Full & Final CF Report

7/29/2019 Full & Final CF Report

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Abstract

This paper focuses on investigating the effect of the revenue, Expenses, Liquidity, leverage,

interest rate, GDP growth & Large Scale Manufacturing Growth on the Profitability of the firm

of Fauji Cement Company. To proceed with this, the capital structure of this firm has been

analyzed by adopting an econometric framework over a period of twenty quarters. We used

pooled regression in order to check the reliability of our model and found that the, liquidity has

positive impact on the firms profitability and DFL. These results might provide a useful guide to

the Cement firms managers in designing the strategies in a way which may boost profit.

Introduction

Liquidity refers to how quickly and cheaply an asset can be converted into cash. Money (in the

form of cash) is the most liquid asset. Assets that generally can only be sold after a long

exhaustive search for a buyer are known as illiquid.

In business, economics or investment, market liquidity is an asset's ability to be sold without

causing a significant movement in the price and with minimum loss of value. Money, or cash on

hand, is the most liquid asset. An act of exchange of a less liquid asset with a more liquid asset iscalled liquidation. Liquidity also refers both to a business's ability to meet its payment

obligations, in terms of possessing sufficient liquid assets, and to such assets themselves. A

liquid asset has some or more of the following features. It can be sold rapidly, with minimal loss

of value, any time within market hours. The essential characteristic of a liquid market is that

there are ready and willing buyers and sellers at all times. Another elegant definition of liquidity

is the probability that the next trade is executed at a price equal to the last one. A market may be

considered deeply liquid if there are ready and willing buyers and sellers in large quantities. This

is related to the concept ofmarket depth that can be measured as the units that can be sold or

bought for a given price impact. The opposite concept is that ofmarket breadth measured as the

price impact per unit of liquidity.

Speculators and market makers are key contributors to the liquidity of a market, or asset.

Speculators and market makers are individuals or institutions that seek to profit from anticipated
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increases or decreases in a particular market price. By doing this, they provide the capital needed

to facilitate the liquidity. The risk of illiquidity need not apply only to individual investments:

whole portfolios are subject to market risk. Financial institutions and asset managers that oversee

portfolios are subject to what is called "structural" and "contingent" liquidity risk. Structural

liquidity risk, sometimes called funding liquidity risk, is the risk associated with funding asset

portfolios in the normal course of business. Contingent liquidity risk is the risk associated with

finding additional funds or replacing maturing liabilities under potential, future stressed market

conditions. When a central banktries to influence the liquidity (supply) of money, this process is

known as open market operations.

Liquidity is a prime concern in a banking environment and a shortage of liquidity has often been

a trigger for bankfailures. Holding assets in a highly liquid form tends to reduce the income

from that asset (cash, for example, is the most liquid asset of all but pays no interest) so banks

will try to reduce liquid assets as far as possible. However, a bank without sufficient liquidity to

meet the demands of their depositors risks experiencing a bank run. The result is that most banks

now try to forecast their liquidity requirements and maintain emergency standby credit lines at

other banks. Banking regulators also view liquidity as a major concern.

The Background of Pakistans Cement Industry

The cement industry has grown leaps and bounds in the last few years from a total capacity of a

mere 15mntpa in 2003 to a generously growing sector of 36mntpa in 2007; cement industry has

become one of the most flourishing sectors in the country. Being an integral part of the growing

economy of Pakistan, the cement industry responded well to the high asks of the market and

looks prepared to do so in the future too. Dynamics have changed considerably in the past 5

years; a supply glut which lasted for almost a decade in the 90s, finally disappeared when thegovernment of Pakistan aggressively approached the improvement of infrastructure in the

country. Combined with a hike in demand for housing, the industry is in for good times.

Pakistan secured 5th position because of high demand of cement in nearby countries and by

capturing new markets such as African countries, Qatar & Iraq. Pakistan could achieve the mark

of 13 to 14 million tonnes exports by the end of the fiscal year keeping in view Indian market
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which has once again started importing cement from Pakistan. The export of cement from

Pakistan to India showed a sharp decline after Mumbai attacks.

SECTOR OUTLOOK

GDP

GDP growth has a high correlation with cement consumption of a country. Pakistans GDP

growth has averaged around 7% in the past 4 years and in the same period domestic demand for

cement rose at an average of 15% per annum. The per capita consumption of cement in 2003 was

75kg which increased briskly to 110kg in 2007. Despite such hefty increase, per capita

consumption remains to be one of the lowest in the region, which leaves a lot of room for

improvement.

