IFRS Adoption and Value Relevance of Accounting Information: Evidence from a Developing Country

Abstract

The purpose of this study is to investigate the impact of International Financial Reporting Standard (IFRS) adoption on value relevance of accounting information in Sri Lanka by comparing value relevance of accounting information in pre- and post-IFRS adoption periods. This study employs Ohlson (1995, Contemporary Accounting Research, 11(2), 661–687) price regression model to explain value relevance of accounting information. It explains market value per share (MVPS) using earning per share (EPS) and book value of equity per share (BVEPS). The pre-IFRS period is designated as 2010 through to 2011, and the post-IFRS period is designated as 2012 through to 2014. The sample comprises 188 firms and 935 firm-year observations which nearly constitute to all firms listed in Colombo Stock Exchange except those not having at least two annual reports before and after the year 2012 and those having extreme and incomplete data. It is found that both BVEPS and EPS significantly and positively explain MVPS during the periods followed by IFRS adoption although EPS was not a significant predictor of MVPS prior to IFRS adoption. Pooled regression with data of both regimes, however, maintains that BVEPS and EPS significantly and positively explain MVPS. Although the overall predictive power of value relevance model improved in the years that followed IFRS adoption, value relevance of BVEPS has declined in post-IFRS implementation. However, the decline in value relevance of BVEPS perhaps has been compensated by improved quality of earning thereby making EPS as a significant predictor of market value of equity in the post-IFRS periods. These findings were not rebutted or changed even at the exclusion of the transitional year of 2012 from the sample. This study contributes to the extant value relevance literature and IFRS studies by investigating the impact of IFRS adoption in a developing economy and for the first time in Sri Lanka.

Keywords

Accounting IFRS Sri Lanka SLFRS value relevance Ohlson model

Introduction

Improvements and rigorous enforcement of accounting standards are commonly sought as mechanisms to improve financial reporting quality and lowering information asymmetry. According to Chalmers Navissi, and Qu (2010), improvement to accounting standards is regarded as an important pillar of any economic reforms that aim at more efficient functioning of capital markets. Studies analysing managerial discretion in different accounting regimes claim that degree of freedom permitted in accounting standards determines the quality of financial reports (e.g., Dye & Sunder, 2001; Goncharov & Zimmermann, 2006; Sayed, 2015). According to Goncharov and Zimmermann (2006), different accounting standards provide different accounting choices, applications of which, therefore, results in different financial reporting quality. Adoption of International Financial Reporting Standard (IFRS) is thus widely held as a measure to reform financial reporting and accounting standards in particular to promote efficient capital market. International accounting standards (IAS) facilitate effective economic and financial integration across borders. The debate on international harmonization of accounting standards started in the 1960s. Although the international initiatives on harmonizing national accounting standards formally commenced in 1973 with the establishment of the International Accounting Standards Committee (Bae, Tan, & Welker, 2008), the global recognition of IFRS became largely evident and accelerated followed by their adoption by European Union (EU) in 2002 which enacted that EU-registered companies shall mandatorily adopt IFRS by 2005 (Bebbington & Song, 2007). Consequently, IFRS has established it as an internationally accepted accounting standard. In this context, IFRS adoption and harmonization of financial reporting is being extensively investigated in developed and developing countries. The conventional viewpoint regarding the adoption of IFRS is that they will inter alia result in improvement in financial reporting quality, corporate governance and stewardship, informed economic decision making thereby more efficient financial market behaviours which consequently maximize the use of economic resources. This belief is simply captured by value relevance of accounting information. Ball (2006) echoes the conventional perspective on IFRS and claims that IFRS lead to more accurate, comprehensive and timely financial statement information as compared to domestic standards. Ball (2006) also argues that IFRS lead to more informed equity valuation thereby lowering the risk to investors, provided that financial statement information is not accessed from other sources.

Considering the nature of financial reporting standards in developing economies and the merits of IFRSs, Ismail, Kamarudin, Zijl, and Dunstan (2013) argue that the impact of the adoption of IFRS in developing countries could be more significant than is found in developed markets. However, in contrast to widely held views on IFRS, Fox Hannah, Helliar, and Veneziani (2013) claim that there were some differences in the experiences of IFRS implementation among stakeholders from different jurisdiction which inform to us that the impact of IFRS is never guaranteed just because of mere adoption of the uniform standards but rather tends to rely largely on the dynamics of the locality of the adoptee. Thus, numerous empirical researches have also challenged the traditional wisdom that uniform reporting standards result in improved financial reporting and enhanced utility and value relevant of financial information. Although majority of empirical investigations proves that adoption of IFRS improves financial reporting quality thereby increased value relevance of accounting information, there are notable empirical researches that report evidences in contrary (e.g., Callao, Jarne, & Laínez, 2007; Dobija & Klimczak, 2010; Doukakis, 2010; Hung & Subramanyam, 2007; Jeanjean & Stolowy 2008; Jermakowicz Prather-Kinsey, & Wulf, 2007; Khanagha, 2011; Lambertides & Mazouz, 2013; Van der Meulen, Gaeremynck, & Willekens, 2007).

As implied by Fox et al. (2013), IFRS is based on the expectations/interest of a large set of stakeholders from hundreds of economies of various dimensions thereby making application of IFRS, as it is to certain economy may not be relevant, appropriate or optimal solution unless otherwise it is empirically tested. Besides, Fearnley Gillies, Hines, and Willett (2007) report that IFRS is increasingly perceived to be overly complex and complicating the search for appropriate form of financial reporting. Fox et al. (2013), who interviewed preparers, users and auditors of annual reports and accounting regulators in the UK (also including Ireland) and Italy, report that there was widespread agreement that costs exceeded the benefits of reporting under the new standards and also further recognized the fact that international standard setters have a large set of stakeholder views to manage, and it is therefore important that standard setters are aware of the costs and benefits of their accounting requirements. Further, the impact of IFRS adoption on value relevance may be highly sensitive to firm characteristics and the choice of regulatory benchmarks (Brown, 2011; Christensen, Lee, & Walker, 2007; Clarkson, Hanna, Richardson, & Thompson, 2011). It is also argued that the impact of IFRS adoption may differ depending on the quality of the domestic generally accepted accounting principles (GAAP) that are used prior to IFRS adoption (Beisland & Knivsfla, 2015). Although it is clear that the impact of IFRS in all jurisdictions is not similar nor in conformity with the conventional viewpoint thereon, nor its benefits are guaranteed just by mere adoption, Sri Lanka has adopted IFRS into its local accounting standards. The implied wisdom led to the full-scale adoption of IFRS could be that IFRS provides inter alia more value-relevant financial information to investors, the prominent user of general-purpose financial statements, and various other users of financial statements thereby addressing information asymmetry between investors and reporting entity. However, Papadatos and Bellas (2011) prove that firm size matters in realization of impact of IFRS. The firms’ size and characteristics in Sri Lanka as compared to those in developed economies, which often originates the ideologies behind IFRS, may be substantially different; thereby, creating a reasonable fear whether the IFRS-based Sri Lanka Accounting Standards would yield to the country. It is therefore interesting and of economic importance to examine whether the adoption of IFRSs is relevant to Sri Lanka, a developing economy, which is among the countries that adopted IFRS early in the region. Thus, this study seeks to explore whether IFRS were relevant to Sri Lankan situation and what effects their application had in accounting value relevance two years after the initial full-scale application.

