Demand The willingness and ability to buy How does marginal analysis inform simple pricing decisions? How can the concept of elasticity inform managerial decisions? How can managers learn about consumer demand? Professor Spry University of St. Thomas - PowerPoint PPT Presentation

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Demand The willingness and ability to buy How does marginal analysis inform simple pricing decisions? How can the concept of elasticity inform managerial decisions? How can managers learn about consumer demand? Professor Spry University of St. Thomas

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Title: Demand The willingness and ability to buy How does marginal analysis inform simple pricing decisions? How can the concept of elasticity inform managerial decisions? How can managers learn about consumer demand? Professor Spry University of St. Thomas


1
Demand The willingness and ability to buy How
does marginal analysis inform simple pricing
decisions? How can the concept of elasticity
inform managerial decisions? How can managers
learn about consumer demand? Professor
Spry University of St. Thomas
  • Economics 600
  • 600pm-900pm

2
Todays agenda
  • Demand functions
  • Linear Demand Functions and Curves
  • Players Theater Example
  • Own-Price, Cross-Price, and Income Elasticities
    of Demand
  • Applications of Demand Estimation
  • Forecasting prices of FCC Licenses
  • The Demand for Hoosier Lottery Tickets

3
Motivating Example Red Lobster
  • All you can eat crab dinner
  • For that 2nd and 3rd and helping,
  • What is the marginal cost to customer?
  • What is the marginal benefit to customer?
  • What is the marginal benefit cost to Red
    Lobster?
  • What if steak? Fish chips?

4
Demand Function for Indiana Lottery Games
  • The relationship between the quantity demanded of
    a good or service and all influencing factors
  • Qd f(X1, X2,X3,X4 Xn)
  • where Qd is quantity demanded per period and the
    Xis are the factors influencing demand
  • Example Demand for Indiana Lottery Tickets
  • Q quantity of Lottery Tickets purchased per
    period
  • X1 Price per ticket (expected loss)
  • X2 Price of other goods
  • X3 Average income per period
  • X4 A binary variable for a state border
  • Other variables such as advertising, proximity to
    riverboat casinos, seasonal variables

5
Demand Curve
  • Definition A demand curve shows the amount of a
    good/service consumer(s) are willing and able to
    buy per period at various prices all else
    constant
  • Plug in values of other variables, such as
    income, prices of substitutes, ect. into the
    demand function to obtain the demand curve as a
    function of the price of the good only
  • Pa-bQ or Q(P)

6
Modeling demand as a constrained choice problem
  • The consumer has
  • Desire to maximize satisfaction from a variety of
    purchases
  • Tastes preferences affected by advertising and
    other factors
  • A budget constraint for those purchases
  • Affected by income, prices of goods services
    under consideration

7
The Logic of Consumer Choice and Demand
  • Change in a demand factor
  • E.g. lower price of good gt change in budget
    constraint gt reduces opportunity cost of
    purchasing this good gt purchase more units
  • Movement along a single demand curve
  • E.g. increase income gt expands budget constraint
    gt buy more of many goods and services
  • Demand curve shifts
  • E.g. persuasive advertising gt shapes tastes
    preferences gt may sway consumer toward this
    product without requiring a price decrease
  • Demand curve shifts

8
Market Demand Function for PTC Tickets
  • Q 117 - 6.6P 1.66Ps - 3.3Pr 0.00661I
  • where P is PTC ticket price, Ps is price of
    symphony tickets, Pr is price of nearby
    restaurant meals, and I is average per capita
    income.
  • Suppose the variables have the following values
  • Ps 50
  • Pr 40
  • I 50,000
  • Substituting variable values (except for P) into
    the equation and rounding
  • Q 400 6.6P demand curve or
  • P 60 0.15Q (inverse) demand curve

9
Graphing the demand curve for PTC
PTC demand curve P 60 0.15Q Think of P as
the Y variable Think of Q as the X
variable 60 is the vertical Y intercept -0.15
is the slope (change in Y/change in X)
10
How Many Tickets Should PTC Sell Using Linear
Demand Curve Facts
  • In general, if
  • P a bQ (linear)
  • TR aQ bQ2
  • MR a 2bQ
  • This is an application of the derivative formula.
  • If f(x)axb then f(x)abxb-1.

Dont sell as much as possible, maximize your
profits!!!! If it is worth producing, produce
until Marginal Revenue Marginal Cost!!
11
Marginal Analysis and Pricing
  • Q 400 6.6P demand curve or
  • P 60 0.15Q (inverse) demand curve

12
Price elasticity of demand
  • Measures the sensitivity of quantity demanded to
    changes in demand factors
  • The price elasticity of demand is given by
  • (all else constant)

Does a given (often a 1) change in the price of
the good lead to a small reduction or a huge,
titanic reduction in the QUANTIY DEMANDED??
Absolute Value
13
Determinants of price elasticity
  • Availability of substitutes
  • Size of good in consumer budget
  • Time period for consumer adjustment
  • Discuss a) Southwest Airlines estimates the
    short-run price elasticity of business air travel
    to be 2 and the long-run elasticity to be 5.
    Does this seem reasonable? Explain.
  • b) Would the market demand for business air
    travel be more or less elastic than Southwests?
    Why?

