Managerial Economics Assignment-I,II & III.byregn No.pg121213

7/31/2019 Managerial Economics Assignment-I,II & III.byregn No.pg121213

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Mgl. Economics. Assignment.by Umapati Y Bhat 1

BhavanS Executive Management

Programme

Subject:Managerial Economics

Faculty Name:Prof. K Ravi

Case Study on : M/s Asian Paints Limited

Submitted by

Name:Umapati Y Bhat

Reg No:PG121213

Date:10th Mar12


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INDEX

Sl.No. Description Page

1 About Asian Paints Ltd., 3

2 Data & Sources 4

I

Advertisement Expenses Vs. Net Sales (Sales is a function Of Advertisement)

I.1 Excel Results 5

I.2 Interpretation 6

I.3 Graphs / Diagrams 7

I.4 Recommendation 8

I.5 Growth rate & Forecast 9

II

Cobb Douglas Production Function (

Production, Capital and Labour relationships)

II.1 Data Tabulation with log values 10

II.2 Excel Results 11

II.3 Interpretation 12

III

Asian Paints - it's position in paintindustry (Industry Type & MarketStructure)

13


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About Asian Paints:

Asian Paints is Indias largest paint company and Asias third largest paint company, with agroup turnover of Rs 7700 Crore. The group has an enviable reputation in the corporateworld for professionalism, fast track growth, and building shareholder equity.

Asian Paints established in 1942 at Mumbai, today operates in 17 countries and has 24paint manufacturing facilities in the world servicing consumers in over 65 countries.Besides Asian Paints, the group operates around the world through its subsidiaries

Berger International Limited, Apco Coatings, SCIB Paints and Taubmans.Forbes Global magazine USA ranked Asian Paints among the 200 Best SmallCompanies in the World for 2002 and 2003 and presented the 'Best under a Billion'award, to the company. Asian Paints is the only paint company in the world toreceive this recognition.Forbes has also ranked Asian Paints among the Best under a Billion companies in

Asia In 2005, 06 and 07.Product Range covers both Decorative and Industrial use. In Decorative paints,

Asian Paints is present in all the four segments v.i.z Interior Wall Finishes, ExteriorWall Finishes, Enamels and Wood Finishes.Introduced many innovative concepts in the Indian paint industry like - ColourWorlds (Dealer Tinting Systems), Home Solutions (painting solutions Service), KidsWorld (painting solutions for kids room), Colour Next (Prediction of Colour Trendsthrough in-depth research) and Royale Play Special Effect Paints, just to name afew.Vertical integration has seen it diversify into products such as Phthalic Anhydrideand Pentaerythritol, which are used in the paint manufacturing process.Reg Joint Ventures

Asian Paints also operates through APPG (50:50 JV between Asian Paintsand PPG Inc, USA, one of the largest automotive coatings manufacturer inthe world) to service the increasing requirements of the Indian automotivecoatings market.

Another 50:50 JV with PPG has been proposed which will service theprotective, industrial powder, industrial containers and light industrialcoatings markets.

Asian Paints achieved sales Rs 6322.2 Crore with PBDIT as Rs.1232.7Crore (excluding group companies).


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Data & Sources:

Data for this study is down loaded from companys website -

http://www.asianpaints.com/applications/financial_result.aspx . Data available for 7 Finacial

Years starting from 2003-04 till 2010-2011. For current Financial Year past 3 quarterresults are available however as the Financial year shall complete on 31st Mar12, the

same is not considered here for the study. 2002-03 data is obtained from 2003-04 result

for Production-Labour- Capital function study.

Figures are converted to single numbering forms i.e in Crore as prior to 2007 fin. Results

are in Millions and later in Crores.

Sales as a function of advertisement expenditure

Table 11 Sales Revenue and Advertisement Expenses in Crore

Currency

INRSl.NO Financial

Year

Advertisement

Expenses 'X"

Net Sales

Revenue "Y"

