Cement
industry of Pakistan
Cement
Industries of Pakistan
Cement
industry of Pakistan
Cement
Industries of Pakistan
Introduction:
“Working
Capital management is concerned with the problems that arise in
attempting to manage the current assets, the current liabilities and
the interrelationship that exists in between them. The success of an
organization to a greater extent depends upon the effective
management of working capital. The present work
therefore is a modest attempt in this direction by undertaking a
study of working capital management.”
Management of working
capital is an important component of corporate financial management
because it directly affects the profitability of the firms.
Management of working capital refers to management of current assets
and of current liabilities (Reheman and Nasr, 200).
“Cement
Industry is one of the major industries of Pakistan. Pakistan is rich
in cement raw material. Currently many cement plants are operating in
private sector. Pakistan Cement Industry has huge potential for
export of cement to neighboring countries like India, U.A.E,
Afghanistan, Iraq & Russian States.
”
2. History:
“ The
industry was privatized in 1990 which led to setting up of new
plants. Although an oligopoly market, there exists fierce competition
between members of the cartel today.
The
industry comprises of 29 firms (19 units in the north
and 10 units in the south), with the installed production
capacity of 44.09 million tons. The north with installed
production capacity of 35.18 million tons (80 percent) while the
south with installed production capacity of 8.89 million tons
(20 percent), compete for the domestic market of over 19 million
tons. There are four foreign companies, three armed forces companies
and 16 private companies listed in the stock exchanges. The
industry is divided into two broad regions, the northern region and
the southern region. The northern region has around 80 percent share
in total cement dispatches while the units based in the southern
region contributes 20 percent to the annual cement sales.
Cement
industry is indeed a highly important segment of industrial sector
that plays a pivotal role in the socio-economic development. Since
cement is a specialized product, requiring sophisticated
infrastructure and production location. Mostly of the cement
industries in Pakistan are located near/within mountainous regions
that are rich in clay, iron and mineral capacity. Cement industries
in Pakistan are currently operating at their maximum capacity due to
the boom in commercial and industrial construction within Pakistan.
T he
cement sector is contributing above Rs 30 billion to the national
exchequer in the form of taxes.
Cement
industry is also serving the nation by providing job opportunities
and presently more than 150,000 persons are employed directly or
indirectly by the industry.
“ ”
2.1.Fiscal Performance 2009:
“
After witnessing substantial
growth in all three quarters of fiscal year (FY) 2008-09, cement
sector concluded the fourth quarter with a handsome growth of 1,492
percent on yearly basis, All Pakistan Cement Manufacturers
Association’s report revealed on 29th September 2009.
Higher
retention prices (up 59 percent) and high rupee based export sales
amid rupee depreciation (20 percent) drove profits up north. However,
this growth is magnified, as FY2007-08 was an abnormally low profit
period for the sector.
Moreover,
the performance is skewed towards large players with export potential
as profitable companies in both years posted increase of just 109
percent, said analyst at JS Research Atif Zafar.
He
said that cumulative profitability of companies in FY09 stood at Rs
6.2 billion or $78.2 million as compared to Rs 386 million or $6.2
million depicting a massive growth of 1,492 percent. Companies with
profits in both the years posted 109 percent earnings improvement.
”
3. Working Capital Management & Profitability Pakistani Cement Firms
The
cement industry is one of the main beneficiaries of the
infrastructure boom in the world. With stout demand and tolerable
supply, cement industry is growing exceptionally fast and it has a
bright future ahead. Working
Capital Management has its effect on liquidity as well on
profitability of the firm. In this research, we have selected a
sample of 07 Pakistani firms listed on Karachi Stock Exchange for a
period of 03 years from 2008 – 2010, we have studied the effect of
different variables of working capital management including the
- Receivable collection period,
- Return on asset ,
- Net profit margin,
- Receivable collection period,
- Inventory turnover period,
- Current ratio
- Debt ratio, ”
3.1. The problem statement:
“Does Working
Capital Management Affect Profitability of Pakistani Cement Firms?”
4. Objectives:
• To
find out the relationship b/w of working capital & profitability
of Pakistani Cement industries.
- To find out the effects of different components of working capital management on profitability.
• To
draw conclusion about relationship of working capital management and
profitability of the Pakistani cement industries.
