1st
Business and Economic Research
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Determinants of Firm’s Financial Performance: An
Empirical Study on Textile Sector of Pakistan
Ali Abbas (Corresponding Author)
Hailey College of Commerce, University of the Punjab Lahore, Pakistan
Tel:-
E-mail:-
Zahid Bashir
Faculty of Finance at School of Business, Economics & Management Sciences
Imperial College of Business Studies Lahore, Pakistan
Tel:-
E-mail:-
Shahid Manzoor
Hailey College of Commerce, University of the Punjab Lahore, Pakistan
Tel:-
E-mail:-
Muhammad Nadeem Akram
Mezan Bank, Quaid-e-Azam Industrial Estate Branch Lahore, Pakistan
Tel:-
Received: July 5, 2013
doi:10.5296/ber.v3i2.3958
E-mail:-
Accepted: July 18, 2013
URL: http://dx.doi.org/10.5296/ber.v3i2.3958
Abstract
The current study aims to find out the determinants significantly affecting the firm’s financial
performance in textile sector of Pakistan for the period-. The researcher used
panel/longitudinal data set which are created with the help of State Bank of Pakistan’s annual
publication named as “Financial statement analysis of companies (non-financial) listed in KSE
for the period 2005 to 2010 which is available at www.sbp.org.pk online. The researcher used
one-way fixed effect model due the presence of cross-sectional fixed effect in the regression
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results. The dependent variable was profitability as a measure of firm’s financial performance
while the independent variables were leverage, growth, firm’s size, risk, tax, tangibility,
liquidity and non-debt tax shield. The firm’s performance in textile sector is significantly
affected by Short term leverage, Size, risk, tax and non-debt tax shield while taking long term
leverage as first independent variable, the leverage becomes insignificant along with tax factor.
The textile sector should consider the above said factors because these factors significantly
increasing or decreasing firm’s financial performance. The findings of the current research are
limited and applicable to non-financial sector of Pakistan only. It is not applicable to financial
sector due to their difference of capital structure. In addition, the researcher used ROI as
measure of firm’s financial performance while the future research can have ROA, ROE, EPS
etc as firm’s financial performance.
Keywords: Firm’s performance, Textile sector, Return on Investment
1. Introduction
There are a total number of 411 firms in non-financial sector of Pakistan which is subdivided
into 12 sectors while Textile sector is the largest and the first sector which comprise of a total
number of 164 firms which covers 40% of the overall non-financial sector of Pakistan. The
researcher used the financial data of 139 firms of textile sector because the remaining firms
missed some of the financial records required for analysis. The textile sector represent a large
part of the non-financial sector of Pakistan, the financial performance of this sector may
influence the performance of the other sectors. The basic and fundamental duty of every
financial manager is to maximize the shareholder’s wealth and to increase firm’s value which is
possible when the firm’s financial performance can be increased. The researcher’s aim during
this research is to identify the number of factor that determines the firm’s financial
performance. The previous studies conducted on firm’s performance indicates that a large
number of factors affect significantly the firm’s performance. David Durand (1952) presented
different theories for starting the argument on firm’s value. David Durand (1952) presented
first theory with the name of Net Income (NI) approach, then after wards he presented Net
Operating income approach and finally traditional approach to justify his opinion. He was of
the view that increasing leverage can increase firm’s performance but he could not provide the
operational justification to validate his point of view. Modigliani and Miller (1958) in their
theses revealed it is not mandatory that a firm using leverage or not can have difference in their
value. For the validity of their research they presented an operational justification with the
name of arbitrage process. The arbitrage process states that investor purchases shares or make
investment at low prices and sales their investment or shares at high prices simultaneously in
different markets. Modigliani and Miller (1963) also found that debt provide the tax shield
advantage in the form of interest. A lot of studies afterwards reveal that corporate financial
performance or firm’s performance influenced by a number of factors that should keep in mind
while making financial decision to increase a firm’s performance. The researcher used the
framework of Zeitun and Tian (1997). They used leverage, growth, size, tax, risk and
tangibility to see their effect on corporate performance of Jordan non-financial sector. The
researcher extended the regression model by including liquidity and non-debt tax shield
(depreciation) to make this study more comprehensive.