0

5

10

15

20

25

30

China Japan Thailand Turkey Pakistan Germany

Country Wise Production (mtpa)


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PSDP

PSDP (Public Sector Development Projects) has been a trigger in the revival of the cement

industry in Pakistan. Since the Government initiated an expansive plan for improvement ininfrastructure, the industry has been bearing its fruit. The expenditure on PSDP has bloated from

PKR 82bn in FY03 to PKR 520bn in FY08, an increase of more than five folds. Its high

correlation with cement demand exhibited prosperity for the industry.

The industry responded well to this sudden increase in demand as major companies underwent

timely expansion plans and besides a few glitches, the demand was always met successfully. The

cement production in the country went up from 11mntpa in FY03 to 24mntpa by FY07. These

expansions made sure that the high expenditure on construction activity did not convert into a

negative balance of trade hence it encouraged the government to continue its approach. We

expect the PSDP to increase in the coming years, although at a lower rate. The PSDP expenditure

is forecasted to cross the PKR 700bn mark by FY12 and if the recent surge is anything to go by it

may well surpass our expectations. As mentioned before the cement industry is well equipped to

handle this growth due to excess supply, the current capacity of 36mn tons per annum is

expected to elevate to 55mn tons per annum over the next 5 years. All the economic indicators

point in the right direction for the cement Industry and we believe industrys production will

grow at a robust rate of 12% per annum for the next 5 years.


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HOUSING SECTOR

Housing sector is one of the major drivers of growth for the cement industry. GOP has been very

active in encouraging the private sector investment in real estate. Incentives announced for thehousing sector include the improvement in availability of housing finance by encouraging

commercial banks to extend housing loans. This factor is again closely linked with GDP growth

in the country, as the economy blossoms the housing sector should thrive along with it. Having

one of the lowest cement prices in the region and emergence of international builders on the local

scenario should further push for a smooth growth rate in the housing sector.

Current demand for housing is estimated at 570,000 units/annum vis--vis about 300,000 units

being built annually, mostly in urban areas. The housing backlog, estimated at 4.3 mn units in

1998, has thus increased to around 6.5 mn units in 2006 and is likely to increase further. Thus,

there is a lot of scope for heavy escalation in real estate business in Pakistan to meet this

backlog. The financial institutions in the country are showing keen interest in private housing

sector too.

DAMS

Construction of dams is another avenue of profitability for cement manufacturers. Although the

impact is not as big as the chain effect of PSDP and housing sector, it is still significant. The

government is considering building 5 major dams out of which 3 are in Punjab and 1 each in

Sindh and NWFP.

All these factors indicate that dams will become inevitable for the country and government will

soon commence their construction. The total cement requirement for these projects is

approximately 15mn tons and this will be spread over 7-10 years (approximately 1.5 - 2.1mntpa

additional consumption), hence we do not expect a large impact instead we think individual

manufacturer will benefit over a long period of time.


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Review of Literature


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Variable description, Methodology and Sample

This section presents the measurement of the variable and discussion of different measures of the

variables, null hypothesis and methodology used to test the hypothesis and provides information

about the source of data.

Explanation of Variables

We use eleven variables in the final model of our study namely Profitability, sales revenue, Cost

of goods sold, Selling expenses, Administrative expenses, Financial charges, Quick ratio, Total

Debt to Total Assets, Average Market Interest Rate, GDP growth, Large Scale Manufacturing

Growth Rate of Pakistan in our econometric model (as explained below) to identify their relative

impact (negative or positive) on the profitability of the Cement Company of Pakistan. The

measurement of variables such as profitability, itself is a hot debate among the financial

economics as practitioners. We apply debt ratio also as a measure of leverage but it doesnt make

our model significant so we follow the existing literature as mention and adopted simple but

effective measures of the said variable as used in Mr. Jamal Zubairi research paper.

Profitability (as Dependent Variable)

Profitability refers to the ability of a company to earn profit. Profitability is expressed in terms of

several popular numbers that measure one of two generic types of performance: "how much they

make with what they've got" and "how much they make from what they take in". We take

profitability as Net Profit Margin. The Net profit margin tells you how much profit a company

makes for every $1 it generates in revenue or sales. Profit margins vary by industry, but all elsebeing equal, the higher a company's profit margin compared to its competitors, the better.
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Sales Growth (as Independent Variable)

Sales revenue is the total amount of money that the firm has earned from the sale of all its goods

and services during a given time period. This is usually six months or a year. If a firm produced

just one product or service the sales revenue would be the price of the product multiplied by thenumber of the product sold. In the case of more than one product or service the revenue from

each needs to be added together. The figure for sales revenue in the profit & loss account does

not necessarily mean that the firm has received all that money because although they may have

sold that quantity of the product they may still be owed some of the money as debtors.

