Market Demand Analysis:
Q1. Construct a demand schedule for a product X for alternative prices Re.1, 2, 3,
4,and 5 given its demand function : Dx = 90 – 2Px. Draw the demand curve for
the same? What is its mathematical attribute?
P = 1 ….. Dx = 90 – 2 Px = 90 – 2 x 1 = 90 – 2 = 88
P = 2 ….. Dx = 90 – 2 x 2 = 90-4 = 86
P = 3 ….. Dx = 90 – 2 x 3 = 90-6 = 84
P = 4 … Dx = 90 – 8 = 82
P = 5 … Dx = 90 – 10 = 80
Mathematical attribute = Dx = f (Px), ∆ Dx < 0
Q2. The demand curve for a commodity X is represented by Qx = 160000 –
1000Px. Construct the demand schedule assuming initial price to be Rs.100 and
consequent increase by Rs.10 upto Rs.150. Plot the demand curve.
P = 100 Dx = 160000 – 1000 Px = 160000 - 1000 x 100 = 160000 – 100000 =
P = 110 Dx = 160000 – 1000 x 110 = 160000 – 110000 = 50000
P = 120 Dx = 40000
P = 130 Dx = 30000
P = 140 Dx = 20000
P = 150 Dx = 10000
Q3. Suppose the demand function for Komal butter in a town is estimated to be Qd
= 600 – 5P when Qd is the quantity demanded of butter (in ‘000 kgs per week) and
P stands for price,
a) estimate at what price demand would be zero.
If Qd = 0 , then 0 = 600 – 5P, 5P = 600 P = 600/5 = 120.
When demand is zero, price is Rs.120.
b) Draw a demand curve at alternative prices Rs.25, 35, 50, 60 and 80.
P = 25, Qd = 600 – 5P = 600 – 5 x 25 = 600 – 125 = 475
P = 35, Qd = 600 - 5P = 600 – 5 x 35 = 600 – 175 = 425
P = 50 Qd = 600 – 5 x 50 = 600 – 250 = 350
P = 60 Qd = 600 – 5 x 60 = 600 – 300 = 300
P = 80 Qd = 600 - 5 x 80 = 600 – 400 = 200
c) What is the statistical characteristics of this demand curve. – Downward sloping
showing demand steadily falls as price increases.
Q4. Central Plaza conducted a study of the demand for men’s ties. It found that the
average monthly demand (D) in terms of price (P) is given by the equation D =
800 – 5P.
How many ties per day can its store expect to sell at a price of Rs.100 per tie?
Demand Equation for ties is Dx = 800 – 5P.
If P = 100 Dx = 800 – 5 x 100 = 300
Demand is 300 per month, or 10 per day.
If the store wants to sell 500 ties per month, what price it should charge?
If Dx = 500, 500 = 800 – 5P, 5P = 800 – 500 = 300, P = 300/5 = 60.
Q5. Demand equation of Sonam tiles is estimated as P = 8000 – 24Q, Find
i) the marginal revenue when Q = 100 and Q = 200
When Q = 100 MR = 8000 – 24 x 100 = 8000 – 2400 = 5600
When Q = 200 MR = 8000 – 24 x 200 = 8000 – 4800 = 3200
TR is Max. when MR = 0 When MR = 0 8000 – 24Q = 0 24Q = 8000, Q =
8000/24 = 333
Q6. The demand function for beer in a city is given as Qd = 400 – 4P,
Where Qd = quantity demanded of beer (in ‘000 bottles per week), P = price of
beer per bottle.
a) Construct a demand curve assuming price Rs.10, 12, 15, 20, 25 per bottle.
b) At what price would the demand be zero.
c) If the producer wants to sell 380,000 bottles per week, what price should he
Ans. P = 10 : Qd = 400 – 4 x 10 = 360
P = 12 : Qd = 400 – 4 x 12 = 352
P = 15 : Qd = 400 – 4 x 15 = 340
P = 20 : Qd = 400 – 4 x 20 = 320
P = 25 : Qd = 400 – 4 x 25 = 300
a)The data has been plotted on a graph as under :
300 310 320 330 340 350 360 Qd
Scale : Y-axis 2 cm – 10, For convenience, there is the scale from origin on x-axis.
DD is the linear demand curve derived on the basis of the given function and given
the alternative prices.
b)In the equation : Qd = 400 – 4P, let us put Qd = 0
400 – P = 0 , 4P = 400, P = 100.
That is to say, at the price of Rs.100 per bottle, the demand for beer will be
c) 380,000 bottles is 380 (‘000 omitted)
In the given equation Qd = 400 – 4P, let Qd = 380, 380 = 400 – 4P, 4P = 400 –
4P = 20, P
The producer should fix the price at Rs.5 per bottle, in order to sell 380,000
bottles per week.
