Analysis

The impact of working capital management on profitability
Usman Hameed
Student of MBA First Semester
Superior college
Lahore, Pakistan
Introduction
Working capital management is a very important component of corporate finance because it
directly affects the liquidity and profitability of the company. It deals with current assets and
current liabilities. Excessive levels of current assets can easily result in a firm’s realizing a
substandard return on investment.
However firms with too few current assets may incur shortages and difficulties in maintaining
smooth operations (Barton & Simko 2002). Efficient working capital management involves
planning and controlling current assets and current liabilities in a manner that eliminates the risk
of inability to meet due short term obligations on the one hand and avoid excessive investment in
these assets on the other hand (Mackenzie 2003). With regard to current liabilities, the firm is
responsible for paying these obligations on a timely basis. Liquidity for the ongoing firm is not
reliant on the liquidation value of its assets, but rather on the operating cash flows generated by
those assets (Petty & Guthrie 2004). Taken together, decisions on the level of different working
capital components become frequent, repetitive, and time consuming.
Corporate finance is primarily used with three decisions: capital structure decisions, capital
Budget decisions, and working capital management decisions. Working Capital Management is a
very sensitive area in the field of financial management (Leland 1998). It involves the decision
of the amount and composition of current assets and the financing of these assets. Current assets
include all those assets that in the normal course of business return to the form of cash within a
short period of time, ordinarily within a year and such temporary investment as may be readily
converted into cash upon need. The Working Capital Management of a firm in part affects its
profitability.
The ultimate objective of any firm is to maximize the profit. But, preserving liquidity of the firm
is an important objective too. The problem is that increasing profits at the cost of liquidity can
bring serious problems to the firm. Therefore, there must be a tradeoff between these two
objectives of the firms. One objective should not be at cost of the other because both have their
importance. If we do not care about profit, we cannot survive for a longer period.
On the other hand, if we do not care about liquidity, we may face the problem of insolvency or
bankruptcy. For these reasons working capital management should be given proper consideration
and will ultimately affect the profitability of the firm. Firms may have an optimal level of
working capital that maximizes their value.


A popular measure of Working Capital Management (WCM) is the cash conversion cycle, i.e.
the time lag between the expenditure for the purchases of raw materials and the collection of
sales of finished goods. The longer this time lags, the larger the investment in working capital
(Gompers, 1995).A longer cash conversion cycle might increase profitability because it leads to
higher sales.
However, corporate profitability might also decrease with the cash conversion cycle, if the costs
of higher investment in working capital rise faster than the benefits of holding more inventories
and granting more trade credit to customers. Cash Conversion Cycle is the sum of days of sales
outstanding (average collection period) and days of sales in inventory less days of payables
outstanding. Cash conversion cycle is likely to be negative as well as positive.
A positive result indicates the number of days a company must borrow or tie up capital while
awaiting payment from a customer. A negative result indicates the number of days a company
has received cash from sales before it must pay its suppliers (Gerald Epstein, 2003). Of course
the ultimate goal is having low CCC, if possible negative. Because the shorter the CCC, the more
efficient the company in managing its cash flow.

A financial benefit that is realized when the amount of revenue gained from a business activity
exceeds the expenses, costs and taxes needed to sustain the activity. Any profit that is gained
goes to the business's owners, who may or may not decide to spend it on the business. Calculated
as a profitability of Total Revenue less Total Expenses.
Purpose of the study
The purpose of this quantitative study working capital management to profitability here in this
model, working capital management is considering as independent variable and profitability
which are dependent variable. Working capital management is a measure of your business'
efficiency and short-term financial health. Positive working capital means you are able to pay off
short term liabilities; negative working capital means your business cannot meet its short term
liabilities with current assets.
Net Operating Profitability which is a measure of Profitability of the firm is used as dependant
variable. It is defined as Operating Income plus depreciation, and divided by total assets minus
financial assets. Average Collection Period Used as alternative for the Collection Policy is an
independent variable. It is calculated by dividing account receivable by sales and multiplying the
result by 365 (number of days in a year). The Cash Conversion Cycle is used as a comprehensive
measure of working capital management is another independent variable, and is measured by
adding Average Collection Period with Inventory Turnover in Days and deducting Average
Payment Period. Current Ratio which is a usual measure of liquidity is calculated by dividing
current assets by current liabilities.






