A Panel Data Analysis of the Interactions Between Lagged Profitability and Firms’ Financial Performance: Evidence from the Ghana Stock Exchange (GSE)

How to cite this paper: Mohammed Musah | Yusheng Kong | Stephen Kwadwo Antwi "A Panel Data Analysis of the Interactions between Lagged Profitability and Firms’ Financial Performance: Evidence from the Ghana Stock Exchange (GSE)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 24566470, Volume-3 | Issue-4, June 2019, pp.633-638, URL: https://www.ijtsrd.c om/papers/ijtsrd23 848.pdf


INTRODUCTION
Corporations perform unique functions for the growth and development of all economies. Such establishments cannot operate at their maximum without sound financial viabilities (Mwangi &Murigu, 2015). According to King'ori, Kioko and Shikumo (2017), financial performance is a measure of organisations' achievement of goals, policies and operations, stipulated in monetary terms. It symbolizes firms' financial healthand can be compared with similar firms in one same industry (Agola, 2014). Mwangi and Murigu(2015) also explained financial performance as a measure of organisations' earnings, profits and appreciations, as evidenced by a rise in the entities' share price. Financial performance in terms of profitability, is viewed as an essential pre-requisite for the survival, growth and competitiveness of all firms. It is also viewed as the cheapest source of business finance (King'ori, Kioko&Shikumo, 2017; Agola, 2014;and Mwangi &Murigu, 2015).
Without comprehensive financial performance, firms cannot draw outside capital to meet their set objectives in this everchanging and competitive business environment (Chen & Wong, 2004; and Asimakopoulos, Samitas, &Papadogonas, 2009). Buoyant financial performance does not only advance firms' state of soundness, but also plays a vibrant role in enticing policyholders and shareholders to provide liquidity to firms (Mwangi &Murigu, 2015;Charumathi, 2012;Agola, 2014; King'ori, Kioko&Shikumo, 2017;and Chen, & Wong, 2004).The financial performance of firms is explained by a lot of factors amid them is lagged profitability. As such, many studies have been conducted to explore the association between lagged profitability and firms' financial performance. For instance, Coban (2014) studied the interactions between growth and the profitability of manufacturing firms in Turkey. Panel data from 137 listed firms for the period 1997 to 2012 was used for the study. From the study's system-GMM (Blundell &Bond, 1998) technique of data analysis, lagged profitability had a significantly positive relationship with the firms' current year's profitability. Maja used for the study. Among the study's findings, lagged profitability had a significantly positive connection with the firms' performance. Farah and Nina (2016)  The aforementioned studies among others, are flawed in scope in that, they failed to explore the strength and direction of the linear relationship that existed between lagged profitability and the financial performance of nonfinancial firms listed on the Ghana Stock Exchange (GSE). This study was therefore conducted to help fill that gap. Specifically, the study sought to examine the relationship between lagged profitability and the firms' financial performance as measured by ROA; determine the association between lagged profitability and the firms' financial performance as measured by ROE; and to identify the affiliation between lagged profitability and the firms' financial performance as measured by ROCE.
This study adds to the existing pool of literature on lagged profitability and its association with firms' financial performance. This will serve as a reference source for students and researchers who may want to conduct further studies on this current topic. The rest of the study is organised as follows; section two presents literature and hypothesis that supported the topic understudy; whilst section three concentrates on the study's research model and methodology. In the fourth section, various results that related to the study are outlined; whilst the fifth section discusses the study's findings and tests the formulated hypothesis. The sixth section finally presents the study's conclusion and policy implications.  (2005) examined the profitability determinants of manufacturing and service sector firms in France, Italy, Spain, Belgium and the UK. Through the dynamic panel data approach, past profitability had a significantly positive influence on the firms' profitability as measured by ROA. Neil (2009) conducted a study to identify the financial statement variables that were likely to have an impact on firms' profitability. From the study's findings, preceding year's net profit margin and 3-year returns were significant determinants of the firms' profitability as measured by ROA.

