Factors
affecting profitability of Sri Lankan Business
Abstract
Purpose –
The purpose of this paper is to examine the factors affecting profitability in
Sri Lankan listed companies listed in Colombo Stock Exchange (CSE), Sri Lanka. It has been argued that profitability is the
main pillar for any company to survive in the long run. Although profitability
is the primary goal of all business ventures, scant attention has been paid to
the factors that affect profitability in developing countries. This study investigates
the factors affecting profitability in Sri Lankan -listed companies.
Design/methodology/approach –
This research is based on five independent variables that were empirically
examined for their relationship with profitability. These variables are: firm
size (as measured by total sales), working capital (WC), company efficiency
(assets turnover ratio), liquidity (current ratio) and leverage (debt equity
ratio). Data of 83 companies listed on Colombo Stock Exchange covering the
period from 2015 to 2017 were extracted from companies’ annual reports. Pooled ordinary
least squares regression and fixed-effects were used to analyze the data.
Findings –
The findings show a strong positive relationship between company efficiency
(Asset Turnover), Liquidity (Current Ratio) and profitability. The results also show a negative relationship between debt
equity ratio and profitability
Research limitations/implications – Due to the time limitation, the
data includes only 83 companies listed in Colombo Stock Exchange, Sri Lanka
from 2015 to 2017.
Practical implications –
These results benefit internal users (such as mangers, shareholders and
employees). They can realize the determinants of enhancing the profitability of
their company after the depreciation of the Sri Lankan currency and therefore
concentrate more on the factors that enhance their companies’ profitability. On the other side,
other external users (such as investors, creditors, new established companies,
tax authority) also may get advantages of these results. It is clear that those
users concern about the profitability of companies and the determinants of
their profitability after the currency’s depreciation.
Originality/value –
This study differs than previous studies since it focuses on non-financial
listed companies in Sri Lanka
Keywords Profitability, Sri Lanka, Efficiency, Leverage, Liquidity,
Working capital
1. Introduction
One of the main goals of any company
is to be sustainable in any competitive environment. To do so, it is important
for the company to develop, implement and maintain strategies that can enhance
its performance. This can be done by investigating the internal and external
factors that may have an impact on the company’s profitability. The quality and
efficiency of managers depend on their ability to identify those elements that
can lead to increase the profitability. In general, profitability is defined as
the earnings of a company that are generated from revenue after deducting all
expenses incurred during a given period. It is one of the most important
factors that signal management’s success, shareholders’ satisfaction,
attraction for investors and the company’s sustainability (Bekmezci, 2015).
Undoubtedly, the ultimate goal of any firm is to maximize the wealth of its
shareholders by increasing the value of its stocks. Previous studies have found
a positive relationship between earnings and stock values (Kalama, 2013). In
other words, if earnings announcements come as expected or are better, stock
prices will increase, but if earnings announcements fall short of expectations,
the stock prices will decline
A majority of companies, if not all,
realize the concept and the importance of profitability but they may not know
how to enhance it and what the factors affecting profitability are. This is
more obvious during a time of crisis; some companies attempt to preserve their
financial status by undertaking risky measures, but due to limited experience
and high risks, these kinds of actions more often than not result in worsening
their financial status.
Identifying the factors which
determine profitability is still one of the major concerns of researchers. A
number of previous studies have investigated the factors that influence
profitability of firms, including size (Stierwald, 2010a, b; Yazdanfar, 2013;
Mohd Zaid et al., 2014); working capital (WC) management (Goddard et al., 2005;
Chowdhury and Amin, 2007; Alipour, 2011; Charumathi, 2012); age of the firm
(Geroski and Jacquemin, 1988; Bhayani, 2010; Agiomirgianakis et al., 2013); and
leverage (Burja, 2011; Mistry, 2012; Boadi et al., 2013). However, previous
studies have shown inconsistent findings that make generalization questionable.
Based on this, this study is concerned with profitability in Sri Lanka.
The main challenge Sri Lankan
companies are facing is how to achieve stability and sustainability. In order
for a company to achieve this, it is crucial that the company has a good
knowledge of specific internal and external conditions within which the company
operates. The quality and efficiency of managers depend on their ability to
identify those elements that can enhance company performance and profitability
(Burja, 2011). This is also applicable for Sri Lankan companies if they wish to
continuously compete in the emerging market.
Based on previous studies, this
study examines the impact of five factors on companies’ profitability by using
six financial indicators, namely, total sales, WC, assets turnover ratio,
current ratio, debt equity ratio.
The profitability factor is measured by using ROE and EPS.