Objective
To examine the impact of working capital management and profitability in sector of Pakistan like
Cement industries from 2009 to 2013.
 To examine the relationship between Working capital Management and Average
collection period
 To examine the relationship between Working capital Management and Cash conversion
cycle
 To examine the relationship between Working capital Management and Current ratio
 To examine the relationship between Average collection period and Net operating
profitability
 To examine the relationship between Cash conversion cycle and Net operating
profitability
 To examine the relationship between Current ratio and Net operating profitability
Significance
This study is significant for financial management practices in Pakistani Cement industries.
Results will indicate relationships between working capital management and profitability and
will assist owner-managers and financial managers to improve performance and profitability of
their businesses by managing working capital efficiently and effectively.
 It will be helpful for policy makers to make such economic policies which are worth full
for economy.
 The Government can also take help by this research before making budgets and other
related policies.
 Government can check and predict where the need is for improvement and which sector
is requiring more attention regarding economic growth.
 It will also helpful for future researchers to research in this sector and can get their
required information from it.
 The study has its own significance that how this research will apply practically and prove
helpful for economists.
Research Question
What is the impact of Working Capital Management on Profitability of Pakistan?
Hypothesis:
H
1:
There is a relationship between Working capital Management and Net Profitability.
H
0
: There is no relationship between Working capital Management and Net Profitability.



H
2
: There is a relationship between Working Capital Management and Average Collection
Period.
H
o
: There is no relationship between Working Capital Management and Average Collection
Period.

H
3
: There is a relationship between Working Capital Management and Cash Conversion Cycle.
H
o
: There is no relationship between Working Capital Management and Cash Conversion Cycle.

H
4
: There is a relationship between Average Working Capital Management and Current Ratio.
H
o
: There is no relationship between Average Working Capital Management and Current Ratio.

H
5
: There is a relationship between Average Collection Period and Net Operating Profitability.
Ho: There is no relationship between Average Collection Period and Net Operating Profitability.

H
6
: There is a relationship between Cash Conversion Cycle and Net Operating Profitability.
Ho: There is no relationship between Cash Conversion Cycle and Net Operating Profitability.

H
7
: There is a relationship between Current Ratio and Net Operating Profitability.
H
o
: There is no relationship between Current Ratio and Net Operating Profitability.

(Raheman, 2003) This study shows strong negative relationship between variables of working
capital management and profitability of the companies. He found that as the cash conversion
cycle increases, it leads to decreasing profitability of the firm.
(Elijelly, 2004) This article shows the relationship between liquidity and conversion cycle on
sample of joint stock companies of Saudi Arabia, and concluded that negative relationship
between liquidity and conversion cycle.
(Sana, 2006) Working capital of any firm shows the position of liquid assets it holds to build its
business. It is important to analyze the situation as to how the companies manage their working
capital and find out a relationship between firm’s profitability and the working capital
management. The results suggested that managers can generate positive return for the
shareholders by effectively managing working capital
(Padachi, 2006) The study was an attempt to assess the impact of working capital management
on profitability of small manufacturing companies and its results were expected to contribute to
the existing literature on working capital and SMEs. The study shown that the paper and printing
industry has been able to achieve high scores on the various components of working capital and
this has positively impact on its profitability.
(Saad, 2010) This study was conducted with an attempt to bridge the gap in the literature. The
study used only secondary data, In applying correlations and multiple regression analysis, the
result shows that there are significant negative associations between working capital variables
with firm’s market value and profitability.


