Question Details

(solution) Discussion Board Week 2 1. "Estimating Demand and Its


Discussion Board Week 2

1.   "Estimating Demand and Its Elasticities" and Statistical Estimation of the Demand Curve
ECO550 Week 2 Scenario Script: Models of Supply and Demand, and Non-Price

 

Determinants of Each

 

Slide # Topics Slide 1 Scene 1 Narration An older cottage style family run

 

business (Katrina?s Candies)

 

Slide 2 Scene 2

 

Herb and Maria are in Herb?s office

 

reviewing the demand model Herb and

 

Renee formulated and discussing the

 

data Maria compiled for estimating the

 

model. ECO550_2_2_Herb-1:Good day,

 

Maria. Thanks for responding so

 

quickly to my request for data.

 

ECO550_2_2_Maria-1:Hello, Herb.

 

No problem, I am assigned to the team

 

to help with the data so when I received

 

your email, I started looking for the data

 

immediately.

 

ECO550_2_2_Herb-2:Fantastic. Let?s

 

get started by reviewing the data you

 

compiled. Then you can explain how I

 

can use Excel to estimate the model.

 

ECO550_2_2_Maria-2:First, would

 

you review the model with me? I need

 

to understand how the model is setup.

 

ECO550_2_2_Herb-3:Oh, okay.

 

Recall from our team meeting that the

 

team?s task is to provide Ken with

 

information he can use to respond to the

 

Board of Directors? request to expand

 

Katrina?s into international markets.

 

ECO550_2_2_Maria-3:Yes, I do recall

 

that.

 

ECO550_2_2_Herb-4: Renee and I

 

met after the team meeting and decided

 

the best way to proceed is to build a

 

model of the demand for Katrina?s new

 

sugar-free-chocolate candy then use the

 

model to predict the demand. In the

 

model, the quantity of Katrina?s sugarfree-chocolate candy is the dependent variable and there are five

 

independent variables. Show the 5 variables on projector:

 

Price of Katrina?s Sugar Free

 

Chocolate;

 

Price of the substitute good;

 

Complementary good;

 

Income;

 

Number of buyers in the market. ECO550_2_2_Maria-4: Very

 

interesting! Could you please go over

 

these five independent variables with

 

me?

 

ECO550_2_2_Herb-5: Sure! The first

 

independent variable is theprice of

 

Katrina?s sugar-free chocolate. The

 

model must include the price of sugarfree-chocolate; otherwise, there is no

 

demand curve.

 

Next is the price of the substitute good.

 

In the case of chocolate, caffeinated

 

coffee is the substitute good. Then there

 

is the complementary good; for

 

Katrina?s model, we selected bottled

 

water; therefore the price of bottled

 

water is the next independent variable.

 

Income is another variable typically

 

included in a demand curve. For our

 

model, we selected median household

 

income.

 

Last, since we are interested in the

 

market for Katrina?s sugar-freechocolate, the number of buyers in the

 

market is included as an independent

 

variable.

 

ECO550_2_2_Maria-5: Thanks for

 

going over that. You and Renee were

 

certainly busy!

 

ECO550_2_2_Herb-6: Yes, we were! I

 

am going to use the data you provided

 

to estimate the model to see if we

 

selected the right set of determinants.

 

Then, Renee and I can use the model to

 

develop other measures that tell us more

 

about the market for Katrina?s sugarfree-chocolate. Slide 3 Scene 3

 

In Herb?s office to explain concept of

 

estimation

 

Shows the model on the projector ECO550_2_3_Maria-1:You mentioned

 

a lot of terms that are sort of new to me.

 

In this case what does ?estimate? mean?

 

ECO550_2_3_Herb-1:Here this may

 

help with the concept of estimation,

 

here?s what the finalized model should

 

look like. We will talk about the actual

 

estimation process in a few moments.