The prime objective of this research therefore is to evaluate the impact of the full-scale adoption of IFRS on the value relevance of accounting information in Sri Lanka by comparing the magnitude of value relevance of accounting information pre- and post-adoption of IFRS.

Significance of the study is that although there are values relevance studies in Sri Lanka, no evidence has been reported after the adoption of IFRS in 2012. This study hence seeks to fill that gap in literature. IFRS adoption is expected to enhance the comparability, relevance and reliability of financial statements, thereby increasing cross-border investments and more efficient capital market functions. After the IFRS adoption in Sri Lanka, no scientific study has been reported with respect to evaluation of the impact driven by the implementation of IFRS. Thus, this is the first study, according to the knowledge of the researcher, which investigates value relevance of accounting information in connection with IFRS adoption in Sri Lanka. The results and conclusions of this investigation will be beneficial for standards setters and policymakers to adopt reporting standards responsive to the local economic environment. Further, this study would be a useful addition to the global literature on harmonization and IFRS implementation because Sri Lanka is an emerging economy whose reporting context is substantially different from that of developed countries.

Review of Literature

Nijam and Jahfer (2015) reviewed the commonalities among the findings from recent empirical evidences reporting the value relevance of accounting information of listed companies in Sri Lanka. They conclude that accounting information of companies listed in Colombo Stock Exchange (CSE) is value relevant. They also captured that all those studies reviewed covered the periods prior to the accounting reform in 2012 in which Sri Lanka fully converged to IFRS. Therefore, the investigation of value relevance of accounting information in Sri Lanka with data including periods followed by IFRS adoption is necessary and recommended. The findings of prior studies evaluating the impact of IFRS on value relevance of accounting information are inconsistent across jurisdictions. IFRS studies on value relevance tend to make conclusions about two broader aspects. The main aspect is the conclusion about the gross, total or overall impact of IFRS adoption on value relevance of accounting information. The improvement in the explanatory power of the models denotes the total/overall impact of IFRS adoption (Karampinis & Hevas, 2009). Increase or decrease in explanatory power of value relevance model respectively indicates improvement or depletion of value relevance of accounting information. The other aspect is the conclusion about the impact of IFRS adoption on individual predictors in the model, that is, the impact on incremental value relevance of a specific accounting information. The value relevance of individual predictors may increase or decrease followed by the IFRS adoption despite the increase or decrease in the overall explanatory power of the value relevance models.

The total impact of IFRS on value relevance of accounting information has been held positive in many jurisdictions. This has been inferred by an improvement of/increase in the explanatory power of the value relevance model fitted to the IFRS data as compared to that of non-IFRS data. Jermakowicz et al. (2007) report that accounting information of DAX-30 companies in Germany are more value relevant under IFRS or US GAAP or when they are cross-listed on the New York Stock Exchange. Barth, Landsman, and Lang (2008) examined firms from 21 different countries, applying IAS between 1994 and 2003, and reported that IFRS period account for more value relevance of accounting information for the sample firms than for a matched sample of firms. IFRS lead to more value relevant of accounting measures than under UK GAAP (Iatridis & Rouvolis, 2010). IFRS based accounting information has been held to be more value relevant than those under China GAAP (e.g., Bao & Chow, 1999; Chalmers et al., 2010; Chamisa, Mangena, & Ye, 2012; J. Liu & Liu, 2007; Sami & Zhou, 2004). Multiple studies in Greece also confirm that IFRS adoption improves the value relevance of accounting information (e.g., Iatridis & Rouvolis, 2010; Karampinis & Hevas, 2009; Tsalavoutas & Dionysiou, 2014). It is also reported that IFRS adoption associate with higher value relevance in Malaysia (e.g., Ismail, 2013; Kadri, Aziz, & Ibrahim, 2009). The value relevance of accounting information in Turkey also improved in the post-IFRS period (e.g., Kargın, 2013; Türel, 2009).

Meanwhile, there are also studies, even at the jurisdictions reviewed previously in the study, concluding that IFRS did not create any impact on value relevance of accounting information and even many studies report that IFRS reduced the value relevance of accounting information. Eccher and Healy (2000) report a finding that is not favourable to IFRS. They document that earnings under China GAAP record a higher relation with stock returns than IFRS earnings in the A-share market in China. Hu (2002) reports that earnings and book values of B-share companies listed in the SHSE are more value relevant than those based on IFRS. Hung and Subramanyam (2007) found no evidence to support the claim that IFRS increases value relevance of book value or net income in Germany. Callao et al. (2007) also did not observe evidence for that IFRS associate with improved value relevance of accounting information in Spain. According to Dobija and Klimczak (2010) and Bolibok (2014), IFRS adoption did not significantly increase the value relevance of accounting information in Polish market. Khanagha (2011) claims that value relevance of accounting data decreased with IFRS application in United Arab Emirates. Papadatos, and Bellas (2011) report that IFRS implementation in Greece did not improve the relative value relevance of accounting information.

The second major aspect focused or concluded by IFRS studies conducted in value relevance perspective is the IFRS effect on value relevance or incremental value relevance of the specific accounting information concerned. Earnings per share, book value of equity, research and development expenditure, goodwill, other capitalized intangible assets and unrealized gain are some of the key accounting information that have been used for testing the differential value relevance or incremental value relevance caused by the IFRS adoption (Nijam & Jahfer, 2016). Value relevance of earning has improved followed by the adoption of IFRS (e.g., Bao & Chow, 1999; Barth et al., 2008; Bartov, Goldberg, & Kim, 2005; Iatridis & Rouvolis, 2010; Ismail et al., 2013; Jermakowicz et al., 2007; Türel, 2009). In contrast, IFRS adoption has also been found to decrease the value relevance of earning (e.g., Beisland & Knivsfla, 2015; Kadri et al., 2009; Karampinis & Hevas, 2009; Negakis, 2013). The other fundamental accounting information that warrants attention is book value of equity. Value relevance of book value of equity has improved followed by the adoption of IFRS accounting to various studies (e.g., Bao & Chow, 1999; Barth et al., 2008; Beisland & Knivsfla, 2015; Elshamy, Al-Hajri, & Bassam, 2014; Hung & Subramanyam, 2007; Iatridis, 2010; Jermakowicz et al., 2007; Kadri et al., 2009; Kargın, 2013; Türel, 2009). IFRS also have led to a decreased value relevance of book value of equity. Papadatos and Bellas (2011) claim that introduction of IFRS in Greece did not improve the relative value relevance of book value and net income, either separately or in combination.

