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Table 4.6 Panel A reports the results of estimating the price model for the main sample of all financial firms, including banks, over the study period (1998-2012) and for the pre-IFRS adoption period (1998-2004), as well as the IFRS adoption period (2006-2012). Panel B reports the results for the sub-sample of banks. As pointed out in equation 3.12 in Chapter 3, this study uses fixed effect estimator with robust standard errors in the first empirical part of the thesis.

Starting with Panel A, the estimated valuation coefficient on book value of equity per share, 𝑏₁, is statistically insignificant for the entire sample period, and over both the pre-IFRS adoption and the IFRS adoption periods. In terms of earnings per share, the valuation coefficient, 𝑏2, is positive and statistically significant for the entire study period (at the 0.05 level). The coefficient increases from 1.672 (significant at the 0.05 level) in the pre-IFRS adoption period to 2.82 (significant at the 0.01 level) after IFRS adoption.

Results of the same test for the sub-sample of banks show that the valuation coefficient on book value of equity per share, 𝑏1, is always negative but is statistically different from zero (significant at the 0.01 level) only for the pooled sample that includes the entire period.80 The valuation coefficient on earnings per share, 𝑏₂, is always positive, and shows an increase from 2.389 (significant at the 0.01 level) over the period of pre-IFRS adoption to 2.452 (significant at the 0.01 level) after the mandatory introduction of IFRS in 2005. This evidence of changes in the coefficients following IFRS adoption is comparable to that reported by Agostino et al. (2011) and Manganaris et al. (2015) regarding European financial firms.

80 _{Section 4.4 provides possible explanations for the negative coefficient on the book value of equity. This}

explanation is not emphasised here given that different accounting standards are used to prepare the financial statements of the sample firms (i.e. local accounting standards before 2005 and IFRS since 2005), which might drive these results.

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Table 4. 6 The impact of IFRS adoption on value relevance of accounting information

Panel A Financial Firms (inc. Banks) Panel B Banks (only)

Pooled Pre-IFRS IFRS Pooled Pre-IFRS IFRS

VARIABLES Coeff. (1998-2012) (1998-2004) (2005-2012) (1998-2012) (1998-2004) (2005-2012) BVPS 𝑏1 0.151 0.0317 -0.0127 -0.107*** -0.0232 -0.0315 (0.191) (0.0625) (0.0394) (0.0373) (0.0697) (0.0442) EPS 𝑏2 2.733** 1.672** 2.82*** 3.192*** 2.389*** 2.452*** (1.248) (0.682) (0.423) (0.566) (0.914) (0.538) Constant 25.33*** 42.02*** 28.25*** 34.84*** 33.27*** 29.14*** (9.030) (4.217) (2.815) (4.823) (4.606) (4.564) Year dummy 𝐷𝑡

yes yes yes yes yes yes

Observations 2799 1,263 1536 2,131 963 1,168

No of firms 194 194 194 148 148 148

Within R2 _{0.416 0.242 0.514 0.378 0.244 0.494}

Difference 0.2719*** 0.247***

Notes: Robust standard errors in parentheses. *, **, *** indicate statistical significance at the 0.10, 0.05, and 0.01 levels (two- tailed), respectively. The table reports the fixed effect estimation of the price model as follows: 𝑃𝑖𝑡= 𝑏0+ 𝑏1𝐵𝑉𝑃𝑆𝑖𝑡+

𝑏2𝐸𝑃𝑆𝑖𝑡+ δ𝐷𝑡 +𝜀𝑖𝑡, where 𝑃𝑖𝑡 is the market value per share of firm i three months following the end of fiscal year t. 𝐵𝑉𝑃𝑆𝑖𝑡 is the book value of equity per share for firm i at the end of fiscal year t. 𝐸𝑃𝑆𝑖𝑡 is the reported earnings per share of firm i over the fiscal year t and 𝐷𝑡 are year dummy variables. The difference in the value relevance of accounting information between pre-IFRS adoption period (1998-2004) and IFRS adoption period (2005-2012) is measured by the difference in the within explanatory power of price model, within 𝑅2_{, over the two periods.The significance of the difference in within 𝑅}2 _{is tested based on Z statistics} = (𝑅𝑝𝑜𝑠𝑡2 − 𝑅𝑝𝑟𝑒2 )/ (𝜎𝑅𝑝𝑜𝑠𝑡2 2 _{+ 𝜎} 𝑅𝑝𝑟𝑒2 2 )^0.5 where 𝜎_𝑅 𝑝𝑜𝑠𝑡 2 2 and 𝜎_𝑅 𝑝𝑟𝑒2 2

are the variance of coefficients of determination of the within-group estimator using bootstrap methods following Agostino et al. (2011: 444). The results are reported for the entire sample of financial firms in Panel A and for the sub-sample of banks in Panel B.

