Transcript Elasticity

ELASTICITY
Managerial Economics
Jack Wu
ELASTICITY
NEW YORK CITY TRANSIT AUTHORITY

May 2003: projected deficit of $1 billion over
following two years
Raised single-ride fares from $1.50 to $2
 Raised discount fares

One-day unlimited pass from $4 to $7
 30-day unlimited pass from $63 to $70


Increased pay-per-ride MetroCard discount from 10%
bonus for purchase of $15 or more to 20% for
purchase of $10 or more.
NY MTA
MTA expected to raise an additional $286 million
in revenue.
 Management projected that average fares would
increase from $1.04 to $1.30, and that total
subway ridership would decrease by 2.9%.

MANAGERIAL ECONOMICS
QUESTION
Would the MTA forecasts be realized?
 In order to gauge the effects of the price increases,
the MTA needed to predict how the new fares
would impact total subway use, as well as how it
would affect subway riders’ use of discount fares.


<Note> We can use the concept of elasticity to
address these questions.
OWN-PRICE ELASTICITY: E=Q%/P%
Definition: percentage change in quantity
demanded resulting from 1% increase in price of
the item.
Alternatively,
% _change_in_quantity_demanded
% _change_in_price
OWN-PRICE ELASTICITY: CALCULATION
CALCULATING ELASTICITY

Arc Approach:
Elasticity={[Q2-Q1]/avgQ}/{[P2-P1]/avgP
% change in qty = (1.44-1.5)/1.47 = -4.1%
 % change in price = (1.10-1)/1.05 = 9.5%
 Elasticity=-4.1%/9.5%
=-0.432

CALCULATING ELASTICITY

Point approach:
Elasticity={[Q2-Q1]/Q1}/{[P2-P1]/P1}
% change in qty = (1.44-1.5)/1.5= -4%
% change in price = (1.10-1)/1= 10%
Elasticity=-4%/10%=-0.4
OWN-PRICE ELASTICITY
|E|=0, perfectly inelastic
 0<|E|<1, inelastic
 |E|=1, unit elastic
 |E|>1, elastic
 |E|=infinity, perfectly elastic

OWN-PRICE ELASTICITY: SLOPE
Steeper demand curve
means demand less
elastic
 But slope not same as
elasticity

DEMAND CURVES
Price
perfectly inelastic
demand
perfectly elastic
demand
0
Quantity
LINEAR DEMAND CURVE
Vertical intercept: perfectly elastic
 Upper segment: elastic
 Middle: Unit elastic
 Lower segment: inelastic
 Horizontal intercept: perfectly inelastic

OWN-PRICE ELASTICITIES
Product
Automobiles
Chevette
Civic
Consumer products
music CDs
cigarettes
liquor
football games
Utilities
electricity (residential)
telephone service
water (residential)
water (industrial)
Market
Elasticity
U.S.
U.S.
-3.2
-4
Aus
U.S.
U.S.
U.S.
-1.83
-0.3
-0.2
-0.275
Quebec
Spain
U.S.
U.S.
-0.7
-0.1
-0.25
-0.85
OWN-PRICE ELASTICITY: DETERMINANTS


availability of direct or indirect substitutes
cost / benefit of economizing (searching for better
price)

buyer’s prior commitments

separation of buyer and payee
AMERICAN AIRLINES
“Extensive research and many years of experience
have taught us that business travel demand is
quite inelastic… On the other hand, pleasure
travel has substantial elasticity.”
Robert L. Crandall, CEO, 1989
AADVANTAGE
1981: American Airlines pioneered
frequent flyer program
 buyer commitment
 business executives fly at the expense of
others
FORECASTING:
WHEN TO RAISE PRICE
 CEO:
“Profits are low. We must raise prices.”
 Sales
Manager: “But my sales would fall!”
 Real
issue: How sensitive are buyers to price
changes?
FORECASTING

Forecasting quantity demanded

Change in quantity demanded = price elasticity of
demand x change in price
FORECASTING:
PRICE INCREASE

If demand elastic, price increase leads to
proportionately greater reduction in purchases
 lower expenditure


If demand inelastic, price increase leads to

proportionately smaller reduction in purchases

higher expenditure
INCOME ELASTICITY, I=Q%/Y%
Definition: percentage change in quantity
demanded resulting from 1% increase in income.
Alternatively,
% _change_in_quantity_demanded
% _change_in_income
INCOME ELASTICITY
I >0, Normal good
 I <0, Inferior good
 Among normal goods:
0<I<1, necessity
I>1, luxury

