Asian Journal of Social Sciences and Management Studies ISSN(E) : 2313-7401 ISSN(P) : 2518-0096 Vol. 4, No. 1, 1-9, 2017 http://www.asianonlinejournals.com/index.php/AJSSMS 1 The Impact of the New Accounting Reporting Among Listed Firms in Nigerian Stock Market Musa Yelwa Abubakar1 Nasiru Abdulsallam2 Muhammad Yusuf Alkali3 1,2 Department of Accounting Usmanu Danfodiyo University Sokoto, Nigeria 3 Department of Accounting Waziri Umaru Federal Polytechnic Birnin Kebbi Kebbi State, Nigeria ( Corresponding Author) Abstract The study discusses the relationship between accounting disclosures and market value under new accounting reporting. The study addresses whether accounting information has improved after the IFRS adoption among Nigerian listed firms. The study adopted Ohlson (1995) stock price model that has commonly been used in the capital market for a 5-year data of 129 companies listed in the Nigerian stock market. The Findings of the study have shown disaggregated assets and liabilities have a strong relationship with stock price. However, there is higher association after the adoption of IFRS from the adjusted R 2 . Furthermore, current assets presented more explanatory power than all other variables in the model, signifying that investors rely on current assets for decision making. However, Cramer (1987) Z statistics provided no significance difference in value relevance between the two periods. A possible explanation of the changes could be that investors do not view accounting information to be different in the two periods. Therefore, policy makers, standard setters, and regulators need to come together to address the issue of IFRS adoption by firms in Nigeria. Keywords: Accounting information, Value relevance, Assets, Liabilities. JEL Classification: G10, G14, G15. Contents 1. Introduction ........................................................................................................................................................................... 2 2. Literature Review .................................................................................................................................................................. 2 3. Data and Methodology........................................................................................................................................................... 4 4. Discussion of Results .............................................................................................................................................................. 5 5. Robust Test ............................................................................................................................................................................ 6 6. Conclusions ............................................................................................................................................................................ 7 References .................................................................................................................................................................................. 8 Citation | Musa Yelwa Abubakar; Nasiru Abdulsallam; Muhammad Yusuf Alkali (2017). The Impact of the New Accounting Reporting Among Listed Firms in Nigerian Stock Market. Asian Journal of Social Sciences and Management Studies, 4(1): 1-9. DOI: 10.20448/journal.500/2017.4.1/500.1.1.9 ISSN(E) : 2313-7401 ISSN(P) : 2518-0096 Licensed: Contribution/Acknowledgement: This work is licensed under a Creative Commons Attribution 3.0 License All authors contributed to the conception and design of the study. Funding: This study received no specific financial support. Competing Interests: The authors declare that they have no conflict of interests. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study was reported; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. History: Received: 24 August 2016/ Revised: 1 September 2016/ Accepted: 26 September 2016/ Published: 27 October 2016 Ethical: This study follows all ethical practices during writing. 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Introduction This study explores the relevance of accounting information on the disaggregated assets and liabilities after the adoption of International Financial Reporting System(IFRS) in Nigeria. The study adopted the most widely used Ohlson (1995) price model to determine whether accounting information is more value relevant after the adoption of IFRS in Nigeria. The motivation of this study is premised on the quality of accounting information reported by the World Bank in the year 2010. The report of the world bank in the period was that Nigerian accounting and auditing reporting suffered a serious neglect, non-update of domestic accounting standard, non-compliance, and disclosures of accounting reporting by the companies. Also, Nigerian stock market is one of the biggest markets in Africa and among the emerging markets in the world, therefore, conducting a study in the market