Q7. Truett and Ruett (1980) described the following demand function for a brand
X of microwave ovens :
Qx = f (Px, Pz, Nw, Y, A)
Where Qx = quantity demanded per year for brand X of microwave ovens in a
Px = price of X brand
Pz = price of Z brand
Nw= number of working women
Y = mean annual household income
A = annual advertising expenditure
Assuming hypothetical data, we may state the demand estimation as under :
Qx = 11,93,200 – 100Px + 20 Pz + 0.002 Nw + 1.8Y + 0.3A
On this basis, given that Px = 8000, Pz = 9000, Nw = 800,000 in a city, Y =
100,000 A = 60,000
We can estimate the demand for X brand microwave oven as follows:
Quantity demanded Qx = 11,93,200 – (100 x 8000) + (20 x 9000) + (0.002 x
800,000) + (1.8 x 100,000) + (0.3 x 60,000)
= 11,93,200 – (800,000 + 180,000 + 1600 + 180,000 +
= 11,93,200 – 11,63,400
29,800 microwave ovens of X brand are purchased annually in this city.
Case Study –Problems: On combined effects of elesticities of demand:
Price effect and income effect together on the demand for a particular product can
be captured through combined effects of price and income elasticities of demand
by using the following equation :
Q2 = Q1 [1 + ep (%∆P) + em (%∆M)
Where Q1 = initial (current period) quantity demanded
Q2 = estimated demanded quantity in relation to changes in price and
P = price
M = income
ep = price elasticity of demand
em = income elasticity of demand.
Q8(1) Panavision a TV manufacturing company, is planning to increase the price
of its television sets by 10 % next year. The economic report of the company has
forecast a rise in per capita income by 5% during the period. Panavision economic
adviser has estimated price elasticity for the TV set at – 1.4 and income elasticity
at 2.2. The Panavision currently sells 50,000 TV sets.
Give the forecast for the sales. Is it advisable to raise the price of TV sets as has
been decided in this case when each TV set is currently priced at Rs,10,000?
Given particulars :
Ep = -1.4, em = 2.2
Q1 = 50,000
%∆P = 10% %∆M = 5%
Q2 = 50,000 [1 + (-1.4(0.10) + (2.2)(0.05)]
= 50,000 x 0.97 = 48,500
Thus, positive income effect is more than offset by the negative price effect. As
such, sales will decline to 48,500.
At initial price of Rs.10,000 annual revenue of the firm is Rs,50 lakhs.
When the price is raised to Rs.11,000, 48,500 TV sets are expected to be sold.
This would fetch a revenue of 48,500 X 11000 = Rs. 53.35 lakhs.
Thus, the company is going to gain and should, therefore, proceed by its decision.
Q9. A number of empirical studies of automobile demand in a country have
observed that the price elasticity is approx. -1.2 and the income elasticity is + 2.8.
The current sales amount to 8 million units. If the price rises by 10% and income
rises 5% next year, how many cars are expected to be sold?
Ans. Given price effect on price elasticity ep = - 1.2%
Income effect on income elasticity em = 2.8%
%∆Q = ep x ∆P + em x %∆M = -1.2 x 10% + 2.8 x 5%
Demand for automobiles = Qa = 1.02 x 8 million = 8.16 million cars.
Q2 = Q1[1+ eP (∆P) + eM(∆M)]
= 8 [1 + -1.2(.10) + 2.8(.05)]
= 8 ( 1 - 0.12 + 0.14)
= 8 x 1.02
Demand for automobiles : Q2 = 8.16 million cars.
Q10.Illustration: Cross elasticity as a measure of the effect of change in the
fares on the demand for rail service and vice-versa.
The cross elasticity of demand for a train service from station A to station B is the
rate of change in the number of train tickets sold on that route in relation to the
percentage change in the price of Bus service for the same route.
If the bus company reduced its fare from Rs.40 to 35, the following data is
Fare (Rs.) Daily No. of
Bus Rail Bus Rail
Before fare change 45 40
After fare change 45 35
Percentage change 0 -12.5%
Cross elasticity ec = %∆Q in Rail service = -20% = 1.6
%∆P in Bus service -12.5%
Such a high cross elasticity reflects that the market demand is greatly
responsive to the competitive price variation.
Advertising or Promotional Elasticity of Demand:
Q11.In case several products, the market demand is influenced through
advertisement or promotional efforts. The demand function in this case may be
stated as :
Qx = f (A),
Where Qx = demand for the product X measured through the quantity sold in
A = advertisement expenditure of the firm.
