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GNDU Question Paper-2023
Bachelor of Business Administration
B.B.A 1
st
Semester
Managerial Economics-I
Time Allowed: Three Hours Maximum Marks: 100
Note: Attempt Five questions in all, selecting at least One question from each section. The
Fifth question may be attempted from any section. All questions carry equal marks.
SECTION-A
1. Describe the concept of elasticity of demand. Explain its measurement in detail.
2. Critically discuss the law of equi-marginal utility in detail.
SECTION-B
3. Discuss the theory of revealed preference approach in detail.
4. What is Supply? Discuss the law of supply and its limitations in detail.
SECTION-C
5. Explain the law of returns to scale in detail and also its implications.
6. Write short notes on the following:
(a) Concept of total, marginal and average costs.
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(b) Theory of cost in short run and long run.
SECTION-D
7. Explain the features of perfect competition and discuss the equilibrium of firm under
perfect competition in the short run and long run.
8. What is monopolistic competition? Discuss the price and output determination under
monopolistic competition.
GNDU Answer Paper-2023
Bachelor of Business Administration
B.B.A 1
st
Semester
Managerial Economics-I
Time Allowed: Three Hours Maximum Marks: 100
Note: Attempt Five questions in all, selecting at least One question from each section. The
Fifth question may be attempted from any section. All questions carry equal marks.
SECTION-A
1. Describe the concept of elasticity of demand. Explain its measurement in detail.
Ans: A chai stall price puzzle
Every morning at the corner of a busy Amritsar lane, Harjit serves chai and samosas. One
day, milk prices jump, so he considers raising the chai price from 10 to 12. But a doubt tugs
at him: “If I charge more, will customers stop buying—or will they still come because they
love my masala mix?” That tiny hesitation is the heart of a big economic idea: elasticity of
demand. It’s the measure of how sensitive buyers are to changes—if a small price tweak
scares them away, demand is elastic; if they shrug and keep buying, demand is inelastic.
Let’s turn Harjit’s puzzle into a clear roadmap you can use in exams and real decisions.
Concept of elasticity of demand
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• Core idea: Elasticity of demand measures how strongly the quantity demanded
responds to a change in one of its determinants (usually price). When the response is
sharp, demand is elastic; when it barely changes, demand is inelastic.
• Price elasticity of demand (PED): This is the most common form—responsiveness of
quantity demanded to a change in price. Because price and quantity demanded
typically move in opposite directions, PED is negative; in practice, we often use its
absolute value.
• Other elasticities (for completeness):
o Income elasticity (YED): Response of demand to changes in consumer
income.
o Cross elasticity (XED): Response of demand for one good to price changes of
another (substitutes or complements).
• Why it matters: Elasticity guides pricing, tax policy, revenue forecasts, and resource
allocation. For a seller like Harjit, it answers: “If I raise price by 10%, what happens to
sales and revenue?”
Degrees and interpretations of price elasticity
• Perfectly inelastic (0):
o Ep=0|. Quantity demanded does not change with price (a vertical demand
curve).
o Example: Life-saving drugs in emergencies.
• Inelastic (<1):
o 0<Ep<1. Quantity demanded changes by a smaller percentage than price.
o Example: Table salt; a price rise barely dents consumption.
• Unitary (=1):
o Ep=1|. Quantity changes by the same percentage as price; total revenue
stays constant when price changes.
o Example: A carefully balanced market segment.
• Elastic (>1):
o Ep>1|. Quantity changes by a larger percentage than price.
o Example: Branded snacks with many substitutes.
• Perfectly elastic (∞):
o Ep→∞. Even a tiny price increase drives demand to zero (a horizontal
demand curve).
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o Example: Identical commodities in perfectly competitive markets.
Measurement methods you must know
Percentage (proportionate) method
• Definition: Measures elasticity as the ratio of percentage change in quantity
demanded to percentage change in price.
• Notes: Negative sign indicates inverse relation; in answers, state magnitude unless
sign is specifically required.
Point elasticity (calculus/instantaneous method)
• When used: To find elasticity at a specific point on a demand curve.
• Linear curve shortcut: For a straight-line demand curve, slope
is constant. A
geometric result gives:
• Interpretation: As you move down a straight-line demand curve, elasticity falls from
>1 to <1, equals 1 at the midpoint, and hits 0 at the intercept.
Arc elasticity (midpoint method)
• When used: When price and quantity change by finite amounts between two points;
avoids bias from choice of base.
• Why midpoint: Using averages of price and quantity treats the movement from
P1,Q1, to P2,Q2, symmetrically.
Total expenditure (or outlay) method
• Idea: Looks at how total expenditure (or seller’s total revenue) changes when price
changes.
• Rules after a price change:
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o Elastic demand:
▪ If price falls and total expenditure rises, or price rises and total
expenditure falls.
o Inelastic demand:
▪ If price falls and total expenditure falls, or price rises and total
expenditure rises.
o Unitary elasticity:
▪ Total expenditure remains unchanged.
• Use case: Quick diagnosis without calculus—excellent for concept questions and
MCQs.
Revenue method (link to marginal revenue)
• Formula: Relates elasticity to average revenue (AR) and marginal revenue (MR).
• Implications:
o If MR>0, then Ep>1 > 1 (elastic region).
o If MR=0, then Ep=1| = 1 (unitary).
o If MR<0, then Ep<1| < 1 (inelastic region).
• Why useful: In theory questions linking demand and revenue, this gives elasticity
from revenue data without price-quantity pairs.
A worked example that feels real
• Scenario: Harjit contemplates raising chai price from 10 to 12. He estimates daily
cups will drop from 100 to 80.
• Arc elasticity (midpoint):
• Interpretation: Ep≈1.22>1|. Demand is elastic in this range. A price increase would
reduce total revenue:
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• Decision hint: If Harjit’s goal is higher revenue, this price rise is unwise at current
responsiveness. If costs demand a rise, he should consider differentiating (better
cup, loyalty card) to reduce elasticity.
• Point elasticity (if we had a demand function): Suppose near P=11P=11, the local
slope is
=−10 cups per rupee, and quantity is Q=90Q=90.
• Consistency: The instantaneous measure mirrors the arc estimate—nice cross-check
for your exam answer.
Graphical intuition that sticks
• Straight-line demand:
o Top segment (high price, low quantity): Ep>1| elastic.
o Midpoint: Ep=1| unitary.
o Bottom segment (low price, high quantity): Ep<1| inelastic.
• Constant-elasticity curves:
o Demand of the form Q=kP
−e
has constant elasticity ee at every point. A
special case PQ=k gives unitary elasticity throughout.
• Total expenditure lens:
o Moving along a downward-sloping curve, total revenue rises in the elastic
region, peaks at unitary elasticity, and falls in the inelastic region.