This study intends to achieve the following objectives:
(1)
to examine the relationship between
firm size and profitability;
(2)
to examine the relationship between
WC and profitability;
(3)
to examine the relationship between
company efficiency and profitability;
(4)
to examine the relationship between
company liquidity and profitability; and
(5)
to examine the relationship between
company leverage and profitability.
This study is organized into five
sections as follows: Section 2 displays briefly previous studies. Section 3
explains the source of data, the hypotheses under investigation and the
research model. Results of the tested hypotheses are included in Section 4.
Finally, Section 5 concludes the study.
2. Literature review
2.1 Previous empirical studies
It has been proven that a business
will not survive if it is not profitable, and a business that is highly
profitable has the ability to reward its owners with high returns on their
investment. Thus, companies that want to achieve stable profitability need to
know internal and external factors that may have a significant effect on
profitability. Earlier and recent studies have attempted to determine the
financial indicators for profitability by empirically examining different
factors that have theoretical relationships with profitability, like size
(Mehta, 1955; Comanor and Wilson, 1969); net operating profitability (Ito and
Fukao, 2006; Rahman et al., 2010; Burja, 2011); liquid ratio, receivables turnover
ratio and WC to total assets (Singh and Pandey, 2008); debt ratio (Burja,
2011); return on total assets (Padachi, 2006); return on invested capital and
return on assets (ROA) (Narware, 2010); financial leverage (Burja, 2011);
equity ratio (Burja, 2011); market share (Nagarajan and Barthwal, 1990);
current assets ratio (Singh and Pandey, 2008; Burja, 2011); and R&D (Fenny
and Rogers, 1999). Some related studies have examined these aspects in
different countries, like Huang and Song (2006) and Chakraborty (2010) in
China; Akintoye (2008) in Nigeria; Pirtea et al., Burja (2011), Moldovan et al.
(2013) and Vătavu (2014) in Romania; Sivathaasan
et al. (2013) in Sri Lanka; Kaen and Baumann (2003), Hoffmann (2011) and Growe
et al. (2014) in the USA; Raza et al. (2012) and Bhutta and Hasan (2013) in
Pakistan; Dencic-Mihajlov (2014) in Serbia; Geroski et al. (1997) in the UK;
Fenny and Rogers (1999) in Australia; Claver et al. (2006) in Spain; Ito and
Fukao (2006) in Japan; Chander and Priyanka (2008) in India; Asimakopoulos et
al. (2009) in Greece; and Goddard et al. (2009) in 11 European countries. Some
of these studies are descriptive and others are empirical, which show the
relationship between profitability and its determinants.
The findings of previous studies
have broadly highlighted a number of variables that have a significant impact
on companies’ profitability. All these variables,
namely, company size, age, risk, liquidity, leverage, industry type, capital
intensity, skill, concentration ratio, capacity utilization, market share,
advertising intensity, R&D intensity, retention ratio, growth in revenue,
long-term financing, turnover ratios, ownership characteristics, exports,
working assets, indebtedness level, etc., are equally popular among
researchers. However, previous studies differ from each other because of the
period the study was undertaken, ranging from one year (as seen in Jones et
al., 1973; Barthwal, 1984) to 20 years (Kaur, 1997), or because of focusing on
country-specific and firm-specific factors (Kaur, 1997; Glancey, 1998; Ito and
Fukao, 2006); and inter-industry-specific factors (Barthwal, 1984; Nagarajan
and Barthwal, 1990; Grinyer and McKiernan, 1991). In addition, the review also
shows that most of the research work relating to inter-industry profitability
has been conducted in developed countries. Vătavu (2014) examined the
determinants of financial performance in 126 Romanian companies listed on the
Bucharest Stock Exchange over a period of ten years (2003–2012). The analysis
was based on cross-sectional regressions; performance was measured by ROA,
while the IVs were debt, asset tangibility, size, liquidity, taxation, risk,
inflation and crisis. The outcomes of regression analysis indicate that profitable
companies operate with limited borrowings. Tangibility, business risk and the
level of taxation have a negative impact on ROA. Although earnings are
sustained by significant sales turnover, performance is affected by high levels
of liquidity. Periods of unstable economic conditions, reflected by high
inflation rates and the financial crisis, have a strong negative impact on
corporate performance.
Several financial indicators, such
as current ratio, liquidity ratio, receivables turnover ratio and WC to total
assets, have been examined in other studies (Singh and Pandey, 2008); while
some studies have considered performance assessment expressed by earnings
before interest and taxes and the associated risks resulting from the influence
of using a certain financing structure (Akintoye, 2008), or expressing it
through economic value added, ROE, operating profit margin (OPM) and EPS
(Rayan, 2008).