(Martínez Solano, 2010) Working capital management is important because of its effects on the
firm’s profitability and risk, and consequently its value. This study find a significant negative
relation between an SME’s profitability and the number of days’ accounts receivable and days of
inventory.
(Bhaskar Bagchi1, 2012) This study empirically investigated the effect of working capital
management on firm’s profitability as measured by return on total assets and return on
investment using a sample of Indian FMCG companies. Results of this study show negative
association between working capital management variables and firms’ profitability.
(Afza, 2010) This study investigated the potential relationship of aggressive and conservative
policies with the accounting and market measures of profitability of Pakistani firms. The findings
of study suggested that there exist a negative relationship between working capital management
measures and profitability.
(visscher, 1998) This study looked at ten diverse industry groups to examine the relative
relationship between their aggressive/conservative working capital policies. Visscher concluded
that the industries had distinctive and significantly different working capital management
policies. The study also showed a high and significant negative correlation between industry
assets and liabilities policies.
(Ajilore, 2009) This research utilized panel data econometrics in a pooled regression, and shows
a significant negative relationship between net operating profitability and the average collection
period, inventory turnover in days, average payment period and cash conversion cycle.
(Gill, 2010:) The finding indicates that slow collection of accounts receivables is correlated with
low profitability.
(Dr Ioannis Lazaridis, 2004)The purpose of this paper is to establish a relationship that is
statistical significant between profitability. The results of this research showed that there is
statistical significance between profitability, measured through gross operating profit, and the
cash conversion cycle
(Vida Mojtahedzadeh, 2011)This study explore the relationship between working capital
management and corporate profitability. Result shows a negative significant relationship exists
between cash conversion cycle, Number of Days of A/P, Number of Days of A/R and corporate
profitability
(soenen, 1998) This research show relationship between working capital management and value
creation for shareholders. Result shows a strong negative relationship between the length of the
firm's net-trade cycle and its profitability.
(Sharma, 2008) worked on the relationship between profitability and cash conversion cycle for
firms in India, and found a negative relationship between profitability and the number of days in
inventory.
(James Ghthrie, 2004) This research examines the relationship between profitability and
liquidity. Result shows that the cash conversion cycle or the cash gap is of more importance as a
measure of liquidity than current ratio that affects profitability.


(Uyar, 2009) The Corporate liquidity can be assessed in the context of two different aspects
static or dynamic. Research found a significant a positive relationship of the CCC when
compared to the working capital ratios.
(Eljelly,2009) Empirically examined the relationship between profitability and liquidity. Result
shows that significant effect on profitability at the industry level.
(Simko, 2002) This research paper examined the efficiency of working capital management of
the Indian Textile companies during 1992 – 1993 to 2001 – 2002. By using regression analysis
found that some of the sample firms successfully improved efficiency during these years.
Population & Sampling
The Sample of listed ten annual report Pakistani cement sector is drawn for the purpose of
analysis five cement firms are selected The company of cement sectors in Pakistan is a
population. Sample size is 5 cement annual report of cement sector
Data collection
The results will be compiled on the basis of information collected from all sources and shall be
analyzed for the purpose of final interpretation. I choose annual report tool to collect data on all
variables. There are data collection tool for secondary of organization and, management, and
Finance research widely used technique for getting secondary data. A organization describes a
population by providing, a quantitative or numeric description of some fraction of the
population, the sample through the data analyses process of annual report of organization this
enables a researcher to generalize the findings from a sample of responses to a population.
Adding together, data collected with the help of annual report of organization useful for data
analyses.
Limitation
I have lack of expertise and due to lack of time this study limited on 5 companies of Cement and
select only last 5 year data. Due to limited availability of resources our research is limited to
cement industries of Pakistan. It also limits the findings to be applied to other industries and
organizations.

Ethical Consideration
Ethics are considered as the most important element while collecting data from the cement
industries Annual Reports. Developing this proposal as well as during the complete research
process, ethical issue will be deeply and wholly kept in consideration since the introduction of
research problem statement till Writing and disseminating the whole research. Their identities
will be kept secret from the others and it will ensured to them that the information collected from
them will only be used for the research purpose.



