liquidity-profitability tradeoff existence in turkey an empirical

Copernican Journal of Finance & Accounting
2016, volume 5, issue 2
e-ISSN 2300-3065
p-ISSN 2300-1240
Baser, F., Gokten, S., Kucukkocaoglu, G. & Ture, H. (2016). Liquidity-profitability tradeoff existence in Turkey: an empirical investigation under structural equation modeling. Copernican Journal of Finance & Accounting, 5(2), 27–44. http://dx.doi.org/10.12775/CJFA.2016.013
Furkan Baser*
Ankara University, Turkey
Soner Gokten**
Baskent University, Turkey
Guray Kucukkocaoglu***
Baskent University, Turkey
Hasan Ture****
Gazi University, Turkey
liquidity-profitability tradeoff existence in turkey:
an empirical investigation
under structural equation modeling
Keywords: liquidity-profitability tradeoff, structural equation modeling, working capital management.
J E L Classification: G30, M10.
Date of submission: January 24, 2017; date of acceptance: January 30, 2017.
Contact information: [email protected], Department of Insurance and
Actuarial Sciences, Ankara University, Ankara, Turkey.
**
Contact information: correspondent author, [email protected], Department of
Management, Baskent University, Baskent Universitesi, Baglica Kampusu Eskisehir Yolu
20. km, IIBF, Isletme Bolumu, 06810, Ankara, Turkey, phone: +9 (0312) 246 66 66 - (1113).
***
Contact information: [email protected], Department of Management,
Baskent University, Ankara, Turkey.
****
Contact information: [email protected], Department of Econometrics, Gazi
University, Ankara, Turkey.
*
28
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
Abstract: Firms in emerging markets could show a tendency to have high liquidity positions by ignoring the liquidity-profitability tradeoff in terms of working capital management due to gained experiences from stressed times. Accordingly, this study empirically examines the validity of liquidity-profitability tradeoff in Turkish market via
structural equation modeling. The functions of liquidity and profitability as latent variables of the model are constituted from Piotroski’s criterias of liquidity/solvency, operating efficiency and profitability. The hypothesized model for the inexistence of the
validity of liquidity-profitability tradeoff was verified and there is a moderate level of
positive effect between liquidity and profitability in Turkey. The findings indicate that
(1) current ratio or its variants as single-handed variables are inadequate to explain liquidity-profitability relation and (2) leverage seems to be the most important indicator
as taken into account on working capital management decisions. Turkish firms apply
prudent working capital management to overcome possible liquidity shocks.
Introduction
Liquidity and profitability tradeoff is a crucial issue discussed in the literature
under the management of current assets and current liabilities to obtain optimum profitability. Thus, efficient liquidity management involves planning and
controlling current assets and current liabilities to eliminate the risk of insolvency by not meeting the short-term obligations on time. Besides, liquidity is
one of the most important control variable that accounts for firm profitability
as well (Iatridis & Kadorinis, 2009).
Solely, in the frame of working capital approach, cash management is a nonnegligible concept which directly affects the profitability of a firm especially
in short term (Schneider, 1988; Johnson & Aggarwal, 1988; Unsworth, 2000;
Raspanti, 2000). In this regard, working capital management is considered as
a useful tool in managing of funds to meet current operations. However, instead
of using working capital as a measure of liquidity, accounting literature advocate the use of current and quick ratios to make temporal or cross sectional
comparisons. Nevertheless, the ultimate measure of the efficiency of liquidity
planning and control is the effect it has on profit (Eljelly, 2004).
According to Sanger (2001), working capital represents a safety cushion for
providers of short-term funds of the company, and as such they view the availability of excessive levels of working capital and cash in a positive way. However,
from an operating point of view, working capital has increasingly been looked
at as a restraint on financial performance, as these assets do not contribute to
profit. Argued vividly by Nicholas (1991), companies usually do not think about
improving liquidity management before reaching to a crisis conditions or becoming on the verge of bankruptcy. Thus, any increase in cash or cash-similar
liquidity- profitability tradeoff existence in turkey…
29
positions creates a tradeoff on profitability by lying behind passive funds to
generate profit. In this sense, liquidity ratios as a measure of company’s ability to pay debt obligations and its margin of safety play an important role on
evaluating the financial decisions of tradeoff between liquidity and profitability (Gitman, 1974; Richard & Laughlin, 1980; Hawawini et al., 1986; Kamath,
1989; Gentry et al., 1990; Boer, 1999; Eljelly, 2004).
Liquidity ratios mostly represent the summarized indirect results of financial decisions related with the financial structure. From this point of view, as the
market conditions restrict the capabilities of decision makers in terms of working capital management, they could not have the opportunity to determine the
level of current assets according to liquidity-profitability tradeoff mechanism.
The reality is that liquidity management focuses on profitability in good times
but in troubled times systematic risk put pressure on profitability and firms
need sufficient liquidity positions to survive (Summers & Wilson, 2000). In this
sense, liquidity-profitability tradeoff issues may long be ignored on the formation of financial structure. That means liquidity-profitability tradeoff concept
in financial management decisions could not be valid in some markets, especially for emerging ones, as prudent behaviors come from the past.
This study concentrates on testing the existence of the validity of liquidityprofitability tradeoff in Turkish market, which has many financial experiences
on troubled times under liquidity shocks. To get a clear picture, we first need to
go back to 1980s where Turkey has first started to adopt the rules of free market economy, free competition, and a liberalized foreign trade practices by applying neo-liberal policies to integrate into international markets. Throughout
the years Turkey has faced with several financial crises because of unsteady
economic and political environment forces and became dependent to IMF and
its policies with standby agreements.
Structural reforms applied as part of standby agreements showed positive effects on Turkish economy especially after 2002. Inflation and interest
rates have fallen significantly and the currency stabilization program has been
achieved. Growth rate in 2004 was realized as 9.9 percent and interestingly,
high growth rates were accompanied by a reduction in inflation rates which
were reduced to single-digit figures in 2004 after almost 30 years.