Profitability is the main concern of
Sri Lankan-listed companies as it is the concern of other related parties.
However, the studies done in Sri Lanka are very few and the focus has been
mostly on two sectors, i.e. the banking and Insurance sectors. Nevertheless,
all of these studies have highlighted the importance of profitability at the
microeconomic level. Mohd Zaid et al. (2014) examined the determinants of
profitability based on construction companies in Malaysia. The data were
collected for the period of 2000–2012. This study used ROE to measure the
profitability of companies; debt equity ratio to measure capital structure;
quick ratio to measure liquidity; sales to measure the size of companies; and
term premium to measure the economic cycle. The result shows that liquidity and
size have significant relationships with profitability. A negative and insignificant
relationship is found between capital structure and profitability. Another
study (unpublished) by Ulfana Nisa (2015) examined factors that affected
profitability during the financial crisis of 2008. The ROA was used as a
measurement for company profitability, while size, liquidity, leverage, sales
growth and gross domestic product were examined as IVs. The data of 161 listed
companies for the period of 2001–2012 were analyzed using ordinary least
squares (OLS) and fixed-effects estimation. The findings show that leverage has
a negative and significant relationship with ROA; and size, liquidity and sales
growth have a positive and significant relationship with ROA. However, gross
domestic product does not have a significant relationship with ROA. In general,
in today’s economy, where strong competition dominates and where all processes
are highly dependent on information (Alarussi et al., 2009), the success of a
company requires specific measurements and management systems. To comply with
the principle of rational economics, a company must systematically analyze its
financial result, or in other words, analyze profitability. Parkitna and
Sadowska (2011) affirmed that when determining the profitability index of a
business entity, it is important to use many variants of the numerator and
denominator to gain more information about a company. This paper is concerned
with the profitability of companies in Malaysia and chooses the most common
variables in order to check whether the determinants of profitability for
developed countries are applicable in Malaysia’s case as a developing country
following the depreciation of the Malaysian Ringgit. The results of the study
will be useful for related parties, including management, shareholders,
financial analysts and investors.
2.2 Selection of variables,
hypotheses
Profitability is significantly
affected by different factors. Many empirical studies have been done to explore
the association between various factors and profitability in different
countries and they have produced mixed results. For example, Pathak (2011)
found a significantly negative association between level of debt and
profitability. This result is not consistent with studies done on western
economies but consistent with some of the studies done for Asian countries. One
important reason for this conflicting result can be the high cost of borrowing
in developing countries, like Malaysia, compared to western countries. Hadlock
and James (2002) suggested corporations with high level of profitability having
a high level of debts. Arbabiyan and Safari (2009) found a positive
relationship between short-term debts and profitability (ROE) but a negative
relationship between long-term debts and ROE, when they studied 100
Iranian-listed firms from 2001 to 2007. In addition, Wiwattanakantang (1999)
reported a negative relationship between leverage and ROA by using the data of
270 Thai companies. Similar results were found by Huang and Song (2006).
This study attempts to focus on
financial indicators, i.e. firm size (total sales), WC, company efficiency
(assets turnover ratio), liquidity (current ratio) and leverage (debt equity
ratio and leverage ratio) as IVs and profitability as the dependent variable
(DV ), measured by ROE and EPS
2.2.1 Firm size. Size is considered
as a proxy for many positive aspects, including profitability. Ha-Brookshire
(2009) found a positive and significant relationship between size and
profitability when he examined US non-manufacturing companies. Similar results
were reported by Stierwald (2010a, b) when he examined large companies in
Australia. The resource-based theory states that the more the access to
financial resources, the lesser the cost of capital. This is applicable for big
size firms. As the size of the company increases, it is easier for it to access
more financial resources which lead to the lower cost of capital and higher
profit. Punnose (2008) and Malik (2011) showed a positive relationship between
firm size and profitability. Nguyen (1985) found that large foreign-owned firms
generally earn higher profits than large domestic firms. However, Keith (1998)
found that size has a limited value in explaining profitability when he
examined 38 small manufacturing firms in the Tayside Region of Scotland.
Goddard et al. (2005) examined the determinants of profitability for
manufacturing and service firms in Belgium, France, Italy and the UK. The
results provide evidence of a negative relationship between size, gearing ratio
and profitability. This study examines the association between firm size and
profitability. Firm size is measured by total sales, which is the same
measurement used by Kajüter (2006). Based on the above discussion, the first
hypothesis is drawn as follows:
H1. There
is a positive association between company firm size and profitability.