Determinants of elasticity (why responsiveness differs)
• Availability of substitutes:
o More substitutes → more elastic. If many cafés sell similar chai, a small price
rise pushes customers elsewhere.
• Nature of the good:
o Necessities → inelastic; luxuries → elastic. Daily necessities resist change;
indulgences get postponed.
• Proportion of income:
o Higher budget share → more elastic. A 10% increase on an expensive item
bites more than on a cheap one.
• Time horizon:
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o Short run → inelastic; long run → elastic. People need time to adjust habits or
find alternatives.
• Definition of the market:
o Narrow definition → more elastic. “Masala chai from Stall A” has more
substitutes than “hot beverages.”
• Addiction and habits:
o Strong habits → inelastic. Habitual buyers are slow to cut back.
• Possibility of postponement:
o Easier to postpone → more elastic. You can delay a new phone, not asthma
medicine.
• Complementarity:
o Strong complements reduce elasticity. If tea and biscuits are paired, a price
change in one affects the other’s demand.
• Durability and second-hand markets:
o Durable goods often more elastic over time. Repairs or used options soften
price hikes.
• Advertising and differentiation:
o Brand loyalty reduces elasticity. Unique value makes buyers less price-
sensitive.
These determinants are exam gold: they explain why the same percentage price change can
provoke very different quantity responses across products and contexts.
Common pitfalls and exam-smart tips
• Confusing slope with elasticity:
o Slope uses absolute changes; elasticity uses percentage changes. A flat curve
isn’t always “more elastic” at every point—use PQ with slope for point
elasticity.
• Forgetting the sign:
o PED is negative by definition; report magnitude unless asked to include the
sign. Write “elastic (|E|>1)” to be precise.
• Using base rather than midpoint:
o For finite changes, always prefer arc (midpoint) formula to avoid base-year
bias.
• Mixing regions on a linear curve:
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o Remember: top elastic, middle unitary, bottom inelastic. Draw and label—
quick diagrams fetch easy marks.
• Ignoring total revenue logic:
o Pair any elasticity result with a revenue implication. Examiners love “so what”
clarity.
A brief closing scene
A week later, Harjit tries a different move: he keeps chai at 10 but introduces a “ginger
boost” cup at 12 with a splash of adrak and jaggery. Regulars keep buying, and some trade
up. Without touching the base price, he nudges the demand for a differentiated product—
lowering elasticity by offering unique value. His daily revenue rises, not because customers
were forced to pay more, but because they chose to.
That’s elasticity, humanized: it’s not just a ratio; it’s a story about choices, timing, and
alternatives. In summary, elasticity of demand tells you how quantity reacts when price (or
income, or other prices) moves; you measure it with point, arc, total expenditure, and
revenue methods; you interpret degrees from perfectly inelastic to perfectly elastic; and you
apply determinants to predict real-world behavior. Master these steps and you won’t just
solve exam problems—you’ll see the market moving around you, one small change at a
time.
2. Critically discuss the law of equimarginal utility in detail.
Ans: A simple story to set the stage
Imagine you’ve saved 100 rupees for a college fest. You’re hungry, tired, and excited. At the
food stalls, you can buy momos, a cold coffee, and a plate of golgappas. Each first bite or sip
feels heavenly, but as you keep buying more of the same thing, the thrill drops a little. The
first cold coffee wakes you up; the second is nice; the third feels… unnecessary. Without
realizing it, your mind keeps asking: “Where does the next rupee give me the most
happiness?” That quiet, everyday question is the heart of the law of equimarginal utility.
The core idea and the rule
The law of equimarginal utility (also called the law of substitution or the law of maximum
satisfaction) says: to get the most total satisfaction from a limited budget, a consumer
allocates spending across goods so that the marginal utility per rupee is equal across all
goods.
• Formal rule:
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• Budget constraint:
Your spending on all goods must fit your money (M).
• Intuition: If
1 more rupee on (x) makes you happier than 1 more rupee on
(y). So you shift some money from (y) to (x) until equality is restored. When the
fractions are equal, there’s no better reallocation; you’ve maxed out your
satisfaction.
A quick ordinal perspective
Even if we don’t measure utility in numbers (cardinal utility), the same idea emerges via
indifference curves. At the best choice, the marginal rate of substitution equals the price
ratio
This is just another way of saying “the trade-off you’re willing to make equals the trade-off
the market asks of you.”
A warm, numeric example
Suppose prices are: momos (P
m
=20), cold coffee (P
c
=40), golgappas (P
g
=10), and your
budget (M=100).
Assume marginal utilities (just illustrative):
• Momos: (MU) falls with each plate: 80, 60, 40, 20, 10
• Cold coffee: 120, 60, 30
• Golgappas: 40, 30, 20, 10, 5
Compute marginal utility per rupee:
• Momos: (80/20=4), (60/20=3), (40/20=2), (20/20=1), (10/20=0.5)
• Cold coffee: (120/40=3), (60/40=1.5), (30/40=0.75)
• Golgappas: (40/10=4), (30/10=3), (20/10=2), (10/10=1), (5/10=0.5)
Start “spending” your 100 rupees one unit at a time on the highest MU per rupee
available:
1. Best is 4: buy momos (20) and golgappas (10). Running total: 30.
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2. Next best is 3: candidates are momos (second plate) and cold coffee (first), and
golgappas (second). Choose any sequence, but watch the budget:
o Take cold coffee (40). Total: 70.
o Take momos (second plate, 20). Total: 90.
o With 10 left, take golgappas (second, 10). Total: 100.
Check the last chosen marginal utilities per rupee:
• Momos last unit: 3
• Cold coffee last unit: 3
• Golgappas last unit: 3
You’ve equalized
across goods at 3. Any reshuffle that breaks this equality lowers total
satisfaction. That’s the law in action—calm, mechanical, and deeply intuitive.
Assumptions behind the law
• Diminishing marginal utility:
The extra satisfaction from additional units declines after some point. Without this,
the law can’t “pull” choices into balance.
• Cardinal or comparable utility:
We often pretend utility can be measured so we can compute
. The ordinal view
replaces numbers with preference rankings but preserves the optimality condition
via MRP=
• Rational choice and consistency:
Consumers are assumed to compare options carefully and make stable choices that
reflect their preferences and constraints.
• Given prices and income:
Prices and budget are treated as known and fixed during the decision.
• Divisible goods and no transaction frictions:
You can buy fractional units if needed, and there are no search costs, time costs, or
minimum-size bundles.
Each assumption smooths the road so the “equalize MU per rupee” car can drive. In reality,
the road has bumps.
Criticisms, limits, and real-world wrinkles
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• Measurement problem:
Utility is subjective. Assigning numbers to “happiness” is questionable.
o Implication: The law is best seen as a metaphor or as an ordinal condition
using indifference curves, rather than a literal calculator.
