International Financial Reporting Standards

Executive Summary

In the last decade, national setters of accounting standards have become aware of the emerging need for efficient standards that can be used to regulate financial institutions. Countries within the Middle East such as Kuwait, Lebanon, Bahrain, Qatar, the UAE, Oman and Jordan have acknowledged the need to be proactively involved in financial opportunities and have been at the forefront in adopting the International Financial Reporting Standards (IFRS). The primary aim of this research study is to highlight the accounting information value relevance in companies within Kuwait, Lebanon, Bahrain, Qatar, the UAE, Oman and Jordan, which have embraced the IFRS in financial information reporting. This could illustrate the outcome of integrating the IFRS on accounting information value relevance within the seven countries. Through portfolio and regression approaches, the results obtained indicated that there is value relevance in accounting information in the seven countries for companies that embraced the IFRS. A comparative analysis of the results obtained after and before the adoption of the IFRS indicted an enhancement in the value relevance of accounting information for these companies in all seven countries. The results can be inferred to mean that adoption of the IFRS improved the accounting information value relevancy in the companies that adopted the international standards in the seven countries.

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Introduction

Research Background

Many countries in the Middle East have little or no reasonable accounting standards besides political and economic uncertainty. However, in the last two decades, economic reforms and different market liberalization policies have come into play within the Arab world markets. Specifically, accounting reforms within the Arab world, in terms of adaptation of the IFRS, have encouraged the maturity and development of the financial markets. For instance, in Bahrain, Jordan, Oman, Qatar, and the UAE, the commercial companies’ law was passed in the year 2002 which requires firms to carry out financial reporting, in terms of financial statements in line with the IFRS (Bade & Parkin 2013). In the year 2003, Kuwait and Lebanon followed the trend. By the year 2007, all companies listed in the respective securities markets had to follow the IFRS in publishing their financial statements (Deloitte 2007).

The quality and value of any accounting information are established by the level of satisfaction by the user of the information. Therefore, most accounting research is often carried out to establish the usefulness and relevance of the information highlighted through any accounting process. Basically, several factors affect the quality of accounting information such as regulatory devices in the form of accounting standards (Verriest 2007). This means that accounting standards that are of high quality might provide consistent, relevant, reliable, and comparable information on the financial performance of an economy. Despite the inexistence of a standardized accounting quality definition, several quality dimensions have become accepted. The most common measure of accounting quality has been the value relevance approach, which can be used to assess the relevance of information on accounting for the consumption of the stakeholders. For instance, Beaver (2011) observed that the “theoretical groundwork of value relevance studies is a combination of valuation theory plus contextual accounting and financial reporting arguments (accounting theory) that allows the researcher to predict how accounting variables” (Beaver 2011, p. 35).

Research Problem Statement

Several studies have been carried out on the performance of companies that follow the IFRS in terms of the value relevance of accounting information. For instance, Barth (2008) established that “companies which followIAS/IFRS voluntarily supply higher quality accounting information than companies that apply local accounting standards” (p. 34). Despite this revelation, the author was also categorical that economic and political factors might affect the financial reporting at the local level even for companies that apply the IFRS standards. The institutional setting of a country might also influence the accuracy and relevance of accounting information as was established by research by Ball and Brown (2006) within the European Union market. It is important to review the relationship between the adoption of the IFRS and the value relevance of accounting information within Kuwait, Lebanon, Bahrain, Qatar, the UAE, Oman and Jordanfinancial markets. The findings may reveal the actual reasons motivating the improved or declining value relevance of accounting information in the Gulf region (Qystein&Frode 2007; Ohlson 2009).

Purpose of the Research

The purpose of this research project is to establish the underlying effects of adopting IFRS on the value relevance of accounting information for companies within the mentioned financial markets.

Hypothesis

Null Hypothesis (H0): Country-specific factors do not have an effect on the value relevance of accounting information

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Alternative hypothesis (H1) Hypothesis: Country-specific factors have an effect on the value relevance of accounting information.

Research Gap

Despite a series of researches in the western markets and efforts by respective governments to proactively develop their financial markets, there is no empirical study that has been carried out within the Arab world to establish the effect of IFSR on the value relevance of accounting information. Therefore, this case study will aim at filling this research gap. The study will aim at investigating the value relevance of accounting information in the mentioned countries. Particularly, the study will establish whether the quality and relevance of accounting information has improved within the seven countries or not, despite the efforts by these governments through accounting institutions to adopt the IFRS.

Research Contribution

The contribution of the proposed study is reviewing the value relevance in a context that has never been examined before within the Arab world. Another contribution is studying the impact of the financial crisis on value-relevance in Arab countries. In addition, the proposed case study will review the impact of country-specific factors on value-relevance in Arab countries by using up-to-date institutional factors (Barzegari 2010). The findings of the research project will be beneficial to financial experts within the mentioned countries in making comprehensive and value-relevant financial statements. Besides, the recommendations made may enable the companies within the mentioned markets to adopt the most sustainable financial reporting models within acceptable international and local accounting information standards.