2.2.2 Working capital. Grinyer and
McKiernan (1991) found that WC is amongst the variables that play a significant
role in explaining corporate profitability. This is the result that was
obtained when the data of 45 UK electrical companies was examined. Similar
results were found by Chowdhury and Amin (2007), who investigated the
profitability of pharmaceutical companies listed on the Dhaka Stock Exchange.
The results provide evidence of the impact of WC on profitability as measured
by ROA. In addition, Alipour (2011) employed the multiple regression technique
and the Pearson correlation test on 1,063 companies on the Tehran Stock
Exchange. The results show a significant relationship between WC management and
profitability. In developing countries, Malik (2011) tested the profitability of
35 life and non-life insurance companies in Pakistan. The findings reveal a
positive and significant relationship between WC and profitability. Similar
results were found by Burja (2011). However, Dong and Su (2010) found a
negative relationship between WC management and profitability for firms listed
on the Vietnam Stock Market. Since the results are not consistent in developing
countries, this study examines the association between WC and profitability in
Malaysian-listed companies, and based on the above discussion, the second
hypothesis is as follows:
H2. There
is a positive association between WC and profitability.
2.2.3 Company efficiency. There is
no doubt that efficiency is the cornerstone to achieve higher profits.
Efficiency can refer to the operations per se or to the whole company. Innocent
et al. (2013) tested the profitability of the pharmaceutical industry in
Nigeria covering 11 years from 2001 to 2011. The results show a negative and
insignificant relationship between profitability and debt turnover ratio,
creditor’s velocity and total assets turnover ratio. Inventory turnover ratio
is also found to have a negative but significant relationship with
profitability. Warrad and Al Omari (2015) studied the impact of total assets
turnover ratio and fixed assets turnover ratio on ROA of firms in the Jordanian
industrial sector. A simple liner regression was used to test the impact during
the period of 2008–2011. The study shows a significant impact of total assets
turnover ratio on the Jordanian industrial sector’s ROA. Hence, changes in ROA
can be explained by total assets turnover ratio. However, a prior study
conducted by Selling and Stickney (1989), using data from a group of Compustat
companies over a period from 1977 to 1986, examined total assets turnover and
OPM ratios as they related to ROA. Their sample was classified into 22
industries; they found negative correlations between total assets turnover and
OPM ratios in 15 of them. Another study by Reed and Reed (1989) found the total
assets turnover and OPM ratios are negatively correlated. Fairfield and Yohn
(2001) studied the use of OPM and assets turnover ratios to forecast future
profitability. They found that the two variables are negatively correlated, and
that the correlation is statistically significant. Skolnik (2002) used the
non-financial firms in the S&P 500 and a time-frame of 1989 through 1999 to
study the relationship among operating returns, OPM and total assets turnover
ratios. He found that the total assets turnover ratio decreased over the study
period while the OPM ratio increased. Consequently, he found a statistically
significant and negative correlation between total assets turnover and OPM
ratios. As the results show contradiction in this relationship, this study
examines the assets turnover ratio as one of profitability measurements. It is
expected that there is a positive relationship between company efficiency
(measured by assets turnover ratio) and profitability. Therefore, based on the
above discussion, the third hypothesis is as follows
H3. There
is a positive association between company efficiency and profitability.
2.2.4 Company liquidity. Liquidity
is defined as the ability of a firm to convert an asset to cash quickly. It is
also defined as the ability of a firm to pay off its short-term obligations.
Liquidity is measured by a number of ratios, such as current ratio, quick ratio
and cash ratio. Liquidity is very important to run the business properly.
Bhayani (2010) examined factors that influence profitability for cement firms
covering the period from 2001 to 2008. He concluded that liquidity, age of the
firm, operating ratio, interest rate and inflation are important determinants
of profitability for the Indian cement industry. Boadi et al. (2013) found a
positive relationship between liquidity and profitability. Elsiefy (2013)
tested the determinants of profitability of commercial banks in Qatar and found
evidence of a strong relationship between liquidity and profitability for
Islamic banks. A more recent study by Al-Jafari and Alchami (2014) investigated
the determinants of profitability of Syrian banks utilizing the generalized
method of moments technique. Their results reveal that liquidity ratio, credit
risk, bank size and management efficiency affect significantly the
profitability of Syrian banks. Similarly, Pratheepan (2014) tested the
determinants of profitability for 55 Sri Lankan manufacturing companies using
static panel models. The results show that size has a significantly positive
relationship with profitability. Likewise, Mohd Zaid et al. (2014) investigated
the factors affecting profitability for construction companies in Malaysia.