• Behavioral biases and bounded rationality:
People satisfice, rely on habits, anchor on defaults, or get swayed by framing.
o Implication: Consumers may not keep updating
; they often follow rules of
thumb: “Always get one coffee,” “Never skip dessert,” even when MU per
rupee is lower.
• Income and substitution effects:
A price change does two things: alters relative attractiveness (substitution) and
changes purchasing power (income).
o Implication: The simple
; equality captures the substitution logic but
abstracts from complex income effects, which can lead to anomalies.
• Giffen and strongly inferior goods:
For some goods, when prices rise, people buy more due to a dominating negative
income effect.
o Implication: The neat “spend where
; is highest” logic does not predict
such corner cases well without a fuller demand framework.
• Complementarity and indivisibilities:
Goods used together (printers and ink) or sold in lumpy units (a whole pizza) break
the smooth divisible model.
o Implication: Equalization can fail; the best choice may be a bundle with
deliberately uneven
; across items.
• Uncertainty and learning:
Before trying something, you don’t know its MU. You learn by doing, and
expectations can be wrong.
o Implication: Early choices might “overinvest” in familiar goods and only
gradually re-balance as you discover true marginal utilities.
• Time and intertemporal trade-offs:
Today’s coffee affects tonight’s sleep; saving today buys future goods.
o Implication: The relevant principle becomes: equalize discounted marginal
utility per rupee across time, which requires patience, self-control, and
beliefs about the future.
• Transaction costs and attention scarcity:
Searching for the best deal takes time and mental energy.
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o Implication: Even if
; is higher elsewhere, the cost of finding/switching
can justify sticking with a “good enough” option.
• Distribution and ethics are ignored:
The law is about one person maximizing their own satisfaction.
o Implication: It’s silent on fairness or social welfare unless expanded into
broader frameworks.
When corner solutions happen
Sometimes the equality never holds for interior bundles. If for all affordable quantities
the optimum is to spend everything on (x). In pictures, the highest indifference
curve touches the budget at an axis. This is common with strong preferences or very low
prices.
Why it still matters (for students, businesses, and policy)
• Personal budgeting and study time:
Think of hours as your currency. The “next hour” rule says: keep shifting time among
subjects until the gain from the next hour is equalized.
o Practical tip: When an extra hour on one subject teaches you less than an
extra hour on another, switch.
• Business pricing and product mix:
Firms guess consumers’ marginal utilities through data: click-throughs, repeat
purchases, time-on-app.
o Use: Set prices and promotions to nudge customers until their perceived
;
for your product edges out rivals. Bundles try to raise total MU without a
proportional price hike.
• Public policy and welfare programs:
If the “next rupee” gives more utility to the poor than the rich, transfers can raise
total welfare.
o Caveat: Utility can’t be directly compared across people, but the
equimarginal idea inspires “spend where the next unit does the most good,”
from health budgets to environmental policy.
• Environmental allocation:
The cheapest emissions cuts are done first, then progressively costlier ones—
equalizing marginal abatement cost across sources reflects the same principle.
The second, smaller story
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A shopkeeper in a small town stocks her shelves with a fixed weekly budget. In the past, she
bought equal numbers of three snack brands. Then she starts watching: which brand’s next
dozen packs sell quickest and please customers most? She shifts spending toward that
brand until the extra rupee on any brand brings the same “next unit” satisfaction (measured
by sales and smiles). She’s not solving equations—but she lives the law.
Bringing the critique and the core together
The law of equi-marginal utility is a beautiful compass, not a perfect GPS. As a compass, it
points to a simple truth: keep moving resources toward the option where the next unit
helps you most, and stop when the “next unit help” is balanced everywhere. As a GPS, it
struggles with potholes—biases, indivisible goods, complementarities, uncertainty, and the
fuzziness of measuring happiness.
Still, even with those limits, the law captures how smart choices evolve: experiment, notice
where the next rupee (or minute, or calorie, or kilowatt) does the most good, and keep
rebalancing. In class, that’s an equation. In life, it’s a habit. And when your festival budget
runs out and you’re content with what you chose, you’ve probably followed it—without
ever naming it.
SECTION-B
3. Discuss the theory of revealed preference approach in detail.
Ans: A simple story to set the stage
Imagine you’re at a college canteen with ₹100 in your pocket. You walk past the counters
and finally choose a plate of noodles and a cold drink. You could have picked a sandwich or
a dosa, but you didn’t. Without saying a word, your choice reveals something powerful: you
preferred noodles and cold drink over the other options available at those prices. That’s the
heart of the Revealed Preference Theory—your actions speak louder than your words.
What is Revealed Preference Theory?
The Revealed Preference Approach, developed by economist Paul Samuelson, is a way to
understand consumer behavior without asking them directly about their preferences or
measuring their utility. Instead, it looks at actual choices made under given constraints (like
income and prices) and infers preferences from those choices.
In simple terms:
• If a consumer chooses bundle A over bundle B when both are affordable, then
bundle A is revealed preferred to B.
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• This approach avoids the need for abstract concepts like “utility” and focuses on
observable behavior.
The logic behind the theory
Let’s break it down with a relatable example.
Suppose Riya has ₹200 and goes shopping. She sees two combinations of goods:
• Bundle A: 1 dress and 1 pair of earrings
• Bundle B: 2 tops and 1 pair of shoes
Both bundles cost ₹200. Riya chooses Bundle A.
According to Revealed Preference Theory:
• Riya revealed that she prefers Bundle A over Bundle B.
• We don’t need to ask her why. Her choice tells us enough.
Now, if prices change and Riya chooses Bundle B in a future situation, we can analyze
whether her preferences have changed or whether Bundle A was no longer affordable.
This method is grounded in reality—it trusts what people do, not what they say.
The axioms of Revealed Preference
To make this theory work consistently, economists introduced a few rules or axioms:
1. Weak Axiom of Revealed Preference (WARP)
If a consumer chooses A over B when both are affordable, then they should not choose B
over A in another situation where both are still affordable.
• Why it matters: It ensures consistency. If someone flips preferences without any
change in constraints, it’s irrational.
2. Strong Axiom of Revealed Preference (SARP)
If A is revealed preferred to B, and B to C, then A should be revealed preferred to C.
• Why it matters: It adds transitivity. If you prefer A over B and B over C, logically, you
should prefer A over C.
These axioms help economists build demand curves and predict behavior without needing
utility functions.
A second story: The snack stall mystery
At a college fest, a snack stall offers samosas, burgers, and rolls. Every day, the prices
change slightly. The stall owner, curious about student preferences, starts tracking what
people buy when different combinations are affordable.
He notices:
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• When samosas and burgers are both affordable, most students pick samosas.
• When rolls and samosas are affordable, rolls are chosen.
• When burgers and rolls are both affordable, burgers win.