Research Limitations and Delimitation

The findings of the proposed study might not be the only magic bullet in determining the effectiveness of accounting information reporting within the mentioned markets and other economies in the Arab world. This means that the findings will only provide the trend in value relevance of accounting information within the Arab world following the adoption of the IFRS by companies operating in the mentioned countries. This means that the findings will be limited to the IFRS as the only determinant of value relevance of accounting information in the case study markets. In order to minimize this limitation, the research will be carried out through regression and correlation to establish existing relations in each of the seven countries as independent cases (Dung 2010).

Literature Review

Empirical Literature Review

Basically, a case study on the value relevance of accounting information evaluates the existing relationship between market values and the actual accounting information. Several studies have been carried out in the past across the western markets to establish the link between equity values and accounting numbers. For instance, as early as the year 1966, there was a study carried out by Modigliani 1966 on the value relevance of accounting information. This study employed data from the electricity industry to show that earnings on equity contribute the largest towards the marketplace value of a company or industry (Verriest 2007). In another study carried out by Qystein and Frode (2007) to evaluate the value relevance of accounting information in Norway for a period of 40 years, the findings revealed that Norwegian GAAP value relevance did not decline for the entire period.

Several studies have been carried out on the performance of companies that follow the IFRS in terms of the value relevance of accounting information. For instance, Barth (2008) established that “companies which followIAS/IFRS voluntarily supply higher quality accounting information than companies that apply local accounting standards” (p. 34). Despite this revelation, the author was also categorical that economic and political factors might affect the financial reporting at the local level even for companies that apply the IFRS standards. The institutional setting of a country might also influence the accuracy and relevance of accounting information as was established by research by Ball and Brown (2006) within the European Union market.

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A study by Dung (2010) testing the value-relevance of accounting information in terms of formation of the financial statements within the Vietnamese stock market indicated that “the value relevance of accounting was statistically meaningful, though weaker than in other developed and emerging markets” (Dung 2010, p. 67). In another study by Filip (2010) to investigate the direct impact of the adoption of the IFRS on the value relevance of accounting information within the Romania market, the results indicated that proactive and strategic IFRS implementation has the consequence of increasing the value relevance of the recorded earnings (Aljifri 2008).

Literature Discussion

The above literature indicates that adoption of the IFRS has a positive effect on the value relevance of accounting information for companies across the world. Specifically, companies that adopted international accounting standards such as the IFRS had better performance and value-relevant accounting information. There are a number of qualities that enable the accounting information to satisfy the needs of various users. The first quality is that the accounting information is relevant. The information is presented in a way that it is able to influence the decision of a user (McLaney&Atrill 2008). Besides, the information makes it possible for the users to be able to endorse past events and forecast future events easily. Further, the accounting information presented is often material. Thus, the information presented should not change materially in the event that errors or falsifications are established. This can be achieved through reinventing the conceptual framework of operations. The second quality is that accounting information gives a faithful representation of the financial position of the entity. This implies that the accounting information is complete, neutral and free from error. Some of the other qualities are that accounting information is comparable, verifiable, timely, and understandable. Therefore, literature from the western market indicates that adoption of the IFRS has a positive effect on the value relevance of accounting information in companies.

Impacts of Accounting Standards on Company Performance within the Arab World

Close to the countries under investigation, there are only three studies that have been carried out on the IASs for Bahrain and the UAE market environments. The first study was conducted by Joshi and Basteki (1999) on the progress of the local accounting standards following the adoption of the IASs by the Bahrain accounting institutions (Ohlson 2009, Ho 2001). The findings suggested that organizations operating within Bahrain should be more proactive in adhering to the IASs standards and that its application should be regulated by the local accounting regulatory body (Thinggaarda&Damkierb 2008). The second study was carried out by Joshi and Ramadhan (2002) to examine different existing accounting practices and the level of adoption of the IASs by small and medium companies within the value market in Bahrain. The findings revealed that 86% of the participating companies in the study were applying the IASs because they thought the standard was applicable in the preparation of accounting information. The last study was conducted by Aljifri and Khasharmeh (2006) to investigate the IASs sustainability within the UAE market environment through nonparametric and parametric approaches. The findings revealed that the majority of user groups of the IASs argued that it is sustainable and should be adopted by brokers, auditors, financial analysts, and financial managers in financial reporting within the UAE (Marat &Shoult 2005; Marquardt &Wiedman 2004). Besides, existing literature within the Arab market indicates that the adoption of IASs has a positive impact on organization performance, in terms of financial reporting.