The degree of responsiveness of demand to changes in advertising
or Promotional elasticity of demand (eA ) is measured thus:
eA = % or proportionate change in sales
% or proporationate change in advt. expenditure
= ∆Q x A
= 10,000 x 50,000 = 0.63
In particular, point elasticity is used when the price-quantity changes are
infitesimally small – (assuming that a small price change is indicated by a virtual
point on the demand curve).
When there is a substantial price change, a discrete movement is observed. In such
a case, arc elasticity is preferable.
For all practical purposes, when price change is over 5 per cent, it is better to use
arc elasticity measurement to capture a more realistic idea of demand elasticity.
The arc advertising elasticity is measured as :
eA arc = ∆Q x A1 + A2
∆A Q1 + Q2
In the above example,
eA arc = 10,000 x 50,000 + 60,000 = 0.65
10,000 80,000 + 90,000
Case Study: Q12
Adam, the owner of Ever-Joy Ice-cream Centre, near University Campus, was also
a part-time student of management studies in a Commerce College. After having
studied the theory of price elasticity of demand, he thought that the demand for
ice-cream should be price elastic. For an experiment he announced special-reduced
price for the Ever-Joy Ice-Cream cone in the second week of August 2001 under
the 54th Independence Anniversary Week. He observed the following sales
Sales data for Ever-Joy Ice-Cream Cone
August Price Total Sale
Total Sales Revenue
1st week Regular Rs. 5 1000
2nd week Special Rs. 4 1500
Adam worked out price elasticity coefficient in this case to be :
e = ∆ Q x P = 500 x 5 = 2.5
∆P Q 1 1000
Finding demand elasticity to be much above unity, he inferred that the price
reduction led the total sales revenue to increase.
This outcome encouraged him to reduce the price in October on a permanent basis
to Rs.4.50. To his utter surprise he found that his average sales revenue rather
declined to Rs.4770.
What happened? Though the average weekly demand had risen to 1060 with the
price reduction, the sales revenue declined. Because this time the degree of price
e = 60 x 5 = 0.6 which turned out to be less than unity. Adam was
0.5 1000 suddenly demand became price inelastic? Why?
What is wrong?
Reasons: Adam’s approach to price policy was purely theoretical, assuming all
other things being equal. He did not care to look at other factors influencing the
demand for ice-cream, such as possibilities like winter, climatic adverse effects,
similar price war by the rival shops in the area.
Besides, Adam offered a 20% price reduction temporarily in August only for a
week, so most buyers responded to take advantage and probably the rivals did not
retaliate knowing it a short-term phenomenon at that time.
Further, now when the buyers realized that price-reduction in October is
permanent, they did not react much on the buying spree. Earlier, the buyers
expected that after the celebration week, the prices will go back to original level
and therefore purchased more. Thus future expectation was also not taken into
consideration while determining the second price reduction.
Therefore, business decision of Adam was misled by overestimation of price
elasticity from the very short=term data in a special situation rather than
resorting to demand estimation based on the long-term sales data under
Q13. When the price of a commodity X was Rs.10 per unit, people consumed 3000
units. With a fall in price to Rs.9 they consumed 3150 units. State the formula and
measure the elasticity of demand of X.
Elasticity of demand of X = ex = % change in demand = ∆Dx = 5 =
% change in price. ∆Px 10
The Serpell Report (1983) on Railway finances in England, for instance, measured
price elasticity of demand for rail services on some routes to be fairly inelastic
(-0.15); hence suggested fares rise of 40 per cent for London commuters. In this
case, work out the revenue effect if fare is raised from ₤10 to ₤14 and daily 1000
passengers are traveling on this route. Should the authorities accept this
suggestion? Give your comment.
Elasticity of demand e = %∆ Q, -0.15 = ∆Q Therefore, ∆ Q = 40 x -0.15 = -
%∆ P 40%
Total revenue = Old Price = ₤10, New Price = ₤ 14 , % change ∆P is 40%.
Initial Revenue PxQ = ₤10 x 1000 = ₤10,000
Demand after fare rise = - 6% = 1000 – 6% = 1000 – 60 = 940.
