Search This Blog

Loading...

Share It

Friday, April 27, 2012

Cement industry of Pakistan


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).







0 comments:

Twitter Delicious Facebook Digg Stumbleupon Favorites More