4.1 Methodology:
The purpose of this
research is to contribute towards a very important aspect of
financial management known as working capital management with
reference to Pakistan. Here we will see the relationship between
working capital management practices and its affects on profitability
of 07 Pakistani firms listed on Karachi stock Exchange for a period
of three years from 2008 – 2010. This section of the article
discusses the firms and variables included in the study, the
distribution patterns of data and applied statistical techniques in
investigating the relationship between working capital management and
profitability.
5. Data Set & Sample
The data used in
this study was acquired from Karachi Stock Exchange (KSE), internet
and web sites of different firms. Data of firms listed on the KSE for
the most recent three and web sites of different firms. Data of firms
listed on the KSE for the most recent three years formed the basis of
our calculations. The period covered by the study extends to three
years starting from 2008 to 2010. The reason for restricting to this
period was that the latest data for investigation was available for
this period. The sample is based on financial statements of the 94
Pakistani firms, listed on KSE including firms from different sectors
of our economy. Because of the specific nature of their activities,
firms in financial sector, banking and finance, insurance, leasing,
modarabas, business services, renting and other services are excluded
from the sample. Finally, the firms with data of the number of day’s
accounts receivable, number of days inventories,number of days
accounts payable and operating income are included in sample.
6. Variables
This study
undertakes the issue of identifying key variables that influence
working capital management of Pakistani firms. Choice of the
variables is influenced by the previous studies on working capital
management.
All the variables
stated below have been used to test the hypotheses of our study. They
include dependent,
independent and some control variables:
- Receivable collection period,
- Return on asset ,
- Net profit margin,
- Receivable collection period,
- Inventory turnover period,
- Current ratio
- Debt ratio, ”
7. Analysis
Descriptive
analysis shows the average, and standard deviation of the different
variables of interest in the study. It also presents the minimum and
maximum values of the variables which help in getting a picture about
the maximum and minimum values a variable can achieve.
Table 4.1 presents
descriptive statistics for 94 Pakistani non financial firms for a
period of three years from 2008 to 2010. The mean value of net
operating profitability is 13.3% of total assets, and standard
deviation is 11.5%. It means that value of the profitability can
deviate from mean to both sides by 11.5%. The maximum value for the
net operating profitability is 68.4% for a company in a year while
the minimum is -46.6%.
The cash conversion
cycle used as a proxy to check the efficiency in managing working
capital is on average 73 days and standard deviation is 160 days.
Firms receive payment against sales after an average of 55 days and
standard deviation is 70 days. Minimum time taken by a company to
collect cash from receivables is 1 day while the maximum time for
this purpose is 654 days. It takes an average 78 days to sell
inventory with standard deviation of 90 days. Here, maximum time
taken by a company is 958 days, which is a very large time period to
convert inventory into sales. Firms wait an average 60 days to pay
their purchases with standard deviation of 99 days. Here, minimum
time taken by a company is 0.25 days which is unusual, and maximum
time taken for this purpose is 900 days. To check the size of the
firm and its relationship with profitability, natural logarithm of
sales is used as a control variable. The mean value of log of sales
is 20.83 while the standard deviation is 1.70. The maximum value of
log of sales for a company in a year is 25.87 and the minimum is
14.73.
8. Pearson’s Correlation Coefficient Analysis
Pearson’s
Correlation analysis is used for data to see the relationship between
variables such as those between working capital management and
profitability. If efficient working capital management increases
profitability, one should expect a negative relationship between the
measures of working capital management and profitability variable.
There is a negative relationship between gross profitability on the
one hand and the
measures of working capital management on the other hand. This is
consistent with the view that the time lag between expenditure for
purchases of raw material and the collection of sales of finished
goods can be too long, and that decreasing this time lag increases
profitability.
Current ratio is a
traditional measure of checking liquidity of the firm. In this
analysis the current ratio has a significant negative relationship
with profitability (measured by net operating profitability). The
coefficient is – 0.126 and pvalue
of (.003). The result is significant at . = 1%. It indicates that
the two objectives of liquidity and profitability have inverse
relationships. So, the Pakistani firms need to maintain a balance or
tradeoff between these two measures.