Summary of the Literature Review

As indicated in the findings of the empirical research on the value relevance of accounting information, the application of accounting standards has an impact on the quality of financial statement reporting. However, there is no empirical study on the effect of IFRS on the value relevance of accounting information in the mentioned countries. There is, therefore, a need to carry out research on the impact of IFRS on the quality of accounting information within the above countries.

Methodology

Regression

Regression approach will be used to model the relationship between the dependent and the independent variables. This approach will be used to establish the capacity of earnings to clarify the yearly market-adjusted returns. The earnings return model will be appropriate for doing this (Filip 2010; Hung 2001). Easton and Harris’s (1991) market return model has been frequently utilized in research studies that scrutinize the value relevance (Easton & Harris 1991; Kothari 2004). This model makes use of the earnings level and changes in the earnings as the independent variables while the dependent variable is the annual market return on stocks. Therefore, the market return model will be applied to examine the effect of country-specific determinants regards the value of accounting information in the seven countries (Alijifri&Khasharmeh 2006; Hellstrom 2006). The earnings return model is specified below.

Rjt = β0 + β1EPSjt / Pjt-1 + β2(EPSjt – EPSjt-1) / Pjt-1 + ejt

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Rjtrepresents the annual return of shares. It also includes the cash dividends paid.

EPSjtrepresents the annual earnings per share of the firms at time t.

(EPSjt – EPSjt-1) represents the annual change in earnings per share between two consecutive periods.

Pjt-1 represents the price of the stock.

ejt represents the error term.

Correlation analysis

The analysis will show the nature of the relationship between the explanatory variables and the explained variables. Also, it will evaluate the explanatory power of the independent variables by evaluating the coefficient of determination (Baltagi 2011; Madura 2014). Therefore, the hypothesis will be tested using regression and correction analysis.

Data

The data collected comprises the earnings per share and the price of shares of 14 companies that are registered in the mentioned countries. The annual data of the variables have been collected for the period between 2005 and 2014 (Creswell 2009; Frankfort-Nachmias&Nachmias 2008). Further, the data are collected from the Arab market database and the respective website of the stock exchange market for the mentioned countries (Zughaibi&Kabbani 2016). Data for the companies selected will be collected from before the use of International Financial Reporting Standards (IFRS) was adopted in these countries and after the adoption of the standard. A summary of data for the variables for the seven countries is presented below.

Kuwait

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
0.02 22.1 0.442 0.045249
0.02 16.1 0.322 -0.271493 0.062112 0
0.02 14.3 0.286 -0.111801 0.06993 0
0.02 12.1 0.242 -0.153846 0.082645 0
4.4121 32.088 141.58 0.03
4.4503 31.515 140.25 -0.01 0.03 0.00
4.6031 20.819 95.83 -0.32 0.05 0.00
1.9482 35.526 69.21 -0.28 0.03 -0.03
After
0.04 10.2 0.408 0.68595 0.098039 0.0826
0.01 8.9 0.089 -0.781862 0.11236 -0.074
0.04 8 0.32 2.595505 0.125 0.3371
0.04 10.5 0.42 0.3125 0.095238 0
0.04 11.9 0.476 0.133333 0.084034 0
0.01 22.6 0.226 -0.525210 0.044248 -0.063
1.9291 29.605 57.111 -0.174836 0.033778 -3E-04
1.7954 26.167 46.98 -0.177387 0.038216 -0.002
2.0055 19.1 38.305 -0.184656 0.052356 0.0045
2.2156 22.538 49.935 0.303619 0.04437 0.0055
2.5212 22.538 56.823 0.137931 0.04437 0.0061
2.7695 16.617 46.021 -0.19010 0.060179 0.0044

(Source: Zughaibi&Kabbani 2016).

Lebanon

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
1.84 29.3 53.912 0.0341
1.71 28.1 48.051 -0.109 0.0356 -0.002
1.56 27.1 42.276 -0.12 0.0369 -0.003
0.69 23.7 16.353 -0.613 0.0422 -0.021
2.31 16.8 38.808 0.0595
2.33 16.5 38.445 -0.009 0.0606 0.0005
2.41 10.9 26.269 -0.317 0.0917 0.0021
1.02 18.6 18.972 -0.278 0.0538 -0.053
After
0.3 22.1 6.63 -0.595 0.0452 -0.024
0.38 24.4 9.272 0.3985 0.041 0.0121
0.83 40.7 33.781 2.6433 0.0246 0.0485
1.64 14.7 24.108 -0.286 0.068 0.024
1.69 13 21.97 -0.089 0.0769 0.0021
1.65 12.9 21.285 -0.031 0.0775 -0.002
1.01 15.5 15.655 -0.175 0.0645 -5E-04
0.94 13.7 12.878 -0.177 0.073 -0.004
1.05 10 10.5 -0.185 0.1 0.0085
1.16 11.8 13.688 0.3036 0.0847 0.0105
1.32 11.8 15.576 0.1379 0.0847 0.0117
1.45 8.7 12.615 -0.19 0.1149 0.0083

(Source: Zughaibi&Kabbani 2016).