Methodology

Sample and Data Collection

SLFRSs and LKASs that are purely moulded based on corresponding IFRSs and IASs, respectively, were to be adopted in financial reporting of listed firms in Sri Lanka from 1 January 2012. Companies were in transitional process of reporting in the year 2012 in which the SLFRSs and LKASs were pronounced for the first time adoption. The research period is five years, from 2010 to 2104, and the period is divided as pre-IFRS (2010–2011) and post-IFRS (2012–2014) periods to observe improvements on the value relevance of accounting information. This adoption of at least two fiscal years before and after the adoption of IFRS is in conformance with many previous studies in other jurisdictions (e.g., Doukakis, 2010; Kadri et al., 2009; Karampinis & Hevas, 2009). The impact on value relevance will be analysed with and without the data corresponding to the year 2012 in which SLFRS were first time adopted by firms so that transitional effect can be understood. At the time that this research was conducted, there were 297 firms listed in CSE in 20 sectors as per the official website information of CSE as accessed in April 2015.¹ However, CSE online directory has published the annual reports of only 289 companies. Out of these 289 firms, 236 firms’ financial years end on 31 March, and the financial year-end for 53 firms is 31 December. The survey of annual reports also found that 64 firms did not have at least two annual reports before and after the year 2012, the year in which IFRS was fully adopted. These organizations might have been listed only during any one of the year covered under this study. Therefore, this study excluded all such 64 firms. Karampinis and Hevas (2009) also excluded from the sample all firms for which they could not collect the required data for all the years covered by this study in order to facilitate comparison of results. From the remaining 225 firms whose financial statements are publicly accessible from CSE’s online directory, 21 companies had not yet published the annual report for the year 2013/2014 until May 2015. Thus, only 204 companies had at least two annual reports before and after the year 2012, and all such companies were taken as the initial sample. This gave 1020 firm-year observations. Table A1 presents the population composition and sectoral distribution of the population. However, 85 observations were again excluded from this sample on the account of unavailability of all relevant data and extreme values/unusual observations. Elimination of 85 observations thus ended up with an exclusion of 16 firms. This finally gave a sample of 188 firms and 935 firm-year observations which can be summarized in Table 1. Further, the depiction in TableA2 presents in detail the sample composition according to the sectors and the percentage of coverage of the sector in the sample.

Table 1.

The Sample Firm-Year Observations Distributed in Years under Study

Year	Number of Observation	Accounting Periods
		Pre-IFRS (2010–2011)	Post-IFRS (2012–2014)
2010	186	186	–
2011	187	187	–
2012	188	–	188
2013	188	–	188
2014	186	–	186
Total Firm-Year Observations	935	373	562

Source: Survey data.

For this research, we have used secondary data extracted primarily from annual reports published by firms listed in CSE. Annual reports were accessed from CSE’s online database. Market value per share (MVPS) or stock prices of companies under investigation were obtained from CSE. Data on book value of equity per share (BVEPS) and earning per share (EPS) were collected from annual reports of listed firms publicly published.

Model Specification

Numerous other similar empirical studies that sought to assess the impact of IFRS through the improvements in value relevance of accounting information have employed value relevance model adopted by Ohlson (1995). Ohlson’s value relevance model is basically stated as follows: Pit =+1it +2it +it

where Pit is stock price of firm i at time t, BVit is the book value of equity of firm i at year t, EPSit is the reported earnings per share of firm i at the time t and εit is error term. However, in value relevance studies, some researchers focus on the relationship between the accounting earnings and stock returns (Ball & Brown, 1968; Collins & Kothari, 1989, 2001; Kothari & Zimmerman, 1995) while others examine the association between book value and market value of equity (Barth, 1991; Shelvin, 1991). It is however noted that value relevance studies usually examine the influence of accounting earnings and book value of equity in predicting share prices (Collins, Maydew, & Weiss, 1997). Kadri et al. (2009), Karampinis and Hevas (2009), Chalmers at al. (2010), Chamisa et al. (2012), Kargın (2013), and Beisland and Knivsfla (2015) are some examples of researches that have explored the impact of IFRS adoption through changes in value relevance, and all these studies have used the Ohlson model to operationalize the concept of value relevance of accounting numbers. The present study also employs Ohlson (1995) value relevance model (price model) in order to accomplish its objectives. This study represents the stock price (P), the dependent variable in the Ohlson model, through MVPS prevailed as at the date of financial reporting, that is, the end of the financial year. As normality of MVPS, the dependent variable was achieved with Ln transformation; the basic price model is as follows: Lnitititit

where LnMVPSit is Ln of MVPS of firm i in the year t (at the end of fiscal year), BVEPSit is the BVEPS of firm i in the year t and EPSit is the reported earnings per share of firm i in the year t and εit represents the error term. The value relevance of the sample firms is tested in five dimensions. The first one is to test value relevance of accounting information for each year under study using yearly cross-sectional regression of share price on earnings per share and BVEPS. The value relevance of accounting information for yearly data is to be tested to capture the changes in explanatory power of yearly value relevance models. This would be instrumental to demonstrate if the explanatory power, as compared to pre-IFRS adoption period, increases or depletes in the years that followed IFRS adoption. Yearly cross-sectional regression models can be represented as follows: Lnitititit

where LnMVPSit is Ln of MVPS of firm i at time t (at the end of fiscal year), BVEPSit is the BVEPS of firm i at year t and EPSit is the reported earnings per share of firm i at the time t, and εit represents the error term. The second dimension of this evaluation is to test the value relevance of accounting information of sampled firms for the whole research duration of five years, including pre- and post-periods of IFRS adoption. This would be achieved by running pooled regression of share price on earnings per share and BVEPS. Pooled regression will answer if accounting information in Sri Lanka continues to be value relevant in multi-year observations corresponding to the latest five years. Pooled regression model can be stated as follows: Lnit, (slfrs + slas)it, (slfrs + slas)it, (slfrs + slas)it

where LnMVPS it, (slfrs + slas) is Ln of MVPS of firm i during the study periods corresponding to both pre- and post-IFRS adoption in the year 2012, BVEPS it (slfrs + slas) is the BVEPS of firm i during the study periods corresponding to both pre- and post-IFRS adoption in the year 2012 and EPS it (slfrs and slas) is the reported earnings per share of firm i during the study periods corresponding to both pre- and post-IFRS adoption in the year 2012, and εit represents the error term. Third dimension of this analysis is to evaluate the value relevance of accounting information separately for pre- and post-IFRS adoption periods. This is achieved by running pooled regression for Model 5(a) and Model 5(b). The results to these pooled regression models will exhibit the nature of value relevance of accounting information separately under each regime, pre- and post-IFRS adoption.