Cost of goods sold (as Independent Variable)

An income statement figure which reflects the cost of obtaining raw materials and producing

finished goods that are sold to consumers. Cost of goods sold (COGS) includes the direct costs

attributable to the production of the goods sold by a company. This amount includes the

materials cost used in creating the goods along with the direct labor costs used to produce the

good. It excludes indirect expenses such as distribution costs and sales force costs. COGS appear

on the income statement and can be deducted from revenue to calculate a company's gross

margin.

Selling expenses (as Independent Variable)

Selling expenses represent expenses needed to sell products (e.g., sales salaries, commissions

and travel expenses, advertising, freight, shipping, depreciation of sales store buildings and

equipment). Cost incurred to sell (e.g., advertising, salesperson commission) or distribute (e.g.,

freight-out ) merchandise. It is one of the types of operating expenses and is a period cost.

Direct selling expenses are expenses that can be directly linked to the sale of a specific unit such

as credit, warranty and advertising expenses. Indirect selling expenses are expenses which cannot

be directly linked to the sale of a specific unit, but which are proportionally allocated to all units

sold during a certain period, such as telephone, interest and postal charges. General and

administrative expenses include salaries of non-sales personnel, rent, heat and lights.
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Administrative expenses (as Independent Variable)

The expenses that an organization incurs not directly tied to a specific function such as

manufacturing/production or sales. These expenses are related to the organization as a whole as

opposed to an individual department; also referred to as "administrative cost".

An expense related to the enterprise as a whole, as opposed to expenses related to specific

functions such as manufacturing. Administrative Expense is the "A" of the major income

statement cost/expense category "SG & A" (See Selling, general, and administrative expenses).

Financial charges (as Independent Variable)

The finance charge, or total dollar amount you pay to borrow, includes the interest you pay plus

any fees for arranging the loan. Total cost ofborrowing, including interest charges, commitment

fees, and other charges paid by the borrower for availing the loan facility.

A finance charge is expressed as an annual percentage rate (APR) of the amount you owe, which

allows you to compare the costs of different loans. The cost of obtaining and using credit;

typically applied to credit cards or other consumer loans, such as car loans. Finance charges

typically include interest due on outstanding balances as well as fees for special services, such as

cash advances. The federal Truth in Lending Act requires that the finance charges must be

disclosed to customers before issuing credit.

Quick ratio (as Independent Variable)

An indicator of a company's short-term liquidity. The quick ratio measures a company's ability to

meet its short-term obligations with its most liquid assets.

Also known as the "acid-test ratio" or the "quick assets ratio".
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In finance, the Acid-test or quick ratio or liquid ratio measures the ability of a company to use its

near cash or quick assets to immediately extinguish or retire its current liabilities. Quick assets

include those current assets that presumably can be quickly converted to cash at close to their

book values.

Total Debt to Total Assets (as Independent Variable)

Measure of a firm's assets financed by debt and, therefore, a measure of its financial risk. The

lower this ratio, generally the better off the firm. A metric used to measure a company's financial

risk by determining how much of the company's assets have been financed by debt.

The debt to total assets ratio is an indicator of financial leverage. It tells you the percentage of

total assets that were financed by creditors, liabilities, debt. A debt ratio of greater than 1

indicates that a company has more debt than assets; meanwhile, a debt ratio of less than 1

indicates that a company has more assets than debt. Used in conjunction with other measures of

financial health, the debt ratio can help investors determine a company's level of risk.

Average Market Interest Rate (as Independent Variable)

Interest is a fee paid on borrowed assets. It is the price paid for the use of borrowed money or

money earned by deposited funds. Assets that are sometimes lent with interest include money,

shares, consumer goods through hire purchase, major assets such as aircraft, and even entire

factories in finance lease arrangements. The interest is calculated upon the value of the assets in

the same manner as upon money. Interest can be thought of as "rent of money". When money is

deposited in a bank, interest is typically paid to the depositor as a percentage of the amount

deposited; when money is borrowed, interest is typically paid to the lender as a percentage of the
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amount owed. The percentage of the principal that is paid as a fee over a certain period of time

(typically one month or year), is called the interest rate.