Using these choices, he builds a mental map of preferences—without asking a single
question. He adjusts his stock accordingly. That’s Revealed Preference in action—real
choices guiding real decisions.
Strengths of the Revealed Preference Approach
• No need for utility measurement It avoids the abstract and often unrealistic idea
of assigning numbers to happiness.
• Based on actual behavior It’s grounded in what consumers really do, not what
they claim.
• Useful for policy and market analysis Governments and businesses can use
revealed preferences to understand demand patterns and design better offerings.
Limitations and criticisms
• Ignores psychological factors It doesn’t account for emotions, habits, or irrational
behavior.
• Assumes consistency Real people sometimes make inconsistent choices due to
changing moods, peer pressure, or lack of information.
• Limited to observed choices If a consumer never faces a certain choice, we can’t
infer their preference.
• No insight into intensity of preference We know what someone prefers, but not
how much more they prefer it.
Why it still matters
In a world flooded with data, the Revealed Preference Approach is more relevant than ever.
Every click, purchase, and swipe reveals something about consumer preferences. Companies
use this data to tailor ads, recommend products, and design user experiences—all without
asking a single question.
Even in economics exams, this theory stands out because it’s practical, intuitive, and
elegant. It teaches us that sometimes, the best way to understand someone is to watch
what they do, not just listen to what they say.
Final thoughts
Revealed Preference Theory turns everyday choices into powerful economic insights.
Whether it’s a student picking snacks or a shopper choosing between brands, each decision
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is a tiny window into their preferences. And when we piece those windows together, we get
a clear, consistent picture—one that’s built not on assumptions, but on actions.
So next time you choose noodles over dosa, remember: you’re not just eating—you’re
revealing your preferences, and writing a silent story that economists love to read.
4. What is Supply? Discuss the law of supply and its limitations in detail.
Ans: A simple story to set the stage
A neighbourhood baker wakes up at 4 a.m. every day and bakes 100 loaves of bread. One
week, there’s a food fair nearby and customers are willing to pay a higher price per loaf. The
baker thinks, “If the price is higher, I can cover the overtime wages, buy a bit more flour,
and keep the ovens running longer.” So he bakes 150 loaves. The next week, demand cools
and the price dips; he cuts back to 90 loaves to avoid leftovers. Without reading any
economics, the baker just acted out the idea behind supply: when the price goes up,
producers are willing to offer more; when the price goes down, they pull back—other things
held constant.
Meaning of supply
Supply is the quantity of a good or service that producers are willing and able to offer for
sale at different prices over a given period, assuming other factors remain unchanged. It’s
not a single number; it’s a whole relationship between price and quantity.
• Individual vs. market supply: The supply curve of a single producer shows their
willingness to sell at various prices. Market supply is the horizontal sum of all
individual supply curves.
• Supply schedule and curve: A supply schedule lists quantities offered at different
prices; plotting these points gives the upward-sloping supply curve.
• Movement vs. shift: A change in the good’s own price moves you along the supply
curve. Changes in other factors—input costs, technology, taxes—shift the whole
curve.
The law of supply
The law of supply states: other things being equal, the quantity supplied of a good rises
when its price rises, and falls when its price falls. In symbols, for the good’s own price PP
and quantity supplied Qs:
• Economic intuition: Higher price makes production more profitable. Firms can cover
higher marginal costs (like overtime, premium inputs), so they expand output. Lower
price squeezes margins; firms scale back, or some exit.
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• Micro-foundation: A competitive firm’s supply in the short run is the portion of its
marginal cost curve above the shutdown point. As PP rises, the firm equates PP with
marginal cost at a higher output, so Qs increases.
• A tiny numeric sketch: Suppose the baker’s marginal cost of each additional batch
rises: ₹60, ₹70, ₹85, ₹100, ₹120. If the market price is ₹80, he’ll produce up to the
last batch with MC ≤ 80, say 2 batches. If price rises to ₹110, producing the fourth
batch now makes sense. Price up, quantity supplied up.
• Ceteris paribus matters: The “other things equal” clause freezes everything except
the good’s own price. If flour gets cheaper or a new oven arrives, that’s a shift in
supply, not a movement along it.
Key determinants that shift supply
• Input prices: When wages, raw materials, or energy get cheaper, costs fall and
supply shifts right. Costlier inputs shift it left.
• Technology and productivity: Better methods, automation, or learning-by-doing
reduce marginal costs, shifting supply right.
• Number of sellers and capacity: New entrants or added capacity increase market
supply; exits or closures do the opposite.
• Government policies: Taxes raise costs (shift left), while subsidies lower costs (shift
right). Regulations can restrict or enable supply.
• Prices of related goods (in production): If corn becomes more profitable than
wheat, some land switches, reducing wheat supply.
• Expectations: If producers expect higher future prices, they may withhold today’s
output (left shift), and vice versa.
• Natural conditions and shocks: Weather, disease, or supply chain disruptions shift
supply, especially in agriculture and commodities.
You can summarize this relationship as:
Only P moves you along the curve; the rest shift the curve.
Limitations and exceptions to the law of supply
• Capacity constraints and fixed factors (short run): In the very short run, output can’t
increase no matter the price because capacity is maxed out. The supply curve
becomes vertical at the capacity limit. At low outputs, it can be flat if excess capacity
exists; once constraints bind, extra units get costly fast.
• Perishable goods and “sell-it-now” pressure: Fishermen landing a big catch near
closing time may accept lower prices to avoid spoilage, temporarily producing a
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downward or kinked relationship. The law describes planned supply, but
perishability can force sales even when prices fall.
• Agriculture and time lags: Farmers decide months in advance. When price rises
today, quantity supplied responds with a delay (planting/harvest cycles). Short-run
supply may look inelastic or even show cobweb patterns where quantity overshoots
and undershoots across seasons.
• Learning curves and economies of scale (declining marginal costs): In early stages of
a new industry, average and marginal costs can fall as output rises due to learning,
specialization, or network effects. Over some ranges, firms might supply more at
lower prices (to build scale), softening or reversing the usual upward slope.
• Joint products and by-products: Producing beef yields leather; refining oil yields
gasoline, diesel, and other fractions. The supply of one product depends on the co-
product’s market, not just its own price, complicating the simple one-good law.
• Input bottlenecks and step costs: When an extra shift requires hiring specialized
staff or leasing another plant, costs jump discretely. Supply can look like steps rather
than a smooth slope, and price hikes within a step may not increase output until the
next capacity chunk is added.
• Market power and pricing strategy: The textbook law assumes competitive price-
taking. A firm with market power chooses price and quantity together. Its “supply”
isn’t a simple function of price alone; it depends on demand and strategic objectives
(e.g., limit pricing).
• Regulatory and contractual rigidities: Price controls, quotas, long-term contracts,
and minimum delivery obligations can lock output irrespective of current price,
breaking the straightforward price–quantity link.
