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The study aims to investigate the impact of IFRS adoption on the value-relevance of financial statements in Nigeria. In line with existing literature, this study adopts a longitudinal research design using historical company and stock market data to test the null hypotheses. A diagrammatic representation of the hypotheses being tested can also be found in Figure 1 above. The specific null hypotheses to be tested in this study are as follows:

Figure 1 The study aims to investigate the impact of IFRS adoption on the value-relevance of financial statements in Nigeria. In line with existing literature, this study adopts a longitudinal research design using historical company and stock market data to test the null hypotheses. A diagrammatic representation of the hypotheses being tested can also be found in Figure 1 above. The specific null hypotheses to be tested in this study are as follows:

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demands more difficult and unrealistic (Nakpodia et al., 2018). Some of the variations between the Nigerian GAAP and the IFRS standards can be found in Table 1 below.
demands more difficult and unrealistic (Nakpodia et al., 2018). Some of the variations between the Nigerian GAAP and the IFRS standards can be found in Table 1 below.
The compliance level of Nigerian companies to the NASB standards was below the international average of 91% before IFRS adoption (Kasum, 2011). Also, Nigeria is one of the late adopters of IFRS. During the years while Nigeria was enforcing its GAAP standards, many developing and developed countries were adopting IFRS. This meant that the financial statements of Nigerian companies were becoming less comparable to those of other countries. Accounting and Management Information Systems
The compliance level of Nigerian companies to the NASB standards was below the international average of 91% before IFRS adoption (Kasum, 2011). Also, Nigeria is one of the late adopters of IFRS. During the years while Nigeria was enforcing its GAAP standards, many developing and developed countries were adopting IFRS. This meant that the financial statements of Nigerian companies were becoming less comparable to those of other countries. Accounting and Management Information Systems
A sample of listed companies was selected based on listing status. Only companies that were consistently listed throughout the sample period were selected so that each company acts as its own control, thus preventing sample variation bias (Outa et al., 2017). The number of listed companies in Nigeria was relatively stable at 173 (fluctuated only slightly during the sample period with a peak of 213 in 2010). However, only 85 of these companies were found to be consistently listed through the period from 2007 to 2016. This is because several companies either delisted or shut down during the sample period. These companies were excluded from the sample to prevent sample variation bias. Using the sampling criteria, only the 85 consistently listed companies were selected. Also, due to missing data points, the number of observations for each year was less than 85. This led to an unbalanced panel dataset of 618 (less than 850) observations across the pre and post-IFRS period (Table 2). The companies’ data were obtained from the Bloomberg market data terminal and Datastream financial database.
A sample of listed companies was selected based on listing status. Only companies that were consistently listed throughout the sample period were selected so that each company acts as its own control, thus preventing sample variation bias (Outa et al., 2017). The number of listed companies in Nigeria was relatively stable at 173 (fluctuated only slightly during the sample period with a peak of 213 in 2010). However, only 85 of these companies were found to be consistently listed through the period from 2007 to 2016. This is because several companies either delisted or shut down during the sample period. These companies were excluded from the sample to prevent sample variation bias. Using the sampling criteria, only the 85 consistently listed companies were selected. Also, due to missing data points, the number of observations for each year was less than 85. This led to an unbalanced panel dataset of 618 (less than 850) observations across the pre and post-IFRS period (Table 2). The companies’ data were obtained from the Bloomberg market data terminal and Datastream financial database.
Table 3. Variables measurement and representation
Table 3. Variables measurement and representation
‘ollowing the methodology of some recent existing literature (Elhamma, 2023; Lompotis & Balios, 2023), a preliminary test was done to detect if there has been an ncrease in overall value relevance as a result of IFRS adoption. Afterward, H1, H2, < H3 were tested by investigating the significance of such increase using the nteractions of IFRS with the different accounting figures. For the preliminary test, i basic OLS estimation was done using the Ohlson model to test for changes in the yverall value relevance of the accounting figures. Tests for omitted variable biases vere also carried out to determine which of pooled, fixed, and random effect model vas more appropriate. Finally, standard error biases were anticipated (depending on he results of the post-diagnostic tests) using the panel-corrected standard error or Jriscoll-Kraay standard error to ensure that the model results were unbiased. This The descriptive statistics of all variables were extracted to show the sample distribution characteristics (Table 4). To test the different hypotheses of the study, the data collected were analyzed using Stata. All the figures were calculated in the local currencies. The stock price figures were collected for 3 months after the fiscal year end of each sample company. The average earnings per share figure was N1.720. The positive average EPS figures indicate that the sample companies are relatively profitable. The average book value per share figure was N8.90. This indicates the net asset belonging to shareholders per unit of shares owned which the company uses to generate the earnings per share. The average figure for the book value per share, when compared to the average earnings per share, indicates an average return on investment (i.e. EPS/BVPS) of about 19.33%. The average cash flow per share figure was N3.91. Upon comparison with the EPS figures, the cash flow figures were found to be greater. This suggests that the sample companies had significant amounts of accrued and non-operating expenses.