In addition, a global financial shock of 2007, as an external factor, affected
Turkey like all other countries. Right after the spread of US based financial crisis to all over the world, central banks started to install monetary policies to
cultivate recovery and funds started to move to the emerging markets to ob-
30
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
tain satisfactory returns based on an increase in global money supply. Turkish
market appeals foreign investment with nearly 70 billion USD capital inflows
per year between 2002 through 2013. By paying the last loan repayment in
the amount of 422.1 million $ (the total amount of payment was 23.5 billion $
during 2002–2013) in 2013, Turkey initialized its position against IMF. Also, in
year 2013, Turkey ranked as the sixth biggest economy in Europe and the sixteenth in the world. With regards to this historical background, we expect that
Turkish firms could show a tendency to have high liquidity positions by ignoring the liquidity-profitability tradeoff in terms of working capital management.
As they have become more prone to financial crises and learned from the past
experiences, this paper selected year 2014 to test this alleging remarks as this
year represent a boom phase in the Turkish economy.
As the acceptance of general rules or conclusions are challenging in financial
researches and they are based on a lot factors that are not directly observable
(Titman & Wessels, 1988; Harris & Raviv, 1991), expecting the invalidity of the
negative relationship between liquidity and profitability cannot come as a surprise when the conditions of emerging markets are compared with emerged
ones. Financial structure decision-making is even more complicated when it
is examined in developing countries where markets are characterized by controls and institutional constraints (Boateng, 2004). Therefore, most studies in
the literature analyzing the financial structure topic in developed markets depict many institutional similarities and could be accepted as efficient. Accordingly, relevant studies for emerging markets depict many institutional differences as well (Schulman et al., 1996; Wiwattanakantang, 1999; Chen, 2004).
Under these conditions, as an emerging market economy, it is not contrary to
expect positive relation between liquidity and profitability for Turkish firms.
From this point of view, this paper tests the validity of liquidity-profitability
tradeoff for firms in Turkish market by applying Structural Equation Modeling
(SEM). In this sense, the functions of liquidity and profitability are constituted
by using Piotroski (2000) criterions1 and then SEM is applied.
1
Current ratio (CR), gross margin (MARGIN), leverage (LEV) and asset turnover
(TURN) which are the criterions of liquidity/solvency and operating efficiency, are
used as the determinants of liquidity function. Return on assets (ROA), cash flow from
operations (CFO) and accruals (AC) which are the criterions of profitability, are used as
the determinants of profitability function.
Sample includes 187Istanbul).
active firms listed and
tradedthe
on National
Market of
Istanbul S
Exchange
Exchange (BIST-Borsa
(BIST-Borsa Istanbul). National
National Market
Market is
is the largest
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of BIST,
BIST, where
where
Exchange
(BIST-Borsa
Istanbul).
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where
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equities
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companies that
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liquidity
- profitability
tradeoff
existence
in turkey
…
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n
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nancial
service
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the
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bersare
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Research methodology
Functions
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with Determinants
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with
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with Determinants
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The
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Sample
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That
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Exchange
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equities
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average
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ments
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4 period
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quidity
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thethe
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quidity
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statements
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quidity
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this sense,
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as
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accepted
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of
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accepted as
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the frame
frame
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ca
management:
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more
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the
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management: As is known, increase in CR means more liquidity. On the other hand, C
C
management:
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is
known,
increase
in
CR
means
more
liquidity.
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the
other
hand,
CR
management:
As
is
known,
increase
in
CR
means
more
liquidity.
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the
other
hand,
C
the
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the summarized
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derive from
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the
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The
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andin
is
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firms
inprofitability
terms of
of liquidity.
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CR
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Theaffect
relationship
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profitability
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using
the
financial
structure
of
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in
terms
of
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this
reason,
CR
or
its
affect
the
financial
structure
ofsingle-handed
firmsand
in terms
of liquidity.
Forevaluate
this
reason,
or
its vv
ants
should
not
be
thought
determinants
the
of
ables.
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means
functions
of as
liquidity
profitability
refer to
latent
variables
ofCR
structura
ants
should
not
bemeans
thought
as
single-handed
determinants
to
evaluate
the level
level
of cur
cur
latent
variables.
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functions
of liquidity
and profitability
refer
latent
ants
should
not
be
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as
single-handed
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to
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the
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cur
ants
should
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to
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the
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of
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variables
structural
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respectively.
of these in detailcur
equation
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of these Determinants
functions are described
in
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assets.
functions
are
in detailthe
in this part
of the paper.
MARGIN
is
for
assets
level
thisassets.
part
of
thedescribed
paper.
MARGIN
is the
the one
one of
of the major
major determinants
determinants
for current
current
assets
level in
in the
the fram
fram
2
4
5
,2MARGIN3,for
LEV
and4 TURN
by:
Liquidity
is
defined
as
the
function
of
CR
MARGIN
is
the
one
of
the
major
determinants
current
assets
level
in
the
fram
3
5
MARGIN
is
the
one
of
the
major
determinants
for
current
assets
level
in
the
fram
accounting
practices:
Increase
in
MARGIN
causes
an
increase
in
cash
or
receivables
andinTURN
Liquidity
is practices:
defined as Increase
the function
of CR , MARGIN
accounting
in MARGIN
causes an, LEV
increase
cash orbyreceivables
accounting
practices:
Increase
in
MARGIN
causes
an
increase
in
cash
or
receivables
accounting=practices:
Increase
in of
MARGIN
causes
an increase inaffect
cash or receivables
counts.
means
high
MARGIN
should
(1)
Liquidity
�(CR
counts. Which
Which
means
high level
level
of� , TURN
MARGIN
should positively
positively affect the
the liquidity
liquidity
�
� , MARGIN
� , LEV
� ).(1)
counts.
Which
means
high
level
of
MARGIN
should
positively
affect
the
liquidity
counts. Which means high level of MARGIN should positively affect the liquidity o
firm.