14
Estimated Price Elasticities
  • Prescription drugs (Baye, Maness, Wiggins in
    Applied Economics 29 (1997))
  • Cardiovascular 0.4
  • Anti-infective 0.9
  • Psychotherapeutic 0.3
  • Anti-ulcer 0.7
  • Recreation 1.1 (short term) 3.5 (long term)
  • Clothing 0.9 (short term) 2.9 (long term)
  • Alcohol tobacco0.3 (short term) 0.9 (long
    term)
  • Baye, Jansen, Lee, in Applied Economics 24
    (1992)

15
Calculating elasticity from a linear Demand
Curve point price elasticity
  • ? Information requirements
  • Demand curve equation
  • Qa-ßP, ß ?Q/?P
  • Initial price and quantity
  • Q
  • P

16
Calculating elasticity Using a linear demand Curve
  • The demand curve facing the Como Park Golf Course
    is Qd100 2P
  • The current price is 20.00 for a round of golf.
  • 60 golfers play Como per day.
  • What is the own-price elasticity of demand at
    Como at a price of 20.00?

17
Calculating elasticity arc price elasticity
  • ?Information requirements
  • Quantity demanded before and after the price
    change
  • Q1
  • Q2
  • Price before and after the price change
  • P1
  • P2

18
Calculating elasticity arc price elasticity

19
Example Housing Sales
  • From March to April of 1998, the price of an
    average single-family home decreased from
    128,200 to 127,100. Interest rates and income
    were unchanged.
  • Housing sales increase from 4,700,000 to
    4,890,000.
  • Source WSJ, May 27, 1998

20
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
D
Q
21
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
5


D
100
Q
22
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
5


D
100
Q
23
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
S2
5


D
100
Q
24
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
S2
5

2

D
100
160
Q
25
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
S2
5

2

D
100
160
Q
26
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
S2
5

2

D
100
160
Q
27
Total Spending and the Shape of the Demand Curve
Inelastic Demand
P
S1
S2
5

A
2

C
B
D
100
160
Q
28
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1

D

Q
29
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1

5


D

100
Q
30
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1

5


D

100
Q
31
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1
S2

5


D

100
Q
32
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1
S2

5

4

D

100
240
Q
33
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1
S2

5

4

D

100
240
Q
34
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1
S2

5

4

D

100
240
Q
35
Total Spending and the Shape of the Demand Curve
Elastic Demand
P
S1
S2

5

A
4

D
C
B

100
240
Q
36
Cross-Price Elasticity
  • Positive if substitutes negative if complements
  • Cross-price elasticity of demand for new car
    sales from a change in gas prices - 0.214
  • (McCarthy, in Economic Inquiry 28 (July 1990),
    pp. 530-43)
  • Interpretation?

37
Income Elasticity of Demand
  • Inferior good lt0
  • Normal good gt0
  • Luxury good gt1
  • Examples of income elasticities of demand
  • Powerball 0.9
  • Daily games 0.68
  • Instant games 0.4

38
Log-Log Demand Functions Constant Elasticity of
Demand
  • Assumption
  • Constant own-price elasticity of elasticity of
    demand and constant income elasticity of demand

39
Estimating Demand Multiple Regression Technique
  • Information requirements
  • Hypothetical demand relationship
  • Q a bP cPsubst dI eAdvert.
  • Data
  • series for Q, P, Psubst , I, Advert.

40
Estimating Demand Multiple Regression Technique
  • Use statistical program (e.g. Excel) to estimate
    parameters using multiple regression techniques
  • a, b, c, d, e
  • Assess summary statistics to judge reliability

41
Caution Demand Estimation Problems
  • Omission of relevant variables
  • Important demand variable
  • Identification problem
  • Price changes may not be exogenous
  • Supply shifts muddy the water
  • Critical issue because estimates of parameters
    can be seriously biased

42
Demand Estimation in Telecom
  • CEO of a regional tel. Co. was interested in
    bidding on licenses for airwaves in the region
    that the FCC was licensing off. Purpose was for
    wireless communications networks. He read a New
    York Times article that contained the following
    data price paid per license in 10 different
    regions (Millions of dollars), number of licenses
    sold, quantity of licenses, and regional
    population (millions). Given the three
    logarithmic data series, he clicked the
    regression tool button and found the following
    relation
  • Ln P 2.23 1.2 ln Q 1.25 ln Pop
  • The estimated equation should give him info on
    how much he should expect to bid to buy a
    license. You can show that with log-linear
    demand functions such as this one, the estimated
    coefficients equal elasticities. Since the
    population in the region is 7 percent higher than
    the average, this means
  • or the
    change in P 8.75.
  • Thus, the CEO would expect to pay 8.75 higher
    in his region. The data showed the average price
    to be 70.7 million for a license. So he should
    expect to pay 76.9 million.
  • What type of information would the CEO want to
    know whether to place a high degree of confidence
    in this estimate? Why?

43
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44
Looking Forward
  • Assignment 1 Due Sept. 30, Oct. 4 or 5
  • Due at start of class!
  • Read Managerial Economics Chapter 5
  • Moneyball and the Oakland As
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