Interest is compensation to the lender for the risk of not being paid back, and for forgoing other

useful investments that could have been made with the loaned asset. These forgone investments

are known as the opportunity cost. Instead of the lender using the assets directly, they are

advanced to the borrower. The borrower then enjoys the benefit of using the assets ahead of the

effort required to obtain them, while the lender enjoys the benefit of the fee paid by the borrower

for the privilege. The amount lent, or the value of the assets lent, is called the principal. This

principal value is held by the borrower on credit. Interest is therefore the price of credit, not the

price of money as it is commonly believed to be.

GDP growth (as Independent Variable)

GDP (Gross Domestic Product) is the total dollar amount of all goods and services produced.

The growth rate is the percentage increase or decrease of GDP from the previous measurement

cycle. Even though the BEA reports quarterly, the growth rate is annualized so it can be

compared to the previous year. The GDP growth rate is driven by retail expenditures,

government spending, exports and inventory levels. Rises in imports will negatively affect GDP

growth.

The GDP growth rate is the most important indicator of economic health. If GDP is growing, so

will business, jobs and personal income. If GDP is slowing down, then businesses will hold off

investing in new purchases and hiring new employees, waiting to see if the economy will

improve. This, in turn, can easily further depress GDP and consumers have less money to spend

on purchases. If the GDP growth rate actually turns negative, then the U.S. economy is heading

towards a recession.

Economic growth can either be positive or negative. Negative growth can also be referred to by

saying that the economy is shrinking. Negative growth is associated with economic recession and

economic depression.
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Economic growth is a term used to indicate the increase of total GDP. It is often measured as the

rate of change ofgross domestic product (GDP). Economic growth refers only to the quantity of

goods and services produced; it says nothing about the way in which they are produced.

Economic Development, a related term, refers to change in the way goods and services are

produced; positive economic development involves the introduction of more efficient or

"productive" technologies or forms of social organization.

Large Scale Manufacturing Growth Rate (as Independent Variable)

The manufacturing sector grew at an average rate of 8 percent from the sixties to the eighties, but

fell to 3.9 percent during the nineties. This was mainly caused by reduction in investment levels

due to lack of continuity and consistency in policies. Political instability law and order position

in the major industrial centers, transport bottlenecks, as well as unreliability and inadequate

availability of power supply at affordable rates were additional factors pulling down the sector.

The sector has shown impressive recovery recently and has grown at a compound rate of 10.9

percent per annum during 2001 05, with Large Scale Manufacturing (LSM) growing even

faster, becoming 19.9% in 2005. The contribution of Large-Scale Manufacturing at basic prices

stand at Rs 844 billion as compared with Rs 264 billion in 2000-01, figures from the Census of

Large-Scale Manufacturing Industries (CMI) 2005-06 show.

LSM contribution to GDP also called as Gross Value Added (GVA) at producers prices has

been estimated at Rs 912 billion as compared with the previous Census 2000-01 amount of Rs

280 billion. Political and macroeconomic stability, rationalization of tariffs, increase in investments,

improved utilization of productive capacity, and growth in demand for manufactured products,

resulting from higher exports and consumer financing have been the major factors leading to this

growth.
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Methodology and Hypotheses

The main object of the study is to know whether the revenue, Expenses, Liquidity, leverage,

interest rate, GDP growth & Large Scale Manufacturing Growth affects the profitability of the

firms in the automobile sector of Pakistan.

Hypotheses

1. Hypothesis (Ho): Profitability of the firm is not significantly positively affected by theSales Growth.

2. Hypothesis (Ho): Profitability of the firm is not drastically affected by the Cost of Sales.3. Hypothesis (Ho): Profitability of the firm is not significantly affected by the Selling

Expenses.

4. Hypothesis (Ho): Profitability of the firm is not considerably affected by theAdministrative Expenses.

5. Hypothesis (Ho): Profitability of the firm is not extensively affected by the FinanceCost.

6. Hypothesis (Ho): Short Term Liquidity does not have a significant impact on theProfitability of the firm.

7. Hypothesis (Ho): Profitability of the firm is not significantly affected by the Debt Ratio.8. Hypothesis (Ho): Market Interest Rate Profitability of the firm is not significantly

affected by the Interest Rate.

9. Hypothesis (Ho): GDP of the country doesnt have a significant impact on firmprofitability.

10.Hypothesis (Ho): Profitability of the firm is not significantly affected by the LSMGrowth.