 

ECO550_2_3_Maria-2: I?m not too

 

sure of what this model contains, could

 

you explain further? Show on the projector: The notation on

 

the left side of the equal sign,

 

Qsubscript-d-k-s-f-c represents the

 

dependent variable ECO550_2_3_Herb-2: Gladly! The

 

notation on the left side of the equal

 

sign, Q subscript-d-k-s-f-c represents

 

the dependent variable which is the

 

quantity of Katrina?s sugar-freechocolate candy. The terms on the

 

right-side of the equal sign are the

 

independent variables I just explained.

 

ECO550_2_3_Maria-3: That makes a

 

lot more sense now! Where does the

 

estimation process come into play?

 

ECO550_2_3_Herb-3: Estimating the

 

model means to find values for the

 

coefficients, which in our model are the

 

?b?s?. Coefficients are numeric values

 

that indicate how much the quantity of

 

the dependent variable will change as

 

independent variables change. The data

 

you compiled will be used to calculate

 

the coefficient values. This information

 

is important as it helps determine the

 

quantity demanded of sugar-freechocolate changes in response to

 

changes in the independent variables

 

included in the model.

 

ECO550_2_3_Maria-4:Okay, got it.

 

You?ve used the terms ?dependent

 

variable? and ?independent

 

variable?while explaining the model.Could you provide me with some

 

insight on these terms?

 

ECO550_2_3_Herb-4:Yes, of course.

 

A dependent variable is a variable that

 

changes value when changes occur in

 

some other variable. The term

 

?variable? is used to capture the fact

 

that the value can change. On the

 

flipside, an independent variable is a

 

variable that impacts or causes a change

 

in the dependent variable.

 

ECO550_2_3_Maria-5:Okay, Herb, I

 

think I understand now. Can you give

 

me examples of dependent and

 

independent variables that are different

 

from Katrina?s sugar-free-chocolate

 

candy?

 

ECO550_2_3_Herb-5:Yes I can,

 

Maria. I believe a good example is

 

umbrellas. Think about umbrella sales,

 

when the weather changes from clear to

 

rainy, people buy more umbrellas. This

 

is especially prevalent with people who

 

may have left their umbrellas at home.

 

In this example, the quantity of

 

umbrellaspurchased changes when the

 

weather changes, so it is quite easy to

 

identify the dependent and independent

 

variables in this example. The

 

quantity of umbrellas sold is the

 

dependent variable while rain is the

 

independent variable.

 

ECO550_2_3_Maria-6:That?s

 

anexcellent example, Herb. I understand

 

exactly how the model functions now.

 

The independent variables you and

 

Renee selected will explain what caused

 

or is causing the demand for Katrina?s

 

sugar-free chocolate candy to change.

 

ECO550_2_3_Herb-6: Yes, Maria,

 

that?s right. Using the data you

 

provided, we are going to see how well the model we formulated explains the

 

demand for sugar-free-chocolate candy. Slide 4 Scene 4

 

Herb?s office to go over the data Maria

 

collected. ECO550_2_4_Herb-1: Maria, could

 

you update me on the data you collected

 

for this project?

 

ECO550_2_4_Maria-1:I located most

 

of the data you requested involving the

 

number of sugar-free-chocolates

 

Katrina?s sold since introducing the new

 

candy and the selling prices. You will

 

notice that this data is available in our

 

accounting database. However, I had to

 

search outside of the database for other

 

data.

 

ECO550_2_4_Herb-2: What other data

 

did you need to acquire and how did

 

you go about doing this search?

 

ECO550_2_4_Maria-2:I needed to

 

find the prices of coffee and I simply

 

did a Google search and looked for

 

reliable sources of information

 

pertaining to concepts such as the price

 

of coffee. Insert the URL for the Census Bureau Show a pictures of the Strayer Resource

 

Center ECO550_2_4_Herb-3: Okay, that

 

leaves data on the price of water,

 

median income and the number of

 

buyers. Where did you retrieve data for

 

these independent variables?