Lnit slasit slasit slasit Lnit slfrsit slfrsit slfrsit

where LnMVPSitslas and LnMVPSitslfrs are respectively Ln of MVPS of firm i during the periods respectively pre- and post-IFRS adoption. BVEPSitslas is BVEPS of firm i during the periods before IFRS adoption while BVEPSitslfrs represents BVEPS of firm i during the periods after IFRS adoption. EPSitslas and EPSitslfrs are reported EPS of firm i during the periods respectively pre- and post-IFRS adoption and where εit represents the error term. Fourth angle of this analysis is to view if IFRS adoption in Sri Lanka has significantly affected the value relevance of accounting information of firms listed in CS. Thus, Model 6 is designed to explore the improvements of the value relevance of accounting data after IFRS implementation. For this purpose, a dummy variable is introduced into Model 6. If the dummy variable is significant, it implies that IFRS adoption has significantly impacted the value relevance of accounting information variable/s.

Lnititititit

where LnMVPSit is Ln of MVPS of firm i at time t (at the end of fiscal year), BVEPSit is the BVEPS of firm i at year the end of the year t and EPSit is the reported earnings per share of firm i at the time the end of the year t, DSLFRSit demotes dummy variable to represent different accounting regimes. Sri Lanka Financial Reporting Standards regime is represented by nominal value of ‘0’ if observation is before IFRS adoption and ‘1’ for IFRS adoption and εit represents the error term. In order to demonstrate the effect, if any, on the regression Model 6 due to the inclusion or exclusion of the transitional year 2012, Model 6 would be analysed as Model 6(a) and Model 6(b) which respectively including and excluding the year 2012, the transitional year, the year in which IFRS-based SLFRSs were first time adopted.

Further, incremental value relevance revealing the impact of IFRS adoption separately for BVEPS and EPS is also to be examined as a part of the investigation of IFRS impact. In order to investigate the effect of the change in financial reporting regime on value relevance of book value and earnings, Model 7 is fitted. Model 7 seeks to capture the impact of IFRS adoption on BVEPS and EPS by introducing interaction terms into the model. Prior IFRS studies in other jurisdictions have also used interaction variables to capture the incremental value relevance of accounting data (e.g., Beisland & Knivsfla, 2015; Chalmers at al., 2010; Kadri et al., 2009; Kargın, 2013). The present study also thus introduces two interaction variables to capture the effect on BVEPS and EPS due to the changes in financial reporting regime. DSLFR*BVEPS (dummy variable to represent different accounting regimes times BVEPS) representing the interaction between IFRS adoption and book value whereas DSLFRS*EPS (dummy variable to represent different accounting regimes times earnings per share) representing the interaction between IFRS adoption and earnings per share. Dummy variable to represent different accounting regimes is represented by nominal value of ‘0’, if observation is before IFRS adoption and ‘1’ for IFRS adoption. Model 7 is thus represented as follows: Lnitititititit

β3 and β4 present the difference between coefficients of book value and earnings per share for the pre- and post-IFRS periods. If the difference of coefficients is positive (negative), the value relevance of the variable concerned increases (decreases) in the post-IFRS period. Further, in order to explain the effect if any on the regression Model 7 due to the inclusion or exclusion of the transitional year 2012, Model 7 would be analysed as Model 7(a) and Model 7(b) which respectively includes and excludes the year 2012, the transitional year, the year in which IFRS-based SLFRSs were first time adopted.

Results and Discussion

Descriptive Statistics

The sample originally comprised of 188 companies listed in CSE as on 31 December 2014. After removing the extreme values (10 observations), the dataset contains 935 firm-year observations representing 186 cases each in 2010 and 2014, 187 observations in 2011 and 188 cases each in the years 2012 and 2013. Table 2 shows the descriptive statistics of each variable with yearly breakdown of the total cases. According to Table 2, mean BVEPS has increased over the years from 2010 to 2014 respectively from Rs.82.68 to Rs.119.66. The standard deviation of mean BVEPS has also increased over the years except a brief decline from Rs.146.66 in the year 2011 to Rs.145.55 in the year 2012. The standard deviation of BVEPS is relatively high during IFRS period than the periods prior to IFRS adoption. It is however noted that mean BVEPS has recorded relatively a large growth of 31.46 per cent from 2012 to 2013 which may be associated to the accounting regime change in Sri Lanka in 2012. Correlation tests of pool sample between market value, book value and earnings reveal that market values are positively and significantly correlated with book values and earnings (significant at 0.001 levels). Book values are also positively significantly correlated with earnings (significant at 0.001 levels). Correlation results are provided in Table 3.

Table 2.

Descriptive Statistics for Yearly Data

		n	µ	σ	σ2	Median	Min	Max
BVEPS	2010	186	82.68	126.92	16107.81	41.20	–142.85	804.29
	2011	187	82.89	146.66	21509.83	34.88	–62.80	1241.24
	2012	188	85.96	145.55	21186.13	38.53	–24.09	822.09
	2013	188	113.73	198.95	39581.23	45.47	–41.05	962.39
	2014	186	119.66	206.15	42499.63	48.20	–51.41	1042.39
EPS	2010	186	6.69	21.49	461.88	2.68	–209.90	89.63
	2011	187	12.41	36.75	1350.91	3.21	–87.54	354.02
	2012	188	13.21	38.71	1498.25	3.18	–69.12	333.14
	2013	188	9.57	24.44	597.21	3.39	–84.35	210.33
	2014	186	11.34	26.53	703.59	2.70	–16.10	240.69
MVPS	2010	186	163.45	296.93	88169.98	72.75	1.50	3000.00
	2011	187	252.15	416.83	173750.05	105.50	2.40	2650.00
	2012	188	200.81	404.27	163437.25	66.55	1.90	2400.00
	2013	188	190.25	392.87	154346.62	62.25	1.50	2488.00
	2014	186	191.68	371.02	137659.41	60.95	2.20	2200.00

Source: Authors’ own findings.

Table 3.

Correlation Results

		BVEPS	EPS	MVPS	LnMVPS
BVEPS	r	1	–	–	–
	Sig. (2-tailed)	–	–	–	–
EPS	r	0.604***	1	–	–
	Sig. (2-tailed)	0.000	–	–	–
MPSV	r	0.658***	0.559***	1	–
	Sig. (2-tailed)	0.000	0.000	–	–
Ln MVPS	r	0.609***	0.459***	0.724**	1
	Sig. (2-tailed)	0.000	0.000	0.000	–
n = 935

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

Value Relevance of Accounting Information

Yearly Regression

Table 4 presents the regression results for yearly data. Regression model fitted to each year is significant at 0.001 level. F-statistics of the regression models has increased in each year subsequent to IFRS adoption. It is noteworthy that the adjusted R2 in 2010 and 2011, which are the years prior to the adoption of IFRS, are respectively 35 per cent and 33 per cent. However, the adjusted R2 in 2012, the year in which IFRS was adopted, has increased as 41 per cent, which is 24 per cent increase as compared to the year 2011. Adjusted R2 also has continuously increased to 44.9 per cent in the year 2013 and 46.6 per cent in 2014, the years under IFRS regime. It is also observed that BVEPS has been powerful explanatory factor than EPS in each year of observation. Intercept yet remains significant at the 0.001 level throughout the years.