Revenue when fare is increased= ₤14 x 940 = ₤ 13160
Comment: Since demand is fairly inelastic, even with increase in fare, its revenue
effect is positive and substantially high;
Therefore, the railway authorities should accept the suggestion made by the Serpell
Q14. Suppose the sales for bicycles in Pune at various prices are as follows:
Price of a bicycle Quantity demanded
Per month ’ooo bicycles
Calculate the arc elasticity of demand between:
(i) The price of 500 and 1000
(ii) The price of 500 and 700
(iii) The price of 1000 and 700
(i) Change in quantity demanded = 25 – 15 = 10
Change in price is 500 – 1000 = 500
arc elasticity of demand e arc = ∆Q x P1 + P2 = 10 x 500 + 1000
∆P Q1 + Q2 500 25 + 15
= 10 x 1500 = 15000 = ¾ = 0.75
500 x 40 20000
(ii) When P1 = 500 and P2 = 700, Q1 25 and Q2 = 22 , ∆P = 200, ∆Q = 3
Arc elasticity of demand e arc = 3 x 500 + 700 = 3600 = .38
200 25 + 22 9400
(iii) When P1 = 1000 and P2 = 700, Q1 15 and Q2 = 22, ∆ P = 300, ∆Q = 7
Arc elasticity of demand e – arc = 7 x 1000 + 700 = 11900 = 1.07
300 15 + 22 11100
Q15. A firm increases its advertisement expenditure from Rs.60000 to 75000. Its
sales increases by 20% from the initial volume of 90000 units. Measure the
promotional elasticity of demand.
A1 = 60000 A2 = 75000 ∆ A = 15000
Q1 = 90000 Q2 = 90000 + 20% = 108,000, ∆Q = 18000
Promotional elasticity eA = ∆Q x A = 18000 x 60000 = 0.8
∆A Q 15000 x 90000
Arc advertising elasticity = eA =∆Q x A1 + A2
∆A Q1 + Q2
eA arc = 18000 x 60000 + 75000 = 0.82
15000 90000 + 108000
Q16. Assume that the average price of a new car in Mumbai is Rs.2, 60,000 and
90000 cars are sold at this price in a year. If the price elasticity of demand for new
cars is 1.7 what will be the effect on annual sales when the average price of a new
car declines to Rs.2,45,000.
Given: ep = 1.7 P1 = 260000 P2 = 245000 ∆ P = 15000 = 5.77% Q1 =
Price elasticity of demand = ep = ∆ Q 1.7 = ∆ Q ∆Q = 1.7 x 5.77 =
Q2 = 90000 + 9.80 x 90000 = 90000 + 8820 = 98820 cars
Sales increased by 9.8% or 8820 cars. Revenue R1 = 260000 x 90000 =
Rs.2340,00,00,000 (2340 Cr.)
-do- R2 = 245000 x 98820 =
EQUILIBRIUM OF THE FIRM
Objective Of the firm: May have more than one objective. Profit Maximisation is
one. Others may or may not be related to profit maximization.
Neo-classical theory assumes that Profit maximization is the sole objective of the
firm. Having been popular for a long time, “equilibrium of the firm” is
synonymous with the “profit-maximising condition” of the firm in the near future.
1. The firm has control over price-output policy.
2. It has a downward sloping demand curve.
3. It is facing upward moving Average Cost Curve.
Point of Maximum Profit or Equilibrium : Marginal Revenue.(MR) = Marginal
Price and Output(Quantity) at this level are equilibrium output and equilibrium
Some basic concepts:
Revenue: Sales revenue = sale price x number of output sold = Total revenue.
Average revenue = Total Revenue/Output. (Demand Curve of the firm)
It indicates the price realized at different levels of output.
Marginal Revenue = Diff. In Total Revenue/Diff. In output.
Revenue earned by selling an additional unit of output (price of last unit).
Assuming the demand function (AR = P)for the product as
P = 100 – 4X = AR
TR = X.P
= X (100 – 4X)
= 100 X – 4X2
MR = dTR/dX = 8X
Cost - Total Cost = Total Fixed Cost + Total Variable Cost TC = TFC + TVC
Average Cost = Total Cost /Output = TC/X
Marginal Cost = diff. In Total Cost/diff. In output
= dTC = dTFC + dTVC
dX dX dX
When total cost TC = 50 + 20X, MC = 20.
Total Revenue - Total Cost = Total Profit.(∏)
Total Profit TП = TR - TC
= (X.P) – (TFC+TVC)
= X (AR) – X (AC)
= X (AR – AC)
Average Profit AП = TП/X = TR/X - TC/X = (AR-AC)
Marginal Profit MП = diff.TП/diff. In X
= d TП/dX
The condition of maximization (equilibrium) require that d TП/dX = 0 and d2
TП/dX2 is –ve.
These are called the first order and second order conditions.
Here, total profit is to be maximized.