Bahrain

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
0.05 16.8 0.84 0.0595
0.09 16.5 1.485 0.7679 0.0606 0.0476
0.1 10.9 1.09 -0.266 0.0917 0.0067
0.11 18.6 2.046 0.8771 0.0538 0.0092
0.11 11.1 1.221 0.0901
0.09 12.1 1.089 -0.108 0.0826 -0.016
0.06 14.2 0.852 -0.218 0.0704 -0.028
0.11 10.4 1.144 0.3427 0.0962 0.0587
After
0.13 15.2 1.976 -0.034 0.0658 0.0098
0.13 12.6 1.638 -0.171 0.0794 0
0.14 12 1.68 0.0256 0.0833 0.0061
0.17 16.6 2.822 0.6798 0.0602 0.0179
0.19 14.6 2.774 -0.017 0.0685 0.0071
0.22 13.5 2.97 0.0707 0.0741 0.0108
0.1 10.9 1.09 -0.047 0.0917 -0.009
0.07 11.6 0.812 -0.255 0.0862 -0.028
0.06 9.3 0.558 -0.313 0.1075 -0.012
0.09 17.6 1.584 1.8387 0.0568 0.0538
0.09 12 1.08 -0.318 0.0833 0
0.12 12.2 1.464 0.3556 0.082 0.0278

(Source: Zughaibi&Kabbani 2016).

Qatar

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
5.45 8.84 48.178 0.1131
7.8 10.26 80.028 0.6611 0.0975 0.0488
15.26 13.32 203.26 1.5399 0.0751 0.0932
10.69 11.3 120.8 -0.406 0.0885 -0.022
-0.42 4.9 -2.058 0.2041
-0.34 5.3 -1.802 -0.124 0.1887 -0.039
-0.22 6.9 -1.518 -0.158 0.1449 -0.067
-0.26 7.2 -1.872 0.2332 0.1389 0.0264
After
11.78 8.3 97.774 -0.191 0.1205 0.009
12.66 9.5 120.27 0.2301 0.1053 0.009
12.61 12.4 156.36 0.3001 0.0806 -4E-04
13.33 15.4 205.28 0.3128 0.0649 0.0046
12.42 13.9 172.64 -0.159 0.0719 -0.004
13.74 10.7 147.02 -0.148 0.0935 0.0076
-0.82 10 -8.2 3.3803 0.1 0.2991
-0.71 6.8 -4.828 -0.411 0.1471 -0.013
-0.57 5.1 -2.907 -0.398 0.1961 -0.029
-0.47 5.2 -2.444 -0.159 0.1923 -0.034
-0.29 6.3 -1.827 -0.252 0.1587 -0.074
-0.26 4.8 -1.248 -0.317 0.2083 -0.016

(Source: Zughaibi&Kabbani 2016).

UAE

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
0.37 6.1 2.257 0.1639
0.2 5.7 1.14 -0.495 0.1754 -0.075
0.08 4.6 0.368 -0.677 0.2174 -0.105
0.05 4.2 0.21 -0.429 0.2381 -0.082
-1.88 10.3 -19.36 0.0971
1 25.2 25.2 -2.301 0.0397 -0.149
1.1 26.1 28.71 0.1393 0.0383 0.004
0.56 23.1 12.936 -0.549 0.0433 -0.019
After
0.71 5 3.55 15.905 0.2 3.1429
0.85 4.8 4.08 0.1493 0.2083 0.0394
0.82 3.8 3.116 -0.236 0.2632 -0.007
0.73 5.7 4.161 0.3354 0.1754 -0.029
0.49 7.6 3.724 -0.105 0.1316 -0.058
0.37 8.1 2.997 -0.195 0.1235 -0.032
0.14 50.3 7.042 -0.456 0.0199 -0.032
0.38 14.8 5.624 -0.201 0.0676 0.0341
0.42 13.9 5.838 0.0381 0.0719 0.0071
0.39 13.3 5.187 -0.112 0.0752 -0.005
0.48 16.9 8.112 0.5639 0.0592 0.0174
-0.75 10.2 -7.65 -1.943 0.098 -0.152

(Source: Zughaibi&Kabbani 2016).

