LA POLÉMICA ENTRE LA VISIÓN CUANTITATIVA Y LA VISIÓN CUALITATIVA DE LA

5.4.2.1 Dependent variables: Accounting conservatism

The study uses two proxies to measure accounting conservatism: (i) the C-Score measure (CON-KW) of Khan and Watts (2009), and (ii) the accrual-based measure (CON-ACC) of Givoly and Hayn (2000).

5.4.2.1.1 The C-Score measure (CON-KW)

Following Khan and Watts (2009), the current study uses C-Score as the first firm-year measure of conservatism. The C-Score measure is based on the timely loss recognition measure introduced by Basu (1997). The standard Basu (1997) regression is specified as

Xi = β1 + β2Di + β3Ri + β4DiR i+ εi (1) Where i indexes the firm, X is earnings, R is stock returns and D is an indicator variable— it is set equal to one if R is negative and is set equal to zero otherwise—and ε is the

182 regression residual. In the above regression, β3 measures the response of earnings to returns

when returns are positive, and (β3 + β4) measures the response of earnings to returns when

returns are negative. Conservatism thus implies β3 + β4 > β3, that is, β4>0. In other words, β4

captures the incremental timeliness for bad news relative to good news. Basu (1997) calls β4 the asymmetric timeliness coefficient of earnings and uses it as a measure of

conservatism.

Khan and Watts (2009) express the timeliness of good news and the incremental timeliness of bad news as linear functions of firm-specific characteristics for each year. In particular, they use the following specifications to estimate the timeliness of good news (G-Score) and the incremental timeliness of bad news (C-Score), respectively:

G-Score = β3= μ1 + μ2Sizei + μ3MTBi + μ4LEVi (2)

C-Score = β4= λ1+ λ2Sizei + λ3MTBi + λ4LEVi (3) Where Size is the market value of equity, MTB is the market-to-book value of equity and LEV is leverage.

Next, β3 and β4 from equations (2) and (3) are substituted into the regression model (1) to

get the following model:

Xi=β1+ β2Di + Ri (μ1+ μ2Sizei + μ3MTBi + μ4LEVi) + DiRi(λ1+ λ2Sizei + λ3MTBi

+ λ4LEVi)+εi (4)

Consistent with Khan and Watts (2009), the study measures X as net income before extraordinary items scaled by lagged market value of equity, R as annual return calculated by cumulating monthly returns ending with the third month after the fiscal year, Size as the natural log of the market value of equity, MTB as the ratio of market-to-book value of

183 equity at the end of the year, and LEV as long-term debt plus short term debt scaled by market value of equity.

The model (4) is then estimated cross-sectionally on an annual basis to determine the regression coefficient. To calculate C-Score, there are four coefficients of interest: the coefficient of DiRi (λ1), and the interactions of this term with each of Size (λ2), MTB (λ3),

and Leverage (λ4). These four coefficients (λ1-λ4) are then applied to model (3) to calculate

the C-Score. Specifically, the C-Score is constructed by multiplying λ1 by one, λ2 by the

firm year value of Size, λ3 by the firm-year value of MTB and λ4 by the firm-year value of

Leverage. The higher the value of the C-Score, the higher is the level of accounting conservatism of the firm. Table 5.2 reports the mean coefficients from annual cross- sectional estimations of the regression in model (4) above.

As shown in Table 5.2, the coefficient of D x Ret is significantly positive as expected. This suggests that Malaysian listed firms are conservative on average. The coefficient of D x Ret x Size is significantly negative (p<0.05), consistent with larger firms having lower asymmetric timeliness. This indicates that larger listed firms in Malaysia are less conservative. Surprisingly, the coefficients of D x Ret x MtB and D x Ret x Lev are significantly negative (p<0.05). The results reveal that firms with high growth rate and leverage have lower asymmetric timeliness. These findings are inconsistent with those of Khan and Watts (2009), who found that firms in the United States with high leverage and high growth rates have higher asymmetric timeliness.

184 The inconsistency in results could be because U.S. corporate debt is mostly from public sources. Public debt providers monitor firms through public disclosures to ensure that managers do not distribute excessive dividends to shareholders nor compensate themselves at the expense of the debt holders. Therefore, debt holders would expect managers to report earnings conservatively. For growth, US firms are general reliant on public sources of funding, which would require them to provide better quality accounting earnings information. Whereas, in Malaysia funding is primarily through private sources (private debt and private equity). Private sources rely more on private information, thus it may not require better quality publicly disclosed accounting information such as accounting earnings.

185

Table 5.2: Coefficients from the Regression Equation (4)

Xi=β1+ β2Di + Ri (μ1+ μ2Sizei + μ3MTBi + μ4LEVi) + DiRi(λ1+ λ2Sizei + λ3MTBi + λ4LEVi)+ εi

Independent Variable Predicted sign Coefficient t-stat

Intercept -0.092 D 0.267 Ret -0.227 -0.616*** Ret x Size + 0.139 0.648*** Ret x MtB - -0.553 0.3525*** Ret x Lev - 0.423 1.082 D x Ret (λ1) + 3.860 3.127*** D x Ret x Size (λ2) - -0.623 -2.483*** D x Ret x MtB (λ3) + -0.556 -0.520** D x Ret x Lev (λ4) + -1.463 -0.881 D x Size _-0.028 D x MtB _-0.052 D x Lev _0.007 Size _0.002 MtB _-0.002 Lev -0.101 Adjusted R-Square 35.475

x *significant at 0.1 ** significant at 0.05 *** significant at 0.01

Xi is net income before extraordinary items, scaled by beginning of the year market capitalisation. D is a

dummy variable equal to 1 if returns (Ret) are negative and 0 otherwise. MtB is the market-to-book ratio. Lev is leverage, defined as long term debt plus short term debt deflated by market value of equity. The study