Profit function TП = TR – TC
dTП = dTR
BEP in terms of physical units = TFCBreak even point means : Total Cost =
P-AVC (Contribution margin)
BEP in terms of Sales Value :
Break-even Point = Total Fixed Cost/ Contribution Ratio TFC/CR
Contribution Ratio = Total Revenue – Total Variable Cost CR= TR – TVC =
TFC x TR
Total Revenue TR TR -
Q.17 Given the following total cost and total revenue functions, determine the
TC = 480 + 10Q (TFC + TVC (AVC x Quantity)
TR = 50Q
Total Fixed Cost is 480. (TFC)
Average Variable Cost = Rs.10 (AVC)
Total Revenue = 50Q (Given) = Price x Quantity.
TR = TC
50Q = 480 = 10Q 40Q = 480 Q = 12. Break even quantity is 12 units.
TR = 50Q = 50 x 12 = 600, TC = 480 + 10Q = 480 = 120 = 600 Therefore TR =
TC = Breakeven point.
Breakeven price : 50Q = 600 Price x Quantity = 600, Price = Rs.50
Q.18 A firm incurs fixed cost of Rs.4000 and variable cost of Rs.10000 and its
total sales receipts are Rs.15000. Determine the breakeven point.
CR = TR – TVC =( 15000 – 10000) / 15000 = ⅓
BEP = (TFC x TR) / (TR-TFC)
BEP = TFC/CR = 4000 divided by ⅓ = 4000 x 3 = 12000.
= 4000 x 15000 / 15000 – 10000
60000000 divided by 5000 = 12000
BEP means TC = TR TC = TFC + TVC 12000 = 4000 + TVC TVC = 8000
Assumptions of Break-even analysis:
1. Cost function and Revenue Function are linear.
2. Total Cost is divided into Fixed and Variable Costs.
3. Selling price is constant.
4. The volume of sales and volume of production are identical.
5. Average and Marginal Productivity of factors are constant.
6. The product-mix is stable in the case of a multi-product firm.
7. Factor price is constant.
In practice, these assumptions are unlikely to be fulfilled.
Limitations of BEA:
It is static : Everything is assumed to be constant, implying a static condition,
which is unrealistic and unsuitable for dynamic situation.
It is unrealistic: It is based on many assumptions which do not hold good in
practice. Linearity of cost and revenue functions are true only for a limited range
It has many shortcomings: BEA regards profit as a function of output only.
Impact of technical change, better management, division of labour, improved
productivity and other factors influencing profit are ignored.
Its scope is limited to shortrun only: BEA is not an effective tool for longrun
analysis as it is static.
It assumes horizontal demand curve with the given price of the product: This
is not so in the case of a monopoly firm.
It is difficult to handle selling costs in the BEA: Salling costs do not vary with
output. They manipulate sales and effect the volume of output.
The traditional BEA is very simple: It makes no provision for Corporate Income
Usefulness of BEA:
Despite these limitations BEA is a useful tool of analysis. BEA provides a rough
guideline for the alternative possibilities and arriving at a better decision. Of
course, BEA is not a perfect substitute for judgment of commonsense and intuition
possessed by the businessman. But it can be a good supplement to the value
judgment and logical deductions made with commonsense.
BEA is particularly useful for decision making in regard to pricing, cost contro,
product-mix, channels of distribution etc.
• BEA provides microscopic view of the profit structure of the firm.
• Empirical cost functions required in BEA can be of great help for cost
control in business.
• BEA when it provides a flexible set of projections of costs and revenue
under expected future conditions can serve the prupose of profit prediction
and becomes a tool for profit making.
• BEA can be used for determining the ‘safety margin’ regarding the extent to
which the firm can permit a decline in sales without causing losses.
• Safety Margin = Sales – BEP x 100
BEA can be useful in determining the target profit sales volume.
TFC – Target Profit
Target Sales Volume = -------------------------
It is useful in arriving at make or buy decision.
In short, BEA is highly significant in business decision making pertaining to
pricing policy, sales projection, capital budgeting, etc. However, the technique is
to be used cautiously.
Q.19 A firm incurs fixed expenses amounting to Rs.12000. Its variable cost of
product X is Rs.5 per unit. It selling price is Rs.8. Determine its break-even
quantity (BEQ) and safety margin for the sales of 5000 units. Interpret the result.
(i) BEQ = TFC = 12000/ (8-5) = 4000
ii) Safety Margin = Sales – BEQ x 100 = 5000 – 4000 x 100 = 20%
Q.20 BEQ or BEP 4000 units of product X in this case implies that the firm would
not have any loss or profit of selling this level of output at Rs.8. In other words,
this is zero profit-output level because:
∏ = TR – TC
In this case, TR = P.Q = 8 x 4000 = 32000 TC = TFC + TVC = 12000 x 5 x
4000 = 32000 ∏ = 32000 – 32000 = 0.