Oman

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
0.11 11.2 1.232 0.0893
0.15 11.4 1.71 0.388 0.0877 0.0325
0.16 9.8 1.568 -0.083 0.102 0.0058
0.17 7.8 1.326 -0.154 0.1282 0.0064
0.06 9.4 0.564 0.1064
0.05 12.5 0.625 0.1082 0.08 -0.018
0.04 7.7 0.308 -0.507 0.1299 -0.016
0.07 10.1 0.707 1.2955 0.099 0.0974
After
0.15 9.3 1.395 0.052 0.1075 -0.015
0.15 9.2 1.38 -0.011 0.1087 0
0.16 9.5 1.52 0.1014 0.1053 0.0072
0.16 9.7 1.552 0.0211 0.1031 0
0.16 10 1.6 0.0309 0.1 0
0.07 10 0.7 -0.563 0.1 -0.056
0.08 8.7 0.696 -0.016 0.1149 0.0141
0.04 5.7 0.228 -0.672 0.1754 -0.057
0.05 12.2 0.61 1.6754 0.082 0.0439
0.05 15.2 0.76 0.2459 0.0658 0
0.04 11.4 0.456 -0.4 0.0877 -0.013
0.04 17.5 0.7 0.5351 0.0571 0

(Source: Zughaibi&Kabbani 2016).

Jordan

Earnings Per Share Price/Earnings Price per share (EPS * P/E ratio) Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Before
1.67 11.75 19.623 0.0851
1.81 12.55 22.716 0.1576 0.0797 0.0071
0.76 13.15 9.994 -0.56 0.076 -0.046
0.47 13.95 6.5565 -0.344 0.0717 -0.029
0.47 12.3 5.781 0.0813
1.2 13.1 15.72 1.7193 0.0763 0.1263
1.31 13.7 17.947 0.1417 0.073 0.007
1.42 14.5 20.59 0.1473 0.069 0.0061
After
0.44 13.15 5.786 -0.118 0.076 -0.005
0.53 11.35 6.0155 0.0397 0.0881 0.0156
0.4 8.65 3.46 -0.425 0.1156 -0.022
0.47 3.55 1.6685 -0.518 0.2817 0.0202
0.48 4.85 2.328 0.3953 0.2062 0.006
2.33 2.55 5.9415 1.5522 0.3922 0.7947
1.24 13.7 16.988 -0.175 0.073 -0.009
1.07 11.9 12.733 -0.25 0.084 -0.01
1.11 9.2 10.212 -0.198 0.1087 0.0031
0.91 4.1 3.731 -0.635 0.2439 -0.02
0.62 5.4 3.348 -0.103 0.1852 -0.078
0.26 3.1 0.806 -0.759 0.3226 -0.108

(Source: Zughaibi&Kabbani 2016).

Results and Findings

Descriptive statistics

The table presented below will show the descriptive statistics of all the variables that will be used in the earning models. The descriptive statistics will be classified into two groups, that is, before and after the adoption of IFRS (Bade and Parkin 2013; Verbeek 2008).

Variables Earnings Per Share Price/Earnings Price per share (Rjt ) EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Kuwait
Mean 1.4455 19.6607 37.2638 0.0552 0.0616 0.0153
Standard Deviation 1.6603 8.3160 46.2793 0.7148 0.0288 0.0863
Kurtosis -0.6494 -0.9156 0.5972 10.0252 -0.3348 12.8083
Skewness 0.7742 0.3409 1.1656 2.8457 0.8453 3.3333
Lebanon
Mean 1.3645 18.5150 24.0522 0.0172 0.0635 0.0010
Standard Deviation 0.6063 8.2118 13.8265 0.7033 0.0245 0.0207
Kurtosis -0.5774 1.1706 -0.4389 12.8085 -0.6249 2.9964
Skewness 0.0792 1.1525 0.8140 3.3453 0.3168 -0.4427
Bahrain
Mean 0.1115 13.4350 1.5108 0.1784 0.0772 0.0090
Standard Deviation 0.0434 2.6747 0.6965 0.5586 0.0148 0.0250
Kurtosis 0.9520 -0.9186 0.0757 3.5046 -0.7700 -0.0460
Skewness 0.9827 0.4745 0.9465 1.7792 0.1033 0.6112
Qatar
Mean 5.5690 8.8210 66.1454 0.2186 0.1295 0.0110
Standard Deviation 6.4827 3.2739 79.2350 0.9228 0.0480 0.0818
Kurtosis -1.9284 -0.8593 -1.3168 8.3790 -1.2612 9.5909
Skewness 0.2496 0.4596 0.5639 2.7538 0.4010 2.7957
UAE
Mean 0.3255 12.9850 4.8619 0.5239 0.1253 0.1389
Standard Deviation 0.6577 11.2845 9.9501 3.9042 0.0749 0.7518
Kurtosis 6.4071 5.5370 2.8656 16.6185 -1.2124 17.7611
Skewness -2.2268 2.1416 0.3618 3.9959 0.3213 4.2022
Oman
Mean 0.0980 10.4150 0.9819 0.1138 0.1015 0.0018
Standard Deviation 0.0526 2.6005 0.4859 0.5937 0.0250 0.0344
Kurtosis -1.9079 2.2823 -1.5873 2.2915 3.2557 3.0381
Skewness 0.2146 1.0935 0.1048 1.3766 1.0860 0.9010
Jordan
Mean 0.9485 9.8250 9.5972 0.0038 0.1395 0.0367
Standard Deviation 0.5607 4.2428 7.0123 0.6689 0.0980 0.1949
Kurtosis 0.2425 -1.2705 -1.1084 2.7391 1.1032 15.6121
Skewness 0.8893 -0.6762 0.5711 1.6915 1.4740 3.8446

(Source: Zughaibi&Kabbani 2016).

