Analyses and Results of the Total sample period (2000-2013)

We begin the analysis by examining whether the cost of equity differed for IFRS adopters, and whether the heterogeneity in the economic benefits was influenced by the level of uncertainty avoidance (UAI) present in the country. The main prediction for this section is that the economic benefits from IFRS adoption should be greater for those firms that are located in higher UAI countries.

5.1.Analysis of IFRS adoption and UAI on capital market benefits We begin the analysis by examining the influence of UAI on cost of Equity (Realized returns) between firms reporting using IFRS. In Table III-9, we estimate the empirical specification in Equation (1), and include Daske et al’s (2013) SERIOUS adopter variables as additional control variables in subsequent equations. For each dependent variable, our first regression excludes IFRS as an explanatory variable, our second regression includes the IFRS variable as an additional explanatory variable, the third regression adds the interaction of UAI with IFRS alongside the main variables of interest (IFRS and UAI), while the fourth, fifth and sixth variables add each of the SERIOUS variables as an additional control variable. We expect the IFRS variable to be significant and negative for the cost of equity tests, while

we expect the UAI variable to be significant and positive, and finally, we expect the interaction term to be significant and negative.

Table III-9: Analysis of IFRS Adoption and UAI on cost of equity

(1) (2) (3) (4) (5) (6) VARIABLES LNRW LNRW LNRW LNRW LNRW LNRW IFRS 0.2265*** 0.2927*** 0.2928*** 0.2911*** 0.2820*** (6.3815) (6.7290) (6.7540) (6.6976) (6.4797) UAI 0.2503*** 0.2388*** 0.3220*** 0.2995*** 0.3038*** 0.3193*** (9.7297) (9.3094) (6.7292) (6.2677) (6.3124) (6.6940) IFRS_UAI -0.1134** -0.1048** -0.1063** -0.1168** (-2.1457) (-1.9874) (-2.0109) (-2.2157) SERIOUS1 -0.1407*** (-5.1804) SERIOUS2 -0.0810*** (-3.3788) SERIOUS3 -0.1986*** (-6.1412) WLNMCUSD -0.1197*** -0.1279*** -0.1270*** -0.1215*** -0.1206*** -0.1043*** (-22.6829) (-23.5775) (-23.4704) (-22.0819) (-20.8369) (-16.0448) WLNMR -0.0139** -0.0142** -0.0140** -0.0138** -0.0143** -0.0145** (-2.3071) (-2.3508) (-2.3266) (-2.2914) (-2.3740) (-2.4127) USGAAP 0.6897*** 0.8007*** 0.7871*** 0.7865*** 0.7870*** 0.7724*** (9.1978) (10.6385) (10.4354) (10.5078) (10.4738) (10.3014) WVOL 2.1394*** 2.1190*** 2.1165*** 2.1152*** 2.1172*** 2.1264*** (7.6104) (7.5681) (7.5541) (7.5553) (7.5740) (7.6374) LOSS 0.0465* 0.0457* 0.0462* 0.0458* 0.0449* 0.0456* (1.8452) (1.8137) (1.8337) (1.8210) (1.7841) (1.8124) WLEV -0.0266 -0.0252 -0.0250 -0.0249 -0.0229 -0.0247 (-0.5410) (-0.5135) (-0.5092) (-0.5082) (-0.4672) (-0.5028) ENF_EU -0.0266 -0.0356 -0.0382 -0.0400 -0.0380 -0.0588 (-0.6068) (-0.8080) (-0.8672) (-0.9099) (-0.8641) (-1.3277) Constant -3.4285*** -4.5446*** -4.6070*** -4.6436*** -4.6509*** -4.8531*** (-28.1776) (-37.3099) (-37.2676) (-37.6316) (-37.3668) (-37.3998) Observations 20,398 20,398 20,398 20,398 20,398 20,398 R-squared 0.1272 0.1295 0.1298 0.1313 0.1304 0.1318

Year FE YES YES YES YES YES YES

IND FE YES YES YES YES YES YES

Firm Clustering YES YES YES YES YES YES

IFRS is a binary indicator variable. IFRS_UAI is the variable created as a product of the IFRS variable and UAI. UAI is a score developed by Hofstede (2001). SERIOUS 1, 2 and 3 are the firm level transparency variables created by Daske et al (2013). NMCUSD is the natural log of Market Value of Equity in USD. RM is the annualized returns on the relevant index. US is an indicator variable to take into account financial statements prepared using US GAAP. Return VOL is the natural log of the calculated annualized volatility for the stock. LOSS is an indicator variable that is 1 if the firm had a net loss in the prior period. Leverage is the ratio of Total Debt to Book Value of Equity. ENF_EU is a variable obtained from Hail et al (2013) that controls for country level differences in regulatory enforcement changes. The coefficients have been normalised in order to aid in understanding. Control variables denoted with W have been winsorised at the 1% level. t- statistics in parentheses: *** p<0.01, ** p<0.05, * p<0.1.