Future Research
Further researchers could usefully test and verify the points raised in this study across a greater
set of industries. In particular, in order to identify the various circumstances in which the firms
could change their attitudes towards particular sources of working capital, and that in the
different phases of growth cycle, the longitudinal studies utilizing preferably the panel or pooled
data may prove more helpful. A good amount of research work may also be undertaken with the
objective of proposing an ideal combination of WCM strategies and the financial policies which
could be highly conducive to the growth of the firms.

Result & Analysis

GP? OP? NP? AV? CC? CR? W?
Mean 17.13492 65.34501 5.006942 7.039785 1151420. 1.035450 -707217.9
Median 14.69000 8.130000 1.800000 7.230035 -1594.414 0.880000 -592614.0
Maximum 38.18000 595.7900 20.35000 17.79967 31019423 2.640000 5930323.
Minimum 0.052617 -37.11000 -9.070000 1.313547 -1303496. 0.521394 -4525842.
Observations 25 25 25 25 25 25 25
Cross
sections 5 5 5 5 5 5 5

Interpretation:
We apply descriptive analysis. Our variables are working Capital Management, Average
collection period, Cash conversion cycle, Current Ratio, and profitability including these
variables (Operating profit, Gross Profit & Net Profit). That is scale variables so we Apply the
test and to show the values of mean, median, maximum, minimum, observation & cross section.
In order to calculate five figure summary, measure of central tendency and measure of dispersion
regarding all variables the statistical result table has drawn. In case of Gross Profit variable,
Observation of 25 and 5 Cross Section in companies, minimum value=0.052617, maximum
value=38.18000, and median=14.69000. According to measure of central tendency
mean=17.13492, and median=14.69000.
In case of Operating Profit variable, Observation of 25 and 5 Cross Section in companies,
minimum value= (37.11000), maximum value=595.7900, and median=8.13000. According to
measure of central tendency mean=65.34501, and median=8.13000.
In case of Net Profit variable, Observation of 25 and 5 Cross Section in companies, minimum
value= (9.07000), maximum value=20.35000, mean value=5.00, and median=1.80000.
According to measure of central tendency mean=5.006942, and median=1.80000.


In case of Average Collection Period variable, Observation of 25 and 5 Cross Section in
companies, minimum value=1.3135, maximum value=17.7996, and median=7.230035.
According to measure of central tendency mean=7.039785, and median=7.230035.
In case of Cash Conversion Cycle variable, Observation of 25 and 5 Cross Section in companies,
minimum value= (1303496), maximum value=31019423, and median= (1594.414). According to
measure of central tendency mean=1151420, and median= (1594.414).
In case of Current Ratio variable, Observation of 25 and 5 Cross Section in companies, minimum
value= 0.521394, maximum value=2.64000, and median=0.88000. According to measure of
central tendency mean=1.035450, and median=0.88000.
In case of Working Capital Management variable, Observation of 25 and 5 Cross Section in
companies, minimum value= (4525842), maximum value= 5930323, and median= (592614).
According to measure of central tendency mean= (707217), and median= (592614).
4.2 Result & Analysis:
Table -1
Pool unit root test: Summary
Date: 02/22/13 Time: 23:13
Sample: 2008 2012
Series: AV_C1, AV_C2, AV_C3, AV_C4, AV_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -34.3095 0.0000 5 20
Breitung t-stat -1.73724 0.0412 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -15.6897 0.0000 5 20
ADF - Fisher Chi-square 47.5737 0.0000 5 20
PP - Fisher Chi-square 45.2621 0.0000 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 1.56172 0.0592 5 25




** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.

Interpretation:
In order to check mutual stationary between Cash conversion cycle and all related five year data
variable data is computed are normally distributed and these have linear relationship. According
to the table, Pool unit root test Pearson’s r is calculated and significant value p=0.0000<0.05 but
test value which shows that there is stationary relationship between the variables. Hence H
1
is
accepted which means that there is mutual relationship between these variables. The positive
sign of Pearson’s test value shows that there is positive relationship between these variables
which means that increase in Cash conversion cycle may enhance all and vice versa. However
the test value shows that the strength of relationship between these variables is strong (according
to Cohen 1988).
Table 2.
Pool unit root test: Summary
Date: 02/22/13 Time: 23:14
Sample: 2008 2012
Series: CC_C1, CC_C2, CC_C3, CC_C4, CC_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -3.16903 0.0008 5 20
Breitung t-stat -3.05474 0.0011 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -0.83964 0.2006 5 20
ADF - Fisher Chi-square 11.0272 0.3554 5 20
PP - Fisher Chi-square 10.5828 0.3909 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 5.00000 0.0000 5 25




** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.

Interpretation:
In order to check mutual stationary between Cash conversion cycle and all related five year data
variable data is computed are normally distributed and these have linear relationship. According
to the table, Pool unit root test Pearson’s r is calculated and significant value p=0.0000<0.05 but
test value which shows that there is stationary relationship between the variables. Hence H
1
is
accepted which means that there is mutual relationship between these variables. The positive
sign of Pearson’s test value shows that there is positive relationship between these variables
which means that increase in Cash conversion cycle may enhance all and vice versa. However
the test value shows that the strength of relationship between these variables is strong (according
to Cohen 1988).


Table- 3.
Pool unit root test: Summary
Date: 02/22/13 Time: 23:14
Sample: 2008 2012
Series: W_C1, W_C2, W_C3, W_C4, W_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -5.27382 0.0000 5 20
Breitung t-stat -2.64339 0.0041 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -1.94700 0.0258 5 20
ADF - Fisher Chi-square 20.7465 0.0229 5 20
PP - Fisher Chi-square 27.0584 0.0025 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 4.07447 0.0000 5 25


** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.

Interpretation:
In order to check mutual stationary between Working capital Management and all related five
year data variable data is computed are normally distributed and these have linear relationship.
According to the table, Pool unit root test Pearson’s r is calculated and significant value
p=0.0000<0.05 but test value which shows that there is stationary relationship between the
variables. Hence H
1
is accepted which means that there is mutual relationship between these
variables. The positive sign of Pearson’s test value shows that there is positive relationship
between these variables which means that increase in Working capital Management may enhance
all and vice versa. However the test value shows that the strength of relationship between these
variables is strong (according to Cohen 1988).






Table-4.
Pool unit root test: Summary
Date: 02/22/13 Time: 23:15
Sample: 2008 2012
Series: GP_C1, GP_C2, GP_C3, GP_C4, GP_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -10.2316 0.0000 5 20
Breitung t-stat -0.00484 0.4981 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -2.89089 0.0019 5 20
ADF - Fisher Chi-square 21.8966 0.0156 5 20
PP - Fisher Chi-square 21.8966 0.0156 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 3.86357 0.0001 5 25


** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.
Interpretation:
In order to check mutual stationary between Gross profit and all related five year data variable
data is computed are normally distributed and these have linear relationship. According to the
table, Pool unit root test Pearson’s r is calculated and significant value p=0.0001<0.05 but test
value which shows that there is stationary relationship between the variables. Hence H
1
is
accepted which means that there is mutual relationship between these variables. The positive
sign of Pearson’s test value shows that there is positive relationship between these variables
which means that increase in Gross profit may enhance all and vice versa. However the test
value shows that the strength of relationship between these variables is strong (according to
Cohen 1988).







Table -5

Pool unit root test: Summary
Date: 02/22/13 Time: 23:15
Sample: 2008 2012
Series: OP_C1, OP_C2, OP_C3, OP_C4, OP_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -6.17498 0.0000 5 20
Breitung t-stat -0.67420 0.2501 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -2.22612 0.0130 5 20
ADF - Fisher Chi-square 19.0700 0.0394 5 20
PP - Fisher Chi-square 19.1450 0.0385 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 3.40395 0.0003 5 25


** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.


Interpretation:
In order to check mutual stationary between Operating Profit and all related five year data
variable data is computed are normally distributed and these have linear relationship. According
to the table, Pool unit root test Pearson’s r is calculated and significant value p=0.0003<0.05 but
test value which shows that there is stationary relationship between the variables. Hence H
1
is
accepted which means that there is mutual relationship between these variables. The positive
sign of Pearson’s test value shows that there is positive relationship between these variables
which means that increase in Operating Profit may enhance all and vice versa. However the test


value shows that the strength of relationship between these variables is strong (according to
Cohen 1988).