The safety margin 20% in this case suggests that the firm can afford to reduce its
price by 20% increasing the volume of sales by 20% to 5000 units before incurring
Q.21.A firm starts its business with fixed expenses of Rs. 60,000 to produce
commodity X. Its variable cost is Rs2 per unit. Prevailing market price of the
product is Rs.6. How much the firm should produce to earn a profit of
Rs.20,000 at this price.
In this case, we have to determine target profit sales volume (TPS) by using the
TPS = TFC – Target Profit Contribution Margin = Price – AVC = 6 – 2 = Rs.4
TPS = 60,000 – 20,000 = 40000/4 = 10,000
The firm should produce 10000 units of X to earn targeted profit of Rs.20,000 per
unit of time.
Q.22 A manufacturer buys certain components for producing X at Rs.20 per
unit. If he has to make these components, it would require a fixed cost of
Rs.15000/- and average variable cost of Rs.5 per unit. His present
requirement is 1000 units of these components. Advise him whether he should
make or buy them, if he intends to double the output.
In this case we need to measure the BEP of the components.
BEP = TFC Here for P we have to take the purchase price.
P – AVC
BEP = 15000 = 15000 = 1000
20 – 5 15
At 1000 units requirement, it makes no difference whether the firm buys or makes
the components. But when the requirement increases, it is profitable to make the
Q.23 Calculate the break even point from the following data.
Sales = 550 units
Sales Receipts = Rs.28,875
Total Fixed Costs = Rs.10,000
Total Variable Costs = Rs.11,000
BEP = Total Fixed Cost Contribution Ratio CR = TR – TVC =
28,875 – 11000 = 17875/28875
Sales Receipts = 28875 Sales = 550 units Sale Price : 28875/550 = Rs. 52.50
Total Veriable Cost = 11000 AVC = 11000/550 = 20 Total Fixed Cost =
BEP = TFC = 10000/ 52.50 - 20 (Cont. margin = 52.50 – 20 =
P – AVC
Q. 24 Given the following functions, find break-even point.
Total cost = 100 + 5X Total Revenue = 10Y, where X is the quantity sold.
Sale Price = 10Y / X TFC = 100 Cost price per unit = Rs.5 Quantity sold =
BEP = Total Fixed Cost / Cont.Margin 100 – (10Y/X – 5) = 105 – 10Y/
Q.25 A firm purchases ball bearings at Rs.12. Its monthly requirement is
1000 units. It it decides to make its fixed cost would be Rs.18,000 and variable
cost Rs.5 per unit. What is your advice.
P = Purchase price = Rs.12 AVC = Rs.5 TFC = Rs.18000
BEP = TFC/P-AVC = 18000/(12-5) 18000/7 = 2571.43 units.
It is not advisable to make the ball bearings as the requirement is only 1000 units
which is well below the breakeven level.
Q.26 For a new product, a manufacturer set up an infrastructure which costs him
Rs.1,40,000 and variable cost is estimated as Rs.125 for each unit of the product.
The sale price per unit is fixed at Rs.160. Write down the cost function Cx,
Revenue function Rx and Profit function Px for X units of the product. How many
number of units are to be produced in the first year of production so that there may
be no loss or gain during that year.
TFC = 1,40,000 AVC = 125 Sale Price = P = 160 Contribnution margin = P –
AVC = 160 – 125 = 35
BEP = TFC/Cont.margin = 140000 / 35 = 4000 units.
Total Cost = Cost function Cx = 140000 + 125X TR = Revenue function Rx =
At breakeven point Px = Rx – Cx ( Profit) = 0 TR or Rx = TC or Cx
160x = 140000 + 125x 160x – 125x = 140000 35x = 140000 X=
Therefore minimum number of units that should be produced in the first year is
4000 so that there will be no profit/loss.
Q.27 A company produced a commodity with Rs.10000 fixed costs. The variable
costs are estimated to be 25% of the total revenue received on selling the product
at the rate of Rs.6 per unit. Find the total revenue, total cost and profit
If X is the number of units produced, then toal revenue Rx (TR) = 6X
And Variable cost 25% of 6X = 3/2 X
Total Fixed cost TFC = 10,000 TC (Cx) = TFC + TVC = 10000 + 3/2 X
At BEP Px = 0 Therefore TR (Rx) = TC (Cx) 6X = 10000 + 3/2 X 6X
– 3/2 X = 10000
9/2 X = 10000 X = 10000 x 2/9 = 20000/9 = 2222.22 units.
Profit function Px = Rx – Cx = 6X – 10000 – 3/2X = 9/2X – 10000
Q.28. A profit making company wants to launch a new product. It observes that
the fixed cost of the new product is Rs.35000 and the variable cost per unit is
Rs.500. The revenue received on the sale of X units is given by 5000X – 100 X2 .