They found that liquidity and size have a significant and positive relationship
with profitability. However high liquidity may lead to agency cost and may
hinder performance (Ganguli, 2016). Eljelly (2004) did a study on companies
listed on the stock market in Saudi Arabia; he examined the relationship
between profitability and liquidity measured by current ratio and cash gap
(cash conversion cycle). He found a negative relationship between profitability
and liquidity indicators. Similar results were found by Raheman and Nasr (2007)
when they studied 94 Pakistani companies listed on the Karachi Stock Exchange.
Based on the above discussion, the fourth hypothesis is as follows:
H4. There
is a positive association between company liquidity and profitability.
2.2.5 Company leverage. Leverage is
one component of the capital structure of a company. This is because the choice
between debt and equity suggests somehow a trade-off between business and
financial risk. When companies choose more borrowings to finance their needs,
they do not affect corporate ownership (Yazdanfar, 2013). After examining the
data of 12,530 non-financial micro-firms operating in four industrial sectors
in Sweden to measure the factors affecting profitability as well as industry
affiliation, the researcher concluded that companies with a large proportion of
equity based on shareholders’ investment offer better credit rating for the
companies. Therefore, companies using large borrowings face higher risks while
those using more equity tend to operate more conservatively by relying on
internal funds. According to the trade-off theory of capital structure, the
optimal debt level balances the benefits of debt against the costs of debt. The
tax benefits of debt dominate up to certain debt ratio, resulting in higher
ROE, but the benefit would be less than the cost after a certain level of debt
ratio. The more a company uses debt, the less income tax it pays, but the
greater its financial risks (Myers, 1984). Charumathi (2012) examined the
determinants of profitability for the Indian life insurance companies. He found
that leverage has a negative and significant impact on profitability. Eriotis
et al. (2011) investigated the relationship between debt to equity ratio and
profitability. They concluded that financing investments using retained profits
are more profitable than using borrowed funds. Another study conducted by Boadi
et al. (2013) examined the factors affecting profitability for the insurance
companies in Ghana and revealed a positive and significant relationship between
leverage, liquidity and profitability. Agiomirgianakis et al. (2013) found a
positive and significant impact between low cost access to bank financing and
profitability, when they investigated factors that influence profitability for
the tourism industry in Greece. Burja (2011) obtained the same results when he
examined factors that influence profitability for the Romanian chemical
industry.
Generally,
the influence of capital structure on performance is not clearly stated in the
literature. Some studies have argued that companies have higher returns when
they operate with a larger amount of borrowed funds, but there is a negative
influence on long-term debt (Abor, 2005). Other studies have not found any
relationship between financing decisions and profitability (Ebaid, 2009). This
study uses two ratios to measure this variable, i.e. debt equity ratio and
leverage ratio. They show the extent to which the total assets of the company
are funded by loans. For this reason, it is necessary to rationally and
efficiently use this financing method. Based on the above discussion, the fifth
hypothesis is as follows:
H5. There
is a negative association between company leverage and profitability.
3. The
data, sample and model specifications
3.1
Data description
This study utilized secondary data
collected from annual reports of non-financial companies listed on Colombo
Stock Exchange (www.cse.lk)). Due to the time limitation, the data includes only 8
83 companies and covers the period
from 2015 to 2017. The study employs the most important factors that influence
firms’ profitability and commonly utilized in the previous literature. However,
some of variables are new in the Sri Lankan context, i.e. WC and company
efficiency. The variables and their measurements used in this study are listed
in Table I.
Pooled
ordinary least regression was used to analyze the data to find the results.
Two |
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models
were estimated in the study and both measured e profitability as follows: |
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(Model 1): |
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ROE = α β1LTS + β2WC +
β3CRIO + β4ASTRIO + β6DTERIO + ɛ, |
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(Model 2): |
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EPS
= α β1LTS + β2WC + β3CRIO + β4ASTRIO + β6DTERIO + É›, Here, α and β1–β6 are
coefficients, Log of Total Sales (LTS), WC, Current Ratio, Assets Turnover
Ratio and Debt to Equity Ratio are the explanatory variables, and É› is the
error term.