Hypothesis Development
According to Alina (2017), a hypothesis is a suggested solution for an unexplained occurrence that does not fit into current accepted scientific theory. The basic idea of a hypothesis is that, there is no pre-determined outcome. For a hypothesis to be termed a scientific hypothesis, it has to be something that can be supported or refuted through carefully crafted experimentation or observation (Alina, 2017). The ambition of this study could not be achieved without the test of some hypothesis. Therefore, based on the reviews of various literature, the following hypothesis were developed for testing; H01:There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROA. H02:There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROE.
H03:There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROCE.

RESEARCH MODEL AND METHODOLOGY
This study was a quantitative study. The study was quantitative because it was based on numbers and statistics arranged in the form of tables; its findings could be replicated or repeated, given its high reliability; and it was based on a sample that was representative of the entire population. Specifically, the study was correlational because it sought to investigate the association between two variables in which none of the variables was manipulated.
The study was finally panel in nature because its units of analysis were followed at specified time intervals over a long period. In other words, the study collected repeated measures from the same sample at different points in time.
All non-financial firms that listed and traded their shares on the Ghana Stock Exchange (GSE) as of 31 st December, 2017 formed the study's target population. Because the study wanted to deal with a balanced data, a sample was made out of the entire population. The number of years in existence, technical suspension due to one reason or the other, unaudited financial records, non-existence of trend records, incomplete financial statements and the presentation of annual reports in foreign currencies either than that of the Ghana currency (because of the non-stability of the Ghana Cedi to major foreign currencies) were the factors or filters that were considered during the sampling process.
Considering these factors or filters in making a choice out of the entire population implies, the study adopted the purposive or selective sampling technique in its sampling process. After critically considering the various factors or filters during the sampling process, fifteen (15)  Both the descriptive and inferential techniques of data analysis were employed for the study. In the descriptive technique of data analysis, the mean, standard deviation, variance, minimum and maximum values, range, skewness and kurtosis of the study's variables were analysed, whilst the Pearson Product-Moment Correlation Coefficient technique of data analysis was employed to establish the link between lagged profitability and the firms' financial performance as measured by ROA, ROE and ROCE (inferential analysis). All the data analysis were conducted through the use of STATA version 15 statistical software package at α=5% (p≤0.05). Figure 1 shows the conceptual framework that guided the conduct of the study. In the framework, the firms' financial performance is proxiedby Return on Assets (ROA), Return on Equity (ROE) and Return on Capital Employed (ROCE).Return on assets was calculated as the ratio of net income to total assets of the firms. Return on equity was also calculated as the net income divided by the total equity of the firms, whilst the ratio of net income to capital employed was used to compute the firms' ROCE. On the other hand, lagged profitability was obtained by lagging the firms' ROA values by one year. Table 1 presents a detailed summary of the study's variables and their measurements;

EMPIRICAL RESULTS
This aspect presents the empirical results of the study. The empirical results comprise of the descriptive analysis of the study variables and the bivariate associations between lagged profitability and the firms' financial performance as measured by Return on Assets, Return on Equity (ROE) and Return on Capital Employed (ROCE).

