Stockholm Institute for Financial Research Conference; and from Jan Barton, Sudipta Basu, George Benston, Larry Brown, Stephen Brown, Marty Butler, Qi Chen, John Graham, John Hand, Grace Pownall, Eddie Riedl, Michael Smith, Greg Waymire, Joanna Wu and Jerry Zimmerman.

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