Microsoft Word - FK TO MR HASSAN 6 1 Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 189 EXAMINING THE VALUE RELEVANCE OF ACCOUNTING INFORMATION: EVIDENCE FROM NAIROBI STOCK EXCHANGE (NSE) Mehreteab Yonas Kiflom1, *, Zhang Rui2, Lijuan Xiao3, Asif Jam Muhammad Farooq4, Lukman Jimoh Rahim5 1,2,3,4School of Accountancy, Jiangxi University of Finance and Economics, Nanchang, China 5 Department of Accounting, University of Jos, Nigeria * Correspondence: Email address of corresponding author yonas2015.yk@gmail.com +8613177894801 https://doi.org/10.57233/gujaf.v6i1.13 Abstract Prior studies indicate that with the transition of economy from industrial to a technology-driven service-oriented economy, the usefulness of accounting numbers, especially earnings, has reduced. This is shown by the obscurity of the link between market stock prices in accounting figures, especially earnings. Based on his perspective, this study examines the extent of stock price movement explained by the change in key accounting metrics using companies listed on the Nairobi Securities Exchange. The sample comprises 56 listed companies across 23 sectors from 2016 to 2023. Using a panel data fixed effects regression, we examine the impacts of key accounting metrics on market share prices. We find that both (lnEPS β = 0.137; p < 0.05) and (lnDPS β = 0.331; p < 0.01) have statistically significant positive relationships with share prices in the market (lnMSP). In contrast, lnOCF (β = 0.01, p < 0.1) and lnTA (β = 0.013, p < 0.1) have positive but insignificant impact effects. The R-squared of the model is 0.471, indicating that the four accounting variables explain 47.1 % of the movement in stock price. The findings align with the Dividend Signaling Theory and the Bird-in-Hand Theory. Additionally, the findings show the existence of a weak-form efficient market in the Nairobi Stock Exchange. Generally, the study confirms the persistence of accounting information’s value relevance in equity investments in Kenya. Keywords: Market share price; earnings per share; dividends per share; operating cash flows; total assets. JEL Codes: G14, G15, M41 1.0 Introduction Accounting information is generated from accounting process which includes recording, summarizing, processing, communicating, and interpreting organizations’ activities. A complete set of financial statements1 offer insights into a company’s financial performance, financial position, changes in capital, and cash flows. For the information to be useful, it must be of high quality, characterized by relevance, reliability, comparability, and consistency (Pelekh et al., 2020). For a financial reporting system to be effective, users are also required to possess the competence to understand the significance of the information provided and be capable of making rational decisions (Cohen et al., 2022). 1 According to IAS 1, a complete set of financial statements comprises the statements of financial position, profit or loss and other comprehensive income, changes in equity, cash flows, and notes to the financial statements. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 190 Stockholders are among the principal users of accounting information, and they differ in preference for one accounting information over another, depending on their investment strategy, risk tolerance, and time horizon (Lukkarinen, 2020). Value investors prioritize fundamentals like earnings and cash flows, while growth investors focus on revenue growth and future potential. Conservative investors seek stable earnings, whereas risk-tolerant individuals might favor volatility for higher returns (Lerman, 2011; Obaidat, 2016). This diversity attracts researchers, including the authors of this paper, to examine the equity investors’ behaviors toward accounting information, which is reflected in portfolio investments. The influence accounting information on market share price has gained considerable interest among researchers, following Ball and Brown (1968) findings that show accounting information influences share prices (as cited by Lugbenga and Atanda, 2014). Therefore, securities exchanges exhibit substantial responses to accounting information disclosures (Eachempati et al., 2021). Therefore, its usefulness can be measured based on its ability to make changes in stock prices (Imhanzenobe, 2022; Outa et al., 2017). Research by Dontoh et al. (2004) indicates that the usefulness of accounting information, especially earnings, has decreased, which is reflected in the increase of non-information-based (NIB) trading. However, other studies show that accounting information has maintained its relevance across periods despite the change in economic system when it was first developed (industrial economy) till present (high-tech driven service economy) (Barth