• Expectations and inventory behaviour: If producers expect even higher prices
tomorrow, they may hold inventory back today despite rising prices. Conversely, fear
of future declines can trigger extra sales at today’s lower prices.
• Resource exhaustion and non renewables: For exhaustible resources, current
extraction trades off with future scarcity. Optimal supply may reduce at higher prices
to conserve for even higher future returns, deviating from the simple short-run law.
• Labor supply quirks (as an analogy): In labour economics, individual labour supply
can bend backward at high wages (people buy more leisure). This reminds us that
“price up, quantity up” is not universal across all contexts or ranges.
A brief second story
A small apple orchard has one tractor and a handful of workers. When the wholesale price
nudges up, the owner pays overtime and harvests more rows—until dusk. After that, no
matter how high the price climbs that night, apples still on trees can’t be picked until
morning. In the short run, supply hits a wall. A month later, the owner invests in a second
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tractor and seasonal workers. Now, for the next season, the whole supply curve shifts right.
The law of supply operates within those walls; investment moves the walls.
Pulling it together
Supply describes producers’ willingness and ability to sell at various prices over time. The
law of supply captures a clean, useful insight: holding other factors constant, higher prices
call forth greater quantities. It works because profits entice expansion and because marginal
costs usually rise as output stretches existing capacity. Yet real markets bring short-run
rigidities, time lags, co-products, learning effects, and strategy—each bending or shifting the
curve.
For exams and for life, remember the trio:
• Law (movement): Higher PP leads to higher Qs along a given curve.
• Determinants (shifts): Costs, technology, scale, policy, expectations, and nature
move the whole curve.
• Limits: Capacity, perishability, time, joint production, and market power explain
where and why the simple pattern wobbles.
Think like the baker or the orchard owner: respond to price, respect constraints, and invest
to make tomorrow’s supply curve kinder to you.
SECTION-C
5. Explain the law of returns to scale in detail and also its implications.
Ans: Picture a tiny family pickle business in Amritsar. In year one, it’s just one kitchen, one
grinder, and two people. Orders grow. In year two, they double everything—two kitchens,
two grinders, four workers—and production more than doubles because workers specialize:
one handles chopping, another spices, someone else sterilizes jars. In year three, they triple
everything, but now coordination gets messy: labels get mixed, batches wait for lids, and
output rises by less than triple. That journey—more than double, then less than triple—is
the essence of the law of returns to scale.
Meaning and the long-run setting
Returns to scale is about what happens to output when a firm increases all inputs by the
same proportion in the long run, when nothing is fixed.
• Production function:
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• Three possibilities:
o Increasing returns to scale (IRS):
Output rises by a greater proportion than inputs.
• Constant returns to scale (CRS):
Output rises in the same proportion.
• Decreasing returns to scale (DRS):
Output rises by a smaller proportion.
• Elasticity (degree) of scale:
o Definition:
Why increasing, constant, or decreasing returns happen
• Increasing returns to scale (why it happens):
o Specialization and division of labour: Bigger scale lets tasks be split; workers
and machines get faster at narrower jobs.
o Indivisibilities and spreading fixed inputs: Large assets (R&D teams, plant
control rooms, software) don’t need to double to support double output;
their capacity can be shared.
o Geometric advantages: In some processes, doubling capacity doesn’t double
cost (e.g., storage tanks: volume grows faster than surface area).
o Network and learning effects: Coordination improves, suppliers give better
terms, and routines get refined as scale grows.
• Constant returns to scale (why it happens):
o Replicable “plant”: When a firm can copy-paste an efficient unit—hire
another identical team, add another production line—output scales
proportionally.
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o Balanced factor scaling: If all inputs, including management and support,
expand in tune, bottlenecks don’t appear.
• Decreasing returns to scale (why it happens):
o Managerial complexity and coordination costs: Communication chains get
longer; decisions slow; errors multiply.
o Congestion and bottlenecks: Shared services (quality labs, loading bays)
become crowded, idling other inputs.
o Input scarcity or dilution of quality: As scale expands, the next unit of labor
may be less skilled, or input quality varies, dragging productivity.
Visual and numeric intuition
• On isoquants and rays: Draw rays from the origin in input space. With IRS,
isoquants get “closer together” along a ray; with CRS, evenly spaced; with DRS,
farther apart. That spacing encodes how much extra input it takes to reach the next
output level.
• Cobb–Douglas rule of thumb:
o Form:
• Sum of exponents:
o If α+β>1: IRS
o If α+β=1: CRS
o If α+β<1: DRS
More than double: IRS in action.
Costs and returns to scale
Returns to scale describe the technology; costs translate technology into money.
• Long-run average cost (LRAC):
o IRS implies falling LRAC: When doubling inputs gives more than double
output, cost per unit tends to drop as scale increases.
o CRS implies flat LRAC: Cost per unit is roughly constant over a range.
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o DRS implies rising LRAC: Beyond a point, each extra unit costs more on
average.
• Economies vs. returns to scale (don’t confuse them):
o Economies of scale: Cost concept—when LRAC falls with output.
o Returns to scale: Physical output concept—how output responds to
proportional input changes. Often aligned (IRS ↔ economies), but prices of
inputs, learning, and external economies can blur the link.
Strategic and market implications
• Optimal firm size and structure:
o Implication: If IRS persists over a wide range, firms have an incentive to
grow large to reach low unit costs. If DRS kicks in early, efficient firms stay
relatively small and decentralized.
• Market concentration and natural monopoly:
o Implication: When LRAC keeps falling across the market’s entire demand
(e.g., utilities, platforms), one big supplier can be cheapest—a natural
monopoly—inviting regulation of price and access.
• Pricing and entry barriers:
o Implication: Large firms with scale economies can set lower prices, deter
entry, or use limit pricing. New entrants need scale or niches to survive.
• Location, clustering, and external economies:
o Implication: Firms co-locate to share skilled labour pools and suppliers,
amplifying scale benefits beyond the firm (industry-level IRS), shaping
clusters like industrial parks.
• Technology choice and modularity:
o Implication: When DRS looms with size, firms adopt modular, copy-paste
units to stay near CRS zones, preserving agility while scaling output.
• Make-or-buy and scope decisions:
o Implication: If IRS is strong in a component, in-house scale may beat
suppliers; if not, outsourcing leverages someone else’s scale curve.
Economies of scope matter when shared inputs reduce costs across products.
• Long-run supply curve of an industry:
o Implication: With external economies, the industry long-run supply can
slope down; with external diseconomies, it can slope up; with neutrality, it’s
roughly flat—mirroring how average costs behave as the industry scales.
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• Policy and development strategy:
o Implication: Governments prioritize sectors with strong IRS (infrastructure,
networks, tradable manufacturing) to kickstart growth, while ensuring
competition so scale doesn’t calcify into inefficiency.