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1.1 Significance of the Study
Textile sector is the largest industry in Pakistan. It consist of 164 firms which includes 145
firms related to spinning, weaving and finishing while 6 firms consist of made up textiles
articles and the remaining 13 firms are related to other textiles items. From the last many years,
Pakistani textile industry is facing a large number of crises due to continuous load-shedding
from the last many years. A large number of firms in this sector have closed their operations
because without electricity it is not possible to produce any product in textile sector. The
remaining firms are forced to take loan for their survival in order to use generator or private
electricity resources which are much costly. It has increased debt financing trend in this sector
and the firm’s performance is affected largely by this trend. APTMA has requested to
Government of Pakistan to take some serious steps in order to rescue the textile industry for
possible survival by controlling the problem of electricity and restructuring the outstanding
loans. In this way PICIC commercial bank was previously establish to provide loan both short
term and long term according to this sector need and recently NIB bank has been established
for this purpose.
1.2 Objective of the Study
The Textile Sector covers 40% of non-financial industry in Pakistan. It can influence the
performance of other sectors by its financial decision making and actions thereof. The
researcher aims to explore the factors that determine firm’s performance in textile sector of
Pakistan so that the financial performance can be groomed in overall non-financial sector of
Pakistan. The researcher’s objective is to find out the different factors which are significantly
affecting firm’s performance in textile sector of Pakistan for the period- Research Questions
The researcher wants to explore the current study with reference to the following research
questions:
What factors are significantly impacting the firm’s performance in textile industry of Pakistan?
Do the observed factors also consistent with the previous researcher’s findings.
2. Literature Review
A large number of previous studies relating to firm’s performance or sometimes corporate
performance has identified a number of factors that empirically and even significantly affecting
the firm’s performance. There are a little number of research findings available in Pakistani
context relating to firm’s performance however the foreign researchers has done a lot in this
context. The researcher used the framework of Zeitun and Tian (2007) with the extension in
their regression model by adding liquidity and non-debt tax shield and applied this regression
model simultaneously on textile and food sectors of Pakistan. The findings of Zeitun and Tian
(2007) indicated that leverage has a significant and negative relationship with firm’s
performance. They used leverage, growth, size, tax, risk and tangibility as independent variable
to see their effect on firm’s performance. They concluded that firm’s size and tax have positive
and significant relationship with firm’s performance while risk and tangibility have negative
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and significant relationship with firm’s performance. Memon, Bhutto and Abbas (2010)
concluded in their study of capital structure and firm’s performance on textile sector that the
companies in this sector are performance below optimum level of capital structure and also fail
to achieve the economies of scale. Nosa and Ose (2010) found that effective funding required
for the growth and development of the corporations in Nigeria. They suggested enhancing the
regulatory framework for increasing the firm’s performance by focusing on risk management
and corporate governance. Onaolapo and Kajola (2010) found a significant and negative
relationship between debt ratio and firm’s financial performance. The study conducted by
Krishnan and Moyer (1997) found a negative and significant relationship between leverage and
firm’s performance while other factors affecting firm’s performance positively includes size,
growth, tax and risk. Jensen and Meckling (1976) found two types of agency cost; agency cost
of equity holders and agency cost of debt holders. They concluded that a conflict of interest
arises between the management and the shareholders when management take decision against
the interest of shareholders and another conflict arises when the shareholder act against the
interest of debt holders. William (1987) found that decision for high leverage by the
management decreases the conflict between management and shareholders. The leverage can
work as disciplinary device that controls the management from wasting their firm’s resources
according to Grossman and Hart (1982). The researcher in the current study used short term as
well as long term debts as proxy for leverage and also the other factors like growth, size, tax,
risk, tangibility, liquidity and non-debt tax shield for measuring their impact on firm’s financial
performance in textile as well as food sector comparatively for the period-. Data and Methodology
3.1 Data and Source
The type of data is panel/longitudinal and has been created from the State Bank of Pakistan’s
annual publication “Financial Statement Analysis of companies (non-financial) listed in
Karachi Stock Exchange for the period-”. This statement contains the 6 years
financial figures of 12 different sectors relating to non-financial industry having 411 firms in
total and available online at www.sbp.org.pk while the researcher selected the Textile sector
because it covers the greatest part of overall population of non-financial industry in Pakistan.