The column graph presented below shows a comparison of descriptive statistics for the seven countries.

a comparison of descriptive statistics for the seven countries.
(Source: Zughaibi&Kabbani 2016).
a comparison of descriptive statistics for the seven countries.
(Source: Zughaibi&Kabbani 2016).

Summary of descriptive statistics before and after the adoption of IFRS

Earnings Per Share Price/Earnings Price per share Annual return on shares (Rjt ) EPSjt/ Pjt-1 (EPSjt– EPSjt-1) / Pjt-1
Kuwait
Before
Mean 1.9367 23.0685 56.02 -0.19016 0.0498 -0.004
Standard deviation 2.2119 8.94137148 63.9 0.11870 0.0200 0.0114
After
Mean 1.11802 17.38875 24.76 0.17789 0.0693 0.0251
Standard deviation 1.16420 7.38223 25.973 0.85670 0.0318 0.1055
Lebanon
Before
Mean 1.7338 21.375 35.386 -0.241 0.0518 -0.013
Standard deviation 0.6308 6.6369 13.559 0.2151 0.0194 0.0213
After
Mean 1.1183 16.6083 16.4965 0.1463 0.0713 0.0079
Standard deviation 0.4652 8.8617 7.5840 0.8300 0.0252 0.0173
Bahrain
Before
Mean 0.09 13.825 1.2209 0.2327 0.0756 0.013
Standard deviation 0.0233 3.154 0.3914 0.5062 0.0166 0.0342
After
Mean 0.1258 13.1750 1.7040 0.1512 0.0782 0.0071
Standard deviation 0.0485 2.4170 0.7991 0.6028 0.0142 0.0206
Qatar
Before
Mean 4.745 8.5025 55.627 0.2911 0.1313 0.0067
Standard deviation 6.0707 2.9697 75.491 0.7154 0.0468 0.0599
After
Mean 6.1183 9.0333 73.1577 0.1823 0.1283 0.0131
Standard deviation 6.9508 3.5747 84.1636 1.0388 0.0509 0.0932
UAE
Before
Mean 0.185 13.163 6.4321 -0.719 0.1267 -0.071
Standard deviation 0.9235 9.8448 15.479 0.8253 0.0825 0.056
After
Mean 0.4192 12.8667 3.8151 1.1453 0.1245 0.2438
Standard deviation 0.4249 12.5792 3.9427 4.6886 0.0732 0.9144
Oman
Before
Mean 0.1013 9.9875 1.005 0.1745 0.1028 0.0181
Standard deviation 0.053 1.6983 0.5185 0.6238 0.0183 0.043
After
Mean 0.0958 10.7000 0.9664 0.0834 0.1006 -0.0064
Standard deviation 0.0545 3.1022 0.4858 0.6041 0.0295 0.0279
Jordan
Before
Mean 1.1388 13.125 14.866 0.2103 0.0765 0.0119
Standard deviation 0.5186 0.9107 6.5743 0.7986 0.0053 0.0604
After
Mean 0.8217 7.6250 6.0848 -0.0994 0.1814 0.0492
Standard deviation 0.5727 4.1673 4.8769 0.6055 0.1085 0.2378

(Source: Zughaibi&Kabbani 2016).

Correlation analysis

The table presented below shows a summary of the correlation coefficient of the variables.

Kuwait
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 0.516179993 1
(EPSjt – EPSjt-1) / Pjt-1 0.968872825 0.508891632 1
Lebanon
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 -0.337913389 1
(EPSjt – EPSjt-1) / Pjt-1 0.685900246 0.077865592 1
Bahrain
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 -0.657993074 1
(EPSjt – EPSjt-1) / Pjt-1 0.732742631 -0.306133266 1
Qatar
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 -0.383048136 1
(EPSjt – EPSjt-1) / Pjt-1 0.952482484 -0.386848449 1
UAE
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 0.26212176 1
(EPSjt – EPSjt-1) / Pjt-1 0.991961725 0.231932223 1
Oman
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 -0.52207934 1
(EPSjt – EPSjt-1) / Pjt-1 0.830199995 -0.345355405 1
Jordan
Rjt EPSjt / Pjt-1 (EPSjt – EPSjt-1) / Pjt-1
Rjt 1
EPSjt / Pjt-1 0.088910946 1
(EPSjt – EPSjt-1) / Pjt-1 0.71960101 0.508798103

(Source: Zughaibi&Kabbani 2016).

