3. Research design and sample selection
3.1. The Basu conservatism metric
Basu’s (1997) differential timeliness (DT) metric is the most commonly used proxy for conservatism, and is the primary
conservatism metric investigated in this study. Conservatism is measured as the extent to which negative returns (bad
news) are reflected in reported earnings more rapidly than positive returns (good news). The Basu model is as follows:
NIit ¼ a0 þ a1 NEGit þ a2 RET it þ a3 RET it  NEGit þ eit :
ð1Þ
In Eq. (1), NIit is the scaled net income for year t; RETit is the stock return over year t; and NEGit is defined as zero if RETit
is positive, and as one if RETit is negative. Coefficient a2 is the slope coefficient for positive RETit; the slope coefficient for
negative RETit is a2 þ a3; and a3 is the differential slope for bad versus good economic news (differential timeliness, DT).
Earnings are conservative if net income is more sensitive to bad news than to good news, that is, if a3 is positive.
See Appendix for the definitions of all the variables.
3. Research design and sample selection3.1. The Basu conservatism metric Basu’s (1997) differential timeliness (DT) metric is the most commonly used proxy for conservatism, and is the primaryconservatism metric investigated in this study. Conservatism is measured as the extent to which negative returns (badnews) are reflected in reported earnings more rapidly than positive returns (good news). The Basu model is as follows:NIit ¼ a0 þ a1 NEGit þ a2 RET it þ a3 RET it  NEGit þ eit :ð1Þ In Eq. (1), NIit is the scaled net income for year t; RETit is the stock return over year t; and NEGit is defined as zero if RETitis positive, and as one if RETit is negative. Coefficient a2 is the slope coefficient for positive RETit; the slope coefficient fornegative RETit is a2 þ a3; and a3 is the differential slope for bad versus good economic news (differential timeliness, DT).Earnings are conservative if net income is more sensitive to bad news than to good news, that is, if a3 is positive.See Appendix for the definitions of all the variables.
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