Medidas generales para garantizar el respeto y la protección de las

H1c predicts that the introduction of AASB 5 in 2005, which broadened the definition of discontinued operations (DO) by including as DO assets ‘held for sale’, increases the scope for firms to opportunistically classify core expenses as DO, and thereby increase core earnings. If firms report DO opportunistically, I expect unexpected core earnings to increase with the magnitude of income-decreasing DO. However, as is the case with AI, a positive association could also arise from enhanced operations after the discontinuation of a loss-making operation (Barua et al. 2010). In this case, the improvement in core earnings should persist in the following period. However, if the improvement is due to classification shifting, I expect a negative association between the unexpected change in core earnings in year t+1 and DO in year t.

To test H1c, I examine samples from the post-IFRS period (31 December 2005-31 December 2009) only, because the separate reporting of DO ‘below the line’ was extremely rare prior to the adoption of AASB 5.79 The models below are based on those of Barua et al. (2010):

UE_CEt= γ0+ γ1%DOt+ γ2SIZEt+ γ3ROAt+ γ4CFOt+ γ5LEVt+ γ6LOSSt +

γ7AUDITORt+ εt (5a)

UE_∆CEt+1 = ω0+ ω1%DOt+ ω2%DOt+1 + ω3SIZEt+ ω4ROAt + γ5CFOt+ ω6LEVt

+ ω7LOSSt+ ω8AUDITORt+ νt+1 (5b)

79 _{There are only 3 such Australian-domiciled firm-years identified in the Morningstar data in the pre-} IFRS period.

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Where variables are as defined below:

UE_CEt = As defined for Model (3a) in Section 4.3.3.

UE_∆CEt+1 = As defined for Model (3b) in Section 4.3.3.

%AIt = As defined for Models (3a) and (3b) in Section 4.3.3.

IFRS t = An indicator variable = 1 for the period 31 December

2005 to 31 December 2009, 0 otherwise.

%DOt = The value of the net gains from DO (i.e. gains less

expenses from DO) in year t (#8033) multiplied by -1, scaled by sales in year t

Control Variables = As defined for Models (3a) and (3b) in Section 4.3.3 Because a positive value of %DOt indicates that net losses were treated as DO, I expect

%DOt to be positively associated with UE_CEt if firms engage in classification shifting

using DO to inflate core earnings. If such relationship is due to opportunistic classification shifting, I expect the higher than expected UE_CEtin year t estimated in

Model (5a), to reverse in year t+1. Thus, I expect a negative association between %DOt

and UE_∆CEt+1 in Model (5b) as core expenses recur in year t+1 as part of core earnings.80 _{Consistent with Barua et al. (2010), I control for the level of DO in year t+1} by adding %DOt+1 in Equation (5b), and predict a positive coefficient for ω2.81 The remaining control variables are identical to those used in tests of H1a and H1b.

I follow Barua et al. (2010) and further distinguish the effects of negative DO from reported DO because a firm’s classification shifting behaviour could vary depending on the sign of DO. For example, managers might be more likely to engage in greater classification shifting if net DO already represent losses and are less likely to misclassify items as DO if they represent profits (Barua et al. 2010).82 Thus, I

80 _{A negative association is expected only if the coefficient for %DO}

t in the ‘levels’ model was positive. 81 _{Barua et al. (2010) explains that a positive association between unexpected core earnings (UE_CE}

t) and

discontinued operations (%DOt) can arise mechanically due to the use of lagged core earnings (CEt-1) in the expected core earnings model to determine unexpected core earnings. Discontinued operations (DO) are more often loss-making operations that a firm’s core earnings can improve when a loss-making operation is discontinued, therefore mechanically creating a positive association between UE_CEt and

%DOt. Barua et al. (2010) addresses this problem by using restated data to calculate variables for firms

reporting DO. Future replication of this study could explore this option.

82 _{For example, a manager may blame poor firm results on DO sold at a loss by increasing the operating} loss of the DO (Barua et al. 2010).

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substitute %DO_NEGt (DO with aggregate losses) for the net variable %DOt in the

following equations:

UE_CEt= π0+ π1%DO_NEGt+ π2SIZEt+ π3ROAt+ π4CFOt+ π5LEVt

+ π6LOSSt+ π7AUDITORt+ ψt (6a)

UE_∆CEt+1 = λ0+ λ1%DO_NEGt+ λ2%DO_NEGt+1+ λ3SIZEt+ λ4ROAt+ λ5CFOt

+ λ6LEVt+ λ7LOSSt+ λ8AUDITORt + ωt+1 (6b)

Where variables are as defined below:

%DO_NEGt = DO (i.e. gains less expenses from DO) (#8033) multiplied

by -1, scaled by sales, both in year t when reported aggregate DO are income-decreasing, and 0 otherwise.

Other Variables = As previously defined.

If firms opportunistically classify income-decreasing DO, I expect π1 to be positive and λ1 to be negative. I also control for DO in year t+1 by adding %DO_NEGt+1 in Equation (6b) and expect positive coefficients for λ2.