Table 4.

Value Relevance; Yearly Regression

Model 3: LnMVPSit = α + β1BVEPSit + β2EPSit + εit
	N	α	β_bveps	β_eps	Adjusted R²	F-Value	p-Value (2-tailed)
2010	186	3.685	0.005	0.015	0.352	51.270	0.000***
T-Statistic		37.140	6.994	3.360
P-Value (2-tailed)		0.000***	0.000***	0.001**

2011	187	4.109	0.005	0.002	0.330	46.703	0.000***
T-Statistic		40.625	5.883	0.654
P-Value (2-tailed)		0.000***	0.000***	0.514

2012	188	3.560	0.007	0.000	0.417	67.950	0.000***
T-Statistic		36.429	8.346	–0.101
P-Value (2-tailed)		0.000***	0.000***	0.920

2013	188	3.433	0.004	0.012	0.449	77.229	0.000***
T-Statistic		35.579	8.430	3.017
P-Value (2-tailed)		0.000***	0.000***	0.003**

2014	186	3.517	0.004	0.008	0.466	81.703	0.000***
T-Statistic		37.750	8.216	1.967
P-Value (2-tailed)		0.000***	0.000***	0.05*

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

* Significant at the 0.05 level (2-tailed)

Pooled Regression

Diagnostic tests on the assumptions of ordinary least squares indicated heteroscedasticity issue in the pooled data. This problem was remedied by heteroscedasticity consistent covariance matrix estimator which provide heteroscedasticity adjusted t-statistics. The results shown throughout the sections to follow are after resolving the heteroscedasticity problem. Model 4, the pooled regression model fitted with 935 total firm-year observations is significant at 0.001 level with F-value of 290.8. The adjusted R2 is 38 per cent, indicating that book value and earnings of the firms explain 38.3 per cent of the variation of the market value of the firms. BVEPS and EPS are significant predictors of MVPS at the significance level of 0.001 and 0.05 levels respectively. The result implicates that both book value and earnings generated by firms in CSE contain information which are accordingly valued by the equity investors. Table 5 provides the regression results for pooled sample.

Table 5.

Pooled Regression

Model 4: LnMVPS it (slfrs + slas) = α + β1BVEPS it (slfrs + slas) + β2EPS it (slfrs + slas) + εit
	Parameter Estimate	SE	T-Statistic	P-Value (2-tailed)
Intercept	3.690623	0.047258	78.09570	0.0000***
BV	0.004641	0.000311	14.93501	0.0000***
EPS	0.006999	0.002744	2.550780	0.0109*
n	935
Adjusted R²	0.382997
SE	1.172388
F-Value P-Value	290.8842 0.000***

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

*Significant at the 0.05 level (2-tailed)

Testing Value Relevance Separately for Pre- and Post-IFRS Adoption

Regression is also performed to the pooled data before and after the IFRS adoption. Panel A in Table 6 summarizes the regression result for the 373 firm-year observations corresponding to years 2010–2011, the years prior to IFRS adoption. Accordingly, the pre-IFRS mode is significant at 0.001 level with F-statistics of 92.5. Adjusted R2 of this model is 33 per cent, implying that 33 per cent of the variation in MVPS is explained by the model. It is however noted that EPS is not a significant predictor of MVPS prior to IFRS adoption though BVEPS is significant at 0.001 level.

Similarly, Panel B in Table 6 presents the regression result for the 562 firm-year observations corresponding to years 2012–2014, the years followed by IFRS adoption. Accordingly, the post-IFRS model is significant at 0.001 level with F-statistics of 217. Adjusted R2 of this model is 43 per cent, implying that 43 per cent of the variation in MVPS is explained by the model. Both such accounting information as BVEPS and EPS are now individually significant respectively at 0.001 and 0.05 level. It is noted that post-IFRS model records relatively higher adjusted R2 of 43 per cent as compared to adjusted R2 of 33 per cent of the pre-IFRS model. The F-statistics shows a huge increase from 92.5 per cent to 216.9 per cent from pre-IFRS regression model to post-IFRS model. It is observed that the explanatory power of BVEPS has slightly declined during the IFRS adoption period as compared to the one in pre-IFRS period while the explanatory power of EPS records an increase subsequent to the IFRS adoption. Although the earning prior to IFRS adoption was not a significant predictor of equity share price, post-IFRS earning significantly explain equity share price. This informs that the earning quality has improved subsequent to IFRS adoption. The improvement in overall predictive power (i.e., increase in adjusted R2) of value relevance model followed by the adoption of IFRS may therefore be attributed to improved quality of earning that firms reported under IFRS-based SLFRS.

Table 6.

Value Relevance Pre- and Post-IFRS Adoption

	2010–2011
	Parameter Estimate	SE	T-Stat	P-Value (2-tailed)
Panel A. Value Relevance: Pre-IFRS Adoption Model 5(a): LnMVPS_it ^slas = α + β₁BVEPS_it ^slas + β₂EPS_it ^slas + ε_it
Intercept	3.912965	0.085796	45.60786	0.0000***
BVEPS	0.005039	0.000649	7.766345	0.0000***
EPS	0.006692	0.004912	1.362401	0.1739
n	373
Adj R²	0.329859
SE	1.182080
F-Value P-Value	92.55353 0.000***
Panel B. Value Relevance: Post-IFRS Adoption Model 5 (b): LnMVPS_it ^slfrs = α + β₁BVEPS_it ^slfrs + β₂EPS_it ^slfrs + β_it
Intercept	3.524779	0.056467	62.42193	0.0000***
BVEPS	0.004654	0.000364	12.77537	0.0000***
EPS	0.006732	0.003145	2.140570	0.0327*
n	562
Adjusted R²	0.434965
SE	1.137717
F-value P- Value	216.9292 0.000***

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

*Significant at the 0.05 level (2-tailed)

Evaluating the Impact of IFRS Adoption

IFRS Impact on Value Relevance Model

Since the aforementioned model produces the result from a pool sample that comprises data from two different financial regimes, the results due to the adoption of IFRS is not yet known. To identify whether IFRS adoption has increased/decreased the value relevance of book value and earnings, Model 6 needs to be tested. In order to test the effect the IFRS adoption, the model introduces a dummy variable where observation corresponding to the periods prior to the adoption of IFRS is coded as ‘0’, and the observation corresponding to the periods subsequent to the adoption of IFRS is coded as 1. If the dummy variable is significant, it implies that the IFRS adoption has significantly affected the value relevance of accounting information, namely, BVEPS and EPS. Table 7 presents the regression results of the regression Model 6.