Total
firm. amount of the current assets is the fundamental accounting measurement for li
Total
amount of the current assets is the fundamental accounting measurefirm.
firm.position of the financial structure. In this sense, Current Ratio (CR) is generally
quidity
ment for liquidity position of the financial structure. In this sense, Current Ra-
accepted
as the main indicator for liquidity assessment in the frame of working capita
2
2
CR
⁄ShortTermLiabilities
CR =
= CurrentAssets
CurrentAssets⁄
ShortTermLiabilities
2
⁄ShortTermLiabilities
management:
As is known,
increase in CR means more liquidity. On the other hand, CR is
2 CR = CurrentAssets
23
3 CR
⁄ShortTermLiabilities
MARGIN
= (TotalSales
− CostofSales)⁄TotalSales, we use ‘cost of goods sold’ for manufacturin
= CurrentAssets
MARGIN = (TotalSales − CostofSales)⁄TotalSales
.
, we use ‘cost of goods sold’ for manufacturin
3
⁄TotalSales
MARGIN =firms
(TotalSales
−
CostofSales)
, we
use ‘cost
of from
goods sold’
sold’for
for
manufacturin
3summarized
the3commercial
indicator
of
the financial
decisions
which
indicators
tha
and
of
services
service
MARGIN =
(TotalSales
TotalSales
, we
we use
use derive
‘costofofgoods
goodsother
sold’ for
manufacturin
commercial
firms
and ‘cost
‘cost −
ofCostofSales)
services sold’
sold’⁄for
for
service firms.
firms.
manufacturing
or commercial
andsold’
‘costfor
of services
sold’ for service firms.
commercial
firms
and ‘cost offirms
services
service firms.
4
⁄
LEV
LongTermLiabilities
Equities
firms and
‘cost of services
service
firms.
44commercial
affect
the=
financial
structure
of
firmssold’
in for
terms
of liquidity.
For this reason, CR or its vari
⁄
LEV
=
LongTermLiabilities
Equities
.
4
4 LEV = LongTermLiabilities⁄Equities
55
⁄
.
TotalSales
LEV
==
⁄TotalAssets
TURN
=LongTermLiabilities
TotalSales
TotalAssets
ants55 TURN
should
not
be thought
as⁄Equities
single-handed
determinants to evaluate the level of curren
5 TURN = TotalSales⁄TotalAssets
TURN = TotalSales⁄TotalAssets
assets.
MARGIN is the one of the major determinants for current assets level in the frame o
32
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
tio (CR) is generally accepted as the main indicator for liquidity assessment in
the frame of working capital management: As is known, increase in CR means
more liquidity. On the other hand, CR is the summarized indicator of the financial decisions which derive from other indicators that affect the financial structure of firms in terms of liquidity. For this reason, CR or its variants
should not be thought as single-handed determinants to evaluate the level of
current assets.
MARGIN is the one of the major determinants for current assets level in the
frame of accounting practices: Increase in MARGIN causes an increase in cash
or receivables accounts. Which means high level of MARGIN should positively
affect the liquidity of a firm.
In the literature, the relation between leverage (LEV) and size (Total Assets) is discussed frequently. International evidence suggests that leverage is
positively related to size (Rajan & Zingales, 1995; Schulman et al., 1996; Wiwattanakantang, 1999; Booth et al., 2001; Boateng, 2004; Padron et al., 2005;
Gaud et al., 2005; Sayılgan et.al., 2006). Several reasons are depicted on the
positive relation between leverage and size, such as cheaper access to outside
financing, high level of collateral and etc. (Strebulaev, 2007). In this sense,
firms listed and traded on National Market of Istanbul Stock Exchange have
more ability for long term debt financing due to their sizes. In general manner,
long term financing especially for current assets increases liquidity in short
term. Therefore, it is expected that there is a positive relation between LEV
and liquidity as well.
Turnover (TURN) is the indicator of firm sales generated relative to the value of its assets in terms of cash conversion cycles. Therefore, turnover connects
with the operating efficiency of a firm. Any decrease in operational efficiency
make firms depend on more current assets for sustainability. In order to make
a decision on adding TURN as an indicator into liquidity function, a correlation
analysis was executed and the correlation coefficient between CR and TURN
for the data set was found as -0.207 which is statistically significant at 1% (see
Table 1). Accordingly, this study states the expectation of negative relation between the TURN and liquidity.
cussed
cussed frequently.
frequently. International
International evidence
evidence suggests
suggests that
that leverage
leverage is
is positively
positively related
related to
to
current
assets
for sustainability.
In order to
make
a decision
on adding TURN
as an
indica
(Rajan
&
Zingales,
1995;
Schulman
et
al.,
1996;
Wiwattanakantang,
1999;
Booth
(Rajan & Zingales, 1995; Schulman et al., 1996; Wiwattanakantang, 1999; Booth et
et
tor 2001;
into liquidity
function,
a
correlation
analysis
was
executed
and
the
correlation
coeffi
2001; Boateng,
Boateng, 2004;
2004; Padron
Padron et
et al.,
al., 2005;
2005; Gaud
Gaud et
et al.,
al., 2005;
2005; Sayılgan
Sayılgan et.al.,
et.al., 2006).
2006). Sev
Sev
cient
between
CR
and
TURN
for
the
data
set
was
found
as
-0.207
which
is
statistically
reasons
liquidity-are
profitability
tradeoff
existence
inrelation
turkey… between leverage and size,
33 such
depicted
on
the
positive
as
chea
reasons are depicted on the positive relation between leverage and size, such as chea
significant
at outside
1% (seefinancing,
Table 1). Accordingly,
this
study states
the expectation of
negativ
access
high
ofMARGIN,
collateral
and
etc.
access to
to Table
outside
financing, matrix
high level
level
collateral
etc. (Strebulaev,
(Strebulaev, 2007).
2007). In
In
1. Correlation
for CR,of
LEV,and
TURN
relation
between
the
TURN
and
liquidity.
sense,
listed
on
of
Exchange
sense, firms
firms CR
listed and
and traded
traded
on National
National Market
Market
of Istanbul
Istanbul Stock
Stock
Exchange have
have m
m
MARGIN
LEV
TURN
ability
for
long
term
debt
financing
due
to
their
sizes.