‘ollowing the methodology of some recent existing literature (Elhamma, 2023; Lompotis & Balios, 2023), a preliminary test was done to detect if there has been an ncrease in overall value relevance as a result of IFRS adoption. Afterward, H1, H2, < H3 were tested by investigating the significance of such increase using the nteractions of IFRS with the different accounting figures. For the preliminary test, i basic OLS estimation was done using the Ohlson model to test for changes in the yverall value relevance of the accounting figures. Tests for omitted variable biases vere also carried out to determine which of pooled, fixed, and random effect model vas more appropriate. Finally, standard error biases were anticipated (depending on he results of the post-diagnostic tests) using the panel-corrected standard error or Jriscoll-Kraay standard error to ensure that the model results were unbiased. This The descriptive statistics of all variables were extracted to show the sample distribution characteristics (Table 4). To test the different hypotheses of the study, the data collected were analyzed using Stata. All the figures were calculated in the local currencies. The stock price figures were collected for 3 months after the fiscal year end of each sample company. The average earnings per share figure was N1.720. The positive average EPS figures indicate that the sample companies are relatively profitable. The average book value per share figure was N8.90. This indicates the net asset belonging to shareholders per unit of shares owned which the company uses to generate the earnings per share. The average figure for the book value per share, when compared to the average earnings per share, indicates an average return on investment (i.e. EPS/BVPS) of about 19.33%. The average cash flow per share figure was N3.91. Upon comparison with the EPS figures, the cash flow figures were found to be greater. This suggests that the sample companies had significant amounts of accrued and non-operating expenses.
Table 5. REM model for pre-IFRS adoption using DKSE
Table 5. REM model for pre-IFRS adoption using DKSE
IFRS Adoption and the Value-Relevance of Financial Statements Figures in Nigeria The results of the post-diagnostic tests can be seen in Table 5 above. The Wooldridge est for panel autocorrelation was conducted on the pre-IFRS random-effect model. The test showed a statistic of 11.330 with p-value of 0.0014, thus indicating a presence of autocorrelation. The Wald test was also done to detect any presence of panel heteroskedasticity. The statistic showed some presence of heteroskedasticity p<0.05). Finally, the Pesaran test for cross-sectional dependence was also carried out to detect any presence of panel cross-sectional dependence. The test showed presence of cross-sectional dependence (Pesaran CD test stat = 12.25 with p<0.05).
IFRS Adoption and the Value-Relevance of Financial Statements Figures in Nigeria The results of the post-diagnostic tests can be seen in Table 5 above. The Wooldridge est for panel autocorrelation was conducted on the pre-IFRS random-effect model. The test showed a statistic of 11.330 with p-value of 0.0014, thus indicating a presence of autocorrelation. The Wald test was also done to detect any presence of panel heteroskedasticity. The statistic showed some presence of heteroskedasticity p<0.05). Finally, the Pesaran test for cross-sectional dependence was also carried out to detect any presence of panel cross-sectional dependence. The test showed presence of cross-sectional dependence (Pesaran CD test stat = 12.25 with p<0.05).
Table 6. FEM model for post-IFRS adoption using PCSE The DKSE and PCSE models show an increase in the adjusted R? (within R’) figures across the pre- and post-IFRS adoption models (Tables 5 & 6). The modified post- IFRS adoption model had adjusted R’s of about 61.0% while the pre-IFRS adoptior model had adjusted R’s of about 43.1%, thus suggesting an increase in value relevance by about 41.5%.
Table 6. FEM model for post-IFRS adoption using PCSE The DKSE and PCSE models show an increase in the adjusted R? (within R’) figures across the pre- and post-IFRS adoption models (Tables 5 & 6). The modified post- IFRS adoption model had adjusted R’s of about 61.0% while the pre-IFRS adoptior model had adjusted R’s of about 43.1%, thus suggesting an increase in value relevance by about 41.5%.
Table 7. FEM model for the IFRS and EPS interaction using DKSE Fixed effect Model (with Driscoll-Kraay standard errors) The result in Table 7 shows that the IFRS dummy and EPS in isolation were both negative and insignificant (t = -0.92 & -1.79; p>0.05 for both). However, the interaction of IFRS with EPS was positive and significant (t = 5.71 & p<0.05). This shows evidence of a significant impact of IFRS adoption on the value relevance of earnings figures in Nigeria. This is consistent with the result of the pre- and post-
Table 7. FEM model for the IFRS and EPS interaction using DKSE Fixed effect Model (with Driscoll-Kraay standard errors) The result in Table 7 shows that the IFRS dummy and EPS in isolation were both negative and insignificant (t = -0.92 & -1.79; p>0.05 for both). However, the interaction of IFRS with EPS was positive and significant (t = 5.71 & p<0.05). This shows evidence of a significant impact of IFRS adoption on the value relevance of earnings figures in Nigeria. This is consistent with the result of the pre- and post-
Table 8. REM model for the IFRS and BVPS interaction using DKSE Random effect Model (with Driscoll-Kraay standard errors)
Table 8. REM model for the IFRS and BVPS interaction using DKSE Random effect Model (with Driscoll-Kraay standard errors)
lable 8. FEM model for the IFRS and cash flows interaction using DKSE Fixed effect Model (with Driscoll-Kraay standard errors)
lable 8. FEM model for the IFRS and cash flows interaction using DKSE Fixed effect Model (with Driscoll-Kraay standard errors)
Related topics:
Value RelevanceIfrs Adoption
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