would provide a better understanding of the capital market in emerging market. Accounting research after Ball and Brown (1968) produced several studies presenting association between market value and accounting earnings. Immediately, after their study, more researchers on value relevance were carried out to include balance sheet disclosures on total assets and total liabilities, income statements, cash flows, and earnings using Ohlson (1995). However, the prior studies on value relevance focused on the US and UK markets only (Barth, 1994; Barth et al., 1996; Barth et al., 1999). The increasing importance of accounting information within the international markets, lead to more studies investigating the value relevance of accounting information in markets that are non-US developed markets (Amir et al., 1993; Collins et al., 1997; Graham et al., 2000) extended to emerging markets (Chen et al., 2001; Kargin, 2013a; Chebaane and Othman, 2014; Mironiuc et al., 2015; Păşcan, 2015) and in Nigeria (Umoren & Enang 2015; Omokhudu & Ibadin 2015; Mohammed & Lode 2015; Muhammad et al. 2015). The choice for the Nigerian market between the year 2009 to 2011 (pre-adoption) and 2012 to 2013 (after the adoption) is on the fact that, 2009 was the year immediately after the 2008 financial crisis in the country while the period 2012 was the year of IFRS adoption in the country. Another reason for taking Nigeria in Africa was because Nigerian capital market is reported by NSE in 2013 and CIA fact book 2013 to be the second largest capital market after South Africa and the most famous in the West African sub-region. The Nigerian equities market appreciation in 2012 to 2013 made the market be among the best-performing markets in the world (Peter and Nnorom, 2013). Nigerian capital market is reported to be in a weak-form efficiency, therefore, follows a random walk (Sule et al., 2015). The growth of the Nigerian capital market attracted many investors into the capital market, this evident by the increasing number of investors in the economy. The Nigerian domestic bond registration with JP Morgan local currency index in the year 2012 is another milestone for the market. Also, the local bond in Nigeria gets another huge boost in 2013 from the inclusion in the sovereign bonds of Barclay‟s Emerging bond index. This contributes significantly in attracting foreign investors that have an estimated investment in the country of about USD5.6 billion in Nigerian bonds (Peter and Nnorom, 2013). The level of value relevance of accounting information for the sample is operationalised using price regression that has commonly been used in value relevance of accounting information ( see, (Barth et al., 2001; Gordon, 2001; Mechelli and Cimini, 2014)) studies and empirically tested. Share price is being used in the survey as dependent variable while disaggregated assets (Current assets and fixed assets), and liabilities (Current liabilities and non-current liabilities) as independent variables. Panel data regression was employed throughout the regression analysis. The data is divided into two periods as pre-and post-adoption of IFRS. Pre-adoption period commenced from 2009 to 2011 (three Years), and post-adoption is 2012 to 2013(two years). In Nigeria, all listed firms are mandated to report their financial statement by the IFRS effective 2012. However, before the period of 2012 companies in Nigeria were expected to report based on the Nigerian domestic accounting reporting (SAS). Despite the importance of the value relevance of disaggregated assets and liabilities to investors little or no studies were conducted in emerging markets particularly in Nigeria. One of the important study conducted on aggregated assets and liabilities was from Kadri et al. (2010) from Malaysia. Therefore, this study is important for the investors, standard setters and policy makers in Nigeria to understand the relevance of disaggregated assets and liabilities. 2. Literature Review Value relevance has been defined as an association between accounting amounts and security values (Barth & Beaver 2000). The ability for accounting reporting to summarise and capture accounting information affecting share information has been examined in testing the statistical relationship between accounting numbers and market values and mapping from financial statements to “intrinsic” values (Aboody et al., 2002; Hellström, 2006; Vijitha and Nimalathasan, 2014). Similarly, value relevance of financial information can be predictive and statistically measured through the relationship between stock market values from the information reported on the financial statement (Barth et al., 2001) with the ability to the information provided in the annual reports to summarise and capture firm value (Beisland, 2009; Kargin, 2013b). As the ability to account information provided by a financial statement to report and summarise firm value (Păşcan, 2015). Several scholars have studied the value relevance of accounting information in