Descriptive Analysis
From Table 2, ROA had a mean value of 0.0052693. The mean ROA of 0.0052693 implies, the firms were making 0.52693 pesewas of profit on each cedi of investments made from the year 2008 to 2017. The positive mean figure for ROA is an indication that, the assets or investments of the firms were been used efficiently by management to generate profits. The ROA distribution had a maximum value of 0.7656 and a minimum value of -5.6487, leading to a range of 6.4143. The firms' ROA also had a standard deviation of 0.4849762 and a variance of 0.2352019. This implies, data values of ROA deviated from both sides of the mean by 0.4849762, which is an indication that, the data values were not too widely dispersed from the mean.
The figure -10.64317 being the skewness for ROA indicates that, the ROA distribution was highly negatively skewed or skewed to the left. This denotes that, a greater portion of the ROA distribution fell on the right side of the normal curve. In other words, the left tail of the ROA distribution was longer than that of the right tail. The kurtosis coefficient of 124.8778 [excess (K)=124.8778-3.0=121.8778] shows that, the ROA distribution was leptokurtic or slender in shape. Put simply, the ROA distribution was not normally distributed as it had fatter tails that asymptotically approached zero more slowly than the Gaussian distribution, and therefore produced more outliers than the normal distribution. The ROE of the sampled firms also had a mean value of 0.167214. This implies, on the average, every cedi of common stockholders' equity generated 16.7214 pesewas of net income. The positive mean ROE is an indication that, management were efficiently utilizing shareholder's capital to generate income and profits. This serves as a favorable sign for potential investors because, they are likely to get a return on their investments. The positive average ROE is also not just an indication of the firms' profitability, but shows that, the firms were good at using their retained earnings efficiently to generate revenues.
The positive mean ROE of the firms further signposts that, they had a huge economic moat. Thus, the firms had the ability to maintain competitive advantage over their competitors by protecting their long-term profits and market share. The firms having an economic moat also implies, they were worthy enough to generate economic profits for a longer stretch of time, and were able to reinvest those cash flows at a high rate of return for a longer period. The firms' ROE also had a standard deviation of 1.184918 and a variance of 1.404031. This is an indication that, data values of ROE deviated from both sides of the mean by 1.184918, implying, the values were a bit much dispersed from the mean. Return on Equity (ROE) of the sampled firms also had a minimum value of -4.5277 and a maximum value of 12.8951, leading to a range of 17.4228. The distribution for ROE was positively skewed with a coefficient of 7.859589, implying, the right tail of the ROE distribution was longer than that of the left tail. The kurtosis value of 91.75657 [excess (K)= 91.75657-3.0= -88.75657] shows that, the ROE distribution was leptokurtic or slender in shape.
In other words, the ROE distribution was not normally distributed. is an indication that, the ROCE distribution was higher and peakier (leptokurtic) than the Gaussian distribution which shows its abnormality.
Finally, lagged profitability had a mean value of 0.002577, a maximum value of 0.7656 and a minimum value of -5.6487, resulting in a range of 6.4143.The firms' lagged profitability also had a standard deviation of 0.5093136 and a variance of 0.2594003. This implies, dispersions or deviations around the mean lagged profitability was 0.5093136, which is an indication that, the data values of lagged profitability were a bit widely dispersed from the mean. The skewness value of -10.20912 signifies that, the distribution for lagged profitability was highly negatively skewed or skewed to the left. This means, a greater portion of the distribution for lagged profitability fell on the right side of the normal curve. The kurtosis value of 114.0237 [excess (K)=114.0237-3.0=111.0237] is an indication that, the distribution for lagged profitability was higher and peakier (leptokurtic) than the normal distribution, implying it was of abnormal shape.