et al., 2023; Perera and Thrikawala, 2010). In connection this debate, this study aims to provide empirical evidence to one side of the arguement, by concentrating on the earnings per share (EPS), dividends per share, operating cash flows, and total assets impacts on share prices from the perspective of emerging economies where there is a higher concern on the usefulness of accounting figures for investment decisions due to the believe of low transparency in these markets (Salman et al., 2024). This study utilizes companies quoted on the Nairobi Securities Exchange, the largest stock market in East Africa, with a market capitalization of $13.6 billion and 65 listed companies as of 31st May, 2024 (dabafinance.com, 2024). It was established in 1954 and it is a member of the World Federation of Exchanges, the African Securities Exchanges Association (ASEA) and the East African Securities Exchanges Association (EASEA), the Association of Futures Markets, and the United Nations’ Sustainable Stock Exchanges (SSE) initiative (nse.co.ke, n.d.). Moreover, the country was first in the region in adopting the International Financial Reporting Standards (IFRS), with the Capital Markets Authority of Kenya requiring it of all listed companies in 2001 (Atsunyo et al., 2017). All these stated characteristics of the market make it suitable for this research. To assist in the understanding of the market performance from 2017 to 2024, the exchanges’ all-share index is presented in Figure 1. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 191 Source: African Financials Figure 1. Nairobi Securities Exchange All Share Index (NSE-ASI). The NSE-ASI is a weighted index of free-float market capitalization that is used to evaluate the performance of the listed firms. Investors, market participants, and analysts use the NSE-ASI as a gauge of overall NSE performance and as the benchmark index of the Kenyan stock market. It is a real-time index and is calculated by the market capitalization of publicly traded businesses. The study has several potential contributions. First, this study can help companies formulate financial strategies that align with shareholder interests by revealing how key accounting information influences investor perceptions. Second, it equips investors with essential insights into the metrics that drive price movements, thereby enhancing their ability to assess market timing and risks, which is essential for portfolio management. Third, this research provides evidence which may help in addressing inconsistencies regarding the persistence or decline in usefulness of accounting numbers overtime. Additionally, the findings may pave the way for future research in the area. The remaining part of this research article is structured as follows: Section 2 contains review of relevant literature and research hypotheses. Section 3 shows research methodology, incorporating a description of data source and sample selection techniques, variables, and model specifications. Section 4 presents research findings and discussions. Section 5 shows conclusions drawn from the research findings. 2.0 Literature Review Dividend Signaling Theory This theory was introduced by Bhattacharya (1979) and states that dividends are informative about future earnings. Subsequently, Miller & Rock (1985) further developed the notion in "Dividend Policy Under Asymmetric Information", in which dividend changes signal management's profit expectations. Bird-in-Hand Theory This theory was first proposed by Gordon (1959) and later developed by Lintner (1962). It challenges the dividend irrelevance theory of Modigliani-Miller by arguing that an investor Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 192 would prefer to receive a certain dividend to an uncertain capital gain, aligning with the proverb that says a bird in hand is worth more than two in the bush. Efficient Market Hypothesis (EMH) The EMH was introduced by Fama (1970). It states that financial markets efficiently incorporate new information, meaning it’s hard to earn above average market returns. It comes in three forms: weak (prices only include past information), semi-strong (prices reflect all public information), and strong (prices incorporate private information as well). EMH implies that passive investing is preferred because active strategies can’t consistently do better. But market bubbles and behavioral biases serve as a counter to perfect efficiency, critics argue. Although EMH is not perfect, it is an essential concept in finance, affecting both investment strategies and market theories. Empirical Studies The key findings and their implication of the reviewed empirical studies on the significance of accounting numbers are presented in Table 1. Table 1. Summary of empirical studies Study by Key