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Understanding earnings quality - MIT Sloan School of Management

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Exhibit 1, continued<br />

Empirical proxy Theory Strengths and weakness<br />

Accruals<br />

Accruals= Earningst - CFt<br />

Accruals=Δ(noncash working capital)<br />

Accruals= Δ(net operating assets)<br />

Specific accrual components<br />

Residuals from accrual models<br />

Error term from regressing accruals<br />

on their economic drivers<br />

(See Exhibit 2)<br />

ERCs<br />

Rett+1= α+β(EarningsSurpriset)+εt<br />

More informative components <strong>of</strong><br />

<strong>earnings</strong> will have a higher β. More<br />

value relevant <strong>earnings</strong> will have a<br />

higher R 2 .<br />

External indicators <strong>of</strong><br />

financial reporting <strong>quality</strong><br />

∗ AAERs identified by SEC<br />

∗ Restatements<br />

∗ SOX reports <strong>of</strong> internal control<br />

deficiencies<br />

Extreme accruals are low <strong>quality</strong><br />

because they represent a less<br />

persistent component <strong>of</strong> <strong>earnings</strong>.<br />

Residuals from accrual models<br />

represent management discretion or<br />

estimation errors, both <strong>of</strong> which<br />

reduce decision usefulness.<br />

Investors respond to information<br />

that has value implications. A<br />

higher correlation with value<br />

implies that <strong>earnings</strong> better reflect<br />

the fundamental <strong>earnings</strong> process.<br />

Firms had errors (AAERs and<br />

restatement firms) or are likely to<br />

have had errors (internal control<br />

deficiencies) in their financial<br />

reporting systems, which imply low<br />

<strong>quality</strong>.<br />

173<br />

Pros: The measure gets directly at the role <strong>of</strong> an accruals-based accounting<br />

system relative to a cash-flow based system.<br />

Cons: The fundamental <strong>earnings</strong> process differs for firms with extreme<br />

accruals versus less extreme accruals, which hinders interpretation.<br />

Pros: The measure attempts to isolate the managed or error component <strong>of</strong><br />

accruals. The use <strong>of</strong> these models has become the accepted methodology in<br />

accounting to capture discretion.<br />

Cons: Tests <strong>of</strong> the determinants/consequences <strong>of</strong> <strong>earnings</strong> management are<br />

joint tests <strong>of</strong> the theory and the abnormal accrual metric as a proxy for<br />

<strong>earnings</strong> management. Correlated omitted variables associated with<br />

fundamentals, especially performance, are <strong>of</strong> utmost concern given the<br />

dependence <strong>of</strong> normal accruals on fundamentals and the endogeneity <strong>of</strong> the<br />

hypothesized determinants/consequences with the fundamentals.<br />

Pros: The measure directly links <strong>earnings</strong> to decision usefulness, which is<br />

<strong>quality</strong>, albeit specifically in the context <strong>of</strong> equity valuation decisions.<br />

Cons: Assumes market efficiency. In addition, inferences are impaired by<br />

correlated omitted variables that affect investor reaction (including<br />

endogenously determined availability <strong>of</strong> other information), measurement<br />

error <strong>of</strong> unexpected <strong>earnings</strong>, and cross-sectional variation in returngenerating<br />

processes.<br />

Pros: Unambiguously reflect accounting measurement problems (low Type I<br />

error rate). The researcher does not have to use a model to identify low<br />

<strong>quality</strong> firms.<br />

Cons: For AAERs: small sample sizes, selection issues, and matching<br />

problems due to type II error rate. For restatements and SOX firms: problems<br />

with distinguishing intentional from unintentional errors or ambiguities in<br />

accounting rules that lead to errors.

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