different perspectives. Beisland (2009) reported that majority of value relevance researches are related to market efficiency because they can provide the relationship between accounting measures and stock prices. Holthausen and Watts (2001) examined whether the relations between accounting numbers and stock prices are value relevant in explaining market value. Ebaid (2012) studied the influence of accounting-based methods on market returns and prices and their predictive values to be referred to as the value relevance of accounting reporting. Brien (2005) emphasised that relevance and reliability be the capacity of accounting numbers to summarise and capture accounting information that has a significant effect on stock prices. Kommunuri (2008) provided that relevance and reliability of accounting information be two key features of accounting information. Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 3 Barth (1994) measured value relevance of banks' investment securities using fair value and historical cost for both assets and related earnings. The study provides evidence on the two methods of relative and incremental explanatory power with relative measurements error. Barth (1994) documented that fair value measurement estimates from investment securities have more significant explanatory power over historical costs. The results of fair value of gains and losses from securities investment have no significant incremental power; historical cost provides significant incremental explanatory power over fair value. In contrast, Ahmed and Carolyn (1995) document different results compared to Barth (1994) with the controlling effects of other net assets. They found that both Realised and unrealised gains and losses to provide a significant positive effect in regular periods of bank returns, although realised security gains and losses have lower significant effect in a period of weak earnings and capital. Mozes (2002) examined fair value disclosures as required by the Statement of Financial Accounting Standards (SFAS) 119, derivatives disclosure of fair value of the financial instrument to be value relevant. The study adopted residual valuation model to investigate the association between two variables to measure the fair value of book value and security prices of financial instruments. Also, Mozes found that firms with a greater return on investment on capital have a relative cost of capital growth; the estimated relationship will improve and becomes negative in fair value of book value. Barth and Clinch (1998) reported that intangible assets are value relevant regardless of re-evaluation period, and non-financial firms‟ investment is value relevant other than the current year. Baboukardos and Rimmel (2014) concluded that relevant accounting numbers on purchased goodwill generate relevant accounting numbers on companies that have a high disclosure only under IFRS. 2.1. Studies Conducted Related to Value Relevance and IFRS Studies on value relevance research provide contradictive results as a result of factors in which the study is carried out (Mironiuc et al., 2015). However, several studies were conducted on the value relevance in a different environment and context because of the growing number of accounting information demand. Agostino et al. (2011) investigated European banks the relevance of association between stock market, book value and earnings for the periods before and after the adoption of IFRSamong European banks. The findings provided that, book value and earnings to be more informative after the post-adoption of IFRS. Also, Palea (2014) examined the value relevance of different financial statements in Italian firms under GAAP and IFRS. The report of their study showed that separate financial reports were value relevant because they both provided useful information to the capital market. Contrary to expectations, the findings indicated that reporting under IFRS to have less incremental information content than Italian GAAP. Using Bursa Malaysia, Kwong (2010) examined pre- and post-adoption of IFRS for the period of 1993 to 2007 using the balance sheet and income statements. Overall, IFRS was more value relevant than GAAP for investors‟ decision-making and book value, and earnings were significantly valued relevant in the old regime which is consistent with Kadri et al. (2009). In contrast, Kwong (2010) found that earnings had greater value relevance under IFRS than book value under Bursa Malaysia. Prather-Kinsey (2006) measured two different capital markets using earnings announcement (Johannesburg Stock Exchange (JSE), South Africa & Bolsa Mexicana de Valores (BMV) Stock, Mexico), testing the association between book value and earnings with firm market value. He reports that book values were value relevant in both markets, with the significant positive association between earnings or equity values and market value in the published financial statements in the two markets. There was also immediate significant increase in