However, these results are not consistent with the view that IFRS balance sheet numbers, compared to income statements, become more value relevant following IFRS adoption. Some previous studies argue that since IFRS focus more on timely recognition of balance sheet items with a large use of fair value accounting (Ball, 2006), balance sheet numbers reported under IFRS tend to be more emphasised for valuation purposes (i.e. more value relevant) (Hung and Subramanyam, 2007; Karampinis and Hevas, 2011; Tsalavoutas et al., 2012). On the other hand, net income reported in accordance with fair value oriented accounting standards, such as IFRS, becomes more volatile, less persistent, and thereby less value relevant (Schipper and Vincent, 2003; Ball, 2006; Hodder et al., 2006; Hung and Subramanyam, 2007). Overall, the results reported in this chapter demonstrate that there could be a change in the valuation weight (valuation focus) between equity book value versus net income numbers after IFRS enforcement (see Hung and Subramanyam, 2007; Devalle et al., 2010; Agostino et al., 2011). Yet investigating the changes in the valuation roles of equity book value and net income as a result of IFRS

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adoption is beyond the scope of the thesis. It is worth mentioning that the changes in the valuation weights of the balance sheet and the income statement could be caused by the financial crises that hit the economies of the countries in the sample over the period under study. Also, several factors other than financial reporting standards might drive these results, such as country-level institutional environment and firm-level characteristics. Some of these factors are addressed in the examination of the valuation roles of the balance sheet and income statement during the crisis period (see Section 4.4 in this chapter).

As discussed in chapter 3, the valuation coefficient on book value of equity for a sample of financial firms is expected to be close to one. The results in Table 4.6 are not consistent with this expectation. One reason for this could be the scaling methods used in this thesis. Other accounting scholars use alternative scaling methods than number of shares, such as lagged total assets (e.g. Marquardt and Wiedman, 2004; O'Hanlon and Taylor, 2007; Manganaris et al., 2015) and lagged book value of equity (e.g. Lai and Krishnan, 2009; Rees and Valentincic, 2013; Middleton, 2015). As a robustness check, this thesis uses both the lagged total assets (Section 4.6) as well as the lagged book value of equity (Appendix V) as alternative scaling methods. With the alternative scaling methods the coefficient on book value of equity is positive and greater in magnitude as well as closer to one (i.e. its theoretical value). The findings from the estimations using alternative scaling methods yield inference that are largely similar to those obtained from the main estimations scaled by the number of ordinary shares. It is worth mentioning there is no consensus among accounting researchers on the best scaling methods that eliminate scale effect. Barth and Clinch (2009) show evidence that the unscaled price model and the price model scaled by the number of ordinary shares perform best, among other specifications, in mitigating the scale

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effect.81 _{Therefore, this thesis uses the number of outstanding shares to scale all the market and} accounting variables in the price model.

An alternative explanation for the unexpected magnitude of the coefficient on book value of equity is that the coefficient is constrained to be the same across the countries under study. However, most of the countries under study do not have a sufficient number of observations to draw a conclusion from single country regressions.

The first hypothesis, H1A, to be tested is on the impact of IFRS adoption on the value relevance of accounting information. The within explanatory power (within 𝑅2) is the measure under scrutiny, capturing the overall value relevance of book value of equity and earnings. For the main sample of financial firms, the within 𝑅2 is 0.242 in the pre-IFRS adoption period and increases to 0.514 over the IFRS adoption period. The Z statistics, which is computed using bootstrapping techniques (see Agostino et al., 2011: 444), shows that there is a significant increase in the within explanatory power of price model after IFRS enforcement. Similarly, for the sub-sample of banks, the within 𝑅2 increases from 0.244 in the pre-IFRS adoption period to 0.494 following IFRS adoption, and this increase is statistically significant. The results suggest that mandatory IFRS adoption results in an improvement in the value relevance of financial statements prepared by financial firms in Europe. This supports the first hypothesis, H1A, which predicts that the value relevance of accounting information increases following mandatory IFRS adoption by financial firms. These findings are comparable to those obtained in previous studies that document an increase in the value relevance of accounting information after the mandatory introduction of IFRS (Filip, 2010; Devalle et al., 2010; Liu et al., 2011).

81_{Barth and Clinch (2009) posit that compared to other apparently size related scalers, such as book value of equity}

and market value of equity, the number of outstanding shares is a better proxy for scale, because it does not fluctuate widely on a yearly basis, as well as it is less likely to be affected by variation unrelated to the scale effects (such as economy-wide factors) that cause econometric difficulties.

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However, the findings of this study are not consistent with those of prior research reporting a decrease or no improvement in the value relevance of financial statements after mandating IFRS in lieu of domestic financial reporting standards (see, e.g., Karampinis and Hevas, 2011; Aubert and Grudnitski, 2011; Tsalavoutas et al., 2012). In this context two observations should be made. First, compared to the longer time span included in this empirical analysis (eight years of IFRS adoption), existing studies are conducted based on samples related to the early years of IFRS adoption. Investors as well as financial statements analysts might not be familiar with the new standards in the early period of implementation (Li, 2010; Liu et al., 2011; Houqe et al., 2012). Additionally, firms in the transition to IFRS period typically continue their pre-IFRS national accounting “tradition” (Kvaal and Nobes, 2010; Kvaal and Nobes, 2012). Taken together, the

effect of IFRS adoption could be uncertain in the early years of adoption. Second, many previous studies include firms from different industries in their samples, and typically exclude financial firm, which also might explain the different results in this study. Accordingly, Barth et al. (2012) find the adjustment to net income from local accounting standards to IFRS relating to financial instrument under IAS 39 is value relevant for financial firms only, but not for other non-financial firms. More importantly, the empirical findings of this study support the earlier evidence of positive impact of IFRS adoption on the value relevance of financial statements prepared by European financial firms (i.e. the results of Agostino et al., 2011), which is consistent with the view that IFRS adoption results in higher accounting information quality.