Table -6
Pool unit root test: Summary
Date: 02/22/13 Time: 23:16
Sample: 2008 2012
Series: NP_C1, NP_C2, NP_C3, NP_C4, NP_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -4.04710 0.0000 5 20
Breitung t-stat 0.15670 0.5623 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -1.87012 0.0307 5 20
ADF - Fisher Chi-square 17.2294 0.0694 5 20
PP - Fisher Chi-square 20.1327 0.0280 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 5.00001 0.0000 5 25


** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.



Interpretation:
In order to check mutual stationary between Net Profit and all related five year data variable data
is computed are normally distributed and these have linear relationship. According to the table,
Pool unit root test Pearson’s r is calculated and significant value p=0.0000<0.05 but test value
which shows that there is stationary relationship between the variables. Hence H
1
is accepted
which means that there is mutual relationship between these variables. The positive sign of
Pearson’s test value shows that there is positive relationship between these variables which


means that increase in Net Profit may enhance all and vice versa. However the test value shows
that the strength of relationship between these variables is strong (according to Cohen 1988).




Table -7
Pool unit root test: Summary
Date: 02/22/13 Time: 23:17
Sample: 2008 2012
Series: CR_C1, CR_C2, CR_C3, CR_C4, CR_C5
Exogenous variables: Individual effects
Automatic selection of maximum lags
Automatic selection of lags based on SIC: 0
Newey-West bandwidth selection using Bartlett kernel
Balanced observations for each test


Cross-
Method Statistic Prob.** sections Obs
Null: Unit root (assumes common unit root process)
Levin, Lin & Chu t* -5.73861 0.0000 5 20
Breitung t-stat -2.30009 0.0107 5 15

Null: Unit root (assumes individual unit root process)
Im, Pesaran and Shin W-
stat -1.84035 0.0329 5 20
ADF - Fisher Chi-square 19.9183 0.0300 5 20
PP - Fisher Chi-square 28.3810 0.0016 5 20

Null: No unit root (assumes common unit root process)
Hadri Z-stat 3.43482 0.0003 5 25


** Probabilities for Fisher tests are computed using an asympotic Chi
-square distribution. All other tests assume asymptotic normality.



Interpretation:
In order to check mutual stationary between Current Ratio and all related five year data variable
data is computed are normally distributed and these have linear relationship. According to the
table, Pool unit root test Pearson’s r is calculated and significant value p=0.0003<0.05 but test
value which shows that there is stationary relationship between the variables. Hence H
1
is
accepted which means that there is mutual relationship between these variables. The positive
sign of Pearson’s test value shows that there is positive relationship between these variables
which means that increase in Current Ratio may enhance all and vice versa. However the test


value shows that the strength of relationship between these variables is strong (according to
Cohen 1988).




Table -8
Dependent Variable: GP?
Method: Pooled Least Squares
Date: 02/22/13 Time: 23:18
Sample: 2008 2012
Included observations: 5
Cross-sections included: 5
Total pool (balanced) observations: 25


Variable
Coefficie
nt Std. Error t-Statistic Prob.