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We ran the panel regression to test the above hypotheses. Panel data analysis facilitates analysis

of cross-sectional and time series data. The pooled regression, also called the Constant

Coefficients model, is one where both intercepts and slopes are assumed constant. The cross

section company data and time series data are pooled together in a single column assuming that

there is no significant cross section or inter temporal effects. Specifically, the econometric model

is defined as follows:

LSMGDPMIRDA

QRFCADESECGSSGP

10987

6543210

Where

P: Profitability

SG: Sales Growth

CGS: Cost of Goods Sold

SE: Selling Expenses

ADE: Administrative Expenses

FC: Finance Cost

QR: Quick Ratio

DA: Total Debt to Total Assets

MIR: Market Interest Rate

GDP: Gross Domestic Product

LSM: Large Scale Manufacturing


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The possible expected effects of the said variables on firms profitability are reported in Table 1.

Variable Measure Expected Relationship with

Profitability

Sales Growth Qtr to Qtr in % of Sales Positive

COGS Qtr to Qtr in % of Sales Negative

Selling Expenses Qtr to Qtr in % of Sales No Effect

Administrative Expenses Qtr to Qtr in % of Sales Negative

Finance Cost Qtr to Qtr in % of Sales Positive/Negative

Quick Ratio (Current Assets

Inventories)/Current

Liabilities

Positive

Total Debt to Total Assets Total Liabilities/Total Assets Positive/No Effect

Average Market Interest Qtr to Qtr in % No Effect

GDP Growth Qtr to Qtr in % Positive

Large Scale Manufacturing Qtr to Qtr in % Positive

Regression Analysis Results

Using pooled regression technique, we ran the regression of the profitability on sales revenue, Cost of

goods sold, Selling expenses, Administrative expenses, Financial charges, Quick ratio, TotalDebt to Total Assets, Average Market Interest Rate, GDP growth, Large Scale Manufacturing

Growth Rate with an aim to investigate whether these ten variables have or do not have a significant

impact. The regression estimates thus provide the information about the elasticity rather than the slope of

the relevant variables. The estimated results are reported in Table 2.


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Dependent Variable: NET_PROFIT_MARGIN

Method: Least Squares

Date: 12/13/09 Time: 10:32

Sample: 1 20

Included observations: 20

Variable Coefficient Std. Error t-Statistic Prob.

C 0.139343 25.90398 0.005379 0.9958

I__Y_TO_Y_GROWTH_IN_SALE 0.057609 0.118870 0.484638 0.6395

II__COGS____OF_SALES_REV -0.002569 0.109091 -0.023552 0.9817

III__SELL_EXP____OF_SALE 12.31759 5.339808 2.306748 0.0465

IV__ADM_EXP__OF_SALES_ -11.37144 5.285597 -2.151401 0.0599

V__FIN_CHARGES____OF_SAL 0.894365 0.921052 0.971026 0.3569

VI__QUICK_RATIO__IN___ -0.034363 0.028027 -1.226087 0.2513

VII__T_D_TO_T_A__IN___ 0.160098 0.218699 0.732046 0.4828

VIII__AVG_MKT_I____ 1.142096 1.337310 0.854025 0.4152

IX__GDP_GROWTH____ -1.893334 1.531132 -1.236558 0.2475

X__LSM_GROWTH_RATE____ 0.979050 6.600098 0.148339 0.8853

R-squared 0.614542 Mean dependent var 13.99626

Adjusted R-squared 0.186255 S.D. dependent var 5.616816

S.E. of regression 5.066807 Akaike info criterion 6.384791

Sum squared resid 231.0528 Schwarz criterion 6.932444

Log likelihood -52.84791 F-statistic 1.434884

Durbin-Watson stat 1.487576 Prob(F-statistic) 0.299224


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It can be observed from the table that estimated value of the R-square is approximately 0.61. It

implies that the 61 percent variation in profitability of the firms is jointly determined by the said

10 variables and the remaining 39 percent is unexplained. The value of F-statistic (1.434884)

indicates that the overall model is good. The Durbin-Watson statistic is also close to 1.5 that

implies that the successive values of estimated residuals are not dependent on each other. It

means that there is strong evidence to accept the null hypothesis that there is no autocorrelation

problem in the estimated model.

Regarding the significance of individual variables, the empirical results show that the firms

profitability is not significantly associated with the Sales Growth. The p-value is 0.639, as can be

seen from the table, implies that the null hypothesis that the Sales Growth has no significant

impact on profitability, is accepted at 5 percent level of significance. A one percent increase in

Sales Growth leads to about 0.06percent growth in profitability, as the estimated coefficient of

year to year sales growth.

It can be observed that the profitability of the firm is not drastically affected by the cost of sales.