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Table
I - Variables’ measurements
4. Discussion of
results
Mean |
Median |
Std. Deviation |
Minimum |
Maximum |
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Profitability-ROE |
.1656 |
.0925 |
.41457 |
-.44 |
3.94 |
|
Profitability-EPS |
80.7769 |
3.2226 |
703.14258 |
-1248.63 |
10279.61 |
|
Firm Size-LTS |
9.1017 |
9.2083 |
.84126 |
6.26 |
11.14 |
|
Working Capital |
1307998556 |
271189561 |
6309260863 |
-23762000000 |
59775436000 |
|
Co.Ef-Asset turnover |
.0924 |
.0623 |
.13717 |
-.16 |
1.06 |
|
Liquidity-Current Ratio |
3.7595 |
1.5582 |
8.98916 |
.07 |
81.55 |
|
Leverage-Debt to equity |
1.2948 |
.4643 |
8.38195 |
.01 |
131.97 |
Table
II - Descriptive statistics
Table
II shows the descriptive statistics for the sample. The mean (median) of ROE is
0.17 (0.09) whereas the minimum value is negative, showing loss. In addition,
the mean (median) of EPS is 80.78 (3.22); however, the minimum value is
negative. Mean (median) of company efficiency (assets turnover ratio) is 0.92
(0.62); the mean (median) of liquidity (current ratio) is 3.76 (1.56); and,
lastly, the mean (median) of leverage (debt equity ratio) is 0.12 (0.46) respectively.
Correlations |
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|
Profitability-ROE |
Profitability-EPS |
Firm Size-LTS |
Working Capital |
Co.Ef-Asset turnover |
Liquidity-Current
Ratio |
Leverage-Debt to
equity |
Profitability-ROE |
1 |
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Profitability-EPS |
.118 |
1 |
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Firm
Size-LTS |
.271** |
-.056 |
1 |
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Working
Capital |
.039 |
-.009 |
.164** |
1 |
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Co.Ef-Asset
turnover |
.710** |
.346** |
.055 |
.092 |
1 |
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Liquidity-Current
Ratio |
-.014 |
.110 |
-.099 |
.362** |
.064 |
1 |
|
Leverage-Debt
to equity |
.081 |
-.010 |
.045 |
-.018 |
.034 |
.017 |
1 |
**.
Correlation is significant at the 0.01 level (2-tailed). |
Table
III - Correlation between DV and IVs
Table
III shows the correlation between the IVs and the DV in this study. Asset
Turnover and WC are positively correlated with EPS. However, leverage is
negatively correlated with EPS.
Total
sales, WC and assets turnover are positively related with ROE. However, within
the IVs, the maximum correlation is 0.71between ROE and Asset Turnover.
This study focuses on financial
indicators of profitability, i.e. firm size (total sales), WC, company
efficiency (assets turnover ratio), liquidity (current ratio) and leverage
(debt equity ratio). These are the IVs and profitability is the DV, measured by
ROE and EPS.
The first model examines the association
between the five IVs of the study and ROE.Firstly, Housemen test has been done
to select appropriate effect model for the regression of panel data. (Refer
table IV)
Correlated
Random Effects - Hausman Test |
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Equation:
RAND1 |
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Test
cross-section random effects |
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Test
Summary |
Chi-Sq. Statistic |
Chi-Sq. d.f. |
Prob. |
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Cross-section
random |
113.480419 |
5 |
0.0000 |
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Cross-section
random effects test comparisons: |
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Variable |
Fixed |
Random |
Var(Diff.) |
Prob. |
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WC |
0.000000 |
0.000000 |
0.000000 |
0.4554 |
LTS |
0.007518 |
0.056263 |
0.000243 |
0.0018 |
CRIO |
0.000382 |
0.000005 |
0.000001 |
0.5951 |
ASTRIO |
1.067240 |
1.125925 |
0.000104 |
0.0000 |
DTERIO |
-0.051101 |
-0.020147 |
0.000015 |
0.0000 |
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Cross-section
random effects test equation: |
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Dependent
Variable: ROE |
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Method:
Panel Least Squares |
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Date:
11/11/18 Time: 19:03 |
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Sample:
2015 2017 |
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Periods
included: 3 |
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Cross-sections
included: 83 |
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Total
panel (balanced) observations: 249 |
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Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
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|
C |
0.030751 |
0.222523 |
0.138194 |
0.8903 |
WC |
3.26E-12 |
3.22E-12 |
1.011997 |
0.3131 |
LTS |
0.007518 |
0.024446 |
0.307558 |
0.7588 |
CRIO |
0.000382 |
0.001552 |
0.246271 |
0.8058 |
ASTRIO |
1.067240 |
0.044024 |
24.24209 |
0.0000 |
DTERIO |
-0.051101 |
0.010238 |
-4.991355 |
0.0000 |
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Effects Specification |
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Cross-section
fixed (dummy variables) |
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|
R-squared |
0.987308 |
Mean dependent var |
0.164538 |
|
Adjusted
R-squared |
0.980450 |
S.D. dependent var |
0.414328 |
|
S.E.
of regression |
0.057932 |
Akaike info criterion |
-2.588319 |
|
Sum
squared resid |
0.540333 |
Schwarz criterion |
-1.345203 |
|
Log
likelihood |
410.2457 |
Hannan-Quinn criter. |
-2.087944 |
|
F-statistic |
143.9588 |
Durbin-Watson stat |
2.753511 |
|
Prob(F-statistic) |
0.000000 |
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Table
IV – Hausman Test (ROE)
With the result of the Housemen
test, it has been selected to use and fixed-effects model in Pooled ordinary
least squares regression by rejecting the null Hypotheses.