A brief second story
A startup builds one data center. Utilization is low; engineers do everything. As customers
grow, they add racks, automate deployments, and split teams by specialty. Performance
jumps faster than costs—classic IRS. Years later, the company sprawls across regions.
Meetings multiply, handoffs slow, and troubleshooting crosses time zones. Each additional
percent of capacity demands more than a percent of managerial effort—DRS setting in.
They respond by creating semi-autonomous regional pods, returning closer to CRS.
Practical takeaways and caveats
• Stages are typical, not eternal:
o Insight: Many technologies show IRS at low-to-mid scales, CRS around the
sweet spot, and DRS beyond it. The “minimum efficient scale” is where LRAC
bottoms out.
• Measurement is tricky:
o Insight: Observed cost curves reflect input prices, learning-by-doing, and
demand volatility, not just pure technology. Don’t read returns to scale from
a single quarter’s cost data.
• Short run versus long run:
o Insight: Short-run “diminishing marginal returns” (varying one input with
others fixed) is a different concept. Returns to scale is a long-run, all-inputs-
movable story.
• Technology and digital twist:
o Insight: Software and platforms often have strong IRS (near-zero marginal
cost), explaining winner-take-most dynamics; governance and
interoperability then become policy priorities.
In one line
Scale changes the game: early on, doing more makes you better (IRS); at the right size, more
is just more (CRS); push too far, and more becomes messy (DRS). The art of strategy is
finding—and staying near—that sweet spot where your technology, teams, and costs sing in
tune.
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6. Write short notes on the following:
(a) Concept of total, marginal and average costs.
(b) Theory of cost in short run and long run.
Ans: A simple story to set the stage
Imagine Asha, who runs a tiny chai-and-samosa stall near a busy college gate. At first, she
has just one stove, a single helper, and a rented counter. As evenings get crowded, she
wonders: “If I fry a few more samosas, how do my costs change? If I double production, do I
save per piece or spend more?” This everyday puzzle is exactly what cost theory answers—
how costs behave when output changes in the short run and the long run.
Concepts of total, marginal, and average costs
Think of costs as three lenses to view the same business: the full bill, the cost of one more
unit, and the cost per unit.
• Total cost (TC): The whole expense for producing a given output.
[ TC = TFC + TVC ]
Where (TFC) is total fixed cost (e.g., stall rent, a fixed monthly license) and (TVC) is total
variable cost (e.g., potatoes, oil, wages by hours).
• Marginal cost (MC): The extra cost of producing one additional unit. It answers
Asha’s “What does the next samosa cost me?” question.
• Average cost (AC or ATC): The cost per unit produced.
• Average fixed cost (AFC): Fixed cost per unit. It spreads rent and other fixed costs
across each samosa.
• Average variable cost (AVC): Variable cost per unit—ingredients and hourly labour
per samosa.
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• Relationship among averages:
[ AC = AFC + AVC ]
• Intuition:
o TC starts at the level of fixed costs even if output is zero, then climbs as you
produce more.
o MC shows how difficult it is to push production higher; it typically falls first
(better use of resources) then rises (strain on limited capacity).
o AC falls when efficiency improves and rises when extra units become costlier;
it is pulled by MC like a magnet—when MC is below AC, AC falls; when MC is
above AC, AC rises.
Theory of cost in the short run
In the short run, at least one input is fixed—Asha can’t instantly expand her stall size or buy
a new fryer. She must work within current capacity, adjusting labor hours and ingredients.
This leads to two powerful ideas: fixed vs. variable costs, and the law of diminishing
marginal returns.
• Fixed and variable costs:
o Fixed costs don’t change with output in the short run (rent, basic license
fees).
o Variable costs rise as output rises (ingredients, hourly wages, fuel).
• Short-run cost curves and their shapes:
o Total fixed cost (TFC): A flat line—unchanged at all output levels.
o Total variable cost (TVC): Rises with output; at first slowly (efficiency gains),
then faster (congestion and bottlenecks).
o Total cost (TC): Parallel to TVC but starting at TFC. It rises as output
increases, initially gently, later steeply.
• Law of diminishing marginal returns:
o With one input fixed (the single stove), adding more variable inputs (helpers,
hours) eventually leads to smaller extra output per added unit. At some
point, too many hands crowd around the same stove. This is why costs per
extra unit (MC) eventually rise.
• Typical U-shapes:
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o Marginal cost (MC): Usually falls first (better coordination, learning by doing),
then rises (congestion, overtime, equipment strain).
o Average variable cost (AVC) and average cost (AC): U-shaped; they fall while
resources are used more efficiently, and rise once diminishing returns kick in.
o Average fixed cost (AFC): Always falls as output expands, since the same rent
is spread over more units.
• Key intersections:
o MC cuts both AVC and AC at their minimum points. Before the minimum, MC
< average, pulling the average down; after the minimum, MC > average,
pushing it up.
• Managerial takeaways in the short run:
o Produce where the gap between price and MC is favourable and avoid
overloading fixed capacity.
o If price is below AVC, shut down in the short run; you can’t cover even
variable costs.
o Expand cautiously when MC is rising steeply; it signals capacity strain.
Theory of cost in the long run
In the long run, all inputs are variable. Asha can rent a bigger kitchen, buy a second fryer, or
open a second outlet. Now, instead of being trapped by one stove, she can choose the most
efficient scale for any output level.
• Planning horizon and flexibility:
o The long run is a period long enough to adjust plant size, technology, and
organization. No cost is inherently fixed—everything can be right-sized.
• Envelope of short-run average cost (SAC) curves:
o Each plant size has its own SAC curve (short-run average cost).
o The long-run average cost (LAC) curve is the lower “envelope” touching the
bottom points of all possible SACs—showing the least possible average cost
for each output level.
o Firms “ride” different SACs over time as they expand, always trying to stay
close to the LAC.
• Economies and diseconomies of scale:
o Economies of scale (downward part of LAC): Larger scale reduces average
costs due to:
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▪ Technical economies: Better machinery, specialization of tasks.
▪ Managerial economies: Professional management, streamlined
processes.
▪ Purchasing economies: Bulk buying discounts.
▪ Financial economies: Cheaper credit for larger firms.
▪ Network/logistics gains: Improved distribution and utilization.
o Diseconomies of scale (upward part of LAC): Beyond a point, average costs
rise due to:
▪ Coordination complexity: Too many layers slow decisions.
▪ Monitoring difficulties: Productivity slips, communication gaps.
▪ Bureaucracy: Rules pile up, agility fades.
• Minimum efficient scale (MES):
o The output level where long-run average cost is minimized. Operating at or
beyond MES ensures competitiveness in cost. Industries differ: some have
small MES (local bakeries), others large MES (steel plants).
• Long-run marginal cost (LMC):
o The extra cost of producing one more unit when the firm can adjust all
inputs.
