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Econ 555 Assignment – Demand Elasticity and Forecasting

Question

Econ 555

Homework Assignment

on Demand Elasticity and Forecasting

Name:___________________________________________

Part 1. Demand Elasticity (10 points)

The following is a typical regression output from Excel
Spreadsheet:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.50

R Square

0.25

Adjusted R Square

0.17

Standard Error

165.83

Observations

21.00

ANOVA

df

SS

MS

F

Significance F

Regression

2.00

167135.65

83567.83

3.04

0.04

Residual

18.00

495004.09

27500.23

Total

20.00

662139.75

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 99.0%

Upper 99.0%

Intercept

14853.98

2016.40

7.37

0.00

10617.69

19090.27

9049.90

20658.06

OWN PRICE

-49.31

20.72

-2.38

0.03

-92.85

-5.77

-108.96

10.34

WINE PRICE

105.82

49.04

2.16

0.04

3.51

215.15

43.97

255.61

Assume that your consultant was charged with estimating a
demand equation for your company’s product, COOL BEER. While providing you with the above regression
output, she explained that the dependent variable used was the quantity sold
(Q) of COOL BEER and independent variables used were OWN PRICE (P) of COOL BEER
and WINE PRICE (Y). Concentrating on the
yellow-highlighted area, please answer the following questions.

1. What is the
estimated demand equation for COOL BEER? (1 point)

2. Which
coefficients are/is significant at the 5% significance level? (1 point)

3. What is the quantity demanded of COOL
BEER when OWN PRICE = $520 and WINE PRICE = $120?(1 point)

4. What is the own price elasticity of
demand when OWN PRICE = $520 and WINE PRICE = $120?Is it elastic or inelastic?
(2 points)

5. What is the cross-price elasticity of
demand when OWN PRICE = $520 and WINE PRICE = $120? (1 point)

6. Is COOL BEER a complement or a
substitute with WINE? (2 points)

7. Do you think this is a good/bad demand
equation for you to use? State the
reasons for and against your decision to use or not to use it. (2 points)

Part 2. Forecasting
and U-Statistic Calculation (15 points)

Three forecasting
models of N, FBI, and CIA generated the following forecasts where

Nt is
generated by the naïve model.

FBIt
is generated by FBIt = 31.6 + 0.8At-1

CIAt
is generated by CIAt = 31.6 + 0.8At

Raw Data for Forecasting and U-Statistic Calculation

Actual

Forecast Models

Period

At

Nt

FBIt

CIAt

1

27

2

30

27

53.2

55.6

3

42

30

55.6

65.2

4

38

42

65.2

62

5

35

38

62

59.6

6

45

35

59.6

67.6

7

33

45

67.6

58

8

28

33

58

54

9

39

28

54

62.8

10

43

N10=?

FBI10=?

CIA10=?

11

N11=?

FBI11=?

CIA11=?

1. Provide the forecast values of N10,
N11, FBI10, FBI11, CIA10, and CIA11. (1 point each)

N10 =

N11 =

FBI10 =

FBI11 =

CIA10 =

CIA11 =

2. Calculate
the U-statistic for each of the three forecast models.

(If you used a computer software such as Excel
Spreadsheet to calculate the U-statistic, please submit the computer output
along with the HW answer.)

U-statistic for theNaïve Model =

(1 point)

U-statistic for the FBI Model =

(3 points)

U-statistic for the CIA Model =

(3 points)

3. Identify the best and the worst of the
3 forecasting models based on the U-statistics calculated above. (2 points)

The best =

The worst =

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