Find (i) profit function (ii) break even point.
Px (Profit) Rx (TR) Revenue function, Cx (TC) total cost function, then,
Rx (TR) = 5000 X – 100 X2 (Given) Cx = TFC + TVC = 35000 + 500X
Profit = Px = Rx - Cx = 5000X – 100 X2 – 35000 – 500 X = 4500X – 100 X2 –
BEP = Px = 0 Rx = Cx 5000X – 100X2 = 35000 + 500 X
5000X – 500 X – 100X2 = 35000
4500X - 100 X2 - 35000 = 0 (Divide by -100)
X2 – 4500X + 350 = 0
Therefore, X – 10 or X = 35. Breakeven values are 10 and 35.
Q.29 A company has fixed cost of Rs.10000 and cost of producing one unit of its
product is Rs.50. If each unit sells for Rs.75, find the break even value. Also find
the values of x for which the company always results in profit.
Cx = 10000 + 50X (TFC + TVC)
Rx = Sale Price x X = 75X
Profit Px = Rx – Cx = 75X – 50X – 10000
At BEP Px = 0 75X – 50X -10000 = 0
25X = 10000 X = 400
On producing and selling 400 units, the company is neither making a loss/profit.
The company will aways remain on profit if Px > 0 25X – 10000 > 0 giving X >
(Page 863 and 864 …..EX. 18.1 10 sums on this chapter to be practiced )
Chapter 7 – Demand Forecasting:
Demand forecasting is done (a) Personal judgement and experience.
(b) Statistical Methods – more scientific visavis crude
It is better to combine both.
In modern times, different statistical methods are to be used in combination.
Demand forecasting essential structural form and parameters of Demand
Function are necessary.
Statistical Methods : (a) Time Series Data (b) Cross-sectional data.
In time series, historical changes in income, price etc. are used to determine the
change in a variable in relation to time period..
Cross sectional data tries to determine the effect of price, income etc. on the
demand of a commodity – at a point of time.
Basis for : Time series : Basis for : Cross sectional
Historical data and past variation in relation to time Diff. Levels of sales
among different income and age groups
(Period of time) (at a point of time.- in a particular
A combination of Time Series and Cross Sectional Dtata is also used.
Using the above tools – three methods are followed for Demand Forecast.
1. Consumption Level Method.
Data used : Coefficient of Income elasticity and Coeff. Of Price elasticity.
Equation for using Income elasticity:
D* = D (I + M*,em) D = Per capital Demand D* = Projected Per capita
M* = Projected % difference in Per
em = Income elasticity of demand
Equation using Price elasticity of demand:
D* = D (I + P*.e)
D – Present Demand D* = Projected Demand P* = Expected change in price. e =
elasticity of price.
Illustration: Demand estimate using Income elasticity of Demand :
Suppose the income elasticity of demand for chocolates is 3. In the year 1995, per
capital income is 4500 and per capita annual demand for chocolates is 10 million
in a city. It is expected that in the year 2000 per capital income will be increased
by 20 per cent. Then projected per capital demand for chocolates will be :
D* = D (I + em) D* = (10)(1 + 0.5 x 3) = 10 x 2.5 = 25.
Illustration for Demand estimate using Price elasticity of Demand.
Present market demand for the commodity X is 2000 kg at Rs.10 per kg. Its price
elasticity is 2. Suppose the price declines to 5., then expected change in demand
will be :
D* = D (I + P*e) D* = (2000) (1 + 0.5 x 2) = 4000.
2. Trend Projection Method – Graphical or Least Squares Methods. Method of
Least Squares is very popular.
Method of Least Squares : Illustration :
Q.30 Annual Sales of a Company are as follows :
Year: 1991 1992 1993 1994 1995
Sales: 45 56 58 46 75
Using the method of least squares, fit a straight-line trend and estimate the
annual sales of 1997.
Year Sales 1990 = 0
Time – Devn.
Y = 45 + 5X
y x x2 xy (Rs.