The sample consists of 139 companies from textile sector of Pakistan. The findings of the
current study is applicable on all sectors of non-financial industry of Pakistan as the sample
selected covers 4.0% approximately of the whole population of non-financial industry.
It is not applicable on financial industry like banks and insurance sector as their capital
structure is entirely different from non-financial sector.
3.2 Econometric Regression Model
For regression analysis of Panel data, there are three methods available for their regression like
fixed effect, Random effect and constant coefficient regression model. The choice between
fixed effect and random effect is finalized by hausman specification test (1978) while the
choice between random effect and constant coefficient model is finalized by Lagrange
multiplier test. As there is a large number of companies in the current study while the time
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period is small so the data type is short panel according to Baltagi (2005). The researcher
expects a cross sectional fixed effect with constant in the current study and developed the
following regression model for the estimation of current study:
Yit = α1+
+ β1(LV)it + β2(GR)it + β3(SZ)it + β4(RK)it + β5(TX)it
+β6(TN)it + β7(LQ)it + β8(ND)it +
+ Uit
Where
Yit = Firm’s Financial Performance over time. This variable is indicated by Return on
Investment (ROI)
α1 +
= Constant coefficient including cross sectional fixed effect
β1 – β8 = Regression coefficients for measuring independent variables
LV = Leverage
GR = Growth
SZ = Size
RK = Risk
TX = Tax
TN = Tangibility
LQ = Liquidity
ND = Non-debt Tax shield
+ Uit = Error component showing unobserved factor
3.3 Variables and Hypothesis Development
The previous studies have shown a number of proxies for measuring firm’s financial
performance like ROA, ROE, Tobin’s Q, EPS and ROI. Some of these variable required
current market data like Tobin’s Q. The researcher in the current study used Return on asset
(ROI) as dependent variable for measuring firm’s financial performance while the independent
variables includes short term and long term leverage, growth, firm’s size, risk, tax, tangibility
of fixed assets, liquidity and non-debt tax shield (depreciation).
The description of each variable and their expected signs are given below in the following
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table:
Table 1. Explanation of Dependent and Independent variables and Expected signs
ROI
Variables
Leverage
Growth
Size
Risk
Tax
Tangibility
Liquidity
NDTS
Dependent Variable
EBIT/Total Assets
Independent Variables
Description
Short term debt/Total assets, Long term debt/Total Assets
Δ Total Assets/ Total Assets
Natural Log of Total Sales
EBIT/Earning after interest and Tax
Current year’s Tax/Earnings before Tax
Fixed Assets/Total Assets
Current Assets/Current Liabilities
EBIT + Depreciation/Total Assets
Expected Signs
Negative
Positive
Positive
Positive
Positive
Positive
Positive
Positive
On the basis of above table the relationships between dependent and independent variables
have been developed in the following hypothesis:
H1: Leverage (short & long term) should have a negative impact on firm’s performance.
H2: Growth should have a positive impact on firm’s performance.
H3: Firm’s size should have a positive impact on firm’s performance.
H4: There should be a positive relationship between risk and firm’s performance.
H5: There should be a positive relationship between tax and firm’s performance
H6: Tangibility should have a positive relationship with firm’s performance.
H7: Liquidity should have a positive relationship with firm’s performance.
H8: There is a positive relationship between Non-debt tax shield and firm’s performance.