C
-
0.427796 12.78810 -0.033453 0.9736
CC? 5.04E-07 3.88E-07 1.299730 0.2085
CR? 7.117847 9.598411 0.741565 0.4670
AV? 1.301717 0.499183 2.607697 0.0168
W? -6.34E-07 2.25E-06 -0.281403 0.7813


R-squared 0.302865 Mean dependent var 17.13492
Adjusted R-squared 0.163438 S.D. dependent var 12.67272
S.E. of regression 11.59095 Akaike info criterion 7.915182
Sum squared resid 2687.000 Schwarz criterion 8.158957
Log likelihood
-
93.93977 F-statistic 2.172210
Durbin-Watson stat 0.749998 Prob(F-statistic) 0.109227


Interpretation
In order to predict causal relationship between combination of variable Gross Profit from
Average collection period, cash conversion cycle, current ratio, and working capital management
multiple regression analysis is computed. According to table, P=0.9736>0.05 and F=0.1092,
P=0.9736 (in ANOVA table) which shows that there is not a significant relationship between
these variables, hence H
o
is accepted. The beta coefficients are presented in last table. Note that
no significantly. The adjusted R square value was 0.1634. This indicates that 16.34% of the
variance in Gross Profit was explained by the model according to Cohen (1988).








Table -9
Dependent Variable: OP?
Method: Pooled Least Squares
Date: 02/22/13 Time: 23:19
Sample: 2008 2012
Included observations: 5
Cross-sections included: 5
Total pool (balanced) observations: 25


Variable
Coefficie
nt Std. Error t-Statistic Prob.


C
-
181.3674 151.0493 -1.200717 0.2439
CC? -4.34E-07 4.58E-06 -0.094888 0.9253
CR? 122.3517 113.3736 1.079190 0.2933
AV? 15.53199 5.896199 2.634238 0.0159
W? -1.58E-05 2.66E-05 -0.593665 0.5594


R-squared 0.263999 Mean dependent var 65.34501
Adjusted R-squared 0.116799 S.D. dependent var 145.6806
S.E. of regression 136.9089 Akaike info criterion 12.85336
Sum squared resid 374880.7 Schwarz criterion 13.09714
Log likelihood
-
155.6671 F-statistic 1.793470
Durbin-Watson stat 1.152752 Prob(F-statistic) 0.169779


Interpretation
In order to predict causal relationship between combination of variable Operating Profit from
Average collection period, cash conversion cycle, current ratio, and working capital management
multiple regression analysis is computed. According to table, P=0.2439>0.05 and F=0.1697,
P=0.2439 (in ANOVA table) which shows that there is not a significant relationship between
these variables, hence H
o
is accepted. The beta coefficients are presented in last table. Note that
no significantly. The adjusted R square value was 0.1167. This indicates that 11.67% of the
variance in operating Profit was explained by the model according to Cohen (1988).








Table -10
Dependent Variable: NP?
Method: Pooled Least Squares
Date: 02/22/13 Time: 23:19
Sample: 2008 2012
Included observations: 5
Cross-sections included: 5
Total pool (balanced) observations: 25


Variable
Coefficie
nt Std. Error t-Statistic Prob.


C
-
2.978015 6.021389 -0.494573 0.6263
CC? 5.08E-07 1.82E-07 2.785295 0.0114
CR? 2.590006 4.519495 0.573074 0.5730
AV? 0.787805 0.235044 3.351726 0.0032
W? 1.17E-06 1.06E-06 1.102894 0.2832


R-squared 0.536343 Mean dependent var 5.006942
Adjusted R-squared 0.443611 S.D. dependent var 7.316783
S.E. of regression 5.457697 Akaike info criterion 6.408787
Sum squared resid 595.7291 Schwarz criterion 6.652562
Log likelihood
-
75.10984 F-statistic 5.783823
Durbin-Watson stat 0.893859 Prob(F-statistic) 0.002922


Interpretation
In order to predict causal relationship between combination of variable Net Profit from Average
collection period, cash conversion cycle, current ratio, and working capital management multiple
regression analysis is computed. According to table, P=0.6263>0.05 and F=0.0029, P=0.6263 (in
ANOVA table) which shows that there is not a significant relationship between these variables,
hence H
o
is accepted. The beta coefficients are presented in last table. Note that no significantly.
The adjusted R square value was 0.4436. This indicates that 44.36% of the variance in Net Profit
was explained by the model according to Cohen (1988).