H0 : Fixed
Effect Model is appropriate
H1 : Random
Effect Model is appropriate
The
tested results are as follows (Refer Table V)
Dependent
Variable: ROE |
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Method:
Panel Least Squares |
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Date:
11/11/18 Time: 18:59 |
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Sample:
2015 2017 |
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||
Periods
included: 3 |
|
|
||
Cross-sections
included: 83 |
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|
||
Total
panel (balanced) observations: 249 |
|
|||
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|
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
|
|
|
|
|
|
|
|
|
C |
0.030751 |
0.222523 |
0.138194 |
0.8903 |
WC |
3.26E-12 |
3.22E-12 |
1.011997 |
0.3131 |
LTS |
0.007518 |
0.024446 |
0.307558 |
0.7588 |
CRIO |
0.000382 |
0.001552 |
0.246271 |
0.8058 |
ASTRIO |
1.067240 |
0.044024 |
24.24209 |
0.0000 |
DTERIO |
-0.051101 |
0.010238 |
-4.991355 |
0.0000 |
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Effects Specification |
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Cross-section
fixed (dummy variables) |
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|||
|
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|
|
|
|
|
|
|
R-squared |
0.987308 |
Mean dependent var |
0.164538 |
|
Adjusted
R-squared |
0.980450 |
S.D. dependent var |
0.414328 |
|
S.E.
of regression |
0.057932 |
Akaike info criterion |
-2.588319 |
|
Sum
squared resid |
0.540333 |
Schwarz criterion |
-1.345203 |
|
Log
likelihood |
410.2457 |
Hannan-Quinn criter. |
-2.087944 |
|
F-statistic |
143.9588 |
Durbin-Watson stat |
2.753511 |
|
Prob(F-statistic) |
0.000000 |
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Table
V – ROE Fixed Effect Model
In this model, the results show that
Asset Turnover has a significantly positive association with ROE (as
coefficient is 1.06 and significant at 5 percent). Assets turnover is one of
the factors affecting company profitability in Sri Lanka. The result motivates
companies to increase their efficiency (as assets turnover ratio measures the
efficiency) and properly manage their assets to increase their sales and
therefore profitability. This will generate more investment in these companies.
Another determinant of profitability is leverage. It shows a significantly
negative association with ROE However, other variables, i.e. liquidity (as
measured by current ratio) and WC, show a positive relationship with company
profitability (ROE) but not significant. The R2 is 0.987 and the
Adj-R2 is 0.97
The second model examined the
relationship between the same five IVs and EPS.
Firstly, Housemen test has been done
to select appropriate effect model for the regression of panel data. (Refer
table VI)
Correlated Random Effects - Hausman Test |
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Equation: Untitled |
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Test cross-section random effects |
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Test Summary |
Chi-Sq.
Statistic |
Chi-Sq.
d.f. |
Prob. |
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Cross-section random |
12.018219 |
5 |
0.0345 |
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Cross-section random effects test comparisons: |
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|
Variable |
Fixed |
Random |
Var(Diff.) |
Prob. |
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WC |
-0.000000 |
-0.000000 |
0.000000 |
0.2251 |
LTS |
-169.121882 |
-40.935191 |
31123.345882 |
0.4675 |
CRIO |
50.575656 |
17.502020 |
104.622169 |
0.0012 |
ASTRIO |
1470.647577 |
1611.561962 |
34207.135162 |
0.4461 |
DTERIO |
28.412701 |
-5.034796 |
3822.588561 |
0.5885 |
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Cross-section random effects test equation: |
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Dependent Variable: EPS |
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Method: Panel Least Squares |
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Date: 11/11/18
Time: 19:09 |
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Sample: 2015 2017 |
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Periods included: 3 |
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Cross-sections included: 83 |
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|
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Total panel (balanced) observations: 249 |
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Variable |
Coefficient |
Std.