4. Regression Analysis and Discussion on Findings
The researcher used STATA 11 software for the regression analysis of the current study. The
dependent variable is firm’s performance measure ROI while the independent variables
includes Leverage (short, long), Growth, Size, Risk, Tax, Tangibility, Liquidity and Non-debt
tax shield. The descriptive statistics showing mean, standard deviation, minimum and
maximum values of textile sector indicated in table 2 while correlation matrix of textile sector
is indicated in table 3. The regression result using one-way fixed effect model is indicated in
table 4. The presence of fixed cross sectional effect is evidenced by the significant results of
hausman test which validate the name of this model as one way-fixed effect model according to
Baltagi (2005).
Table 2. Descriptive Statistics
Variables
Return on Investment (ROI)
Short term Leverage (S-Lev)
Long term Leverage (L-Lev)
Mean
-
-
-
SD
-
-
-
Min
-1.71287
-
Max-
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Growth (GR)
Firm’s Size (SZ)
Risk (RK)
Tax (TX)
Tangibility (TN)
Liquidity (LQ)
Non-debt Tax shield (ND)
-
-
-
-
-
-
-
-
-42.9379
-
.04
-10.9418
-
The above table 2 indicates the descriptive statistics like Mean, Standard deviation, Min and
Maximum of Firm’s performance (ROI) and other firm’s specific factors like Leverage,
Growth, Size, Risk, Tax, Tangibility, Liquidity and Non-debt tax shield (Depreciation) during
the period- for Textile sector of Pakistan. The above table indicates that short term
leverage has an average (mean) value as 51% in textile sector’s firm’s performance
approximately, while long term leverage showing (mean) value as 22% in Textile sector. The
firm’s Size in Textile sector on average (mean) value showing 139%.
Table 3. Correlation Matrix for Textile Sector
ROI
S-LV
L-LV
GR
SZ
RK
TX
TN
LQ
ND
ROI
1.000
-0.056
-
-0.003
-
S-LV
L-LV
GR
SZ
RK
TX
TN
LQ
ND
1.000
-0.079
-0.109
-
-0.204
-0.044
1.000
-0.108
-0.129
-0.030
-
-0.121
-0.092
-
-0.003
-0.277
-
-
-0.018
-
1.000
-0.007
-
1.000
-0.000
-0.036
-0.609
1.000
-0.101
-0.045
-
1.000
The above table 4.2 indicates the correlation matrix of dependent and independent variables
in textile sector of Pakistan for the period-. It indicates that short term and long
term leverage including tax and tangibility having negative correlation with firm’s
performance while growth, size, risk, liquidity and non-debt tax shield having positive
correlation with firm’s performance in textile sector of Pakistan. The highest correlation is
indicated between non-debt tax shield and firm’s performance as 0.71 approximately
according to the above table.
Table 4. Regression Results – One way fixed effect regression model Dependent Variable =
Firm’s Performance (ROI)
Independent Variables
Leverage (S-Lev,
L-Lev)
Growth (GR)
Firm’s Size (SZ)
Risk (RK)
1st Model (β1=S-LV)
Coefficients P-values
-.0315
**
93
0.026
-
.01869
*0.