In
general
manner,
long
term
fina
ability for long term debt financing due to their sizes. In general manner, long term fina
Sig.1. Correlation
Corr. Coef.
Sig.
Corr.
Coef.
Sig.
Corr.
Coef. TURN
Sig.
Corr. Coef.Table
matrix
forliquidity
CR, MARGIN,
LEV,
ing
for
in
term.
it
(r)
(p)
(r)
(p)
(p)
ing especially
especially
for(p)current
current (r)assets
assets increases
increases
liquidity
in short
short (r)
term. Therefore,
Therefore,
it is
is expe
expe
CR
MARGIN
LEV
TURN
relation
CR that
–
that there
there 1is
is aa positive
positive
relation between
between LEV
LEV and
and liquidity
liquidity as
as well.
well.
Corr. Co- Sig.
Corr. Co- Sig.
MARGIN
0.213**
1
Turnover
(TURN)
is1
0.213**
ef. (r) 0.003
(p)
Corr.
Sig.
Corr.
Sig.
generated
relative
value
ef. indicator
(r)–
(p)of
Coef. (r)
(p)
Coef.to
Turnover (TURN) is the
the
indicator
of firm
firm sales
sales
generated
relative
to(r)the
the(p)
value oo
1
CRassets –0.080
cash
cycles.
LEV
0.278
0.187*
0.010
– turnover
assets in
in terms
terms of
of
cash conversion
conversion
cycles. 1Therefore,
Therefore,
turnover connects
connects with
with the
the opera
opera
MARGIN
0.003
efficiency
of
Any
decrease
TURN
–0.207**
0.005 0.278
–0.230**
0.002in
-0.080
0.187*
LEV
efficiency
of aa firm.
firm.
Any
decrease
in
-
operational
efficiency
depend
–0.033
0.010
10.654
- 1 make
–
operational
efficiency
make firms
firms
depend on
on m
m
-0.207** 0.005
-0.230** 0.002
-0.033
0.654
1
TURN
current
assets
for
sustainability.
In
order
to
make
a
decision
on
adding
TURN
as
an
ind
Correlation
is
at at
thethe
0.050.05
level
(2-tailed).
current assets
for sustainability.
In
order
to make a decision on adding TURN as an ind
* *Correlation
issignificant
significant
level
(2-tailed).
tor
into
function,
aa 0.01
correlation
analysis
Correlation
is
at at
thethe
0.01
levellevel
(2-tailed).
****Correlation
is significant
significant
(2-tailed).
tor
into liquidity
liquidity
function,
correlation
analysis was
was executed
executed and
and the
the correlation
correlation coe
coe
byCR
authors.
TURN
S Source:
o ucient
r c edeveloped
:between
developed
authors.
cient
between
CRbyand
and
TURN for
for the
the data
data set
set was
was found
found as
as -0.207
-0.207 which
which is
is statistic
statistic
significant
significant at
at 1%
1% (see
(see Table
Table 1).
1). Accordingly,
Accordingly, this
this study
study states
states the
the expectation
expectation of
of nega
nega
Profitability
as
realized
measurement
of
Profitability
as the
the
realized and
measurement
ofgained
gainedbenefit
benefitfrom
fromallallbusibusiness perfor
relation between
the
liquidity.
6
7
between
the TURN
TURN
andfunction
liquidity.
,
CFO
and
AC
by:
nessrelation
performance
is defined
as the
of
ROA
6
7
mance is defined as the function of ROA , CFO and AC by
.(2)
��ROA�Correlation
, CFO� , AC� �matrix
Profitability� =Table
.
(2)
Table 1.
1. Correlation
matrix for
for CR,
CR, MARGIN,
MARGIN, LEV,
LEV, TURN
TURN
CR
MARGIN
LEV
TURN
CR(ROE) and returnMARGIN
LEV
Return on equity
on assets (ROA) are
the most usual in-TURN
⁄
ROA = NetIncome
TotalAssets
Corr. Co- the
Sig.
Corr. CoSig.firm in Corr.
Sig. While
Corr.
dicators used to measure
of the
general terms.
Corr. Co- Sig.profitability
Corr. CoSig.
Corr.
Sig.
Corr.
7
ef. (r) � − ROA
(p)
ef. (r)
(p)
Coef. (r) (p)
Coef. (r)
�CFO
⁄
AC
=
TotalAssets
(p)
ef.
(r)
(p)profit from
Coef.the
(r) invested
(p)
Coef. (r)
ROE is a measureef.
of(r)
firm’s efficiency
to generate
capi1
CR
1
CR
tal, ROA
is generally
used to
compare1 companies
0.213**
0.003
- by taking the all kinds of inMARGIN
0.213**
0.003
1
MARGIN
vestments
into
account.
In
this
sense,
because
of the availability
of-- significant
-0.080
0.278
0.187*
0.010
1
LEV
-0.080
0.278
0.187*
0.010
1
LEV
-0.207**
0.005
-0.230**
0.002
-0.033
1
TURN
differences
the equity
of sample0.002
firms and-0.033
the main0.654
concentra-0.207**
0.005values-0.230**
0.654
1
TURN between
* Correlation is significant at the 0.05 level (2-tailed).
* Correlation
at the 0.05
level (2-tailed).
tion of
this paperisissignificant
on the validity
of liquidity-profitability
tradeoff, ROA is pre** as
Correlation
is significant
at the 0.01 level
(2-tailed).
ferred
determinant
of profitability
function.
Also, total investing amount of
** Correlation
is significant
at the 0.01 level
(2-tailed).
Source:
developed
byofauthors.
assets
is
the
identifier
the
total
capacity
of
firm
and the amount of assets repSource: developed by authors.
6
Sig.
Sig.