earnings announcements in the JSE. Khanagha (2011) adopted two periods of accounting information using samples of the ADX under pre- and post-IFRS adoption to determine the value relevance of accounting variables. Two empirical (models) approaches were employed for the study portfolio: return approach and regression-variations approach. The assumption of the adoption of the two methods is that they will offer different viewpoints on the issue of value relevance of accounting information in the ADX. The study adopted 17 entities that are listed on the ADX for the samples of the survey periods of 2001-2008 with 136 firm-year observations for eight years using regression-variation approach; while the portfolio approach employed 119 firm-year observations for seven years. The results obtained from the two methods provide evidence that the portfolio approach has more information content under the ADX capital market before adoption. Similarly, a decline in value relevance of accounting measures after the adoption of IFRS was noticed when the two approaches were combined. This combined results showed that there was no improvement on value relevance after the enactment of the IFRS. This concurs with Francis and Schipper (1999) that portfolio approach measures relevance more than the explained variation test. Several studies on the value relevance of accounting information were conducted in Nigeria using different perspectives. Mohammed and Lode (2015) analysed the value relevance of assets and liabilities on explaining the market value in the Nigerian stock market from 2009 to 2013(five years) for the pre-and post-adoption of IFRS. The report of the study provides evidence of an increase in value relevance of accounting information after the adoption of IFRS. Similarly, Omokhudu and Ibadin (2015) study was related to earnings, cash flows and dividend from 1994 to 2013(ten years). The findings show that earnings, cash flows, and dividend were significantly associated with stock prices, but found book value not to be statistically significant. Furthermore, the study of Uthman and Abdul-Baki (2014) related to the extent of finance theory on the timing of information among Nigerian firms. The study measured IFRS disclosure and fair value valuation of economic events. The study findings revealed that there is a significant relationship between IFRS and finance measurement of information. They conclude that IFRS enhanced value relevance of accounting information in Nigeria. This present study differs with other studies in Nigeria in the sense that, they based their research findings on the book value, earnings, and cash flows. Consequently, the results of the survey were concluded base on the adjusted R 2 , consistent with (Ball et al., 2000; Graham et al., 2000). Even though Mohammed and Lode (2015) Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 4 conducted a study on assets and liabilities in Nigeria, and measured value relevance based on the adjusted R 2 . This study uses selected assets and liabilities that uses adjusted R 2 for the value relevance with an additional test from 1 Cramer (1987) statistics to determine the explanatory power and significant statistics of the adjusted R 2 . 3. Data and Methodology 3.1. Sample Description To determine the value relevance of accounting information, the study generates data derived from 2009 to 2013 from Nigerian listed firms. The periods were petitioned into two as pre-IFRS(2009-2011) and post-IFRS adoption (2012-2013) to observe whether there is an increase in value relevance of accounting information. Two sources for data collection were used, first for non-financial firms data was collected from Thomson Reuters DataStream and Secondly, financial firms data was collected from Bankscope data stream. All companies that have been reporting IFRS in Nigeria and listed in the Nigerian Stock Market were hand picked for the study. Table 1 has the number of samples for the for the study. The first column (column 1) presents cross-sectional years employed for the survey, with 126 samples. The second column (column 2) is the number of observation of 630, 378 and 273-year observations for pooled samples, pre-and post-adoption respectively. The third column (column 3) is the samples for the non-financial firms present 70 companies for pooled, pre-and post-adoption. The fourth column(column 4) is the 350 observation for pooled data and 210 and 140 for the pre-and post-adoption of IFRS respectively. The fifth column(column 5) is the sample of financial firms in the study that 56 for pooled and pre- and post-adoption of IFRS. Last is six column(column 6) that has an observation of 280, 16 and 112 for the pooled, pre-and post-adoption of IFRS. Table-1. Number of firms 2009-2013 Year Column1 Samples Column2 Observ Column 3 Non-financials Column 4 Observ Column 5 Financials Column 6 Observation Pooled Samples 2009-2013 2009-2013 126 630 70 350 56 280 Pre-IFRS 2009-2011 2009 126 378 70 210 56 168 2010 126 378 - - - - 