Table III-9 above presents the results for the cost of equity test (LNBAS). The coefficients for IFRS are significant and positive in all the regressions, suggesting that the use of IFRS results in an increase in the cost of equity. This result is not in line with our expectation that IFRS use should lead to a reduction in the cost of equity, but the results are in line with Daske et al(2013), and suggest that IFRS adoption alone may not be a sufficient factor in reducing the cost of equity.

Moving on to the UAI variable, as expected, the variable is found to be significant and positive in all the regressions, suggesting that a higher level of UAI is generally associated with a higher cost of equity. This result is in line with our first hypothesis.

49 However, the IFRS_UAI variable as expected, was found to be significant and negative, which suggests that the use of IFRS and a higher UAI score interact to cause an improvement (reduction) in the cost of equity. This result is in line with our second hypothesis. However, if we examine the coefficients of the IFRS, UAI, and the interaction terms, it appears that IFRS adopters in higher UAI countries actually suffer from an increase in their cost of equity. This result is not in line with our expectations and will be examined in more detail below. In terms of the control variables, the three SERIOUS variables are observed to be significant and negative as expected. The results therefore imply that financial reporting transparency, whether measured by reporting incentives (SERIOUS 1), improvement in accruals quality (SERIOUS 2), or increased analyst coverage (SERIOUS 3), all seem to indicate a reduction in the cost of equity. This result is consistent with our expectation and is in line with Daske et al (2013).

The proxy for market value of the firm (WLNMCUSD) was found to be significant and negative, suggesting that larger firms tend to enjoy a lower cost of equity This result is in line with previous literature (Daske et al 2013, Fu et al, 2012). The proxy for market momentum (WLNMR) is found to be negative and significant, suggesting that increased market returns results in a decrease in the cost of equity, the results are similar to those found by Daske et al(2008) and Daske et al(2013), when they use market variability as a proxy for market momentum. The indicator variable for firms using US GAAP was found to be significant and positive for, suggesting that the use of US GAAP results in an increase in the cost of equity. the results are not in line with Daske et al (2013), who do not find US GAAP to be significant. The WVOL variable was found to be significant and positive, suggesting that increased firm level return volatility results in an increase in the cost of equity. The LOSS variables were found to be significant and positive, suggesting that firms that have exhibited a loss in the prior period, tend to observe a higher cost of equity. The leverage variable was not found to be significant. Finally, the Hail et al (2013) enforcement variable was found to be negative, though not significant in all the tests.

5.2.Analysis of Mandatory, Voluntary, and Voluntary/Voluntary, and UAI on capital market benefits

In this section, we explore whether the heterogeneity in capital market benefits is driven by whether a firm is an early adopter (V), Voluntary/Mandatory(VM) or a mandatory adopter (MA). In Table III-10, we estimate the empirical specification in Equation (1) except that we bifurcate IFRS into V, VM and M adopters, and include Daske et al’s (2013) SERIOUS adopter variables as additional control variables in subsequent equations. We expect the V,

VM and M adopters and the UAI variable to be significant and negative for the cost of equity tests, while we expect the UAI variable to be significant and positive, and finally, we expect the interaction terms of the adoption groups and UAI to be significant and negative. Table III-10: Analysis of Mandatory versus Voluntary Adoption and UAI on cost of equity