(p)
(p)
-
resents the firm size. In the literature, there is a generalization on the existence
of positive
relation between
size and
profitabilityof
that
derives
from from
different
Profitability
as
the
realized
measurement
gained
benefit
all business
per
Profitability
as
the
realized
measurement
of
gained
benefit
from
ways; such as abilities of firms to generate discounts
from suppliers,
gettingall
fa- business per
6
7
mance
is
as
function
of
AC
vorable
credit
terms and
conditions,
their and
receivables
mance
is defined
defined
as the
the
function success
of ROA
ROA6in,, CFO
CFO
and
AC7 by
by collection and
�
etc. (Eljelly,
2004). Therefore,
is� ,the
indicator to clarify the
Profitability
��ROAROA
AC�summarized
..
(2)
� =
� , CFO
Profitability
(2)
� = ��ROA � , CFO� , AC� �
profitability of a firm relative to its size.
6
66
ROA = NetIncome⁄TotalAssets
ROA = NetIncome⁄TotalAssets .
= �CFO⁄TotalAssets� − ROA
AC
AC = �CFO⁄TotalAssets� − ROA .
77
7
34
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
On the other side, ROA is calculated by accounting numbers based on accruals. Therefore, taking only ROA as an indicator to evaluate the profitability
of a firm is inadequate. In terms of complete disclosure, cash flow from operations (CFO) should be taken into account (Baumol, 1952; Miller and Orr, 1966).
Therefore, CFO is added into analysis as another determinant of profitability
function and it is expected that increase in CFO means increase in profitability.
Non-debt tax shield includes methods generally derived from accounting
techniques to create tax-shield advantages like debt financing. Another alternative advantage comes from the depreciation as a means of reducing corporate taxes (Rubio & Sogorb-Mira, 2012). Thus, in terms of cash generation, tax
deductions under depreciation expenses are the substitutes of tax benefits
from debt financing (DeAngelo & Masulis, 1980). In this case, it could be clearly
expected that firms with high level of fixed assets gain more benefit from nondebt tax shield advantages derives from depreciation (Titman & Wessels, 1988;
Rajan & Zingales, 1995; MacKay & Phillips, 2005; Faulkender & Petersen, 2006;
Wald & Long, 2007; Kale & Shahrur, 2007) and the spread between CFO and net
income should be higher for the firms that have bigger amount of tangible assets. Validity of this expectation causes smaller accounting assessment of profitability in terms of ROA due to high level of total assets for such firms (Table
2). The correlation coefficient between accruals (AC) and ROA for the Turkish
firms is –0.416 and statistically significant at 1% which supports our expectation about non-debt tax shield effect on profitability measurement derives by
ROA calculations. Accordingly, this study states the expectation of negative relation between the AC and profitability.
Table 2. Correlation matrix for ROA, CFO, AC
ROA
CFO
Sig.
(p)
Corr. Coef. (r)
Corr. Coef. (r)
ROA
1
CFO
0.096
0.192
1
AC
–0.416*
0.000
0.050
Sig.
(p)
AC
Corr. Coef. (r)
Sig.
(p)
1
–
–
* Correlation is significant at the 0.01 level (2-tailed).
S o u r c e : developed by authors.
–
0.495
35
liquidity- profitability tradeoff existence in turkey…
Structural Equation Modelling
Structural equation modeling (SEM) is used to model causal relationship between latent variables and to disclose linear relationships between independent and dependent variables. (MacCallum & Austin, 2000; Schumacker & Lomax, 2004; Garcia et al., 2013). SEM refers not to a single statistical technique
but to a family of related procedures such as causal modeling and covariance
structure analysis. (Kline, 2011). In social sciences, these causal models draw
attention because of their ability to describe structural theory bearing on some
phenomenon (Koç et al., 2016).
The specification of the structural model can be presented with graphical presentation, system of simultaneous equations or matrix expression. By
graphical representation, causal relationship between observed variables and
latent variables is introduced visually. Based on the theoretical model developed in Figure 1, we formulated the research hypothesis as follow:
H1: The liquidity of firm has a direct positive effect on profitability (Means, invalidity of liquidity-profitability tradeoff in Turkish market).
Figure 1. Model development
ߜଵ
ߜଶ
ߜଷ
ߜସ
CR
MARGIN
LEV
TURN
ߣଵ௑
ߣଶ௑
ߣଷ௑
ߣସ௑
Liquidity
ߦଵ
S o u r c e : developed by authors.
ߛଵ
Profitability
ߟଵ
ߣଵ௒
ߣ௒ଶ
ߣ௒ଷ
ROA
ߝଵ
CFO
ߝଶ
AC
ߝଷ
Assessing model’s fit in SEM is the most controversial subject. The overall fit
of the observed data to hypothesized model must be assessed before interpreting individual parameters (Jöreskog et al., 1999). Fit indices are used to control
whether the covariance matrix derived from the proposed theoretical model
is different from the covariance matrix derived from the sample (Shook et al.,
2004). A statistically insignificant difference reveals that the errors are insig-
observedobserved
data to hypothesized
model
must
be must
assessed
before interpreting
individual
pa
rameters
(Jöreskog
et al.,
Fit indices
are
used
to
the
covariance
ma
data
to 1999).
hypothesized
model
be control
assessed
before
interpreting
indiv
Assessing
model’s
fit
in SEM
is
observed
data to hypothesized
model
must
be most
assessed
before whether
interpreting
individual
paAssessing
model’s
fit
in
SEM
is
the
controversial
subject.
The
overall
fit
Assessing
model’s
fit
in
SEM
is
the
most
controversial
subject.
The
overall
fit
of
the
rameters
(Jöreskog
et
al.,
1999).
Fit
indices
are
used
to
control
whether
the
covariance
ma
rameters
et al.,Fit
1999).
Fitare
indices
are
used towhether
control
whether
the covari
trix derived
from (Jöreskog
the
proposed
theoretical
model
isto
different
from
thehypothesized
covariance
matrix
observed
data
to
mode
rameters
(Jöreskog
etto
al.,
1999).
indices
used
control
the
covariance
maobserved
data
hypothesized
model
must
be
assessed
before
interpreting
individu
observed
data
totrix
hypothesized
model
must
be
assessed
before
interpreting
individual
patrix
derived
from
the
proposed
theoretical
model
is
different
from
the
covariance
matrix
derived
the proposed
theoretical
isinsignificant
different
from
covarian
derived
fromfrom
the sample
(Shook
et al., 2004).