2011 126 378 - - - - Post-IFRS 2012-2013 2012 126 252 70 140 56 112 2013 126 252 - - - - Source: NSE 2013 3.2. Methodology and Models Most often value relevance models are measured by regressing stock prices and accounting disclosures (Liu et al., 2012). According to Lang et al. (2006) accounting data are expected to be more useful if they show a higher association with market value. The stock price is collected three (3) months after the end of fiscal year as the required by the NSE for announcement date. A test for value relevance for the two the period is conducted with the R 2 as in the equation 1A using Ohlson (1995) model. Price model is reported to have more advantages over return models because the model anticipate accounting earnings components and at the beginning of stock price all anticipated are incorporated (Chen et al., 2001). In contrast, Kothari and Zimmerman (1995) stated that price model produces unbiased coefficients in earnings because prices reveal total earnings information effect. The significant test to compare the differences between R 2 of the two periods was done with 2 Cramer (1987) Then the test of value relevance is conducted with the R2 from Eq. (1) Based on Ohlson (1995) framework. R2 of two consecutive periods are then compared with Cramer (1987). 1A and 1B 1C 1D 1H 1I Where = value of the firm. = Current Assets for firm i at the end of year t = Fixed Assets for firm i at the end of year t = Current Liabilities for firm i at the end of year t =Non-Current Liabilities for firm i at the end of year t = Audit as dummy variable “1” for firms that uses audit „4” and „0‟ otherwise. All variables are deflated by the total number of outstanding shares 1 To determine the statistical significance of adjusted R2 2 Statistical comparisons are based on the expectation and variance of R2 as derived in Cramer (1987). Z-statistics as follows: √ Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 5 4. Discussion of Results Table 2 provides the result of yearly cross-sectional regression data of Model 1, of share price on current assets, fixed assets, current liabilities and non-current liabilities. Ordinary Least Square (OLS) estimation that has commonly been used in value relevance studies is employed to calculate the coefficients estimates. The adjusted R 2 in Table 2 range from 16.19% in 2011 to 22.48% in 2012 with an average mean of 21%. The coefficients of CA, FA, and AUD are positive and significant in each year with a p<0.05% expect in the year 2010 with CA significant level of p<0.10%. Furthermore, variables CL and NCL have a significant negative level as expected with the p<0.05%. The diagnostic test was conducted in the state include, (i) Multicollinearity is appraised by Variance Inflation Factors(VIF). The VIF provide no evidence of multicollinearity issue in the model, and (ii) White (1980) test on heteroscedasticity is found to be significant in some period and not significant in other periods. However, that has been taken care by robust standard error. Table-2.Yearly Cross-sectional Regression of price on Selected Assets and Liabilities Note: P=Price per share for firm i at the end of the year t. CA=current asset for firm i at the end of the year t. FA=fixed asset for firm i at the end of the year t. CL=current liabilities for firm i at the end of the year t. NCL=non-current liabilities for firm i at the end of the year t. AUD= AUD = Auditors as dummy variable “1” for “Big 4” auditors and “0” otherwise. All variables are deflated by the total number of outstanding shares. β= Coefficient of the explanatory variables. white‟s heteroscedasticity- consistent variances and standard error significant level of p<1%, 5%, & 10%. R2=Adjusted R2 within the panel regression. All p-values are estimated based on the White (1980) corrected error for heteroscedasticity Table 3 was divided into two Panels (Panel A and Panel B). Panel A presents pooled data for all the variables and data for the pre-and post-adoption of IFRS. The panel also has the pooled data for CA and FA and also pre-and post-adoption of IFRS. Panel B provides the regression analysis of CL and NLC pooled data and pre-and post- adoption of IFRS. Panel A data is the regression analysis of pooled data that utilises all the observation of 630 from 126 firms for the before and after the adoption of all variables. The panel also provides observations of 378 for the data before the adoption and 252 after the adoption of IFRS. The value relevance of accounting information has shown to improve in the periods after adoption for the pooled data and CA, FA, (total adjusted R2 before=18.77% and after=22.11% for pooled data, CA before=5.48% and after=7.96%, FA before=4.83% and after=6.03%) In the Panel B presents 630 observations from 126 firms for the pooled data of NCL and CL. The panel also provides observations of 378 for the data before the adoption and 252 after the adoption of IFRS. However, the variable NCL provides a greater value relevance of accounting