INCOME ELASTICITY
Item
Consumer products
cigarettes
liquor
food
clothing
newspapers
Utilities
electricity (residential)
telephone service
Market
Elasticity
U.S.
U.S.
U.S.
U.S.
U.S.
0.1
0.2
0.8
1
0.9
Quebec
Spain
0.1
0.5
CROSS-PRICE ELASTICITY: C=Q%/PO%
Definition: percentage change in quantity
demanded for one item resulting from 1%
increase in the price of another item.
 (%change in quantity demanded for one item) /
(% change in price of another item)

CROSS-PRICE ELASTICITY
C>0, Substitutes
 C<0, complements
 C=0, independent

CROSS-PRICE ELASTICITIES
Item
Market
Consumer products
clothing/food
U.S.
gasoline (competing stn) Boston, MA
Utilities
electricity/gas (residential)
Quebec
electricity/oil (residential)
Quebec
bus/subway
London
Elasticity
0.1
1.2
0.1
0
0.25
ADVERTISING ELASTICITY: A=Q%/A%
Definition: percentage change in quantity
demanded resulting from 1% increase in
advertising expenditure.
ADVERTISING ELASTICITY: ESTIMATES
Item
Market
Elasticity
Beer
U.S.
0
Wine
U.S.
0.08
Cigarettes
U.S.
0.04
If advertising elasticities are so low, why
do manufacturers of beer, wine, cigarettes
advertise so heavily?
ADVERTISING
direct effect: raises demand
 indirect effect: makes demand less sensitive to
price

Own price elasticity for antihypertensive drugs
Without advertising:
-2.05
With advertising:
-1.6
FORECASTING DEMAND

Q%=E*P%+I*Y%+C*Po%+a*A%
FORECASTING DEMAND
Effect on cigarette demand of
 10% higher income
 5% less advertising
change
elas.
effect
income
10%
0.1
1%
advert.
-5%
0.04
-0.2%
net
+0.8%
ADJUSTMENT TIME
short run: time horizon within which a buyer
cannot adjust at least one item of
consumption/usage
 long run: time horizon long enough to adjust all
items of consumption/usage

ADJUSTMENT TIME
For non-durable items, the longer the time that
buyers have to adjust, the bigger will be the
response to a price change.
 For durable items, a countervailing effect (that is,
the replacement frequency effect) leads demand
to be relatively more elastic in the short run.

Price ($ per unit)
NON-DURABLE:
SHORT/LONG-RUN DEMAND
5
4.5
long-run demand
short-run demand
0
1.5
1.6
1.75
Quantity (Million units a month)
SHORT/LONG-RUN ELASTICITIES
Item
Nondurables
cigarettes
liquor
gaseline
bus
subway
railway
Durables
automobiles
Factor
Market
Short-run Long-run
price
price
price
income
price
price
price
U.S.
U.S./Canada
U.S.
U.S.
London
London
Philadelphia
-0.3
-0.2
-0.1
0
-0.8
-0.4
-0.5
-3.3
-1.8
-0.5
0.3
-1.3
-0.7
-1.8
price
income
U.S.
U.S.
-0.2
3
-0.5
1.4
STATISTICAL ESTIMATION: DATA
time series – record of changes over time in one
market
 cross section -- record of data at one time over
several markets
 Panel data: cross section over time

MULTIPLE REGRESSION
Statistical technique to estimate the separate effect
of each independent variable on the dependent
variable
 dependent variable = variable whose changes are
to be explained
 independent variable = factor affecting the
dependent variable
DISCUSSION QUESTION

Drugs that are not covered by patent can be
freely manufactured by anyone. By contrast, the
production and sale of patented drugs is tightly
controlled. The advertising elasticity of the
demand for antihypertensive drugs was around
0.26 for all drugs, and 0.24 for those covered by
patents. For all antihypertensive drugs, the own
price elasticity was about -2.0 without
advertising, and about -1.6 in the long run with
advertising.
DISCUSSION QUESTION:
CONTINUED
Consider a 5% increase in advertising
expenditure. By how much would the demand for
a patented drug rise? What about the demand
for a drug not covered by patent?
 Why is the demand for patented drugs less
responsive to advertising than the demand for
drugs not covered by patent?
 Suppose that a drug manufacturer were to
increase advertising. Explain why it should also
raise the price of its drugs.