Findings Value Relevance Dontoh et al. (2004) Increase in non-information- based trading reduces the usefulness of accounting figures in the US. Declined relevance Barth et al. (2023) Despite the economic transition from the industrial to a high-technology driven service-oriented economy, there was no evidence of a decline in the usefulness of accounting information from 1962 to 2014 in the US. Maintained relevance Busari and Bagudo (2021) Both separate and consolidated financial statements are relevant for investment decisions, with the consolidated being more relevant in Nigeria. Relevant Bhatia and Mulenga (2019) Reviewed 90 empirical studies conducted across different countries during 1993-2016 and found that the majority of the studies conclude that accounting reports were relevant both before and after IFRS adoption. Maintained Relevance Imhanzenobe (2022) Reviewed prior studies and found that most of the studies indicate a decline in value relevance of accounting metrics in the US, and suggested that adoption of IFRS enhances the relevance. Declined relevance Badu and Appiah (2018) Earnings and book value metrics have a significant influence on stock price movements in Ghana Strong Relevance Amahalu et al. (2018) EPS and DPS have significant positive impacts on MSP in Nigeria. Strong Relevance Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 193 Tahat and Alhadab (2017) Assessed the influence of book value, EPS, and cash flows on MPS and found that there is no evidence of decline in value relevance of accounting numbers over time in the UK. Maintained relevance Onyango Odhiambo (2013) Dividend and earnings announcements have an insignificant effect on share prices in Kenya. Weak relevance Ali and Chowdhury (2010) Dividend declarations have an insignificant influence on share prices in Bangladesh Weak relevance Arsal (2021) Limited impacts of EPS and DPS on the firm value in Indonesia Weak relevance Source: Authors’ construction Empirical Gaps The existing literature could be viewed as inconclusive. Some scholars argue that accounting metrics have lost their usefulness for investment decisions (Dontoh et al., 2004), while others argue that they have maintained their relevance since their development (Barth et al., 2023). Additionally, while earnings and dividends are among the most common metrics researched, cash flows and total assets have received relatively less attention. Furthermore, while efficient market hypothesis (EMH) is well-studied in developed economies, African markets are often believed to lack efficiency due to lower transparency, which requires empirical validation. Hypotheses Development Previous studies show mixed results about the influence of EPS on share price. As EPS is the fundamental measure of a company's profitability and the primary determinant of the company's intrinsic value, it is believed to influence stock price. Thus, we hypothesize; H1: EPS has a significantly positive impact on market share price in Kenya. Research on the influence of dividend payouts and share prices also shows divergent views. As dividends frequently indicate financial health and potential for future earnings, we hypothesize that; H2: DPS has a significant positive impact on share prices in Kenya. Existing literature shows that cash flows are significantly associated with MSP. Therefore, we hypothesize; H3: Operating cash flows have a strong positive influence on market share price in Kenya. Total assets indicate the resources and business scale of a company, which have a significant relationship with market valuation. Therefore, we hypothesize; H4: Total assets have a significant relationship with market share price in Kenya. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 194 3.0 Methodology Data Source and Sample Selection This study utilizes the audited consolidated financial statements of the companies quoted on the Nairobi Securities Exchange obtained from AfricanFinancials. Data for 56 companies in 23 sectors were available as of August 2024. All the selected companies prepare financial statements in Kenyan shillings (KES)2 and in accordance with IFRS. Two firms were excluded due to insufficient reports, and two others were excluded because their reports are prepared in foreign currencies. Consequently, the sample consists 392 observations covering the period from 2016 to 2023. This study year begins in 2016 because share price data before 2017 were unavailable. Nevertheless, the number of observations is sufficient for robust analyses. Variables Market share price (MSP) is the dependent variable, and it data is sourced from AfricanFinancials, with the closing price of shares on the annual reporting date of each company. The independent variables are: earnings per share, dividends per share, operating cash