Accordingly, Model 6(a) is significant at 0.001 level with F-value of 290.8. The adjusted R2 is 40 per cent, indicating that book value and earnings of the firms explain 40 per cent of the variation of the market value of the firms. Book value is significant at 0.01 levels while EPS is significant at 0.05 level. Dummy variable is significant at 0.001 with negative coefficient of –0.422. The result implicates that there is a significant difference in value relevance of accounting information in pre- and post-IFRS adoption. Negative coefficient of –0.422 for dummy variable implies that MVPS has declined followed by the adoption of IFRS, thereby, declining the value relevance of at least one accounting information. It is noteworthy that this result was not negated even at the exclusion of the transitional year of 2012 from the pooled sample. Thus, Model 6(b) tested with 747 firm-year observation that exclude the observations in the year 2012 during which the firms first time adopted IFRS and has R2 value of 40.4 per cent. Dummy variable continued to be significant at 0.001 with negative coefficient of –0.479 (see Panel B of Table 7).

Table 7.

IFRS Impact on Value Relevance Model

Model 6: LnMVPSit = α + β1BVEPSit + β2EPSit + β3DSLFRSit + εit
	Parameter Estimate	SE	T-Statistic	P-Value (2-tailed)
Panel A. Model 6(a): IFRS Impact on Value Relevance Including the Transitional Period
Intercept	3.936078	0.064712	60.82441	0.0000***
BVEPS	0.004740	0.000309	15.34179	0.0000***
EPS	0.006868	0.002769	2.480266	0.0133*
DIFRS	–0.421976	0.078247	–5.392861	0.0000***
N	935
Adjusted R²	0.401487
SE	1.154687
F-Value P-Value	209.845 0.000***
Panel B. Model 6(b): IFRS Impact on Value Relevance Excluding the Transitional Period
Intercept	3.941038	0.066417	59.33769	0.0000***
BVEPS	0.004487	0.000315	14.25314	0.0000***
EPS	0.008536	0.003890	2.194137	0.0285*
DIFRS	–0.478715	0.085333	–5.609979	0.0000***
N	747
Adjusted R²	0.404442
SE	1.149863
F-Value p-Value	169.8688 0.000***

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

*Significant at the 0.05 level (2-tailed)

IFRS Impact on Value Relevance of BVEPS and EPS

Model 7 is to be tested to investigate the incremental value relevance effect of IFRS adoption on BVEPS and EPS. Table 8 presents the regression results for Model 7.

Table 8.

IFRS Impact on Value Relevance of BVEPS and EPS

Model 7: LnMVPSit = α + β1BVEPSit + β2EPSit + β3DSLFRSBVEPEit + β4DSLFRSEPSit + εit
	Parameter Estimate	SE	T-Statistic	P-Value (2-tailed)
Panel A. Model 7(a): IFRS Impact on Value Relevance of BVEPS and EPS Including the Transitional Period
Intercept	3.676629	0.049336	74.52176	0.0000***
BVEPS	0.005893	0.000660	8.924241	0.0000***
EPS	0.006032	0.005587	1.079602	0.2806
DIFRS*BVEPS	–0.001574	0.000700	–2.249339	0.0247*
DIFRS*EPS	0.000521	0.006314	0.082480	0.9343
n	935
Adjusted R²	0.389177
SE	1.166502
F-Value P-Value	149.7708 0.000
Panel B. Model 7(b): IFRS Impact on Value Relevance of BVEPS and EPS Excluding the Transitional Period
Intercept	3.691133	0.056713	65.08476	0.0000***
BVEPS	0.005840	0.000668	8.740153	0.0000***
EPS	0.006072	0.005542	1.095743	0.2735
DIFRS*BVEPS	–0.002021	0.000735	–2.748844	0.0061**
DIFRS*EPS	0.003428	0.007633	0.449113	0.6535
N	747
Adjusted R²	0.388825
SE	1.164841
F-Value P-Value	119.6501 0.000
Panel C. Regression Obtained after Removing the Incremental Effect of EPS
Intercept	3.677007	0.050682	72.55079	0.0000***
BVEPS	0.005848	0.000774	7.551083	0.0000***
EPS	0.006357	0.002807	2.264416	0.0238**
DIFRS*BVEPS	–0.001511	0.000839	–1.800012	0.0722*
N	935
Adjusted R²	0.391776
SE	1.165891
F-Value P-Value	199.8954 0.000

Source: Authors’ own findings.

Notes: ***Significant at the 0.001 level (2-tailed)

**Significant at the 0.01 level (2-tailed)

*Significant at the 0.10 level (2-tailed)

The inclusion of two more variables into the price model as an interaction to BVEPS and EPS results an adjusted R2 of 38.9 per cent. The coefficient of the interaction variable DIFRS*BVEPS is negative and significant at 0.05 levels whereas interaction variable DIFRS*EPS is not significant. This indicates that the IFRS adoption affects significantly and negatively the value relevance of BVEPS but not that of EPS. The negative sign obtained for the coefficient of DIFRS*BVEPS shows that IFRS adoption has led to a decrease in value relevance of BVEPS. Further, as supported by the results in Panel B in Table 8, this finding was not rebutted even at the exclusion of the transitional year of 2012 from the pooled sample. Rather, the interaction of dummy variable with BVEPS (DIFRS*BVEPS) is significant at 0.01. IFRs adoption has motivated and increased the application of fair value in measurement of assets than ever before. This development has led to an increase in other comprehensive income that is being reported as a component of equity. The concept of other comprehensive income was unfamiliar to Sri Lankan firms until it was imported through the application of ‘LKAS-01: Preparation and Presentation of Financial Statement’ that corresponds to IAS-01. Decline in value relevance of BVEPS followed by the adoption of IFRS may thus be attributed to the addition of other comprehensive income being reported as a component of equity. Strangeness over the recognition of other comprehensive income and its recognition as a part of equity might have reduced its influence or relevance on valuation at these early years after IFRS adoption. At the same time, earning has been found to be a significant predictor of market value of equity followed by IFRS adoption, although it was not the case prior to this accounting standard change (see Table 6). Thus, the decline in the value relevance of BVEPS has been captured in the earning measure which makes earning also to become as a significant predictor of market value of equity in the post-IFRs periods. This is also supported by the findings of regression obtained after removing DIFRS*EPS, the incremental effect of EPS, from Model 7(a), which is presented in Panel C in Table 8.