The p-value is .981, as can be seen from the above table, implies that at 5 percent level of

significance we failed to reject null hypotheses and it tells that cost of sales has no drastic impact

on profitability. A one percent increase in Cost of Sales leads to about a negligible .2 percent

decline in profitability.

Regarding the significance of Selling Expense, the empirical results show that the firm

profitability is not significantly associated with the selling expenses. The p-value is 0.046, as can

be seen from the table, implies that the null hypothesis that the selling expenses has significant

impact on profitability, is rejected at 5 percent level of significance. A one percent increase in

Sales Growth leads to about 12.31 percent growth in profitability, as the estimated coefficient of

Selling Expenses. The relationship between profitability and selling expense is positive as seen

in the table as coefficient of selling expenses.

It can be observed that the profitability of the firm is not drastically affected by the

Administrative expenses. The p-value is .059, as can be seen from the above table, implies that at


19/26

5 percent level of significance we failed to reject null hypotheses and it tells that administrative

expenses has no severe impact on profitability. A one percent increase in administrative expenses

leads to about an 11.37 percent decline in profitability. So this also tells that the administrative

expenses have a negative relationship with profitability.

An interesting finding in this research is that the profitability of the cement company is

positively and significantly related to the financial charges of the firm. It is noticeable that the

coefficient of financial charges is positive which tells that the relationship between the financial

charges and profitability of the firm is positive. A one percentage increase in the financial

charges of the firms leads to almost 0.89 percent growth in profitability of the firm. Since the p-

value is 0.356 so we can conclude that at 5 percent level of significance we failed to reject the

null hypotheses as came on the conclusion that financial charges has no significant impact on the

profitability of the firm.

The estimated model also shows that there is no statistical significant association between the

profitability of the cement company and the quick ratio. On the one hand, the estimated

coefficient of the quick ratio is negative which tells that a one percent increase in the quick ratio

will reduce profitability of the firm by 0.034 percent, and on the other hand, the estimated p-

value is 0.251 which tells that we are not able to reject the null hypothesis that the quick ratio has

no statistical significant effect on the profitability.

As it is also clear from the pooled regression table that the coefficient of total debt to total assets

is positive which shows that the relationship between the total debt to total assets and

profitability is positive. On the other hand we see that the p-value of total debt to total assets is

0.482 and we see that at 5 percent level of significance we accept the null hypotheses and

conclude that the total debt to total assets have no significant effect on the profitability of the

firm. A one percent increase in the total debt to total assets will increase the profitability of the

firm by 0.160 percent.

Regarding the significance of Average Market Interest, the empirical results show that the firm

profitability is not significantly associated with the average market interest. The p-value is 0.415,


20/26

as can be seen from the table, implies that the null hypothesis that the average market interest has

no considerable impact on profitability, is accepted at 5 percent level of significance. A one

percent increase in average market interest leads to about 1.41 percent growth in profitability, as

the estimated coefficient of average market interest. The relationship between profitability and

average market interest is positive as seen in the table as coefficient of selling expenses.

The estimated model also shows that there is no statistical significant association between the

profitability of the cement company and the GDP growth. On the one hand, the estimated

coefficient of the GDP is negative which tells that a one percent increase in the GDP will reduce

profitability of the firm by 1.89 percent, and on the other hand, the estimated p-value is 0.247

which tells that we are not able to reject the null hypothesis that the GDP has no statistical major

effect on the profitability. Since the GDP coefficient is negative as well this tells that the

relationship between GDP and profitability of the firm is negative.

It can be observed that the profitability of the firm is not drastically affected by the LSM growth.

The p-value is 0.885, as can be seen from the above table, implies that at 5 percent level of

significance we failed to reject null hypotheses and it tells that LSM growth has no drastic

impact on profitability. A one percent increase in LSM growth leads to about a 0.979 percent

increase in profitability.


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Conclusion and Policy Implications


22/26

Bibliography


23/26

Annexure

Income Statement and Balance Sheet

Income Statement1Q 04-

052Q 04-

053Q 04-

054Q 04-

051Q 05-

062Q 05-

06

Sales 992560 890807 909194 1128800 1306743 1459544

Less: Government Levies 272275 250657 235070 300216 321982 355520

Less: Cost of Sales 444354 397270 422130 503811 492759 539697

Gross Profit 279930 242879 233992 324774 492001 564327

Other Income 6038 3104 1182 890 6594 9938

285968 245984 235174 325663 498596 574265

Distribution Cost 4866 5883 4746 5836 7260 9793

Administrative Expenses 7466 11320 12077 11428 11903 23823

Other Operating

Expenses

9114 8645 12434 20626 23360

Profit From Operations 267596 219665 209705 295965 458805 517289

Finance Cost 67639 49153 45989 66852 67381 78179

Net Profit Before

Taxation

195696 170511 163715 229115 391424 439110

Taxation Current 4060 3440 3600 4550 5600 6400

Taxation Deferred 55392 46173 55468 5864 126012 132074

Net Profit After Taxation 136243 120898 104647 148701 259812 300636Average Market Interest Rates, LSM Growth and GDP Growth