flows, and total assets. All financial information, in KES, was manually collected from the audited annual financial reports. The statistical software used for data processing is Stata 17. Table 2. Descriptions of Variables Variable Abbreviation Explanation Market Share Price MSP Market value per ordinary share. Earnings Per Share EPS Basic earnings per share. Dividend Per Share DPS Annual dividend per ordinary share. Operating Cash Flow OCF Cash flows related to operating activities. Total Assets TAS Total assets of a company Source: Authors’ Design Model Specification Panel data is a type of data for several entities that are observed across different periods (Rizka Zulfikar, 2018). These entities can include countries, firms, and so on (Oscar Torres- Reyna, 2007). And the periods can be days, weeks, months, quarters, semi-annually, annually, and so on. Pooled OLS Regression Pooled OLS regression is a simple panel technique that pools together cross-sectional and time- series observations without adjusting for individual- or time-specific effects. The model is expressed as: 2 The Kenyan Shilling (KES), symbolized as KSh, is issued by the Central Bank of Kenya. It was introduced in 1966, replacing the East African shilling. As of May 6, 2025, the exchange is approximately 1KES=129 USD, reflecting its value in international markets. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 195 Ƴ , = 𝛽 + 𝛽 𝛸 , + 𝜖 , (1) Where: Ƴ , : Dependent variable 𝛽 : intercept 𝛽 : coefficient of the regressor. 𝛸 , : regressor 𝜖 , : residual Random Effects (RE) The RE model takes into account the panel structure by including entity-specific effects. It assumes the unobserved entity effects are not correlated with the regressors and are randomly distributed (Khalid Ahmed, 2024). Thus, it is included with the regressors as shown in equation 2. Ƴ , = 𝛽 + 𝛽 𝛸 , +ꭒ + 𝜖 , (2) Where: ꭒ denotes the individual entity-specific component that is uncorrelated with X (1) Fixed Effects (FE) The fixed effects model assumes that unobservable entity-specific effects are correlated with independent variables and is constant over time, but vary across entities (Nwakuya & Ijomah, 2017). The model is expressed as: Ƴ , = 𝛽 + 𝛽 𝛸 , +𝛽 𝑍 + 𝜖 , (3) Where: 𝑍 denotes the individual entity-specific component that is correlated with X Model Selection Approaches Torres-Reyna (2007) presents a clear direction in selecting a model in panel data analysis. When there is an indication that entity-specific features affect the independent variables, the fixed effects model is preferred because it effectively controls for this unobservable heterogeneity. When this relation is unclear, diagnostic tests should be conducted to choose the suitable approach. The Breusch-Pagan Lagrange Multiplier test helps to choose between pooled OLS and RE models, and Hausman test to choose between RE and FE. 4.0 Results and Discussions The summary statistics for the sample, which comprises 52 listed companies, are detailed in Table 3. The monetary value of the variables is in Kenyan shillings. Table 3. Descriptive Statistics Variable Obs. Mean Std. Dev. Min. Max. MSP 393 47.628 64.438 2.07 200.5 EPS 413 4.873 7.950 -2.05 23.49 DPS 412 3.287 7.429 0.00 52.00 lnOCF 412 24.31 0.357 23.479 26.339 lnTAS 413 23.677 2.439 15.753 30.73 Source: Authors’ Computation Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 196 All the variables are winsorized at the 1st and 99th percentiles to reduce bias from outliers. Additionally, OCF and TAS are also transformed to their natural logarithmic value as their values are too large for the analysis. Regression Analysis Before running regression, we perform several diagnostic tests to ensure the satisfaction of conditions necessary for the estimation. Diagnostic Tests Multicollinearity Test To test multicollinearity problem in variables, which is a crucial assumption in regression estimation, we conduct the variance inflation factor (VIF) test. Table 4. VIF Test Result Variable VIF 1/VIF lnEPS 2.36 .423700 lnDPS 2.09 .477486 lnTAS 1.30 .770470 lnOCF 1.07 .932396 Mean VIF 1.71 Source: Authors’ Computation The test result shows that each independent variables have values below 5, a level that is not a concern for multicollinearity and is often considered acceptable. Therefore, we decided to retain all these variables for regression analysis. Selecting the Appropriate Model We employed a two-stage model selection approach for this study. First, we conducted the Breusch-Pagan LM test. According to the result (p<0.05), we reject the null hypothesis of no panel effects, supporting the application of panel data methods over pooled OLS. Second, we conducted the Hausman test, and the result (p<0.05) showed us that the FE model implementation is more suitable than the RE model implementation. Therefore, based on these diagnostic tests we choose FE for the regression analysis. Table 5. Breusch and Pagan LM, and Hausman Tests Results Test Chi-Sq. Statistic p-value Breusch-Pagan LM 678.00 0.0000 Hausman 86.5 0.0000 Source: Authors’ Computation Test for Heteroscedasticity To determine whether the standard errors of the variables are heteroscedastic or homoscedastic, we conducted the modified Wald test. The null hypothesis for this test posits that the variances are constant (or homoscedastic). Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 197 Table 6. Wald Test for Heteroskedasticity Test Chi-square statistic P-value Modified Wald test 1.1e+05 0.0000 Source: Authors’ Computation As the p-value is less than the critical value (0.05), we reject the null hypothesis and conclude that the standard errors are heteroscedastic. To address this issue, we opted to employ robust standard errors when running regression. Serial Correlations and Cross-sectional Dependency Tests This paper uses the Wooldridge and Friedman test to check for serial correlation and cross- section dependence, respectively. The Wooldridge test tests for first-order autocorrelation in the residuals (null hypothesis: no autocorrelation). A significant result (p<0.05) suggests that the estimators are biased and need to be adjusted, such as in clustered standard errors or FGLS. The Friedman test tests for the cross-sectional dependence (null hypothesis: independent residuals). Rejection (p<0.05) indicates potential bias and the need to use methods such as PCSE or spatial models. The two tests validate the regression estimators. Table 7. Wooldridge Test and Friedman Test Results Test F-statistic p-value Wooldridge test 1.326 0.252 Friedman test 31.904 0.9834 Source: Authors’ Computation As shown in Table 7, the p-values > 0.05 of both tests show that the regression model does not have serial correlation and cross-sectional dependence issues. Unit Root Test As the non-stationary data can induce spurious regression, we conduct the Fisher-type panel unit root test which aggregates p-values from ADF tests across cross-sections. The test’s null hypothesis is that all the different panels have unit roots. As shown in Table 8, the p-values for all variables is less than, we reject the null hypotheses for all the variables and conclude that all the variables are stationary at level. Table 8. Fisher-Type Unit Root Test Result Variable Inverse chi-squared (P) p-value Modified inv. chi-squared (Pm) p-value lnMPS 333.9185 0.0000 15.9420 0.0000 lnEPS 189.8902 0.0000 5.9554 0.0000 Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 198 lnDPS 146.2693 0.0040 2.9309 0.0017 lnOCF 210.3306 0.0000 7.3727 0.0000 lnTAS 199.7169 0.0000 6.6368 0.0000 Source: Authors’ Computation Test for Need of Time Fixed Effects To decide whether time effects were necessary in our fixed effects model, we performed a joint significance test of year coefficients using the Stata command “testparm”. Based on the result, we rejected the null hypothesis of no fixed time effects (p < 0.05), indicating that it is appropriate to control for time effects in our specification. This result indicates that macroeconomic factors or time effects also substantially affect our dependent variable and should be explicitly included in our regression model. Table 9. Test for the Need of Time Fixed Effects When Running FE Test F-Statistic (6, 51) Prob > chi2 testparm 10.02 0.0000 Source: Authors’ Computation Fixed Effects Regression Analysis Based on the diagnostic tests conducted in the previous section, we conduct FE regression to test our hypotheses. The regression results are presented in Table 10. The standard errors are clustered by firm ID, with 52 clusters, to account for potential heteroscedasticity and within- cluster correlation, and the statistical significance of the coefficients is denoted by ***, **, and * for 1%, 5%, and 10% level, respectively. Table 10. Fixed Effects Regression Result Regressor Coeff. Std.Err. t-stat p-value [95% Conff. Interval] Sign lnEPS .137 .054 2.55 .014 .029 .245 ** lnDPS .331 .076 4.36 .000 .179 .484 *** lnOCF .010 .018 0.53 .600 -.027 .047 lnTAS .013 .06 0.21 .833 -.108 .133 2016b 0 . . . . . 