A statistically
difference
reveal
rameters
(Jöreskog
et
al.,the1999).
Fit i
trix
derived
the from
proposed
theoretical
model
is model
different
from
the
covariance
matrix
rameters
(Jöreskog
et
al.,
1999).
Fit
indices
are
used
to
control
whether
the
covarian
36
Furkan
Baser,
Soner
Gokten,
Guray
Kucukkocaoglu,
Hasan
Ture
rameters
(Jöreskog
et
al.,
1999).
Fit
indices
are
used
to
control
whether
the
covariance
maderived
from
the
sample
(Shook
et
al.,
2004).
A
statistically
insignificant
difference
reveal
that
the
errors
are
insignificant
and
the
model
is
supported.
Various
fit
indices
have
derived
the(Shook
sampleet(Shook
et al.,
A statistically
insignificant
differenc
trix
derived
from
the proposed
theo
derivedtrix
from
the from
sample
al., 2004).
A 2004).
statistically
insignificant
reveals
derived
from
the
proposed
theoretical
model
is different
fromdifference
thematrix
covariance
trix derived
from
the
proposed
theoretical
model
is
different
from
the
covariance
that
the
errors
are
insignificant
and
the
model
is
supported.
Various
fit
indices
hav
that
theare
errors
are
and
theiscompeting
model
supported.
Various
fit have
indi
emerged
to compare
the
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proposed
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or Various
baseline
models.
nificant
and
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model
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supported.
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et
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that
the
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and
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indices
derived
from
the
sample
(Shook
et
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2004).
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statistically
insignificant
difference
derivedpare
fromthe
thefit
sample
(Shook
et
al.,
2004).
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statistically
insignificant
difference
reveals
emerged
to
compare
the
fit
of
proposed
model
with
competing
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of
proposed
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In thisemerged
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In
this
study,
a
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that thebility
errors
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and
the
model
is
supported.
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In this
study,
a
model
containing
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latent
variables
which
were
liquidity
and
profita
was
considered.
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the
profitability
of
firms
is
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In this
study, containing
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which
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liquidity
an
emerged
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compare
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this
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liquidity
and
andInprofitability
considered.
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ଵ ଵߞଵisis
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ߞଵଵ ൌ variable
(3) relating endogenou
ߟଵ ൌdictor)
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variables
to
exogenous
variables,
and
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an
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term.
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(liquidity
of
firm),
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ଵ regression
where
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va
ଵ
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oflatent
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where
is
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(profitability
of
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is
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exogenou
ଵ
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where ߟ
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variable
(profitability
of
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(prerelating
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and
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variables,
and
ߞ
is
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th
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of
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and
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it quantifies
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and
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ଵ because
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and
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to
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and
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bility
and
liquidity
of
firms.
ଵ
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observed
variables
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linked
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latent
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bility
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liquidity
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by in
way
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equation
is ߛଵ because it qu
bility
liquidity
of firms.
model
in
equation
is
ߛ
because
it latent
quantifies
therelationship
hypothetical
relationship
between
p
ଵ
because
it
quantifies
the
hypothetical
between
profitamodel ment
in equation
is
ߛ
equations
for
the
exogenous
and
endogenous
variables.
Equations
of
The
observed
variables
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linked
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variables
by
way
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measurement
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wayvariable
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Equations
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endogenous
are
defined
and liquidity
of
firms.
variables
are
linked
to
latent
variables
by
way
of
equations
dogenous
variable
are defined
as:
and
liquidity
of firms.
bility and
forliquidity
thebility
exogenous
and endogenous
variables.variables.
Equations
of endogenous
variable variable
are defined
for of
thefirms.
exogenous
and endogenous
Equations
of endogenous
ar
as:
observed
variablesare
aredefined
linked
for
the exogenous
and
endogenous
variables.
Equations
ofThe
endogenous
variable
The
observed
variables
are
linked
to
latent
variables
by
way
of
measurement
equ
The observed
variables
are
linked
to
latent
variables
by
way
of
measurement
equations
as:
as:ߣଵ௒௒ ߟଵ ൅ ߝଵ (4)
ൌ
(4)endogenous v
for the exogenous and
as: for
the
andvariables.
endogenous
variables.