A negative
relationship between number of days accounts payable and
profitability is consistent with the view that less profitable firms
wait longer to pay their bills. In that case, profitability affects
the account payables policy and vice versa. An alternative
explanation for a negative relationship between the number of days
accounts payable and profitability could be that Pakistani firms wait
too long to pay their accounts payable. Speeding up payments to
suppliers might increase profitability because firms often receive a
substantial discount for prompt payment.
Pearson’s
correlation (Appendix 1) also displays a significant positive
relationship between the average collection period and cash
conversion cycle; the correlation coefficient is 0.548 and the p
value
is (.000). That ratio is highly significant at . = 1% , which means
that if a firm takes more time to collect cash against the credit
sales it will increase its operating or cash conversion cycle.
There is also a
positive relationship between Inventory turnover in days and the cash
conversion cycle which means that if the firm takes more time to
sell inventory it will lead to increase in the cash conversion cycle
as well. The correlation coefficient is positive and is 0.667, the
pvalue
is again (.000) showing that it is highly significant at . = 1%.
The results of correlation analysis indicate that as far as Pakistani firms are concerned, the working capital management very significantly and strongly affects their profitability.
9. Regression Model: General Least Squares – Cross Section Weights
We have also used
the general least squares model with cross section weights. When we
use the pooled data and cross sections are greater than the time
series, there may be a problem of heteroskedasticity (changing
variation after short periods of time). To counter this problem we
are using the general least squares with cross section weights. In
this regression, the common intercept is calculated for all variables
and assigned a weight. A weighted least square is obtained by first
dividing the weight series by its mean, then multiplying all of the
data for each observation by the scaled weight series. The scaling of
the weight series is a normalization that has no effect on the
parameter results, but makes the weighted residuals more comparable
to the un-weighted residuals.
In the first
Regression, the average collection period and current ratio are used
as independent variables with other control variables.
The coefficient of
C is 0.145 and has a significant p-value
at . = 1%. The coefficient of accounts receivable is negative and it
is highly significant. The coefficient has a significant t-statistics
and a p-value
of (0.0000), which implies that the collection policy of a firm has a
significant effect on profitability. All the other variables are also
significantly affecting the profitability. Liquidity of the company
also has a negative relationship with the dependent variable. The
coefficient of current ratio is -0.015 showing that, when the
liquidity position is better, this has a negative affect on
profitability of a firm. The variable has a
p-value
of 0.0000 which is highly significant at .= 1%. The size of the firm
(measured in terms of log of sales) has a positive impact on
profitability. The coefficient is (0.006) and is highly significant
at . = 1% as the p-value
is (0.0000). It is interpreted that when size of the firm increases,
it will lead to increasing
the profit of the
firm. The debt ratio shows a negative relationship with the dependent
variable, which means that, when the leverage of the firm’s
increases, profitability of the firm decreases. This ratio is highly
significant at . = 1% and the coefficient is (-0.0131). The result
shows that adjusted R-square (
The coefficient of
intercept C is significant and equals 0.225. The coefficient of
inventory turnover in days (a proxy for inventory policy) is
negative, and is highly significant at . = 1%. It implies that the
increase or decrease in the inventory turnover in days, significantly
affects profitability of the firm. It means that the inventory policy
of the firm will affect its profitability. If the inventory is not
converted in sales it will lead to decreasing profitability. All the
other variables also are significantly affecting profitability at .
= 1% except Size of the firm which is significant at . = 5%.
Increase in sales has a positive impact on profitability while all
other control variables like current ratio, debt ratio, and financial
assets to total assets have a significant negative affect on
profitability of the firm. The adjusted (R2
)
= 80%, and it shows the variation in the dependant variable’s
explained by the independent variables. The F-statistic has a value
of 451 and also reflects the high significance of the model.
R2
)
weighted is (79%) which shows that there is 79% variation in the
dependent variable attributable to the independent variables
In second
regression, inventory turnover in days and current ratio are used as
independent variables with other control variables. .