2017 .115 .067 1.73 .089 -.018 .249 * 2018 -.138 .064 -2.16 .035 -.265 -.01 ** 2019 -.307 .075 -4.07 .000 -.459 -.156 *** 2020 -.347 .079 -4.38 .000 -.506 -.188 *** 2021 -.429 .089 -4.83 .000 -.607 -.251 *** 2022 -.547 .091 -6.00 .000 -.729 -.364 *** 2023 -.519 .094 -5.55 .000 -.707 -.332 *** Constant 2.151 1.532 1.40 .166 -.924 5.226 Mean dependent var. 2.882 SD dependent var. 1.491 R-squared 0.471 Number of obs. 392 F-test 9.086 Prob > F 0.000 Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 199 Akaike crit. (AIC) 149.046 Bayesian crit. (BIC) 192.730 *** p<.01, ** p<.05, * p<.1 Source: Authors’ Computation. The FE regression result shows that earnings per share (EPS) have a positive impact on market share price (MSP). A 1% increase in EPS causes a 0.137% increase in MSP. This coefficient is statistically significant at the 5% level. Similarly, dividend per share (DPS) positively affects MSP: a 1% increase in DPS causes a 0.331% increase in MSP. The coefficient is statistically significant at 1%, indicating a strong impact on MSP, a level higher than that of EPS. The confidence intervals for EPS (0.029 to 0.245) and DPS (0.179 to 0.484) do not contain zero, further confirming the statistical significance of both coefficients. Conversely, operating cash flows (OCF) exhibit a weak positive relationship with MSP. A 1% increase in OCF leads to only a 0.01% increase in MSP. This coefficient is statistically insignificant. This finding aligns with Mostafa (2016) a finding in the study of the value relevance of accounting information in the Egyptian stock market, which finds that cash flow information is not among the stock price drivers. Similarly, total assets (TAS) have a weak positive impact on MSP. A 1% increase in TAS causes a 0.013% increase in MSP, which is statistically insignificant. The confidence intervals for OCF (-0.027 to 0.047) and TAS (-0.108 to 0.133) include zero, reinforcing the statistical insignificance. The year variables, with 2016 as the base year, show a statistically insignificant increase in market share prices for 2017, followed by a consistent and significant decline starting from 2018 onward, worsening in 2019. This trend aligns with the destructive economic effects of the COVID-19 pandemic (Baker et al., 2020). While our findings document this decline, identifying its precise causal mechanisms falls beyond the scope of this study. The 0.471 R-squared value shows that the four-accounting metrics used together explain 47.1% of the change in MSP. The model’s F-test (prob > F= 0.000) confirms that the independent variables jointly have a significant influence on the dependent variable. Based on these results, we accept the hypotheses H1 and H2, whereas we reject H3 and H4. 5.0 Conclusion This study provides evidence that accounting information, particularly EPS and DPS, has not declined in its usefulness for investment decisions in Kenya. The findings are consistent with the dividend signaling theory and, bird-in-hand theory. Moreover, they also indicate that the existence of a weak-form market efficiency in the Kenyan Stock Exchange. Finally, based on the findings, we propose that further research into sectoral analysis and ESG disclosure should be carried out, and given the significant decrease in the market share prices after 2019 found in this study, future research is essential to investigate the reasons for this phenomenon. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 200 References Ali, M. B., & Chowdhury, T. A. (2010). Effect of dividend on stock price in emerging stock market: A study on the listed private commercial banks in DSE. International Journal of Economics and Finance, 2(4), 52–64. Amahalu, N., Abiahu, M.-F. C., Chinyere, O., & Nweze, C. (2018). Effect of accounting information on market share price of selected firms listed on the Nigerian stock exchange. International Journal of Recent Advances in Multidisciplinary Research, 5(01), 3366– 3374. Arsal, M. (2021). Impact of earnings per share and dividend per share on firm value. ATESTASI: Journal Ilmiah Akuntansi, 4(1), 11–18. Atsunyo, W., Gatsi, J. G., & Frimpong-Manso, E. (2017). The success of IFRS in Africa: Comparative evidence between Ghana and Kenya. Badu, B., & Appiah, K. O. (2018). Value relevance of accounting information: an emerging country perspective. Journal of Accounting & Organizational Change, 14(4), 473–491. Baker, S. R., Bloom, N., Davis, S. J., Kost, K. J., Sammon, M. C., & Viratyosin, T. (2020). The unprecedented stock market impact of COVID-19. national Bureau of economic research. Ball, R., & Brown, P. (1968). An empirical examination of accounting income numbers. Journal of Accounting Research, 6, 1599177. Barth, M. E., Li, K., & McClure, C. G. (2023). Evolution in value relevance of accounting information. The Accounting Review, 98(1), 1–28. Bhatia, M., & Mulenga, M. J. (2019). Value relevance of accounting information: A review of empirical evidence across continents. Jindal Journal of Business Research, 8(2), 179– 193. Bhattacharya, S. (1979). Imperfect information, dividend policy, and" the bird in the hand" fallacy. The Bell Journal of Economics, 259–270. Brown, S., Lo, K., & Lys, T. (1999). Use of R2 in accounting research: measuring changes in value relevance over the last four decades. Journal of Accounting and Economics, 28(2), 83–115. Busari, K., & Bagudo, M. M. (2021). Comparing