Where (LTC) is long-run total cost. Like in the short run, LMC cuts LAC at its minimum.
• Modern view (flattened or L-shaped LAC):
o With learning-by-doing, modular technology, and digital coordination, the
LAC may flatten after MES or resemble an L-shape—costs fall and then
remain roughly constant over a wide range of output.
One story, two horizons: Asha’s choices
• Short run: Asha has one stove. To meet evening rush, she adds an extra helper and
extends hours. At first, her MC falls—the new helper makes prep faster. But soon
they crowd each other; spills increase, waiting time at the stove grows, and MC rises.
Her AVC and AC fall initially (better use of the stove and labor), then rise as overtime
rates kick in and congestion bites. She realizes there’s a sweet spot where costs per
samosa are lowest and queues are still manageable.
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• Long run: Not wanting to be trapped by the single stove forever, Asha plans an
upgrade. She evaluates three kitchen sizes: small, medium, and large—each with its
own SAC curve. For modest sales, the small kitchen gives the lowest AC; for growing
demand, the medium kitchen becomes cheaper per unit; if she wins a college
canteen contract, the large kitchen—despite higher rent—delivers the lowest LAC
thanks to bulk-buying and streamlined operations. Beyond a certain size, however,
the coordination headaches (more staff, longer lines of command) start lifting
average costs again—classic diseconomies of scale. She aims to operate near MES—
big enough to be efficient, small enough to stay agile.
Key relationships to remember
• Average and marginal:
MC intersects AC and AVC at their minimum points.
• Decomposition of averages:
• Short run vs. long run:
o Short run: Some inputs fixed; U-shaped MC and AC due to diminishing
returns.
o Long run: All inputs variable; LAC is the envelope of SACs; shape driven by
economies and diseconomies of scale.
• Shutdown logic (short run):
o If price < AVC, stop producing temporarily; if price ≥ AVC but < AC, operate to
cover variable costs and part of fixed costs.
Quick wrap-up
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• Total cost is the full bill; marginal cost is the extra rupee for the next unit; average
cost is the cost per unit.
• In the short run, fixed capacity creates a U-shaped cost pattern as diminishing
returns set in; MC steers AC.
• In the long run, firms choose the most efficient scale; LAC reflects the best average
cost for each output level by enveloping all short-run options. Costs fall with
economies of scale, then rise with diseconomies, defining the MES sweet spot.
If you picture Asha timing each batch and counting every potato, cost theory stops being
abstract. It becomes a map for everyday decisions: when to add one more helper, when to
buy a second fryer, and when to stop scaling before efficiency slips away.
SECTION-D
7. Explain the features of perfect competition and discuss the equilibrium of firm under
perfect competition in the short run and long run.
Ans: A simple story to set the stage
Imagine Meera at the dawn-lit mandi, one seller among hundreds, each with baskets of
identical, fresh tomatoes. Buyers stroll by, glancing at prices scribbled on cardboard. If
Meera quotes even a little more than the going rate, customers drift to the next stall; if she
quotes less, she’ll sell out with no extra reward because others instantly match. Meera isn’t
setting the price—she’s accepting it. That’s the heartbeat of perfect competition: many tiny
voices, none loud enough to move the price alone.
Features of perfect competition
• Large number of small firms and buyers: No single firm or buyer can influence price;
each participant is too small relative to the market. The firm is a price taker, not a
price maker.
• Homogeneous product: Tomatoes are tomatoes—buyers don’t care whose stall
they come from. With no brand differences, firms compete purely on price and
efficiency.
• Free entry and exit in the long run: Profits attract new firms; losses push some out.
This flow continues until only normal profit remains.
• Perfect information: Everyone knows the current price, quality, and availability. If
someone tries to charge more, buyers immediately switch.
• Perfect mobility of resources: Labor and capital can move to their best use; there
are no long-term barriers keeping factors stuck in less efficient places.
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• No selling costs or negligible transaction costs: With identical products and
transparent prices, advertising and promotion add little value.
• Horizontal demand for the firm: The market sets a single going price, and each firm
faces a perfectly elastic demand at that price:
AR=MR=PA
The industry’s demand is downward sloping, but the individual firm’s demand is a straight,
horizontal line at the market price.
Short-run equilibrium of the firm
In the short run, plant size is fixed. The firm chooses output to maximize profit subject to
existing capacity.
• Price taking and the decision rule: The firm faces a given price PP. It chooses output
Q where:
So the operative condition is MC=P.
• Shutdown condition: The firm produces only if it can cover variable costs:
The short-run supply curve of the firm is the portion of its MC curve above AVC.
• Profit or loss possibilities:
o Supernormal profit: If P>AC at the MC=MR output, the rectangle (P−AC)×Q is
positive profit.
o Normal profit (break-even): If P=AC, economic profit is zero, but accounting
profit covers opportunity cost.
o Loss minimization: If AVC≤P<AC, the firm operates (covering variable cost
and part of fixed cost) to minimize loss.
o Shutdown point: When P=minAVCP, any lower price implies shutting down.
• Diagram you can draw (mentally or in the exam):
o Axes: Price/cost on the vertical axis, output on the horizontal.
o Curves: U-shaped MC, AVC, and AC. A horizontal line at price P is the firm’s
AR=MR=P.
o Equilibrium: Where MCMC meets the price line. Compare PP with AC to infer
profit/loss; compare P with AVC to check shutdown.
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• Industry adjustment in the short run: The number of firms is fixed. Market price is
determined by the intersection of market demand and short-run market supply (the
horizontal summation of firm supplies). Individual firms then apply MC=MR to
choose their Q.
Long-run equilibrium of the firm and industry
Given time to adjust all inputs, firms can change plant size, and new firms can enter or
existing ones exit. This flexibility reshapes both costs and the number of firms.
• Entry and exit drive profits to normal: If firms earn supernormal profits (P>AC), entry
shifts market supply right, reducing price. If firms incur losses (P<AC), exit shifts
supply left, increasing price. The process continues until:
In long-run equilibrium, each firm earns zero economic profit (normal profit) and produces
at the minimum point of its long-run average cost.
• Productive and allocative efficiency:
o Productive efficiency: Firms operate at minLAC. No production at higher-
than-necessary average cost survives.
o Allocative efficiency: Price equals marginal cost, P=MC. Society’s valuation of
the last unit (price) matches the resource cost of producing it.
• Plant size choice and envelope logic: Each potential plant size has a short-run
average cost curve (SAC). The long-run average cost (LAC) curve is the lower
envelope of these SAC curves. In equilibrium, the firm selects the plant where its
chosen output sits at SAC’s minimum, which coincides with min LAC.