information after the adoption (before= 4.64% and after=4.74%). However, CL presents a decline in the value relevance of accounting information (adjusted R 2 before=3.56% and after=3.45%). The study compares the adjusted R 2 of 2009 and 2011 with that of 2012and 2013 to examine whether there is more value relevance of accounting information after the adoption. Using 3 Cramer‟s (1987) Z statistic test, there is no evidence of significant statistical differences between pre-and post-adoption (Panel A and B, the Z value pre- and post-adoption, pooled data=0.2823, individual variables CA=0.04902, FA=0.04901, CL=0.048803, and NCL=0.48803). Even though the results of adjusted R 2 provide evidence of increase between pre-and post- adoption of IFRS but no evidence the R 2 between the two periods is statistically different. The last columns in the Panel B, last three columns in the Panel B show the incremental explanatory power of value relevance of each of the variables (CA, FA, Cl, NCL) together with the common explanatory power. The variable CA total variant in stock prices explained and increase from 13.29% at the period before to 14.5% in the period after and (FA before= 13.94% and, after= 16.03%, CL before 15.32% and after= 18.66%, NCL before=14.13% and after=17.37%). The results presented in the column suggest an increase in value relevance, but the Cramer‟s Z provides no statistical significance difference between the R 2 . The findings of the study need to be interpreted with care; this is because firms that did not provide data from 2009 to 2013 are excluded from the survey. The study also uses three years before and two years after the adoptions as the number of samples are not equal, with a deficiency of 1 year after the adoption. Furthermore, unlike Graham et al. (2000) their study measured adjusted R2 for only one year within four quarters for 1997 and 3 The Z values in the model did not provide and significant value. P is not significant in all the variables  measure α0 β1 β2 β3 β3 β4 R 2 Coeff 0.3026 0.0802 0.0047 -0.0021 -0.2345 0.6155 0.2097 t-value 1.13 3.28 10.69 -2.65 -3.17 1.98 p-value 0.261 0.001 0.000 0.009 0.002 0.050 vif 1.15 1.01 1.02 1.02 1.11 white 0.0204 0.3652 0.0002 0.2121 0.2131 Coeff 0.4733 0.0756 0.0013 -0.0008 -0.2221 0.6492 0.2294 t-value 1.66 3.99 4.77 -2.65 -3.87 1.98 p-value 0.100 0.000 0.000 0.009 0.000 0.050 vif 1.01 1 1.03 1.02 1.03 white 0.000 0.023 0.002 0.453 0.000 Coeff 0.6417 0.0465 0.0025 -0.0003 -0.1367 0.5994 0.1619 t-value 2.08 1.83 4.23 -0.97 -1.77 1.74 p-value 0.039 0.070 0.000 0.335 0.079 0.085 vif 1.110 1.020 1.070 1.020 1.210 white 0.000 0.213 0.654 0.324 0.654 Coeff 0.6969 0.0591 0.0055 -0.0025 -0.1635 0.5354 0.2248 t-value 2.29 3.59 7.4 -3.83 -3.29 1.58 p-value 0.024 0.000 0.000 0.000 0.001 0.118 vif 1.200 1.300 1.020 1.020 1.010 white 0.054 0.000 0.235 0.243 0.068 Coeff 0.738986 0.0646 0.0046 -0.0024 -0.1791 0.7109 0.2236 t-value 2.6 2.54 6.11 -2.84 -2.34 2.23 p-value 0.010 0.012 0.000 0.005 0.021 0.028 vif 1.010 1.000 1.020 1.020 1.220 white 0.355 0.037 0.088 0.765 0.254 Model1 1A Pit = α0+ β1CAit+ β2FAit+ β3CLit+ β4NCLit+ β4AUDit+µit 2009 2010 2011 2012 2013 Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 6 1998. This study will conclude that Nigerian, adoption of IFRS had a marginal improvement in value relevance of accounting information from 2009 to 2013. Another evidence, Liu et al. (2012) reported that results from adopting IFRS often provides support for the differences on the relevance of accounting information, so also, when a new standard is applied to the same accounting regulations. Table-3. Stock Price Models Panel A: Pooled regression results of selected assets and liabilities ***Significant level 1% **significant level 5% * significant level 10% 1 price regression: SP= α1 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit+µit SP= β1CAit + β5AUDit+µit SP= β2FAit t + β5AUDit+µit Variable definitions for Table 15: SP= Share price of firm three months after the year end t. CA=Current assets per share of firm i at the end of fiscal year t. FA=Fixed assets for firm i at the end of fiscal year t. CL=Current liabilities per share of firm i at the end of fiscal year t. NCL=Non-current assets for firm i at the end of fiscal year t. AUD = Auditors as dummy variable “1” for “Big 4” auditors and “0” otherwise. β= Coefficient of the explanatory variables. R2=Adjusted R2 within the panel regression. Cramer (1987) is for the statistical difference in adjusted R2 between Pre-and Post-adoption of IFRS from table lists p-values. All p-values are estimated based on the White (1980) corrected error for heteroscedasticity Table-3. continued B: Pooled regression results of selected assets and liabilities ***Significant level 1% **significant level 5% * significant level 10% 1 price regression: SP= α1 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit+µit SP= β1CLit + β5AUDit+µit SP= β2NCLit t + β5AUDit+µit Variable definitions for Table 15: SP= Share price of firm three