the Value Relevance of Selected Accounting Information in Consolidated and Separate Financial Statements: The Case of Nigerian Listed Financial Service Firms. Journal of Economics and Sustainability, 3(Number 2), 16–32. Cohen, S., Manes Rossi, F., Mamakou, X., & Brusca, I. (2022). Financial accounting information presented with infographics: Does it improve financial reporting understandability? Journal of Public Budgeting, Accounting & Financial Management, 34(6), 263–295. dabafinance.com. (2024, June 3). The Largest Stock Exchanges in Africa by Market Capitalization. Daba. https://dabafinance.com/en/learn/blogs/the-largest-stock- exchanges-in-africa-by-market-capitalization Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 201 Dontoh, A., Radhakrishnan, S., & Ronen, J. (2004). The declining value‐relevance of accounting information and non‐information‐based trading: an empirical analysis. Contemporary Accounting Research, 21(4), 795–812. Eachempati, P., Ranjan Srivastava, P., Kumar, A., Hua Tan, K., & Gupta, S. (2021). Validating the impact of Accounting Disclosures on Stock Market: A Deep Neural Network approach. Eugene F. Fama. (1970). Efficient Capital Market: a Review of Theory and Empirical Work. The Journal of Finance, 25, 383–417. Gordon, M. J. (1959). Dividends, earnings, and stock prices. The Review of Economics and Statistics, 99–105. Imhanzenobe, J. (2022). Value relevance and changes in accounting standards: A review of the IFRS adoption literature. Cogent Business & Management, 9(1), 2039057. Khalid Ahmed. (2024, January 6). Random Effects Model - What Is It, Examples, Vs Fixed Effects. WallStreetMojo. https://www.wallstreetmojo.com/random-effects-model/#h- random-effects-model-vs-fixed-effects-model Lerman, A. (2011). Individual investors’ attention to accounting information: Message board discussions. New York University, Graduate School of Business Administration. Lintner, J. (1962). Dividends, earnings, leverage, stock prices and the supply of capital to corporations. The Review of Economics and Statistics, 243–269. Lukkarinen, A. (2020). Equity crowdfunding: Principles and investor behaviour. Advances in Crowdfunding: Research and Practice, 93–118. Miller, M. H., & Rock, K. (1985). Dividend policy under asymmetric information. The Journal of Finance, 40(4), 1031–1051. Mostafa, W. (2016). The value relevance of earnings, cash flows, and book values in Egypt. Management Research Review, 39(12), 1752–1778. NSE.com. (n.d.). About NSE - Nairobi Securities Exchange PLC. Retrieved September 28, 2024, from https://www.nse.co.ke/about-nse/ Nwakuya, M. T., & Ijomah, M. A. (2017). Fixed Effect Versus Random Effects Modeling in a Panel Data Analysis: A Consideration of Economic and Political Indicators in Six African Countries. International Journal of Statistics and Applications, 7(6), 275–279. Obaidat, A. N. (2016). Accounting information: Which information attracts investors' attention first. Accounting and Finance Research, 5(3), 107–117. Olugbenga, A. A., & Atanda, O. A. (2014). The Relationship between Financial Accounting Information and Market Value of Firms. In Global Journal of Contemporary Research in Accounting, Auditing and Business Ethics (GJCRA) An Online International Monthly Journal (Vol. 1). www.globalbizresearch.org Onyango Odhiambo, F. (2013). The Influence of Dividends and Earnings Announcements on Shareholders’ Value of Companies Listed at The Nairobi Securities Exchange. Gusau Journal of Accounting and Finance, Vol.6, Issue 1, April, 2025 202 Oscar Torres- Reyna. (2007, December). Panel Data Analysis Fixed and Random Effects using Stata. Outa, E. R., Ozili, P., & Eisenberg, P. (2017). IFRS convergence and revisions: value relevance of accounting information from East Africa. Journal of Accounting in Emerging Economies, 7(3), 352–368. Pelekh, U., Khocha, N., & Holovchak, H. (2020). Financial statements as a management tool. Management Science Letters, 10(1), 197–208. Perera, R., & Thrikawala, S. S. (2010). An Empirical Study of The Relevance of Accounting Information to Investors’ Decisions. Rizka Zulfikar. (2018). Estimation Model and Selection Method of Panel Data Regression: An Overview of Common Effect, Fixed Effect, and Random Effect Model. Salman, R., Abogun, S., Lambo, I. A., Yunus, A. B., & Sanni, P. A. (2024). Impact of financial statements information on market share price of listed insurance firms in Nigeria. FUDMA Journal of Accounting and Finance Research [FUJAFR], 2(4), 111–121. Tahat, Y. A., & Alhadab, M. (2017). Have accounting numbers lost their value relevance during the recent financial credit crisis? Quarterly Review of Economics and Finance, 66, 182– 191. Torres-Reyna, O. (2007). Panel Data Analysis Fixed and Random Effects using Stata. http://www.princeton.edu/~otorres/