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Understanding earnings quality - MIT Sloan School of Management

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Hung (2001) index <strong>of</strong> accrual accounting intensity and negatively associated with share ownership<br />

concentration. Somewhat weaker evidence suggests that the occurrence <strong>of</strong> the accrual anomaly is<br />

negatively related to investor rights. Pincus et al. (2007) interpret the results, taken together, as<br />

suggestive that <strong>earnings</strong> management is associated with the accrual anomaly. Biddle and Hilary<br />

(2006) document that smoothness using the Leuz et al. (2003) measure is associated with lower<br />

investment efficiency as measured by investment cash flow sensitivity metrics (see also Verdi, 2006).<br />

4.4 Summary<br />

The cross-country studies allow inferences about the impact <strong>of</strong> certain control mechanisms<br />

that are not possible using a sample <strong>of</strong> U.S. firms because <strong>of</strong> a lack <strong>of</strong> variation in the control<br />

mechanism within the U.S. This branch <strong>of</strong> studies generally concludes that <strong>earnings</strong> <strong>quality</strong><br />

(including <strong>earnings</strong> management) is influenced by investor protection, bank versus market-oriented<br />

economy, code versus common law tradition, accounting standards, and managers’ and auditors’<br />

incentives. There is not much conflicting evidence. The cross-country variation is generally<br />

asserted to proxy for very broad theoretical constructs such as differences in the demand for<br />

information or the ability <strong>of</strong> accounting rules to reflect fundamental value. The cross-country<br />

studies are not designed to provide inferences about specific internal control mechanisms.<br />

The cross-country studies commonly use return-based <strong>earnings</strong> <strong>quality</strong> measures such as<br />

ERCs and timely loss recognition. There are many differences across countries that can affect these<br />

returns-based metrics other than the institutional factors envisioned as determinants by the<br />

researchers. The studies clearly recognize the potential for alternative explanations for the results,<br />

and most studies either use empirical methods to control for un-modeled sources <strong>of</strong> cross-country<br />

variation or model expected sources <strong>of</strong> variation such as industry concentration. However, even<br />

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