months after the year end t. CA=Current assets per share of firm i at the end of fiscal year t. FA=Fixed assets for firm i at the end of fiscal year t. CL=Current liabilities per share of firm i at the end of fiscal year t. NCL=Non-current assets for firm i at the end of fiscal year t. AUD = Auditors as dummy variable “1” for “Big 4” auditors and “0” otherwise. β= Coefficient of the explanatory variables. R2=Adjusted R2 within the panel regression. Cramer (1987) is for the statistical difference in adjusted R2 between Pre-and Post-adoption of IFRS from table lists p-values. All p-values are estimated based on the White (1980) corrected error for heteroscedasticity 5. Robust Test To find whether the value relevance of accounting information is as a result of non-financial or financial firms. We separate the firms into two for non-financial and financials in Table 4 and Table 5. 5.1. Regression for Non-Financial Firms The result in Table 4 presents regression result of non-financial companies for the selected assets and liabilities. The coefficient of estimates for the pooled data for CA and FA are positively significant, and CL and NCL are negatively significant, all the variables CA, FA, CL and NCL have a significant level of associations p<0.001% with the stock price for the pooled data. The results of before and after the adoption present similar results expect NCL that does not provide any significant level of association with stock prices before and after the adoption of IFRS. The results from the regression provide evidence of increase value relevance of accounting information from the increased adjusted R 2 provided in the table (Adjusted R 2 before=21.49% and after=24.19%). Supporting the pooled data of having higher adjusted R 2 after the adoption of IFRS. The Cramer Z statistics shows no statistically significant difference between the two periods equally. 5.2. Regression of Financial Firms The result in Table 5 presents regression result of non-financial firms for the selected assets and liabilities. The coefficient of estimates for the pooled data for CA and FA are positively significant, and α1 β 1 β2 β3 β4 β5 R2 β 1 Β5 R2 β 2 β5 R2 Coef 0.5823 0.0596 0.0026 -0.0008 -0.1746 0.6394 0.1903 0.26704 0.831783 0.0545 0.0032 0.8319 0.0484 tvalue 4.54 5.51 3.75 -2.83 -5.33 4.39 3.61 5.44 4.24 5.45 p-value 0.000 0.000 0.000 0.005 0.000 0.000 0.000 0.000 0.000 0.000 Coef 0.4775 0.0608 0.0022 -0.0006 -0.1789 0.6407 0.1877 0.0022 0.8385 0.0548 0.0028 0.8429 0.0483 tvalue 2.9 3.65 3.95 -2.12 -3.54 3.4 4.84 4.19 4.58 4.24 p-value 0.004 0.000 0.000 0.034 0.000 0.001 0.000 0.000 0.000 0.000 Coef 0.7199 0.061 0.0051 -0.0025 -0.1691 0.6232 0.2211 0.0087 0.8027 0.0796 0.0053 0.8671 0.0603 tvalue 3.51 4.41 10.21 -4.64 -4.05 2.71 3.83 3.41 5.28 2.61 p-value 0.001 0.000 0.000 0.000 0.000 0.007 0.000 0.001 0.000 0.010 0.2823 0 .49202 0.49601 Price 1 1B: α1 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit 1C: β1CAit + β5AUDit 1D: β2FAit + β5AUDit POOLED DATA 2009-2013 PRE-ADOPTION 2009-2011 POST-ADOPTION 2012-2013 Cram Z Statistic Price 1 β 3 β5 R 2 β 4 β5 R 2 CA R 2 FA R 2 CL R 2 NCL R 2 Comm coef -0.0003 0.8481 0.0346 0.0057 0.844 0.0433 0.1358 0.1419 0.1557 0.0147 0.5804 tvalue 3.58 5.52 5.57 5.5 p-value 0.000 0.000 0.000 0.000 coef -0.0033 0.8543 0.0356 0.0356 0.0052 0.0464 0.1329 0.1394 0.1532 0.1413 0.5668 tvalue -5.87 4.26 6.94 4.24 p-value 0.000 0.000 0.000 0.000 coef -0.0035 0.8378 0.0345 0.0147 0.833 0.0474 0.1415 0.1603 0.1866 0.1737 0.6621 tvalue -1.57 3.51 5.06 3.51 p-value 0.117 0.001 0.000 0.000   0.48803 0.48803 1H: β3CLit + β5AUDit 1I: β3NCLit + β5AUDit Incremental POOLED DATA PRE-ADOPTION 2009-2011 POST_ADOPTION 2012-2013 Cramer-test(p-value) Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 7 CL and NCL are negatively significant, all the variables CA, FA, CL and NCL have a significant level of p<0.001% with the stock price for the pooled data. Table-4. Price Regression Model 1 Non-Financial Selected Assets and Liabilities Price 1 1F: α0 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit α1 β1 β2 β3 β4 β5 R 2 POOLED DATA 2009-2013 coef 1.2631 0.0569 0.0020 -0.0010 -0.1669 0.3206 0.2070 tvalue 4.98 7.08 3.54 -3.45 -6.85 1.2 p-value 0.000 0.000 0.000 0.001 0.000 0.230 PRE-ADOPTION 2009-2011 coef 0.0651 0.0015 0.0009 -0.1921 -0.3986 1.0620 0.2149 tvalue 6.23 3.52 3.84 -6.07 1.13 3.14 p-value 0.000 0.001 0.000 0.000 0.261 0.002 POST-ADOPTION-2012-2013 coef 0.0516 0.0040 0.0026 -0.1407 -0.1789 1.5302 0.2419 tvalue 4.33 8.01 5.85 -3.93 0.45 4.09 p-value 0.000 0.000 0.000 0.000 0.654 0.000 Cramer-test(p-value) 0.4880 ***Significant level 1% **significant level 5% * significant level 10% 1 price regression: SP= α0 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit+µit Variable definitions for Table 3: SP= Share price of firm three months after the year end t. CA=Current assets per share of firm i at the end of fiscal year t. FA=Fixed assets for firm i at the end of fiscal year t. CL=Current liabilities per share of