A positive correlation can be observed between the three countries in Kuwait, UAE, and Jordan. A negative association was observed in some variables in the other four countries (Berk 2004; Blank 2011; Vinod 2008).

Regression

The regression results for the seven countries are summarized in the tables below.

Kuwait

Before
Coefficients Standard Error t Stat P-value
Intercept -0.1057 0.2161 -0.4893 0.6582
EPSjt / Pjt-1 -1.1757 3.5380 -0.3323 0.7615
(EPSjt – EPSjt-1) / Pjt-1 4.8359 6.6965 0.7222 0.5224
ANOVA F Significance 0.7835
R Square 0.15009
After
Coefficients Standard Error t Stat P-value
Intercept -0.0769 0.1614 -0.4766 0.6450
EPSjt / Pjt-1 0.8565 2.2829 0.3752 0.7162
(EPSjt – EPSjt-1) / Pjt-1 7.7902 0.6888 11.3101 0.0000
ANOVA F Significance 1.07659E-06
R Square 0.9528

Lebanon

Before
Coefficients Standard Error t Stat P-value
Intercept -0.1150 0.3272 -0.3515 0.7485
EPSjt / Pjt-1 -1.3683 5.4411 -0.2515 0.8177
(EPSjt – EPSjt-1) / Pjt-1 4.1461 5.4018 0.7675 0.4986
ANOVA F Significance 0.7597
R Square 0.1674
After
Coefficients Standard Error t Stat P-value
Intercept 0.7443 0.4046 1.8397 0.0990
EPSjt / Pjt-1 -12.2329 5.1530 -2.3739 0.0416
(EPSjt – EPSjt-1) / Pjt-1 34.5752 7.4955 4.6128 0.0013
ANOVA F Significance 0.0008
R Square 0.7925

(Source: Zughaibi&Kabbani 2016).

Bahrain

Before
Coefficients Standard Error t Stat P-value
Intercept 1.7691 0.3950 4.4791 0.0207
EPSjt / Pjt-1 -22.0517 5.1406 -4.2897 0.0233
(EPSjt – EPSjt-1) / Pjt-1 10.5050 2.5693 4.0886 0.0264
ANOVA F Significance 0.0264
R Square 0.9114
After
Coefficients Standard Error t Stat P-value
Intercept 0.3520 0.7789 0.4519 0.6621
EPSjt / Pjt-1 -4.6729 9.4634 -0.4938 0.6333
(EPSjt – EPSjt-1) / Pjt-1 23.3842 6.5259 3.5833 0.0059
ANOVA F Significance 0.0012
R Square 0.7752

(Source: Zughaibi&Kabbani 2016).

Qatar

Before
Coefficients Standard Error t Stat P-value
Intercept 0.0009 0.6816 0.0013 0.9990
EPSjt / Pjt-1 1.7309 5.2888 0.3273 0.7650
(EPSjt – EPSjt-1) / Pjt-1 11.6678 3.7837 3.0837 0.0540
ANOVA F Significance 0.0695
R Square 0.8310
After
Coefficients Standard Error t Stat P-value
Intercept 0.1131 0.2528 0.4473 0.6652
EPSjt / Pjt-1 -0.5544 1.8236 -0.3040 0.7680
(EPSjt – EPSjt-1) / Pjt-1 10.6785 0.9948 10.7344 0.0000
ANOVA F Significance 0.000004271
R Square 0.9359

(Source: Zughaibi&Kabbani 2016).

UAE

Before
Coefficients Standard Error t Stat P-value
Intercept -0.2820 0.1448 -1.9478 0.1466
EPSjt / Pjt-1 4.9495 0.8787 5.6329 0.0111
(EPSjt – EPSjt-1) / Pjt-1 14.9038 1.4937 9.9775 0.0021
ANOVA F Significance 0.0046
R Square 0.9724
After
Coefficients Standard Error t Stat P-value
Intercept -0.1869 0.2815 -0.6641 0.5233
EPSjt / Pjt-1 0.7401 2.0605 0.3592 0.7277
(EPSjt – EPSjt-1) / Pjt-1 5.0866 0.1650 30.8340 0.0000
ANOVA F Significance 4.344E-10
R Square 0.9917

(Source: Zughaibi&Kabbani 2016).