(1) (2) (3) (4) (5) (6) VARIABLES LNRW LNRW LNRW LNRW LNRW LNRW M -0.0210 0.1661*** 0.1681*** 0.1651*** 0.1592*** (-0.5435) (3.6965) (3.7454) (3.6743) (3.5406) V 0.8257*** 0.5050* 0.5053* 0.5095* 0.4693* (10.7099) (1.7874) (1.8225) (1.8061) (1.6545) VM 0.4505*** 0.1559** 0.1542** 0.1549** 0.1322* (9.0449) (2.2389) (2.2204) (2.2217) (1.8981) UAI 0.2503*** 0.1635*** 0.3482*** 0.3254*** 0.3299*** 0.3459*** (9.7297) (6.4217) (7.2627) (6.7940) (6.8358) (7.2306) M_UAI -0.3562*** -0.3478*** -0.3490*** -0.3588*** (-6.5451) (-6.4027) (-6.4108) (-6.6044) V_UAI 0.2864 0.2879 0.2848 0.3073 (0.9799) (1.0031) (0.9761) (1.0478) VM_UAI 0.3085*** 0.3228*** 0.3166*** 0.3149*** (3.7099) (3.8886) (3.8053) (3.7909) SERIOUS1 -0.1406*** (-5.3183) SERIOUS2 -0.0809*** (-3.4433) SERIOUS3 -0.1769*** (-5.6292) WLNMCUSD -0.1197*** -0.1224*** -0.1186*** -0.1132*** -0.1123*** -0.0984*** (-22.6829) (-23.0286) (-22.5232) (-21.2032) (-19.9516) (-15.5086) WLNMR -0.0139** -0.0117** -0.0106* -0.0104* -0.0109* -0.0111* (-2.3071) (-1.9646) (-1.7887) (-1.7537) (-1.8371) (-1.8719) USGAAP 0.6897*** 0.8101*** 0.7789*** 0.7785*** 0.7789*** 0.7658*** (9.1978) (10.4791) (10.1273) (10.1917) (10.1652) (10.0098) WVOL 2.1394*** 2.0422*** 2.0133*** 2.0120*** 2.0140*** 2.0231*** (7.6104) (7.5689) (7.4791) (7.4783) (7.4987) (7.5527) LOSS 0.0465* 0.0446* 0.0455* 0.0451* 0.0442* 0.0450* (1.8452) (1.7897) (1.8304) (1.8169) (1.7798) (1.8119) WLEV -0.0266 -0.0259 -0.0200 -0.0199 -0.0179 -0.0196 (-0.5410) (-0.5320) (-0.4112) (-0.4088) (-0.3687) (-0.4038) ENF_EU -0.0266 -0.0483 -0.0604 -0.0623 -0.0602 -0.0785* (-0.6068) (-1.0656) (-1.3636) (-1.4143) (-1.3632) (-1.7594) Constant -3.4285*** -4.3677*** -4.5238*** -4.5377*** -4.5675*** -4.7374*** (-28.1776) (-34.1275) (-34.3932) (-34.5126) (-34.5634) (-34.6027) Observations 20,398 20,397 20,397 20,397 20,397 20,397 R-squared 0.1272 0.1448 0.1503 0.1518 0.1509 0.1519

Year FE YES YES YES YES YES YES

IND FE YES YES YES YES YES YES

Firm Clustering YES YES YES YES YES YES

M is a binary indicator variable equal to 1 if the firm adopted IFRS for the first time when it became mandatory. V is a binary variable equal to 1 if the firm adopted IFRS prior to it becoming mandatory. VM is equal to 1 if the firm was a V prior to 2005 and continues to use IFRS. M_UAI, V_UAI, and VM_UAI are the variables created as a product of the M, V, and VM variables and UAI. UAI is a score developed by Hofstede (2001). SERIOUS 1, 2 and 3 are the firm level transparency variables created by Daske et al (2013). LNMCUSD is the natural log of Market Value of Equity in USD. RM is the annualized returns on the relevant index. US is an indicator variable to take into account financial statements prepared using US GAAP. Return VOL is the natural log of the calculated annualized volatility for the stock. LOSS is an indicator variable that is 1 if the firm had a net loss in the prior period. Leverage is the ratio of Total Debt to Book Value of Equity. ENF_EU is a variable obtained from Hail et al (2013) that controls for country level differences in regulatory enforcement changes. The coefficients have been normalised in order to aid in understanding. Control variables denoted with W have been winsorised at the 1% level. t-statistics in parentheses: *** p<0.01, ** p<0.05, * p<0.1

Table III-10 above shows the analysis conducted on the M, VM, and M adopters. All three groups have coefficients that are significant and positive, suggesting that all three types of

51 adopters suffer from an increase in the cost of equity, though their coefficients are not of the same magnitude.

Moving on to the UAI variable, as in the above analysis, we find that the variable is significant and positive, suggesting that a higher UAI score is associated with a higher cost of equity. This result is in line with our first hypothesis.

Moving on to the three interaction terms, we find mixed results, we find that the V term is not significant though it is found to be positive, while the VM term is found to be positive and significant. Only the M term was found to be significant and negative. When we combine the M variable, with UAI and the M_UAI term, we find that mandatory adopters in higher UAI countries actually benefit from a decrease in their cost of equity. We find that voluntary and voluntary/mandatory adopters actually suffer from an increase in their cost of equity, and this increase is greater for higher UAI companies.

The above result is not in line with our expectations, however if we examine Table III-6, we can see the M group is positively related to firm size, the three Daske et al(2013) measures, to the market momentum measure, and to be negatively related to the volatility measure. This suggests that mandatory firms are larger, are more likely to be SERIOUS adopters, and that they are less likely to experience large volatility in their returns.

Compared to the M group, we find that both the V and VM firms tend to be smaller, less likely to be SERIOUS firms, and to be more likely to experience large volatility in their returns. This difference between the group’s composition is likely causing the difference we observed above, given how these variables are expected to and do behave in our results above.

Moving on to the control variables, all the variables behave as in Table III-9 above and are consistent with prior literature and with our expectations.