Understanding earnings quality - MIT Sloan School of Management
Understanding earnings quality - MIT Sloan School of Management
Understanding earnings quality - MIT Sloan School of Management
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lower book values <strong>of</strong> assets (higher book values <strong>of</strong> liabilities) in the early periods <strong>of</strong> an asset or<br />
liability life. 18<br />
The most frequently used measure <strong>of</strong> timely loss recognition is the reverse <strong>earnings</strong>-returns<br />
regression from Basu (1997).<br />
Earningst+1=α0 + α1Dt + β0Rett+β1Dt Rett + εt<br />
where D = 1 if Ret < 0, and a higher β1 implies more timely loss recognition. The specification is<br />
reported in Exhibit 1. Basu (1997) provides a second measure that is not based on returns.<br />
ΔΝΙτ =α0 +α1NEGDUM+α2ΔΝΙτ_1+α3(NEGDUM*ΔΝΙτ_1) + ετ<br />
where ΔNIt is the change in income from year t-1 to t, scaled by beginning book value <strong>of</strong> total assets,<br />
and NEGDUM is an indicator variable equal to one if ΔNIt-1 is negative. If bad news is recognized<br />
on a more timely basis than good news, negative <strong>earnings</strong> changes will be less persistent and will<br />
tend to reverse more than positive <strong>earnings</strong> changes. This translates into a prediction that α3 < 0,<br />
and Basu (1997) finds support for this prediction. This tendency-to-reverse measure is used in some<br />
papers when equity returns are not available (e.g., Ball and Shivakumar, 2005), and it is used in<br />
other papers to check the robustness <strong>of</strong> the results. 19<br />
Our review <strong>of</strong> the asymmetric timeliness literature focuses on studies <strong>of</strong> the determinants and<br />
consequences <strong>of</strong> asymmetric timeliness, specifically when it is a suggested measure <strong>of</strong> <strong>quality</strong>. Ryan<br />
(2006) provides a recent and thorough review <strong>of</strong> the literature on conservatism, more generally<br />
including measurement issues.<br />
18<br />
Basu (1997) uses the term conditional to describe his measure <strong>of</strong> conservatism, but he does not specifically call it<br />
“conditional conservatism.”<br />
19<br />
The use <strong>of</strong> this measure to check the robustness <strong>of</strong> the results based on the Basu (1997) reverse regression measure has<br />
increased since the publication <strong>of</strong> Dietrich, Muller, and Riedl (2007), which suggests that the reverse regression measure<br />
is biased. Ryan (2006) questions the magnitude <strong>of</strong> the bias, but also provides some possible solutions.<br />
48