Conclusion

The purpose of this study is primarily to assess the impact of IFRS adoption in Sri Lanka on value relevance of accounting information. Only BVEPS was value relevant prior to the adoption of IFRS. Both BVEPS and EPS, which respectively summarize statement of financial position and income statement, however significantly and positively explain MVPS during the periods followed by the IFRS adoption. Pooled regression with data of both regimes also maintains that BVEPS and EPS significantly and positively explain MVPS. It is thus concluded that the accounting information published by firms in CSE continue to be value relevant. This informs that both book value and earnings of firms in CSE contain information which is accordingly valued by the equity investors. However, the predictive power of the Ohlson (1995) value relevance model has increased throughout the years followed by IFRS adoption in 2012. It is also observed that explanatory power of the value relevance model for post-IFRS data is greater than that was obtained for pre-IFRS data. It is also greater than the explanatory power of pooled sample consisting of the data corresponding to pre- and post-IFRS periods. This implies that explanatory power of accounting information over MVPS is relatively greater during the post-IFRS adoption period. This implicates that the usefulness of information reported under SLFRS is more than that were reported prior to IFRS adoption in 2012. Although the overall predictive power of value relevance model (relative value relevance) improved in the years followed by the adoption of IFRS, incremental value relevance of BVEPS has declined in the years followed after the IFRS adoption. These findings were not rebutted or changed even at the exclusion of the transitional year of 2012 from the sample. This decline in value relevance of BVEPS in the years after IFRS adoption may be due to the addition of other comprehensive income being newly reported as a component of equity, of which investors have not valued accordingly may be due to its new arrival and its sensitivity to changes in fair values. At the same time, earning has emerged as a significant predictor of market value of equity followed by IFRS adoption, although it was not the case prior to this accounting standard change. Thus, the decline in the value relevance of BVEPS has been captured by improved quality of earning thereby making earnings as a significant predictor of market value of equity in the post-IFRs periods.

Significance and Limitations

Firms listed in CSE need to maintain a growth in EPS and BVEPS prudently as these accounting figures positively and significantly associate with MVPS, that is, firms may achieve increased price over their shares if EPS and BVEPS are increased. Potential investors seeking to invest in share traded in CSE can value the shares based on BVEPS and EPS as the capital market has valued the firms accordingly over the years. It is suggested that standards setters in particular shall need to ensure the relevance of BVEPS in the years to come and to initiate corrective measure if the decline in value relevance of BVEPS persists. It is suggested for future researchers to investigate the value relevance of different components/properties of equity being reported under SLFRS regime and to identify the relative importance of all equity components including that of other comprehensive income. It is also recommended for future researchers to conduct further researches to evaluate the impact of IFRS adoption in Sri Lanka in different angles. Some of such dimensions of IFRS impact include its influence on earning management, qualitative characteristics of financial statements, earning forecast, corporate governance, auditors’ perspectives and so on. Qualitative investigations are also necessary to evaluate the perceived impacts of IFRS adoption in Sri Lanka.

The study is subject to certain limitations and findings of this research hence need to be interpreted considering such limitations. This study examines the value relevance of companies listed in CSE and thus the companies not listed in CSE have been excluded even though such firms report their financial statements under IFRS-based Sri Lanka Accounting Standards. The study assesses the impact of IFRS adoption using the concept of value relevance of accounting information. BVEPS and EPS are data just summarizing financial statement. The impact on value relevance of financial disclosures reported in financial statements has not been considered in this investigation. The impact on value relevance is sought to be ascertained by comparing the value relevance of accounting information just before and after two years of IFRS adoption in Sri Lanka. Although there are empirical studies in other jurisdictions where similar duration has been used (e.g., Doukakis, 2010; Karampinis & Hevas, 2009), it may be argued that two-year duration that follows after a implementation of IFRS especially in contexts of a developing country is too early to judge the impact on the implementation of IFRS. Besides, not all relevant information that is required for this study has been published by the all the organizations in the sample, thereby, reducing the data available for analysis.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Footnotes

Acknowledgements

The authors is grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the paper. Usual disclaimers apply.

Appendix

Table A2.

Sample Composition and Sectoral Distribution

Sector	Number of Firms Listed	Sample Firms	Representation (%)	Final Firm-Year Observations
Bank finance and insurance	62	25	40	124
Beverage, food and tobacco	21	18	86	90
Chemicals and pharmaceuticals	10	08	80	38
Construction and engineering	04	03	75	15
Diversified holdings	19	11	58	55
Footwear and textile	03	01	33	05
Health care	06	04	67	20
Hotels and travels	37	28	76	140
Information technology	02	01	50	05
Investment trust	09	09	100	45
Land and property	19	13	68	65
Manufacturing	37	27	73	135
Motors	06	06	100	30
Oil palms	05	05	100	25
Plantations	19	09	47	45
Power and energy	08	04	50	20
Services	08	04	50	20
Stores supplies	04	04	100	19
Telecommunications	02	01	50	05
Trading	08	07	88	34
Firms published in CSE	289	188	–	935
Total listed firms	297	–	–	–

Source: Survey data.

Note

References

Bae

K. H.

Tan

& Welker

(2008). International GAAP differences: The impact on foreign analysts. The Accounting Review, 83(3), 598–628.

Ball

(2006). International Financial Reporting Standards (IFRS): Pros and cons for investors. Accounting and Business Research, 36(special issue), 5–27.

Ball

& Brown

(1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 6(2), 159–178.

Bao

& Chow

(1999). The usefulness of earnings and book value for equity valuation in emerging capital market: Evidence from listed companies in the People’s Republic of China. Journal of International Financial Management and Accounting, 10(2), 85–104.

Barth

M. E.

(1991). Relative measurement errors among alternative pension asset and liability measures. The Accounting Review, 66, 159–178.

Barth

M. E.

Landsman

W. R.

& Lang

M. H.

(2008). International accounting standards and accounting quality. Journal of Accounting Research, 46(3), 467–498.

Bartov

Goldberg

S. R.

& Kim

(2005). Comparative value relevance among German, US, and international accounting standards: A German stock market perspective. Journal of Accounting, Auditing and Finance, 20(2), 95–119.

Bebbington

& Song

(2007). The adoption of IFRS in the EU and New Zealand (Working paper). Christchurch: National Centre for Research on Europe, University of Canterbury.

Beisland

L. A.

& Knivsfla

K. H.

(2015). Have IFRS changed how stock prices are associated with earnings and book values? Review of Accounting and Finance, 14(1), 41–63.

10.

Bolibok

(2014). The impact of IFRS on the value relevance of accounting data of banks listed on the Warsaw Stock Exchange. Copernican Journal of Finance & Accounting, 3(1), 33–43.

11.

Brown

(2011). International financial reporting standards: What are the benefits? Accounting and Business Research, 41(3), 269–285.

12.

Callao

Jarne

J. I.

& Laínez

J. A.

(2007). Adoption of IFRS in Spain: Effect on the comparability and relevance of financial reporting. Journal of International Accounting, Auditing and Taxation, 16(2), 148–178.

13.

Chalmers

Navissi

& Qu

(2010). Value relevance of accounting information in China pre- and post-2001 accounting reforms. Managerial Auditing Journal, 25(8), 792–813.

14.

Chamisa

Mangena

& Ye

(2012). Relative value-relevance of accounting measures based on Chinese Accounting Standards and International Financial Reporting Standards. Journal of Accounting in Emerging Economies, 2(2), 162–187.