1Q 04-05

2Q 04-05

3Q 04-05

4Q 04-05

1Q 05-06

2Q 05-06

Avg. Market Interest

Rates

7.75 5.96 6.47 5.18 10.14 9.68

LSM growth 4.98 0.05 0.05 0.05 0.02 0.02

GDP growth 2.25 2.25 2.25 2.25 1.45 1.45

Balance Sheet

1Q 04-

05

2Q 04-

05

3Q 04-

05

4Q 04-

05

1Q 05-

06

2Q 05-

06Current Assets 705968 1148111 721838 1113721 940294 1023039

Inventory / Stock in Trade 59350 99955 91380 55931 58067 67282

Current Liabilities 981156 1295297 1004746 1206945 933617 1126109

Total Liabilities 3862007 2839306 3572960 3774164 3177913 3004048

Total Assets 5937384 6330878 5873883 6233788 5887349 5822697


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Income Statement

3Q 05-06

4Q 05-06

1Q 06-07

2Q 06-07

3Q 06-07

4Q 06-07

1Q 07-08

Sales 1329872 1587297 1473219 1042043 1085203 1179570 1168580

Less: Government

Levies

320403 399413 375323 306040 297875 337514 323337

Less: Cost of Sales 492468 570102 607805 523033 554408 686539 680111

Gross Profit 517001 617781 490091 212970 232920 155517 165132

Other Income 10152 16639 22176 17278 17852 16529 11004

527153 634421 512266 230248 250772 172046 176136

Distribution Cost 8318 6324 9740 7180 6514 17211 7445

Administrative Expenses 14653 16250 18098 14778 14051 24376 22114

Other Operating

Expenses

21948 28192 29483 10657 12348 5610 7367

Profit From Operations 482234 583655 454946 197633 217859 124849 139210Finance Cost 62861 55875 57136 53849 51569 44868 43657

Net Profit Before

Taxation

419373 527780 397810 143784 166290 79981 95553

Taxation Current 3500 5931 5500 3700 3900 4220 4226

Taxation Deferred 127340 167094 123334 42963 60339 102099 28338

Net Profit After Taxation 288533 354755 268976 97121 102051 177860 62989

Average Market Interest Rates, LSM Growth and GDP Growth

3Q 05-06

4Q 05-06

1Q 06-07

2Q 06-07

3Q 06-07

4Q 06-07

1Q 07-08


Rates

10.02 9.18 10.49 11.08 10.57 10.63 11.66

LSM growth 0.02 0.02 0.02 0.02 0.02 0.02 0.01

GDP growth 1.45 1.45 1.70 1.70 1.70 1.70 1.03

Balance Sheet

3Q 05-06

4Q 05-06

1Q 06-07

2Q 06-07

3Q 06-07

4Q 06-07

1Q 07-08

Current Assets 1105783 1579381 1388840 1588593 1208793 1953527 1970285

Inventory / Stock in

Trade

76496 145090 142920 140610 201099 183309 160032

Current Liabilities 1318600 1267198 912551 1140476 893375 1442287 1590726

Total Liabilities 2830182 2915491 2409219 2680943 2220546 2665482 2568101

Total Assets 5758045 6198107 5960811 6144285 5786254 6400688 6366296


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Income Statement

2Q 07-08

3Q 07-08 4Q 07-08 1Q 08-09 2Q 08-09 3Q 08-09 4Q 08-09

Sales 1031661 1195895 1353081 1626362 1619097 1823147 1884717

Less: Government

Levies

264013 292353 321147 357573 368159 445557 467496

Less: Cost of Sales 618341 777964 811398 873150 801430 1045906 906624

Gross Profit 149307 125578 220536 395639 449508 331684 510597

Other Income 1395 2319 92856 63161 95333 20915 11015

150702 127897 313392 458800 544841 352599 521612

Distribution Cost 4664 15245 26029 16719 10375 7333 15833

Administrative Expenses 15891 17033 21457 23671 24083 21501 33931

Other Operating

Expenses

6363 4465 16095 23894 29953 19639 4687

Profit From Operations 123784 91154 249811 394516 480430 304126 467161Finance Cost 33639 31331 38327 72121 92596 37798 22201