1 200304 68.24 1696.65

2 200405 69.92 1941.52

3 200506 90.97 2319.16

4 200607 110.98 2821.29

5 200708 164.85 3419.06

6 200809 197.05 4270.05

7 200910 244.25 5125.08

8 201011 282.35 6322.24

Production as a function of two variable Capital & Labour

Table 21 Production, Capital and Labour in Crore

Currency INR

Sl.NO Financial Year Production in MT Capital in Crore Labour in Crore

1 200304 352381.00 531.54 101.56

2 200405 416082.00 572.22 117.93

3 200506 417233.00 622.28 128.98

4 200607 486896.00 744.07 154.96

5 200708 559586.00 928.50 194.67

6 200809 602922.00 1094.47 238.90

7 200910 726437.00 1557.22 260.84

8 201011 849056.00 1975.32 300.45


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SUMMARY OUTPUT

Regression Statistics

Multiple R 0.993146664

R Square 0.986340296

Adjusted R Square 0.984063679

Standard Error 206.5552154

Observations 8

ANOVA

df SS MS F Significance F

Regression 1 18484558.52 18484558.52 433.2481852 8.00592E07

Residual 6 255990.3421 42665.05701

Total 7 18740548.86

Coefficients Standard Error t Stat Pvalue Lower 95%

Intercept 438.3904961 163.7638278 2.6769678 0.0366841 37.6748459

Advert. Expenses 'X" 19.8662354 0.9544369 20.8146147 0.0000008 17.5308125

RESIDUAL OUTPUT

Observation Predicted Net Sales Revenue "Y" Residuals

1 1794.10 97.46

2 1827.38 114.14

3 2245.68 73.47

4 2643.17 178.13

5 3713.34 294.28

6 4353.03

82.987 5290.72 165.64

8 6047.62 274.62

Regression Analysis Using Excel for Sa


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Interpretation Sales as a function of Advertisement

RSquare: InReferring to Regression results, R Square value is 0.9863 =98.63% which meansthat 98.63% of the total variation in firms sales is accounted for by the variation in the firmsadvertising expenditure.

Hypothesis:

Null Hypothesis : There is no significant influence of advertisement on Net Sales.Alternative Hypothesis: There is significant influence of advertisement on Net sales.

t cal = t stat = 20.814 (from the regression result for independent variable.t tab = 2.447 (from the T Distribution table based on deg of freedom 5 and probability 0.05 and )

Since t cal value 20.814 well exceeds t tab value 2.447 for the 5% level of significance with 6 df,we reject the Null Hypothesis that is that there is no relation between advertisement and sales

and we accept Alternative Hypothesis that there is statistically significant relationship betweenadvertisement and sale at the 5% level. That means we are 95% confident that such relationshipexists. In other words that the Advertising Expenses independent Variable has High Significantinfluence on the Sales dependent variable.

The linear equation of Net Sales and Advertisement expenses can be represented asS = a0 + a1(advertisement)Where S is Net Sales Revenue (Dependent variable)a 0 is Intercept calculated thru Regression using XL tool = 438.390a1 is Slope i.e. co-efficient of Advertisement expenses = 19.86

Advt is Advertisement Expense (Independent variable)

Replacing the appropriate values from Data Analysis obtained from Excel sheet in previous step,the equation is

=a0 +a1(advt)S=438.390 + 19.86 (adv)

Sales revenue shall increase by 438.390+19.86 times advertisement Expenses.


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Net Sales Revenue in Crore V/s Advertisement expensesRepresentation by Scatter Diagram:By taking Sales Revenue and Advertisement Expenses in Crores

Sales Revenue in Crore on Y axisAdertisement Expenses in Crore on X axisBy Taking Log Values for Sales Revenue & Advertisement Expenses

Sales Revenue Log Values on Y axisAdertisement Expenses Log Vales on X axisWe can observe a high influence of advertisement on sales revenue.


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Recommendation:

1. Going by the above study, regression analysis, we got R Square value as 98%. It meansthe 98% variation in sales is explained / related by variation in its advertisemenexpenditure. Hence It is recommended to increase the advertisement expenditure to anoptimum scale as required to reach sales growth rate.

2. As the RSquare value covers 98% variation of sales in relation with advertisement, in themean time Tcal is greater than t Tab we are convincingly recommending to increaseadvertisement expenses by 438.39+19.86 (advt) to achieve desired sales revenue.


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Growth Rate & Forecast:

Sl.NO Financial

Year

Advertisement

Expenses

Net Sales

Revenue

Sales

Growth

rate

Advt

Exp

Increase

Rate

1 200304 68.24 1696.65

2 200405 69.92 1941.52 14.43% 2.40%

3 200506 90.97 2319.16 19.45% 23.15%

4 200607 110.98 2821.29 21.65% 18.03%

5 200708 164.85 3419.06 21.19% 32.68%

6 200809 197.05 4270.05 24.89% 16.34%

7 200910 244.25 5125.08 20.02% 19.32%

8 201011 282.35 6322.24 23.36% 13.49%

9 201112 310.59 6608.47 4.53% 10.00%

9 201112 324.70 6888.88 8.96% 15.00%

9 201112 338.82 7169.39 13.40% 20.00%

9 201112 352.9375 7449.70 17.83% 25.00%

9 201112 381.1725 8021.73 26.88% 35.00%

Forecast Using S=a0+a1(advt.)