Correlational Analysis
This section sought to explore the nexus between lagged profitability and the financial performance of non-financial firms listed on the Ghana Stock Exchange (GSE). The Pearson Product-Moment Correlation Coefficient technique of data analysis was adopted for that purpose and from Table 3, there was an insignificantly positive association between lagged profitability and the firms' ROA at α=5%[r=0.1195, (p=0.1673)>0.05]. Even though the correlation between lagged profitability and ROA was trivial, the positive relationship between them implies, an increase in lagged profitability led to an increase in ROA and vice-versa, and a decrease in lagged profitability also led to a decrease in ROA and vice versa. The strength of association between lagged profitability and ROA can be justified by the coefficient of determination (r 2 =0.0143) which indicates that 1.43% of the variations in ROA was accounted for by lagged profitability and 1.43% of the variations in lagged profitability was explained by ROA. The unexplained variances [98.57% or (1r 2 =0.9857)] may be attributed to other inherent variabilities. The study also discovered an insignificantly negative association between lagged profitability and the firms' ROE at the 5% significance level [r = -0.0122, (p=0.8885)>0.05]. Though the connection between lagged profitability and the firms' ROE was not significant, the inverse link between the two is an indication that, an increase in lagged profitability led to a decrease in ROE and vice-versa. The degree of association that existed between lagged profitability and the firms' ROE can be substantiated by the coefficient of determination (r 2 =0.0001) which shows that 0.01% of the variations in ROE was accounted for by lagged profitability and 0.01% of the variations in lagged profitability was explained by ROE. The unexplained variations [99.99% or (1-r 2 =0.9999)] may be aligned to other factors that did not form part of the study.
Finally, lagged profitability had an insignificantly negative affiliation with the firms' ROCE at the 95% confidence interval [r=-0.0192, (p=0.8255)>0.05]. Even though the relationship between lagged profitability and the firms' ROCE was not significant, the adverse association between lagged profitability and ROCE implies, an increase in lagged profitability led to a decrease in ROCE and vice-versa. The weight of the correlation between lagged profitability and the firms' ROCE can be proven by the coefficient of determination (r 2 =0.0004) which shows that 0.04% of the variations in ROCE was accounted for by lagged profitability and 0.04% of the variations in lagged profitability was explained by ROCE. The unexplained variances [99.96% or (1-r 2 =0.9996)] may be accounted for by other variables that were not included in the study.

DISCUSSIONS AND TESTS OF HYPOTHESIS
This section discusses the study's findings. The discussions are related to the review of relevant literature and are conducted in the order of; the relationship between lagged profitability and the firms' financial performance as measured by ROA; the association between lagged profitability and the firms' financial performance as measured by ROE; and the affiliation between lagged profitability and the firms' financial performance as measured by ROCE. Each subdivision concludes with a test of hypothesis that was developed for the study.

The relationship between lagged profitability and the firms' financial performance (ROA)
The study discovered an insignificantly positive association between lagged profitability and the firms' ROA at α=5% [r=0.1195, (p=0.1673)>0.05]. This finding was inconsistent with that of Odusanya, Yinusa and Ilo (2018) whose research on 114 firms listed on the Nigerian Stock Exchange, found a significantly positive association between lagged profitability and the firms' current year's profitability. The finding was also inconsistent with that of Maja, Ivica and Marijana (2017) whose dynamic study on 956 firms operating in the Croatian food sector, uncovered a significantly positive interaction between lagged profitability and the firms' performance. The finding was further inconsistent with that of Kristina and Dejan (2017) whose research on the agricultural industry of Bosnia and Herzegovina, Hungary, Serbia and Romania, disclosed a significantly positive connection between lagged profitability and the firms' current year's profitability. The finding was finally not in tandem with that of Yazdanfar (2013) whose study on the profitability determinants of micro sector firms operating in Sweden, disclosed a significantly positive link between lagged profitability and the firms' current year's profitability.

Hypothesis Testing
An insignificantly positive association between lagged profitability and the firms' ROA was discovered at α=5%[r = 0.1195, (p=0.1673)>0.05]. The study therefore failed to reject the null hypothesis (H01) that lagged profitability had no significant relationship with the firms' financial performance as measured by ROA, and concluded that lagged profitability had an insignificantly positive affiliation with the firms' financial performance as measured by ROA.

The Association between Lagged Profitability and the Firms' Financial Performance (ROE)
The study also discovered an insignificantly negative association between lagged profitability and the firms' ROE at the 95% confidence interval [r = -0.0122, (p=0.8885)>0.05]. This finding did not support that of Farah and Nina (2016) whose study on small and medium enterprises listed on the Indonesian Stock Exchange, discovered a significantly inverse link between lagged profitability and the firms' current year's profitability. The finding was also in disagreement with that of Isik and Tasgin (2017) whose dynamic panel study on 120 manufacturing firms listed on the Borsa Istanbul Stock Exchange, found a significantly positive association between lagged profitability and the firms' financial performance.
The finding further contrasted that of Ahmad (2015) whose research on 17 non-financial firms listed on the Bahrain Bourse, uncovered a significant affiliation between lagged profitability and the financial performance of the firms as measured by ROE, ROA, EPS and Dividend Yield.The finding was finally in disagreement with that of Vijayakumar (2011) whose study on firms operating in the Indian automobile industry, found a significant association between past profitability and the current year's profitability of the firms.