Third regression is run using the average payment period as an independent variable instead of inventory turnover in days. The other variables are the same as they were in the first and second regression. The coefficient of intercept C is 0.10. The coefficient of average payment period (proxy for payment policy) is negative and highly significant at . = 1%, and implies that the increase or decrease in the average payment period, significantly affects profitability of the firm. The negative relationship between average payment period and profitability indicates that the less profitable firms wait longer to pay their bills. All the other variables are also significantly affecting the profitability. All of them are significant at . = 1%. Size
of the firm
(measured in terms of log of sales) has a positive impact on its
profitability; current ratio has a negative impact on it while other
control variables like debt ratio and financial assets to total
assets have a significant negative affect on profitability of the
firm. The adjusted R2= 81%. The F-statistic has a value of 511, and
the p-value
is 0.0000; all of them reflect high significance of the mode
Fourth regression
is run using the cash conversion cycle as an independent variable. It
is the comprehensive measure of checking efficiency of working
capital management. The other variables are the same as they were in
the first three regressions. Taking the cash conversion cycle as an
independent variable, the result indicates that its coefficient is
negative and is significant at . = 1%. It implies that an increase
or decrease in the cash conversion cycle period, significantly
affects the profitability of the
firm. All the other
variables: size, current ratio, debt ratio and financial assets to
total assets are significantly affecting the profitability at 1%
significance level. The adjusted R2= 83%. The F-statistic also
reflects the highly significance of the model as its value is 560
with p-value
of 0.0000. In general, the results of general least squares method
with cross section weights are indicating the same interpretation
that the working capital management affects profitability of the
company. If the firm can effectively manage its working capital, it
can lead to increasing profitability. We can also interpret that
liquidity and profitability move in opposite directions. And, there
is a need to maintain a trade-off between these two
objectives of the
firm. It is further interpreted that if the firm increases its debt
financing, it will lead to decreasing profitability of the firm in
terms of financial cost. Size of the firm has a direct positive
relationship with its profitability. If the size (measured in terms
of log of sales) increases, it will lead to an increase in
profitability of the firm.
10. Conclusion
Most
of the Pakistani firms have large amounts of cash invested in working
capital. It can therefore be expected that the way in which working
capital is managed will have a significant impact on profitability of
those firms. We have found a significant negative relationship
between net operating profitability and the average collection
period, inventory turnover in days, average payment period and cash
conversion cycle for a sample of Pakistani firms listed on Karachi
Stock Exchange. These results suggest that managers can create value
for their shareholders by reducing the number of days accounts
receivable and inventories to a reasonable minimum. The negative
relationship between accounts payable and profitability is consistent
with the view that less profitable firms wait longer to pay their
bills.
On
basis of the above analysis we may further conclude that these
results can be further strengthened if the firms manage their working
capital in more efficient ways. Management of working capital means
“management of current assets and current liabilities, and
financing these current assets”. If these firms properly manage
their cash, accounts receivables and inventories in a proper way,
this will ultimately increase profitability of these companies.
Correlations
|
||||||
ROA
|
NPM
|
RCP
|
ITP
|
CR
|
||
ROA
|
Pearson
Correlation
|
1
|
||||
Sig.
(2-tailed)
|
||||||
N
|
7
|
|||||
NPM
|
Pearson
Correlation
|
-0.08445813
|
1
|
|||
Sig.
(2-tailed)
|
0.857130258
|
|||||
N
|
7
|
7
|
||||
RCP
|
Pearson
Correlation
|
-0.442142148
|
-0.445598657
|
1
|
||
Sig.
(2-tailed)
|
0.320559258
|
0.316337024
|
||||
N
|
7
|
7
|
7
|
|||
ITP
|
Pearson
Correlation
|
-0.482449535
|
-0.130978857
|
-0.203449745
|
1
|
|
Sig.
(2-tailed)
|
0.272859104
|
0.779545784
|
0.661716479
|
|||
N
|
7
|
7
|
7
|
7
|
||
CR
|
Pearson
Correlation
|
0.463382228
|
0.579432177
|
-0.47172883
|
-0.07996456
|
1
|
Sig.
(2-tailed)
|
0.295000599
|
0.17276916
|
0.2852134
|
0.864681552
|
||
N
|
7
|
7
|
7
|
7
|
7
|
|
QR
|
Pearson
Correlation
|
0.328479752
|
0.549739692
|
-0.145906173
|
-0.25397943
|
0.914300983
|
Sig.
(2-tailed)
|
0.471946708
|
0.201109878
|
0.75493012
|
0.582601911
|
0.003941466
|
|
N
|
7
|
7
|
7
|
7
|
7
|
|
**.
Correlation is significant at the 0.01 level (2-tailed).
|
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