15.

Christensen

H. B.

Lee

& Walker

(2007). Cross-sectional variation in the economic consequences of international accounting harmonization: The case of mandatory IFRS adoption in the UK. The International Journal of Accounting, 42(4), 341–379.

16.

Clarkson

Hanna

J. D.

Richardson

G. D.

& Thompson

(2011). The impact of IFRS adoption on the value relevance of book value and earnings. Journal of Contemporary Accounting and Economics, 7(1), 1–17.

17.

Collins

Maydew

& Weiss

(1997). Changes in the value-relevance of earnings and book values over the past forty years. Journal of Accounting and Economics, 24(1), 39–67.

18.

Collins

& Kothari

(1989). An analysis of international and cross-sectional determinants of ERCs. Journal of Accounting and Economics, 11(2–3), 143–193.

19.

Dobija

& Klimczak

K. M.

(2010). Development of accounting in Poland: Market efficiency and the value relevance of reported earnings. The International Journal of Accounting, 45(3), 356–374. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1084423

20.

Doukakis

L. C.

(2010). The persistence of earnings and earnings components after the adoption of IFRS. Managerial Finance, 36(11), 969–980.

21.

Dye

R. A.

& Sunder

(2001). Why not allow FASB and ISAB standards to compete in the US? Accounting Horizons, 15(3), 257–271.

22.

Eccher

& Healy

P. M.

(2000). The role of international accounting standards in transitional economies: A study of the People’s Republic of China. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=233598

23.

ElShamy

M. A.

Al-Hajri

& Al Bassam

(2014). The value relevance of unrealized gains and losses recognized under IAS 39: Evidence from Kuwait. International Journal of Commerce and Management, 24(4), 355–366.

24.

Fearnley

Gillies

Hines

& Willett

(2007). Bewildered but better informed: A qualitative interview based study into the attitudes of some UK accountants and regulators to the EU IFRS conversion project prior to its implementation in the UK. London: ICAEW. Retrieved from http://eprints.port.ac.uk/13861/22/Publication_7.PDF

25.

Fox

Hannah

Helliar

& Veneziani

(2013). The costs and benefits of IFRS implementation in the UK and Italy. Journal of Applied Accounting Research, 14(1), 86–101.

26.

Goncharov

& Zimmermann

(2006). Do accounting standards influence the level of earnings management? Evidence from Germany. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=386521

27.

(2002). The usefulness of financial statements under Chinese GAAP vs IAS: Evidence from Shanghai Stock Exchange in PRC (Working paper). Kobe: Kobe University.

28.

Hung

& Subramanyam

K. R.

(2007). Financial statement effects of adopting international accounting standards: The case of Germany. Review of Accounting Studies, 12(4), 623–657.

29.

Iatridis

& Rouvolis

(2010). The post-adoption effects of the implementation of International Financial Reporting Standards in Greece. Journal of International Accounting, Auditing and Taxation, 19(1), 55–65.

30.

Ismail

W. A. W.

Kamarudin

K. A.

Zijl

& Dunstan

(2013). Earnings quality and the adoption of IFRS- based accounting standards. Asian Review of Accounting, 21(1), 53–73.

31.

Jeanjean

& Stolowy

(2008). Do accounting standards matter? An exploratory analysis of earnings management before and after IFRS adoption. Journal of Accounting and Public Policy, 27(6), 480–494.

32.

Jermakowicz

E. K.

Prather-Kinsey

& Wulf

(2007). The value relevance of accounting income reported by DAX-30 German companies. Journal of International Financial Management and Accounting, 18(3), 151–191.

33.

Kadri

M. H.

Aziz

R. A.

& Ibrahim

M. K.

(2009). Value relevance of book value and earnings: Evidence from two different financial reporting regimes. Journal of Financial Reporting and Accounting, 7(1), 1–16.

34.

Karampinis

& Hevas

(2009). The effect of the mandatory application of IFRS on the value relevance of accounting data: Some evidence from Greece. European Research Studies, 12(1), 71.

35.

Kargın

(2013). The impact of IFRS on the value relevance of accounting information: evidence from Turkish firms. International Journal of Economics and Finance, 5(4), 71–80.

36.

Khanagha

J. B.

(2011). Value relevance of accounting information in the United Arab Emirates. International Journal of Economics and Financial Issues, 1(2), 33–45.

37.

Kothari

S. P.

(2001). Capital markets research in accounting. Journal of Accounting and Economics, 31(1–3), 105–231.

38.

Kothari

S. P.

& Zimmerman

(1995). Price and return models. Journal of Accounting and Economics, 20(2), 155–192.

39.

Lambertides

& Mazouz

(2013). Stock price volatility and informational efficiency following the mandatory adoption of IFRS in Europe. Journal of Applied Accounting Research, 14(1), 4–17.

40.

Liu

& Liu

(2007). Value relevance of accounting information in different stock market segments: The case of Chinese A-, B-, and H-shares. Journal of International Accounting Research, 6(2), 55–81.

41.

Negakis

C. I.

(2013). The explanatory power of earnings for stock returns in the pre- and post-IFRS era. Managerial Finance, 39(9), 814–824.

42.

Nijam

H. M.

& Jahfer

(2015). Value relevance of accounting information: A review of recently reported evidences from Sri Lanka. Presented at the Fourth Annual International Research Conference 2015, Faculty of Management and Commerce, South Eastern University of Sri Lanka.

43.

Nijam

H. M.

& Jahfer

(2016). International Financial Reporting Standards: A review of status of adoption and approaches for Evaluation. International Letters of Social and Humanistic Sciences, 69, 69–78.

44.

Ohlson

J. A.

(1995). Earnings, book values, and dividends in equity valuation. Contemporary Accounting Research, 11(2), 661–687.

45.

Papadatos

& Bellas

(2011). The value relevance of accounting information under Greek and International Financial Reporting Standards: The influence of firm-specific characteristics. International Research Journal of Finance and Economics, 76, 6–23.

46.

Sami

& Zhou

(2004). A comparison of value relevance of accounting information in different segments of the Chinese stock market. The International Journal of Accounting, 39(4), 403–427.

47.

Sayed

S. A.

(2015). Should analysts go by the book? Valuation models and target price accuracy in an emerging market. Global Business Review, 16(5), 832–844.

48.

Shelvin

(1991). The valuation of R&D firms with R&D limited partnerships. The Accounting Review, 66, 1–22.

49.

Tsalavoutas

& Dionysiou

(2014). Value relevance of IFRS mandatory disclosure requirements. Journal of Applied Accounting Research, 15(1), 22–42.

50.

Türel

(2009). The value relevance of IFRS: The case of Turkey. Acta Universitatis Danubius, Economica, 5(1), 119–128.

51.

Van der Meulen

Gaeremynck

& Willekens

(2007). Attribute differences between US GAAP and IFRS earnings: An exploratory study. The International Journal of Accounting, 42(2), 123–142.