Error |
t-Statistic |
Prob. |
|
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|
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|
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|
C |
1325.934 |
1734.893 |
0.764274 |
0.4458 |
WC |
-4.12E-08 |
2.51E-08 |
-1.636739 |
0.1036 |
LTS |
-169.1219 |
190.5887 |
-0.887366 |
0.3762 |
CRIO |
50.57566 |
12.10388 |
4.178467 |
0.0000 |
ASTRIO |
1470.648 |
343.2328 |
4.284694 |
0.0000 |
DTERIO |
28.41270 |
79.81994 |
0.355960 |
0.7223 |
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Effects Specification |
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Cross-section fixed (dummy variables) |
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|
R-squared |
0.732135 |
Mean
dependent var |
80.77679 |
|
Adjusted R-squared |
0.587387 |
S.D.
dependent var |
703.1424 |
|
S.E. of regression |
451.6630 |
Akaike
info criterion |
15.33453 |
|
Sum squared resid |
32843917 |
Schwarz
criterion |
16.57764 |
|
Log likelihood |
-1821.149 |
Hannan-Quinn
criter. |
15.83490 |
|
F-statistic |
5.058023 |
Durbin-Watson
stat |
2.253069 |
|
Prob(F-statistic) |
0.000000 |
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Table
VI - Hausman Test (EPS)
With
the result of the Housemen test, it has been selected to use and fixed-effects
model in Pooled ordinary least squares regression by rejecting the null
Hypotheses.
H0 : Fixed
Effect Model is appropriate
H1 : Random
Effect Model is appropriate
The
tested results are as follows (Refer Table VII)
Dependent
Variable: EPS |
|
|
||
Method:
Panel Least Squares |
|
|
||
Date:
11/11/18 Time: 19:06 |
|
|
||
Sample:
2015 2017 |
|
|
||
Periods
included: 3 |
|
|
||
Cross-sections
included: 83 |
|
|
||
Total
panel (balanced) observations: 249 |
|
|||
|
|
|
|
|
|
|
|
|
|
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
|
|
|
|
|
|
|
|
|
C |
1325.934 |
1734.893 |
0.764274 |
0.4458 |
WC |
-4.12E-08 |
2.51E-08 |
-1.636739 |
0.1036 |
LTS |
-169.1219 |
190.5887 |
-0.887366 |
0.3762 |
CRIO |
50.57566 |
12.10388 |
4.178467 |
0.0000 |
ASTRIO |
1470.648 |
343.2328 |
4.284694 |
0.0000 |
DTERIO |
28.41270 |
79.81994 |
0.355960 |
0.7223 |
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|
Effects Specification |
|
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Cross-section
fixed (dummy variables) |
|
|||
|
|
|
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|
|
|
|
|
|
R-squared |
0.732135 |
Mean dependent var |
80.77679 |
|
Adjusted
R-squared |
0.587387 |
S.D. dependent var |
703.1424 |
|
S.E.
of regression |
451.6630 |
Akaike info criterion |
15.33453 |
|
Sum
squared resid |
32843917 |
Schwarz criterion |
16.57764 |
|
Log
likelihood |
-1821.149 |
Hannan-Quinn criter. |
15.83490 |
|
F-statistic |
5.058023 |
Durbin-Watson stat |
2.253069 |
|
Prob(F-statistic) |
0.000000 |
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Table
VII – EPS Fixed Effect Model
In the second model, Asset Turnover
and Liquidity show significant positive relationships with profitability (as
measured by EPS). This result reveals that WC plays a significant role in
increasing the company’s profit The R2 is 0.73
and the Adj-R2 is 0.58.
.
5.
Conclusion, limitations and application
This
study aims to determine the factors of profitability in Sri Lankan-listed
companies. Five IVs, namely, firm size (as measured by total sales), WC,
company efficiency (assets turnover ratio), liquidity (current ratio) and
leverage (debt equity ratio), were empirically examined for their relationships
with profitability. Data of 83 companies listed on Colombo Stock Exchange
covering the period from 2015 to 2017, were extracted from companies’ annual reports and pooled OLS
regression was used to analyze the data. The results emphasize strong positive
relationships between Asset Turnover, Liquidity and Leverage and profitability.
This study, as with any other study, has a limitation. The
database is limited to 83 companies and it covers the period from 2015 to 2017,
which is considered as a short time period. However, the findings of this study
benefit both internal users (such as mangers, shareholders and employees) and
external (such as investors, creditors, newly established companies and the tax
authority) users. They can be aware of the factors affecting the profitability
of the companies after the depreciation of the Sri Lankan currency and
therefore concentrate more on the factors that can enhance their company’s profitability. The results may
help the external users to make the right decision. This study provides
empirical evidence that supports the resource-based theory and the trade-off
theory. This study also recommends that future studies include more factors or
conduct a comparative study that includes companies in different countries in
order to figure out whether the determinants of profitability are the same in
different business environments in different countries
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