firm i at the end of fiscal year t. NCL=Non-current assets for firm i at the end of fiscal year t. AUD = Auditors as dummy variable “1” for “Big 4” auditors and “0” otherwise. β= Coefficient of the explanatory variables. R2=Adjusted R2 within the panel regression. Cramer (1987) is for the statistical difference in adjusted R2 between Pre-and Post-adoption of IFRS from table lists p-values. All p-values are estimated based on the White (1980) corrected error for heteroscedasticity All variables before the adoption of IFRS present similar results expect AUD with p<0.01% significant level. After the adoption of IFRS FA and NCL do not provide any significant level of association. The results from the regression provide evidence of increased value relevance of accounting information from the lower adjusted R 2 in the before IFRS adoption (Adjusted R 2 before=23.80% and after=24.89%). The Cramer Z statistics shows no statistically significant difference between the two periods. This could be attributed to non-use of FA and NCL by banks for investments. Also, banking sectors invest mostly in financial assets than non-financial assets. Table-5. Price Regression Model 1 Financial Selected Assets and Liabilities Price 1 1A: SP=α1 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit α1 β1 β2 β3 β4 β5 R 2 POOLED DATA 2009-2013 coef 0.0605 0.0495 0.5006 -0.0939 -0.1573 0.4200 0.2253 tvalue 0.49 3.88 7.51 -6.09 -3.97 2.93 p-value 0.627 0.000 0.000 0.000 0.000 0.004 PRE-ADOPTION 2009-2011 coef -0.0477 0.4690 0.0838 -0.1519 -0.3918 -0.0354 0.2380 tvalue -3.92 6.43 6.91 -3.9 -2.22 -0.23 p-value 0.000 0.000 0.000 0.000 0.028 0.821 POST-ADOPTION-2012-2013 coef 0.1502 0.6365 0.5047 -0.4461 -0.3994 0.1820 0.2489 tvalue 1.78 5.18 1.6 -1.75 -1.64 0.88 p-value 0.078 0.000 0.114 0.083 0.105 0.378 Cramer-test(p-value) 0.45620 ***Significant level 1% **significant level 5% * significant level 10% 1 price regression: SP= α0 + β1CAit + β2FAit + β3CLit + β4NCLit + β5AUDit+µit Variable definitions for Table 4: SP= Share price of firm three months after the year end t. CA=Current assets per share of firm i at the end of fiscal year t. FA=Fixed assets for firm i at the end of fiscal year t. CL=Current liabilities per share of firm i at the end of fiscal year t. NCL=Non-current assets for firm i at the end of fiscal year t. AUD = Auditors as dummy variable “1” for “Big 4” auditors and “0” otherwise. β= Coefficient of the explanatory variables. R2=Adjusted R2 within the panel regression. Cramer (1987) is for the statistical difference in adjusted R2 between Pre-and Post-adoption of IFRS from table lists p-values. All p-values are estimated based on the White (1980) corrected error for heteroscedasticity. 6. Conclusions Before 2012 Nigerian firms have been reporting financial reporting based on SAS as domestic accounting reporting. Although, banks and multinationals companies were making two reports based on SAS and IFRS because of their link with international firms. The law of the country at the period all firms should prepare their financial report based on the SAS and Company and Allied Matters Act of 1990 (CAMA, 1990) However, from 2012 the Nigerian Financial Reporting Council (FRC) of Nigeria mandated all firms listed in the Nigerian stock market to prepare their financial report based on IFRS. The financial crisis of 2008, even though it was a global issue but Nigerian stock market was considerably heating. The failure of the market in the period has made some firms in the capital market to either close down or merge with others. As a result of the turmoil, the Central Bank Nigerian (CBN) issued a bailout to the banks in the period amounting to USD3.3 Billion in 2009. Therefore, this study addresses whether a change in accounting reporting in Nigeria has any effect on the value relevance of accounting information. The result of the study presents an increase in value relevance of accounting information after the adoption of IFRS. The results of non-financial firms provide an increase in value relevance after the adoption of IFRS. An increase in value relevance in financial firms is also noticed in the financial firms. Asian Journal of Social Sciences and Management Studies, 2017, 4(1): 1-9 8 The Cramer Z test for statistical significant provide no significance differences between the two periods all the models. Though the result provides evidence of IFRS improvement from the R 2 but provides no statistical difference of the R2 between the two periods. However, CL and financial asset present lower R 2 after the adoption of IFRS with no statistical differences between the two periods. This lower R 2 in the two models support critics concerns on the fair value of assets and liabilities (Liu et al., 2012). In contrast, the defenders of fair value found that confusing and unnecessary, that changing in value relevance could be as a result of change in the market conditions. References Aboody, D., J. Hughes and J. 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