Understanding earnings quality - MIT Sloan School of Management
Understanding earnings quality - MIT Sloan School of Management
Understanding earnings quality - MIT Sloan School of Management
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
methodology. Studies could make unique predictions across proxies. The predictions may be in<br />
degrees: determinant X is predicted to have a stronger impact on <strong>quality</strong> proxy Y than on Z. Or, the<br />
tests may be designed to assess divergent validity (i.e., counterfactual examples): determinant X is<br />
predicted to be associated with <strong>quality</strong> proxy Y but not with Z. A greater focus on stronger<br />
identification strategies in research designs could help sort out the mixed evidence given the various<br />
methodological issues associated with distinguishing the fundamental component <strong>of</strong> <strong>earnings</strong> <strong>quality</strong><br />
from the process.<br />
3. Proxies for <strong>earnings</strong> <strong>quality</strong><br />
This section juxtaposes the studies according to the proxy they use for <strong>earnings</strong> <strong>quality</strong> (see<br />
Table 1, Panel A). We define three categories <strong>of</strong> proxies: 1) Properties <strong>of</strong> <strong>earnings</strong>; 2) Earnings<br />
response coefficients (ERCs); and 3) External indicators <strong>of</strong> financial reporting <strong>quality</strong> (FRQ).<br />
3.1 Properties <strong>of</strong> <strong>earnings</strong><br />
We distinguish four groups <strong>of</strong> <strong>earnings</strong> properties: Persistence, asymmetric timeliness and<br />
timely loss recognition, smoothness <strong>of</strong> <strong>earnings</strong>, and “benchmarking.” Section 3.1.1 discusses<br />
research that examines the persistence <strong>of</strong> <strong>earnings</strong> and accrual models. Studies that use the term<br />
predictability and examine <strong>earnings</strong> usefulness to predict future cash flows are included in this<br />
section as well. Section 3.1.2.examines research on <strong>earnings</strong> smoothness and variability. The<br />
benchmarking category (Section 3.1.4) includes measures <strong>of</strong> <strong>earnings</strong> relative to any benchmark.<br />
26