Oman

Before
Coefficients Standard Error t Stat P-value
Intercept 0.9894 0.3443 2.8739 0.0638
EPSjt / Pjt-1 -9.9640 3.1827 -3.1307 0.0520
(EPSjt – EPSjt-1) / Pjt-1 12.5156 1.5267 8.1980 0.0038
ANOVA F Significance 0.0057
R Square 0.9682
After
Coefficients Standard Error t-Stat P-value
Intercept 0.4898 0.4289 1.1421 0.2829
EPSjt / Pjt-1 -2.9928 4.2828 -0.6988 0.5023
(EPSjt – EPSjt-1) / Pjt-1 16.4673 4.5282 3.6366 0.0054
ANOVA F Significance 0.0034
R Square 0.7166

(Source: Zughaibi&Kabbani 2016).

Jordan

Before
Coefficients Standard Error t Stat P-value
Intercept 0.03999 0.11279 0.35457 0.74637
EPSjt / Pjt-1 0.17667 1.51998 0.11623 0.91481
(EPSjt – EPSjt-1) / Pjt-1 13.22840 0.09633 137.32 0.00000
ANOVA F Significance 1.87E-06
R Square 0.99985
After
Coefficients Standard Error t Stat P-value
Intercept 0.00753 0.18080 0.04167 0.96767
EPSjt / Pjt-1 -1.28617 0.94573 -1.35998 0.20693
(EPSjt – EPSjt-1) / Pjt-1 2.57176 0.43173 5.95686 0.00021
ANOVA F Significance 0.00046
R Square 0.81855

(Source: Zughaibi&Kabbani 2016).

Discussion

In the case of Kuwait, the explanatory power of the accounting information improved after the adoption of IFRS. This can be seen in the growth of the values of R-square from 15.009% before to 95.28% after the adoption of the set of standards (Field 2013). Also, there was an improvement in the overall regression line and the explanatory power of the specific variables. A similar trend was observed in Lebanon. The explanatory power improved from 16.74% before to 79.25% after the adoption of IFRS. The overall regression line also improved as indicated by the F-test (Filip &Raffournier 2010). The significance of the explanatory variables also improved after the adoption as indicated by the t-tests. In the case of Bahrain, the explanatory power of accounting information dropped after the adoption of IFRS. The coefficient of determination dropped from 91.14% to 77.52%. However, the significance of the overall regression line improved. This indicates that the employment of the set of standards did not enhance the explanatory power of the accounting information. As for Qatar, the coefficient of determination improved from 83.10% to 93.59%. The significance of the overall regression line also improved. A slight improvement in the explanatory power of accounting information was also observed in the UAE. The coefficient of determination grew from 97.24% before the adoption of IFRS to 99.17% after the adoption of the standard. In the case of Oman, the adoption of IFRS did not improve the explanatory power of accounting information. The value of R-square dropped from 96.82% to 71.66%. A similar trend was observed in Jordan (Green &Salkind 2014; Greene 2011; Gujarati 2014; Verbeek 2008). The coefficient of determination dropped from 99.96% before the adoption of IFRS to 81.86% after the adoption (Wang 2010; Zikmund et al. 2012).

The results show that the adoption of accounting IFRS (country-specific factor) improved the relevance of accounting information in four out of the seven countries. Therefore, the null hypothesis will be rejected and this implies that country-specific factors have an effect on the value relevance of accounting information.

Conclusion

Induction is the mechanism of receiving accounts that are beginning their functions on accounting systems. In fact, an organization’s assignee should familiarize new staff members both to the organization and fellow staff members, educating them in the accounting habits, happenings, and culture of the organization. In fact, there are a number of qualities that enable the accounting information to satisfy the needs of various users. The first quality is that the accounting information is relevant. The information is presented in a way that it is able to influence the decision of a user (McLaney&Atrill 2008). Besides, the information makes it possible for the users to be able to endorse past events and forecast future events easily(Ho 2001). Further, the accounting information presented is often material. Thus, the information presented should not change materially in the event that errors or falsifications are established. This can be achieved through reinventing the conceptual framework of operations (Haber, 2004). The second quality is that accounting information gives a faithful representation of the financial position of the entity (Green &Salkind 2014; Greene 2011; Gujarati 2014; Verbeek 2008). This implies that the accounting information is complete, neutral and free from error. Some of the other qualities are that accounting information is comparable, verifiable, timely, and understandable.

The findings indicate that accounting information value relevance in companies within Kuwait, Lebanon, Bahrain, Qatar, the UAE, Oman and Jordan, has resulted in the improved financial performance of these companies. Through the regression approach, the results obtained have indicated that there is value relevance in accounting information in the seven countries for companies that embraced the IFRS. A comparative analysis of the results obtained after and before the adoption of the IFRS indicted an enhancement in the value relevance of accounting information for these companies in all seven countries (Aljifri, 2008). The results can be inferred to mean that adoption of the IFRS improved the accounting information value relevancy in the companies that adopted the international standards in the seven countries.

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