Hypothesis Testing
An insignificantly negative association between lagged profitability and the firms' ROE was discovered at the 95% confidence interval [r= -0.0122, (p=0.8885)>0.05]. The study therefore failed to reject the null hypothesis(H02) that lagged profitability had no significant connection with the firms' financial performance as measured by ROE, and concluded that lagged profitability had an insignificantly negative association with the firms' financial performance as measured by ROE.

The Affiliation between Lagged Profitability and the Firms' Financial Performance (ROCE)
The study finally uncovered an insignificantly negative affiliation between lagged profitability and the firms' ROCE at the 5% level of significance [r = -0.0192, (p=0.8255)>0.05]. This finding disagreed with that of Njimanted, Akume and Nkwetta (2017) whose VAR study for the period 1990 to 2016 established a significantly positive association between lagged profitability and the financial performance of the firms under study. The finding also disagreed with that of Schmidt (2014) whose study on 392 American firms for the period 2005 to 2013, found a significant relationship between lagged profitability and the firms' financial performance.
The finding was further inconsistent with that of Margaretha and Supartika (2016) whose research on 22 Small and Medium Enterprises (SMEs) listed on the Indonesian Stock Exchange, disclosed a significantly negative association between lagged profitability and the contemporaneous profit margin of the SMEs. The finding finally contrasted that of Coban (2014) whose GMM study on 137 listed manufacturing firms in Turkey, established a significantly positive interaction between lagged profitability and the firms' current year's profitability.

Hypothesis Testing
An insignificantly negative affiliation between lagged profitability and the firms' ROCE was discovered at the 5% level of significance [r = -0.0192, (p=0.8255)>0.05]. The study therefore failed to reject the null hypothesis (H03) that lagged profitability had no significant relationship with the firms' financial performance as measured by ROCE, and concluded that lagged profitability had an insignificantly inverse association with the firms' financial performance as measured by ROCE. H01: There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROA.

Correlation Accepted
H02: There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROE.

Correlation Accepted
H03: There is no significant relationship between lagged profitability and the firms' financial performance as measured by ROCE.

CONCLUSION AND POLICY IMPLICATIONS
This study sought to examine the association between lagged profitability and the financial performance of non-financial firms listed on the Ghana Stock Exchange (GSE). Specifically, the study sought to explore the relationship between lagged profitability and the firms' financial performance as measured by ROA; assess the association between lagged profitability and the firms' financial performance as measured by ROE; and to examine the affiliation between lagged profitability and the firms' financial performance as measured by ROCE. Panel data extracted from the audited and published annual reports of fifteen (15) non-financial firms for the period 2008 to 2017 was used for the study. From the study's Pearson Product-Moment Correlation Coefficient estimates, an insignificantly positive association between lagged profitability and the firms' ROA and ROE was established. Also, an insignificantly negative affiliation between lagged profitability and the firms' ROCE was discovered at the 95% confidence interval. Even though the association between lagged profitability and the firms' financial performance was not statistically significant, the positive connection uncovered between lagged profitability and the firms' ROA and ROE is an indication that significant increases in lagged profitability could have led to significant increases in ROA or ROE and vice-versa. Therefore, the determinants of firms' financial performance like liquidity, leverage, capital structure, operational efficiency, size, growth, tangibility, age, inflation, economic growth (GDP), exchange rate, interest rate, competition, corporate taxes and market share among others, should be properly factored into the business decisions of the firms.