1991 45 1 1 45
1992 56 2 4 112
1993 78 3 9 234
1994 46 4 16 184
1995 75 5 25 375
n=5 ∑y = 300 ∑ x = 15 ∑ x2 = 55 ∑ xy = 950
∑ y =300
Take the normal equations: ∑ Y = n.a + b∑ x ; xy = a∑ x + b∑ x2
Substituting the values we have, 300 = 5a + 15b (X3) 900 = 15a + 45b
950 = 15a + 55b
950-900 = 55-45b 10b = 50 b = 5
300 = 5a + 15 x 5 5a + 75 = 300 5a = 225 a = 45
Estimated Trend = Y = n.a. + b.x = 5 x 15 + 5X = 45 + 5X
Now, the st. line equation is Y1991 = 45 + 5(1) = 50
1992 45 + 5(2) = 55
1993 45 + 5(3) = 60
1994 45 + 5(4) = 65
1995 45 + 5(5) = 70 Forecast for 1997 = 45 + 5(7) =
80 i.e. Rs.80,000/-
3. Regression Analysis and Econometric Method. – Most commonly used.
Regression Analysis : Examples:
Increase in Personal disposable income results in Demand for consumer
Increase in Agricultural (farm) income results in Demand for Agri.
Increase in Construction contracts results in Demand for building
material (cement, steel, bricks)
Increase in Automobile bookings results in Demand for spare parts,
petrol, engine oil etc.
Econometric Model for Demand Forecasting:
Haynes, Mote and Paul formula (equation) Y = 2.9 x 0.57X
Y = average number of passengers traveling per day in a city.
X = mid-year estimate of population in lakhs for the city.
Given mid-year population figure, demand for the year can be estimated.
Q.31 In order to predict the demand for passenger transport in Hyderabad, the
following equation was used:.
Y = -2.9 + 0.57 X
The population is estimated to be 1,85,000 on January 1, 1977. Find out the
demand for passenger transport.
Y = -2.9 + 0.57 (185000)
= -2.9 + 105450
= 105447 cars.
Q.32 A departmental store conducted a study of the demand for men’s shirts. It
found that the average daily demand (D) in terms of price (P) is given by the
equation: D = 700 – 5P.
(i) How many shirts per day can the store expect to sell at a price of Rs.100 per
(ii) If the store wants to sell 100 shirts per day, what price should it charge.
(iii)What is the highest price anyone would be willing to pay?
(i) D = 700 – 5P P= 100 D = 700 – 5(100) = 200 shirts.
(ii) 100 = 700 – 5P 5P = 700 – 100 = 600 P = 120 = Rs.120
(iii) Maximum possible price means minimum possible demand. Since demand
cannot be kept as 0, we take it as 1
1 = 700 – 5P 5P = 700 – 1 = 699 P = 139.8 Rs.139.80
Q.33 The price per puchase and the market share of Monkey Brand Cigarettes in a
region are obtained as under :
Price (paise) 82 80 78 76 74 72 70 (Y – axis)
Market share % 5 7 10 15 20 25 30 (X – axis)
Establish A linear demand function on the basis of this information.
What demand do you expect at a price of 60 paise.?(Draw a graph – Market share
Q.34 Given data:
Year 1990 1991 1992 1993 1994 1995
Sales 10 12 15 18 24 25
Forecast the annual sales for 1988.
Q35 By the method of least squares, compute the trend values.
Year 1981 1982 1983 1984 1985
Sales (lakhs) 50 62 78 48 74
Forecast the annual sales for 1988.
Q.36 Project the trend of sales for the next three years from the following data:
Year 1981 1982 1983 1984 1985
Sales (lakhs) 120 140 150 170 190
Q.37 The following series show the sales of fertiulisers in A.P. during 1980-85.
Years: 1980 1981 1982 1983 1984
Sales (lakhs) 83 92 71 90 169
Using the method of least squares, find the trend values and estimate the sales for
the year 1986.
Q.38 Using the following demand equation : Y = - 3.2 + 0.62 X, estimate the
demand for road transport in 1985, if the population of the city is 2,044,000.
Q.39 Project the trend of sales for the next four years:
Year 1995 1996 1997 1998 1999
Sales(lakhs) 120 140 130 145 160
Q.40 Using the method of least squares, estimate the demand for the years 2000
Year 1995 1996 1997 1998 1999
Sales 91 99 95 101 120
Production Analysis - Iso-Quants:
Q.41 The short run production function of a hosiery mill is:
Qx = 112L + 6L2 – 0.1L3
Where Qx is the daily output of banians, L – number of workers employed,
(i) How many workers are employed when the average physical product of banian
(ii) How many workers are employed when the marginal physical product of
banian is maximized?
(iii) If the daily wage rate is Rs.30 and the selling price of the banian is Rs.40 per
piece, how many banians should be produced to maximize profits in this business?
(i) From the production function Qx = 12L + 6L2 – 0.1L3 derive Qx/L as follows:-
Average production per labour = Quantity produced divided by Number of
APL = Qx/L = 12 + 6L – 0.1L2
First derivative of the function is obtained as : d (Q/L) = 6L – 0.2L2
: 6 – 0.2L