Net Profit Before

Taxation

90145 59823 211484 322395 387834 266328 444960

Taxation Current 3826 4518 5160 6719 2752 39423

Taxation Deferred 31572 14140 50814 102109 87024 76668 99199

Net Profit After Taxation 54747 41165 257138 220286 294091 186908 306338

Average Market Interest Rates, LSM Growth and GDP Growth

2Q 07-08

3Q 07-08 4Q 07-08 1Q 08-09 2Q 08-09 3Q 08-09 4Q 08-09


Rates

10.88 10.83 10.46 13.57 14.82 14.86 14.34

LSM growth 0.01 0.01 0.01 -0.02 -0.02 -0.02 -0.02

GDP growth 1.03 1.03 1.03 0.50 0.50 0.50 0.50

Balance Sheet

2Q 07-08

3Q 07-08 4Q 07-08 1Q 08-09 2Q 08-09 3Q 08-09 4Q 08-09

Current Assets 899261 3982369 5294083 4252059 2706981 1541678 1654014

Inventory / Stock in Trade 173336 142366 230089 257149 337508 197635 137451

Current Liabilities 1987707 956397 2454761 2148419 2504454 1696540 2628010Total Liabilities 2996735 1704998 3170512 2709722 3461775 4274619 11755812

Total Assets 6847211 10656016 12454493 12142730 13066422 14175521 21446501


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Data Used for Pooled Regression and other Tests

Year NPM i) SG ii) CGS iii) SE iv) ADE v) FC vi) QR vii)

TDTA

viii) AMI ix) GDP x) LSM

1Q 04-

05

13.726 5.757 44.768 0.490 0.752 6.815 65.904 65.046 7.750 4.975 2.250

2Q 04-

05

13.572 -

10.252

44.597 0.660 1.271 5.518 80.920 44.849 5.957 0.050 2.250

3Q 04-

05

11.510 2.064 46.429 0.522 1.328 5.058 62.748 60.828 6.473 0.050 2.250

4Q 04-

05

13.173 24.154 44.632 0.517 1.012 5.922 87.642 60.544 5.183 0.050 2.250

1Q 05-

06

19.882 15.764 37.709 0.556 0.911 5.156 94.496 53.979 10.137 0.022 1.450

2Q 05-

06

20.598 11.693 -36.977 -0.671 -1.632 -5.356 84.873 51.592 9.680 0.022 1.450

3Q 05-

06

21.696 -8.884 37.031 -0.625 -1.102 -4.727 78.059 49.152 10.023 0.022 1.450

4Q 05-

06

22.350 19.357 35.917 0.398 1.024 3.520 113.186 47.038 9.177 0.022 1.450

1Q 06-

07

18.258 -7.187 41.257 0.661 1.228 3.878 136.532 40.418 10.493 0.022 1.700

2Q 06-

07

9.320 -

29.268

50.193 0.689 1.418 5.168 126.963 43.633 11.077 0.022 1.700

3Q 06-

07

9.404 4.142 51.088 0.600 1.295 4.752 112.796 38.376 10.573 0.022 1.700

4Q 06-

07

15.078 8.696 58.202 1.459 2.067 3.804 122.737 41.644 10.627 0.022 1.700

1Q 07-

08

5.390 -0.932 58.200 0.637 1.892 3.736 113.800 40.339 11.660 0.012 1.025

2Q 07-

08

5.307 -

11.717

59.936 0.452 1.540 3.261 36.521 43.766 10.880 0.012 1.025

3Q 07-08

3.442 15.919 65.053 1.275 1.424 2.620 401.507 16.000 10.827 0.012 1.025

4Q 07-

08

19.004 13.144 59.967 1.924 1.586 2.833 206.293 25.457 10.463 0.012 1.025

1Q 08-

09

13.545 20.197 53.687 1.028 1.455 4.434 185.947 22.316 13.573 -0.019 0.500

2Q 08-

09

18.164 -0.447 49.499 0.641 1.487 5.719 94.610 26.494 14.817 -0.019 0.500

3Q 08-

09

10.252 12.603 57.368 0.402 1.179 2.073 79.223 30.155 14.863 -0.019 0.500

4Q 08-

09

16.254 3.377 48.104 0.840 1.800 1.178 57.708 54.815 14.337 -0.019 0.500

Documents

Full & Final CF Report