Chapter #6
Referencing:

Afza, A. R. (2010). Working Capital Management and Corporate Performance of Manufacturing
Sector in Pakistan. issued 47 .
Ajilore, F. a. (2009). Working capital management and corporate profitability: evidence from
panel data analysis of. volume 3 , 73-84.
Appuhami, R. (2008). volume 4. The Impact of Firms’ Capital Expenditure on Working Capital
Management: An Empirical Study across Industries in Thailand , 8-12.
Bhaskar Bagchi1, J. C. (2012). Influence of Working Capital Management on Profitability: A
Study on indian FMCG companies. vol - 7 ,22 ..
Dr Ioannis Lazaridis, D. I. (2004). “The relationship between working capital management and
profitability of listed companies in the Athens Stock Exchange”.
Elijelly, A. M. (2004). Liqudity- Profitability Trade of An empirical investigation in an emerging
market. vol- 14 , 48-61.
Gerald Epstein, I. G. (2003). Capital Management Techniques In Developing Countries: An
Assessment of Experiences from the 1990's and Lessons For the Future. POLITICAL
ECONOMY RESEARCH INSTITUTE .
Gill. (2010:). The Relationship Between Working Capital Management And
ProfitabilityEvidence From The United States. 1 Business and Economics Journal, , Volume
2010: BEJ-10.
Gompers, P. A. (1995). optamal investment,monitoring,and the staging of venture capital. the
journal of finance , vol. 50 (no.5).
James Ghthrie, I. (2004). Accounting Review. Capital reporting in developing , 251-268.
Leland, H. (2004). Journal 2.2. Prediction of default probabilities in sructural of investing
management .
Maji, G. a. (2003). Working capital management efficiency: a study on the Indian cement
industry. The Institute of Costand Works Accountants of India.
Martínez Solano, P. J. (2010). EFFECTS OF WORKING CAPITAL MANAGEMENT ON SME
profitability.


NAIMULBARI, M. K. (2012). A RESEARCH PAPER ON “THE IMPACT OF WORKING
CAPITAL MANAGEMENT ONPROFITABILITY” OF PHARMACEUTICALS SECTOR IN
BANGLADESH. INDEPENDENT UNIVERSITY, BANGLADESH .
Nasr, A. R. (March 2003). 279-300.
OWOLABI, S. A. (n.d.). THE STUDY OF WORKING CAPITAL MANAGEMENT AS A
FINANCIAL STRATEGY. volume2 (2) , 16-26.
Padachi, K. (2006). Trend in capital managment and its impect on firm performance. Vol-2 , 45-
58.
Raheman, M. N. (2003). Working Capital Management And Profitability – Case Of. Vol.3 No.1.
, 279-300.
Raza, M. A. (2012). The Optimal Relationship of Cash Conversion Cycle with Firm Size and
Profitability. Vol,2 No 4.
Saad, N. E. (2010). Working Capital Management: The Effect of Market Valuation and
profitability in pakistan. Vol.5, No11 .
Sana, S. A. (2006). Impact of Working Capital Management on the Pofitability of oil and gas
sector in pkistan. vol,15.no 3 , 301-307.
Sharma, R. k. (2008). Profibility of Bombay stock exchange , 254-236.
Simko, J. B. (2002). The Balance Sheet as an Earnings Management Constraint. Vol,77 , 1-27.
Soekhoe, S. G. ( 2012). THE EFFECTS OF WORKING CAPITAL MANAGEMENT ON THE
PROFITABILITY OF DUTCH LISTED FIRMS.
soenen, S. a. (1998). Efficiency of working capital management and corporate. volume 8 .
Uyar, A. (2009). The relationship of cash conversion cycle with firm size and profitability: an
empirical investigation in Turkey. International Research Journal of Finance and Economics.
issuense 24 .
Vida Mojtahedzadeh, S. H. (2011). The Relationship between Working Capital Management and
profitability of the listed company tahran Stock Exchange. Issue 76 .
visscher, W. a. (1998). Industry practice relating to aggressiveness/conservative working capital
policies. volume 11 (2) .