Advertisement expense is 310.585

=438.39+19.866(310.585)

=438.39+6170.08

=6608.47Crore

Advertisement Expenses is 324.70Crore=438.39+19.866(324.70)

=438.39+6450.49

=6888.88Crore

Advertisement Expenses is 338.82Crore

=438.39+19.866(338.82)

=438.39+6730.99

=7169.388Crore

Advertisement is 352.93Crore

=7449.697Crore

Advertisement is 381.172

=8021.739Crore


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Production as a function of two variable Capital

& Labour

Table 21 Production, Capital and

Labour in Crore Log Values

Sl.NO

Financial

Year

Production

in MT

Capital in

Crore

Labour in

Crore Production Q Capital K Labour W

1 200304 352381.00 531.54 101.56 12.77247 6.27578 4.62061

2 200405 416082.00 572.22 117.93 12.93864 6.349524 4.770091

3 200506 417233.00 622.28 128.98 12.9414 6.433397 4.859626

4 200607 486896.00 744.07 154.96 13.09581 6.612135 5.043148

5 200708 559586.00 928.50 194.67 13.23495 6.83357 5.271306

6 200809 602922.00 1094.47 238.90 13.30954 6.998026 5.476045

7 200910 726437.00 1557.22 260.84 13.49591 7.350657 5.563907

8 201011 849056.00 1975.32 300.45 13.65188 7.588486 5.705281

Excel Results Cobb Douglas Production Function


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SUMMARY OUTPUT

Regression

Statistics

Multiple R 0.994570807

R Square 0.98917109

Adjusted R

Square 0.984839526

Standard Error 0.036956711

Observations 8

ANOVA

df SS MS F

Significance

F

Regression 2 0.623797038 0.311898519 228.363496 1.22029E05

Residual 5 0.006828992 0.001365798

Total 7 0.63062603

Coefficients Standard Error t Stat Pvalue Lower 95%

Upp

95%

Intercept 9.066486 0.206207 43.967830 0.000000 8.536413 9.596

Capital K 0.387248 0.129151 2.998417 0.030154 0.055255 0.719

Labour W 0.286282 0.155002 1.846964 0.124032 0.112162 0.684

RESIDUAL OUTPUT

Observation

Predicted Production

Q Residuals

1 12.81956718 0.047098922

2 12.89091779 0.04771984

3 12.94902977 0.00762967

4 13.07078478 0.0250210445 13.22185275 0.013099754

6 13.34415086 0.034607746

7 13.50586019 0.009953149

8 13.63843157 0.013448849

Regression Results using XL Cobb

Function:


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Interpretation Cobb Douglas Production FunctionRSquare: InReferring to Regression results, R Square value is 0.989 =98.9% which means that98.9% of the total variation in firms goods produced is accounted for by the variation in the firmscapital and labour deployed.

Hypothesis:

Null Hypothesis : There is no significant influence of Capital K and labour-W on ProductionQ.Alternative Hypothesis: There is significant influence of Capital & Labour on Net goodsproduced.

Fcal = 228.36 (as per our excel analysis)

Ftab = 5.79 (from F distribution table of 5% Significance, taking numerator as 2 and denominator as 5)

Since Fcalculated value F Statistic 228.36 >exceeds critical value of F distribution with 2 and 5 df, wereject the null Hypothysis and accept alternative hypothesis that there is statistically significant relation

between independent and dependent variables

Labor W Coefficient = 0.28

It Indicates that with 1% increase in labour, Quantity of goods produced (roduction) will increase by

0.28%%

Kapital Coefficient = 0.38

It Indicates that with 1% increase in Capital, Quantity of goods produced (roduction) will increase by

0.38%%Since Capital Coefficient > Labour Coefficient, we conclude that the organization is a Capital intensive.

Coefficient of Labor & Capital = alpha + beta = 0.28 + 0.38 = 0.66

which is less than 1, hence we can say that the industry is on decreasing return to scale.

Cobb Douglas Production Function

Q = ln A + a In K + b ln L

= 9.06 + 0.28+ 0.38

= 9.72

Company needs to imprrove on production technology process technology and back handintegration to bring on return to scale side.


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Market Structure Analysis:

Market Structures are-

Perfect Competiton

Monoplistic Comptn.

Monopolistic Comptn.

Oligopolistic Comptn

Asian Paints is 13th largest in the world in paints industry, 3rd largest in Asia and largest in India.

In India even though there are many small brands in paints, howver few branded competitionnamely Kansai Nerolac, Berger Paints, Akzo Noble and Shalimar Paints who have recognisibleimprints in market. Among all Asian Paints is showing over 20% annual growrth rate since 2005

and is one of the company identified as Future Prospective. ( source Stock shastra .com).Fewer sellers, many buyers applies here.

Asian Paints is 13 th in international market with considerable global presence in developingcountries, middle easta nd African countires. Revnue wise they stand globally at 13 th with 1.9Blnagainst the worlds largest paint company Akzo noble with sales revnue of 13Bln UD.

From our study we found Asian paints is Capital intensive industry and has lost of assests interms of plant and machinery. It is having barriers to resource mobility and needs reasonably longtime planning for building capacities / making adjustments

Products are homogeneous as well as differentiated. But BRAND NAME carries weightage in

market.

Asian paints has Price Leader ship they cansell their goods at marginally higher prices ovecompetition as they have established tehir brands well ahead of others.

Also Asian paints has Scal of production and they can continue to produce till P=AVC.

Thus Asian Paints is categoriesd as OLIGOPOLISTIC.


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Managerial Economics Assignment-I,II & III.byregn No.pg121213

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