4
000
.00142
**-
2nd Model (β1=L-LV)
Coefficients P-values
-
--
.01889
*0.000
60
.00144 **0.021
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Tax (TX)
Tangibility (TN)
Liquidity (LQ)
Non-debt Tax shield
(ND)
Constant
Number of
Observations
No of Groups
Overall Model
Fitness
R2 (Within)
R2 (Between)
R2 (Overall)
F-test that all u-i=0
.00775
3
-.0072
14
-.0007
47
.29488
3
-.2505
96
*-
*-
=834
=139
F(8,687)=325.51
Prob>F = 0.0000
-
--
--
-
--
*-
*-
=834
=139
F(8,687)=323.44
Prob>F=0.0000
=0.7913
=0.7902
=0.7833
=0.7926
=0.7847
=0.7866
F(138,687)=1.57
F(138,687)=1.54
Prob>F=0.0001
Prob>F=0.0003
Hausman test
Prob>Chi2=0.000
Prob>Chi2=0.007
Note: The current table is generated by the output STATA 11 regression
result
*significant at 1% level, **significant at 5% level, ***significant at 10%
level
The above table 4.3 indicates results of one-ways fixed effect regression model estimation. The
overall model is statistically fit and significant in both sectors. It indicates that short term
leverage is significant at 5% level in textile sector and showing negative relationship with
firm’s performance and accepts the 1st hypothesis. The negative relation between leverage and
firm’s performance is also consistent with the following researchers like Krisnan and Moyer
(1997), Onaolapo and kajola (2010), Memon, Bhutto and Abbas (2010) and Zeitun and Tian
(2007). It indicates that firm’s performance in textile sector is significantly influenced by short
term debts. Growth is not significant at any level and showing negative relationship which
rejects the 2nd hypothesis. However the negative relationship between growth and firm’s
performance is consistent with the similar findings of previous researchers Zeitun and Tian
(2007) while the other researchers like Krishnan and Moyer (1997), Onaolapo and Kajola
(2010), Memon, Bhutto and Abbas (2010) found positive relationship between firm’s
performance and growth. Firm’s size is significant @1% level and accepts the 3rd hypothesis.
This positive relationship is consistent with the following researchers like Onaolapo and
Kajola (2010), Krishnan and Moyer (1997) and Zeitun and Tian (2007). It indicates that firm’s
size increases firm’s performance in textile sector of Pakistan. Risk is significant at 5% level in
textile sector. It is showing positive relationship which accepts 4th hypothesis. This positive
relationship between risk and firm’s performance is also consistent with the previous
researchers who found the same relationship like Memon, Bhutto and Abbas (2010) and
Krishnan and Moyer (1997). It indicates that more risky firms tend to perform well in textile
sector of Pakistan. Tax is significant at 1% level in textile sector and accepts 5th hypothesis it is
also consistent with the similar findings by Krishnan and Moyer (1997), Memon, Bhutto and
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Abbas (2010) and Zeitun and Tian (2007). Tangibility is not significant at any level in textile
sector. It means that tangibility does not play a significant role for firm’s performance in textile
sector. Liquidity is not significant at any level in both sectors. It has negative relationship with
firm’s performance in textile sector that rejects the 7th hypothesis. The non-debt-tax shield
(depreciation) is significant at 1% level with positive relationship and accepts 8th hypothesis. It
means that non-debt tax shield plays an important and significant role for increasing firm’s
performance in textile sector of Pakistan.
5. Conclusion and Recommendations
The current study concluded that firm’s performance in textile sector of Pakistan is
significantly affected by Short term leverage, size, risk, tax and non-debt tax shield. The
Researchers recommends that the textile sector of Pakistan should make its financial decision
taking into consideration of the above said factors because textile sector is the largest sector in
Pakistan for non-financial industry and it is considered as benchmark for other sectors in
Pakistan. The Findings of the researcher are also consistent with the previous researchers. The
Textile sector should preferably decrease their short term debt financing as it will decrease
firm’s financial performance while all other sector may increase it. The firm should use less
short term debt as it neither provide tax shield advantage and not also cheap as long term debt
financing.
6. Policy Implications
The current research findings empirically implies that the companies in textile sector of
Pakistan has to make their policies by considering short term leverage, firm’s size, financial
risk, tax provision and non-debt tax shield (depreciation) in order to strengthen their
performance. Short term leverage decreases performance significantly so the firms should
avoid short term leverage while all other factors increases firm’s performance in textile sector
of Pakistan.
7. Limitations and Suggestions
The current study is limited and applicable to non-financial industry of Pakistan only. It is not
applicable to financial sector as their capital structure is entirely different from non-financial
sector. The researcher used book value measure for dependent and independent variables. The
future research on firm’s performance may be made through market value measures like
Tobin’s Q etc. The future research may also be conducted on financial sector using the same
models and variables.
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