Equations ofvariable
endogenous
variable are d
௒exogenous
for the exogenous
and
endogenous
Equations
of
endogenous
are
௒
ߟ
൅
ߝ
(4)defined
ൌ
ߣ
௒
௒ଵߟ ଵ ൅ൌߝߣ
ଵ (5)
ߟ
൅
ߝ
(4)
ൌ
ߣ
(5)
௒
ଵ
ଵ
ଵ
ଵ
ଶ
ଶ
as:
ଵ
ଶ
ଶ
as:ൌ ߣଵ ߟଵ ൅ ߝଵ
(4)
௒
as:
௒
ൌൌߣ௒ߣ௒
(5)
ଶ ߟଵ൅൅
ߟଵ ൅ ߝଶ
(5)
ߝߝଷଷ௒ߝߣଶଶ(6)
(6)
ൌ ߣଵ௒ ߟଵ ൅ ߝ(5)
൅ൌ
ൌ
ߣଷଷଶߟߟଵଵଵൌ
ଵ
ଶ
௒
(4)
ߣଵ ߟଵ ൅ ߝଵ
௒ߝ
ൌ ߣଵ ߟൌ
൅
(4)
(6)
ଵ ߣଷ ߟ
ଵଵ ൅ ߝଷ௒
(6)
ൌߝexogenous
ߣଷ ߟଵ ൅ ߝଷ variable are defined as:
௒ and
equations
of
ൌ ߣ௒ଶ ߟଵ ൅ ߝ(6)
ଶ
ൌ ߣ
൅
ଷ௒ ߟ ൅ ߝ variable are defined as:
ଷ ߟଵ of
௒
ൌ
ߣ
(5)
and
equations
exogenous
ଶ variable are defined as:
ଶ ଵ
and
ൌ ߣଶequations
ߟଵ ൅ ߝଶ of exogenous
(5)
and equations
of exogenous
variable
areas:
defined
as: ൌ ߣ௒ ߟ ൅ ߝ
and௒equations
ofߣ௒exogenous
variable are
defined
ଷ
ଷ ଵ
ߟ
൅
ߝ
(6)
ൌ
ଷ
ଷ ଵ
(6)
ൌ ߣଷ ߟଵ ൅ ߝଷ
and equations of exogenous variable
and
equations(7)
of exogenous variable are defined as:
௑
௑
and equations
ofߣexogenous
ൌ
(7)
ଵ ൅ ߜଵ
ଵ variable are defined as:
ଵ ߦଵ
ଵ
ൌ
ൌ ߣߣଵ௑ଵ௑ߦߦଵଵ ൅
൅ߜߜଵଵ
(7)
(7)
௑
ൌ ߣ௑ଶ௑௑ߦଵ ൅ ߜଶ (8)
(8)
ൌ
ൌ ߣߣଶଶߦߦଵଵ ൅
൅ߜߜଶଶ
(8)
(8)
௑
ൌ ߣ௑ଷ௑௑ߦଵ ൅ ߜଷ (9)
(9)
ൌ
ൌ ߣߣଷଷߦߦଵଵ ൅
൅ߜߜଷଷ
(9)
(9)
ൌ ߣ௑ସସ௑௑ߦଵଵ ൅ ߜସସ (10) (10)
ൌ
ൌ ߣߣସସߦߦଵଵ ൅
൅ߜߜସସ
(10)
(10)
where ߣ௒௒௜௜௒, ߣ௝௝௑௑௑ are factor loadings, and ߝ௜௜ , ߜ௝௝ are error terms.
where
are
factorloadings,
loadings, and
and
are
errorterms.
terms.
where
where ߣߣ௜௜,, ߣߣ௝௝ are
are factor
factor
loadings,
and ߝߝ௜௜,, ߜߜ௝௝ are
are error
error
terms.
The data was analyzed and interpreted within the scope of the research in line with the
The
The data
data was
was analyzed
analyzed and
and interpreted
interpreted within
within the
the scope
scope of
of the
the research
research in
in line
line with
with the
the
specified purposes by utilizing descriptive statistics and several statistical analyses. SEM
specified
specified purposes
purposes by
by utilizing
utilizing descriptive
descriptive statistics
statistics and
and several
several statistical
statistical analyses.
analyses. SEM
SEM
and other statistical analyses were performed using IBM AMOS (Analysis of Momen
and
and other
other statistical
statistical analyses
analyses were
were performed
performed using
using IBM
IBM AMOS
AMOS (Analysis
(Analysis of
of Moment
Momen
Structures) and IBM SPSS (The Statistical Package for Social Sciences). Statistical signifiStructures)
Structures) and
and IBM
IBM SPSS
SPSS (The
(The Statistical
Statistical Package
Package for
for Social
Social Sciences).
Sciences). Statistical
Statistical signifisignifi
cance value is set as p < 0.05.
37
liquidity- profitability tradeoff existence in turkey…
The data was analyzed and interpreted within the scope of the research in
line with the specified purposes by utilizing descriptive statistics and several statistical analyses. SEM and other statistical analyses were performed using IBM AMOS (Analysis of Moment Structures) and IBM SPSS (The Statistical
Package for Social Sciences). Statistical significance value is set as p < 0.05.
Empirical results
In order to test the validity of liquidity-profitability tradeoff in Turkish market,
a structural equation model was employed, in which an exogenous latent factor (liquidity) and an endogenous latent factor (profitability) were considered.
The scale for each factor was set by fixing the factor loading to one of its indicator variables and the maximum likelihood method was used to estimate the parameters of the model. The model that satisfies both goodness of fit measures
and theoretical expectations was selected.
The key fit statistics of the structural model summarized in Table 3 shows
a value of χ2 / df = 3.269, CFI of 0.760, GFI of 0.943, AGFI of 0.907, NFI of 0.705,
and RMSEA of 0.079. The statistic of χ2 / df is within the acceptable limit (Schumacker & Lomax, 2004). GFI and AGFI are all above 0.90, suggesting a good
fit between the structural model and the data (Jöreskog et al., 1999; Byrne,
2010). RMSEA is below the suggested threshold value of 0.08 (Brwone & Cudeck, 1993). Therefore, the hypothesized model for the inexistence of the validity of liquidity-profitability tradeoff was verified by SEM, so consistence of the
model to the data was acceptable.
Table 3. Goodness of fit indices
Fit Indices
Model Value
Recommended Value
χ2 / df
3.269
1 to 5
The Comparative Fit Index (CFI)
0.760
0 (no fit) – 1 (perfect fit)
Goodness of Fit Index (GFI)
0.943
0 (no fit) – 1 (perfect fit)
Adjusted Goodness of Fit Index (AGFI)
0.907
0 (no fit) – 1 (perfect fit)
The Normed Fit Index (NFI)
0.705
0 (no fit) – 1 (perfect fit)
Root Mean Sq. Error of Approx. (RMSEA)
0.073
<0.05 (very good) – 0.1 (threshold)
S o u r c e : developed by authors.
38
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
CR
ߜଵ
ߣ௑
௒
ROA
ߝଵ
ߣଵ
Figure 2 presentsଵdetails regarding the parameter estimates
for the modߣଶ௑
MARGIN coefficient estimatesߛfor the hypothesized
el.ߜଶStandardized
௒ model with correߣଶ
ଵ
Profitability
Liquidity
ߝଶ
CFO
ߣଷ௑ presented in Table 4. According to the statistical
sponding t-value are
signifiߟଵ
ߦଵ
௒
ߣଷ
ߜଷ
LEVparameter
cance
of the
estimates from SEM, the hypothesis
which expresses
ߣସ௑
ߝଷ
AC supported.
a positive relationship between liquidity and profitability was
TURN
ߜସ
From standardized coefficient estimate, it is concluded that liquidity-profitability tradeoff is not valid in Turkish market.