• Industry long-run supply (LRS):
o Constant-cost industry: Input prices don’t change as industry expands; the
LRSLRS is horizontal at P=min LAC
o Increasing-cost industry: Inputs get pricier as the industry grows; LRSLRS
slopes upward, and the long-run equilibrium price sits above the original min
LAC of smaller scale plants.
o Decreasing-cost industry (rarer): External economies make inputs cheaper;
LRSLRS slopes downward.
• What stabilizes in the long run:
o Price: Settles at min LAC.
o Firm output: Each firm produces its most efficient scale.
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o Number of firms: Adjusts so that total market quantity equals demand at
that price.
One market day, two time horizons
In Meera’s mandi, a sudden festival rush pushes price up today. In the short run, each
seller can only stretch a bit—longer hours, faster turnover. Price rises, and those with lower
costs earn temporary supernormal profits because P>AC at their MC=MR output. Weeks
later, seeing the sustained demand, more sellers arrive, wholesalers increase deliveries, and
some farmers divert more land to tomatoes. Supply expands, nudging price down until it
rests at min LAC. The rush settles into routine, and everyone earns just normal profit—
efficient, competitive, and stable.
8. What is monopolistic competition? Discuss the price and output determination under
monopolistic competition.
Ans: Monopolistic Competition – A Story of the “Market Street”
Imagine a big, lively street in your city called Market Street. On this street, there are many
shops selling almost the same type of product — let’s say, coffee. But here’s the twist: every
shop tries to be different in some way. One café offers coffee in cute mugs, another uses
organic beans, another has a cozy reading corner, and one café’s barista even sings while
making coffee.
Customers have choices. They can walk into any café they like, but the decision is not only
about price — it’s also about the feel, the quality, and the uniqueness.
This “Market Street” is exactly what monopolistic competition looks like in economics.
1. Meaning of Monopolistic Competition
Monopolistic competition is a market structure where:
• Many sellers are present in the market.
• Products are similar but slightly different from each other (this is called product
differentiation).
• Sellers compete with both price and non-price factors like design, branding, location,
and service.
• Entry and exit in the market are relatively easy.
It’s a mix of two worlds:
• From monopoly, it borrows the idea that each seller has some control over the price
because their product is a little unique.
• From perfect competition, it borrows the idea of having many sellers and buyers.
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Examples in the real world: Fast-food restaurants (McDonald’s, KFC, Subway), clothing
brands, beauty salons, bakeries, and yes — your neighborhood cafés.
2. Key Features of Monopolistic Competition
Before we go deeper into how prices and outputs are decided, let’s break down its main
features in simple terms:
1. Large number of sellers – Many firms are in the market, each selling slightly
different products.
2. Product differentiation – Each firm tries to make its product look unique through
packaging, taste, style, quality, brand name, etc.
3. Some price control – Because their product is different, they can set prices slightly
higher or lower.
4. Free entry and exit – New businesses can join easily, and failing ones can leave.
5. Selling costs – Firms spend on advertising, promotions, or offers to attract
customers.
6. Close substitutes – Even if products are different, they are still alternatives to each
other.
3. Price and Output Determination under Monopolistic Competition
Now comes the real heart of the matter:
How do these firms decide how much to produce and what price to charge?
We can understand this by looking at two situations: Short Run and Long Run.
A. Price and Output in the Short Run
Let’s go back to our Market Street café example. Suppose one café — Sunshine Brews —
offers a unique vanilla-flavoured coffee that no other shop has. Because customers love it,
the café can charge a slightly higher price.
Step-by-step process in short run:
1. Demand curve (AR curve) – Because of product differentiation, the demand for the
café’s coffee is downward sloping. If the café wants to sell more cups, it must lower
the price; if it sells fewer cups, it can keep the price high.
2. Marginal Revenue (MR) curve – This lies below the Average Revenue curve because
the café must lower the price on all units to sell more.
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3. Cost curves (MC & AC) – Like any business, the café has costs for coffee beans, rent,
salaries, etc.
4. Equilibrium point – The café will produce at the output level where MC = MR
(Marginal Cost equals Marginal Revenue).
o This point tells the café how many cups to produce for maximum profit.
5. Price setting – Once output is decided, the café looks up to the demand (AR) curve
to find what price customers are willing to pay for that quantity.
Possible outcomes in short run:
• Supernormal profits – If the demand is high and costs are under control, the café
can earn more than normal profit.
• Normal profit – If costs match revenue, the café just covers its expenses.
• Losses – If competition is too strong or costs are too high, the café may face losses.
B. Price and Output in the Long Run
In the long run, something interesting happens.
Remember how people loved Sunshine Brews vanilla coffee? Other cafés notice this and
decide to introduce their own version. Soon, competition increases. Customers now have
more choices, so Sunshine Brews’ demand falls a bit.
In economics, we say:
New firms enter → market supply increases → price falls → supernormal profits disappear.
Step-by-step in the long run:
1. Because of free entry, new cafés join the market whenever existing ones earn
supernormal profits.
2. The demand for each existing café’s coffee decreases until only normal profits
remain.
3. In the long-run equilibrium:
o Each firm still produces where MC = MR.
o But the price is equal to Average Cost (AC), so there are no extra profits.
4. Firms continue to survive not because they earn huge profits, but because they
cover their costs and maintain their customer base.
4. Diagram Explanation
If we draw it, here’s how it would look:
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Short Run:
• MC = MR determines output.
• Price is found on the demand curve above this output.
• Price is higher than AC → supernormal profits.
Long Run:
• New firms enter → demand curve shifts left.
• Price equals AC at the equilibrium output → only normal profits.
5. Real-Life Story to Wrap It Up
Once upon a time in a small town, there was a bakery called Sweet Crumbs. They sold
chocolate muffins that no one else had. At first, they charged a high price and still had a line
outside every morning (short run supernormal profit).
But soon, two other bakeries started making similar muffins. Customers now had choices,
and Sweet Crumbs had to lower prices and improve quality just to keep customers (long run
normal profit).
In the end, the bakery stayed in business not because it was making a fortune, but because
it found loyal customers who liked the personal touch they gave — a perfect example of
monopolistic competition.
6. Final Summary Table
Aspect
Short Run
Long Run
Number of firms
Fixed
Can change (entry & exit)
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Profits
Supernormal, normal, or loss possible
Only normal profits
Price
Above AC if profits exist
Equal to AC
Output decision
MC = MR
MC = MR
Competition effect
Limited
Stronger due to new entries
In short:
Monopolistic competition is like a busy shopping street where each seller has their own
style. In the short run, uniqueness can bring high profits, but in the long run, competition
catches up, and everyone settles into earning just enough to keep going. The beauty of this
market is that it gives customers variety, and firms freedom to be creative — just like cafés,
bakeries, clothing brands, and salons do in our everyday lives.
“This paper has been carefully prepared for educational purposes. If you notice any mistakes or
have suggestions, feel free to share your feedback.”