Figure 2. Structural model with standardized path coefficients
ߜଵ
ߜଶ
ߜଷ
ߜସ
CR
0.19
0.97
0.24
MARGIN
0.95
LEV
Liquidity
0.44
Profitability
0.08
ROA
ߝଵ
CFO
ߝଶ
AC
ߝଷ
-0.40
-0.24
TURN
S o u r c e : developed by authors.
Table 4. Standardized coefficient estimates of SEM
Path
Standardized Coefficient
Estimate
t – Value
p
0.435
2.350
0.019
–0.237
–1.969
0.049
MARGIN ← Liquidity
0.235
1.963
0.050
CR ← Liquidity
0.190
LEV ← Liquidity
0.951
ROA ← Profitability
0.973
CFO ← Profitability
0.085
1.117
0.264
AC ← Profitability
–0.399
–2.555
0.011
Profitability ← Liquidity
TURN ← Liquidity
S o u r c e : developed by authors.
–
1.937
–
–
0.053
–
liquidity- profitability tradeoff existence in turkey…
Discussion: a detailed look on determinants
39
Inexistence of the validity of liquidity-profitability tradeoff in Turkish market
is not surprising when the results of the determinants used in functions are analyzed. In other words, a clear understanding of this invalidity needs a detailed
look on some determinants as well.
Firstly, all results are consistent with our expectation in terms of the directions of the effects under the comments that mentioned in Section 2.2. CR,
MARGIN and LEV have positive effect on liquidity, while TURN is the only determinant that has negative effect. On the other side, profitability is affected
positively by ROA and CFO, while AC has negative affect on profitability. However, the results create need for making a discussion to explain this invalidity of liquidity-profitability tradeoff in Turkish market. In this sense, remarkable information can be obtained when concentrated on the findings of liquidity
function.
There are meaningful differences between the effect sizes of determinants.
While CR, MARGIN and TURN has relatively low effect size (standardized coefficients for CR, MARGIN and TURN are 0.19, 0.24, –0.24, respectively), LEV
has significantly high effect size (standardized coefficient for LEV is 0.95) on
liquidity. This differentiation of LEV enables us to reveal two main inferences:
(1) The inadequacy of CR or its variants to analyze the liquidity-profitability
tradeoff and (2) the reality of applying prudent working capital management
(P-WCM) by managers in Turkish market as an emerging one.
In the literature, generally, the researches on liquidity-profitability tradeoff
are constructed on separate relationships between CR or its variants and profitability (Eljelly, 2004). In this paper, a more comprehensive analysis is applied
by employing SEM to disclose the effects of all determinants on liquidity all together. As seen from our findings, CR has not much explanatory power on the
liquidity in the frame of financial structure formation. The fundamental reason
of that is CR or its variants are the indirect summarized results of other direct
financial decisions that taken by managers strategically. The word of strategically means that the preferences of managers in financing of current assets.
High level positive effect of LEV on liquidity indicates that managers of
Turkish firms prefer long term liabilities rather than current ones to finance
current assets. In the other words, they apply P-WCM to overcome possible
liquidity shocks (Uremandu, 2012; Modi, 2012; Akoto et al., 2013; Zakaria &
Amin, 2013). This fact is coherent with our point of view, which asserts that
40
Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture
managers behave prudent in financial decisions in Turkey because of their bad
experiences come from troubled times.
On the profitability side the result indicates a moderate level of positive
effect between liquidity and profitability which is the other discussion issue
that needs to be explained in addition to the invalidity of liquidity-profitability tradeoff. Firstly, the significant effect of ROA on profitability, (standardized
coefficient for ROA is 0.97), verifies our choice on using it as a determinant instead of ROE. Since ROA includes the all short and long term financing alternatives especially for current assets, it completely reflects the outcome of applying P-WCM in terms of profitability. As discussed in Kling et al. (2014), cash
holdings increase the ability of firms to cover possible operating loses emerged
especially by liquidity shocks and to reach current liabilities in better conditions as an alternative of financing current assets, for example suppliers are
more willing to provide trade credit to firms with higher liquidity positions.
Also, as discussed in Jung and Kim (2008) study, stockpiling of liquid assets
provides incentives for firms to increase their leverage because cash holdings
decrease potential financial distress costs and increase target debt-equity ratios. In this sense, firms in Turkey decrease financial risks on cash conversion
cycles by applying P-WCM and increase operating efficiency by gaining ability
and flexibility on managing current liabilities.
Conclusion
In this paper, the existence of the validity of liquidity-profitability tradeoff is
analyzed for Turkish market which has many financial experiences on troubled
times that caused liquidity shocks. Our main expectation is that Turkish firms
could show a tendency to have high liquidity position by ignoring the liquidityprofitability tradeoff in terms of working capital management due to gained experiences come from bad times. 2014 is the best fitted year to test this alleging
remark as this year represents the best economic conditions that Turkey has
faced. The data of 187 firms listed and traded on National Market of Istanbul
Stock Exchange (BIST-Borsa Istanbul) are used.
Structural equation modelling is applied to provide a more comprehensive
analysis and the functions of liquidity and profitability are constituted by using Piotroski’s criterions of liquidity/solvency, operating efficiency and profitability to generate structural equation model of the study. The results of the hypothesized model indicate that the existence of liquidity-profitability tradeoff
liquidity- profitability tradeoff existence in turkey…
41
is invalid in Turkey and additionally there is a moderate level of positive effect
between liquidity and profitability.
High level positive effect of leverage on liquidity indicates that managers of
Turkish firms apply prudent working capital management to cover possible operating loses emerged especially by liquidity shocks and this behavior makes
firm more capable in terms of increasing operating efficiency and managing
current liabilities in Turkey. In conclusion, leverage seems the most important
indicator that taken into account on working capital management decisions in
Turkey in the frame of liquidity and profitability relation.
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