 

ECO550_2_4_Maria-3: Well, I

 

retrieved median household income

 

data from the U.S. Census Bureau

 

website. Census data is easy to find,

 

reliable and easy to use. I just went to

 

the Census Bureau website, typed in the

 

key term, ?household income,? then

 

selected the median household income

 

for the appropriate years. ECO550_2_4_Herb-4:Did you know

 

you could have retrieved data on

 

income and other variables by going

 

through Strayer?s Global campus?

 

Resources Center?

 

ECO550_2_4_Maria-4: No, I didn?t

 

know that, Herb. Isn?t access to

 

Strayer?s Resources Center restricted?

 

ECO550_2_4_Herb-5:Yes, only

 

enrolled students, faculty and staff and

 

subscribers can use the Resource

 

Center. However, since there are so

 

many Strayer educated employees here

 

at Katrina?s, we have free access to the

 

Resource Center.

 

ECO550_2_4_Maria-5:That?s great

 

news, Herb!

 

ECO550_2_4_Herb-6: I agree! So in

 

the future when you need to search for

 

data, check out the Resource Center

 

first.

 

Slide 5 Scene 5

 

Herb?s office to go over the data Maria

 

collected and investigate briefly the

 

Resource Center ECO550_2_5_Maria-1:The Resource

 

Center seems very easy to use. I?ll

 

definitely use it next time I need to find

 

data. Let?s see where we are with the

 

data I compiled. I told you about data

 

for the quantity and price of Katrina?s

 

sugar-free-chocolate candy, data on the

 

price of caffeinated coffee and median

 

household income. Now, I have to tell

 

you, I had a problem finding price data

 

for bottled water and finding the

 

number of consumers who purchase

 

chocolate candy.

 

ECO550_2_5_Herb-1:Oh, no. Does

 

this mean we have to change our

 

model?

 

ECO550_2_5_Maria-2:That depends

 

upon whether you accept the proxy

 

variables I found and recommend using them to ?estimate? the model.

 

ECO550_2_5_Herb-2: I?m not quite

 

sure about these ?proxy variables.?

 

Could you elaborate on this concept?

 

ECO550_2_5_Maria-3: Sure thing!

 

When data is not available for a

 

variable, analysts often use data from

 

another variable to capture the same

 

relationship as the original variable. It is

 

this substitute variable that is referred to

 

as ?proxy variable.?

 

ECO550_2_5_Herb-3: Does data for

 

proxy variables work as well when the

 

model is estimated?

 

ECO550_2_5_Maria-4:That depends,

 

in some cases the answer is yes and in

 

others it is no. In order to determine the

 

answer, you are required to estimate the

 

model to find out. Keep in mind that if

 

the proxy data does not work, then the

 

variable is dropped from the model. Slide 6 Scene 6

 

Herb?s office to go over the data Maria

 

collected. Show data table of per capita

 

consumption of bottled water. ECO550_2_5_Herb-4: Thanks for the

 

clarification on this subject. We can

 

continue with our updates on the data

 

you collected.

 

ECO550_2_6_Maria-1:Again, since I

 

was unable to locate the price of bottled

 

water, I had to add a proxy variable.

 

The data I used dealt with the per capita

 

consumption of bottled water.

 

ECO550_2_6_Herb-1:The data I?m

 

looking at shows the per capita

 

consumption of bottled water, by gallon

 

over twelve years. I think this data

 

works well as a proxy. What data did

 

you find to proxy the number of

 

buyers?

 

ECO550_2_6_Maria-2: I had to think

 

hard about a number of buyers proxy. In the end, I found a good proxy in a

 

Department of Commerce report, it is

 

called ?Current Industrial Reports.? The

 

proxy I used dealt with the

 

confectionery exports of domestic

 

merchandise measured in pounds per

 

year.

 

ECO550_2_6_Herb-2:This data also

 

serves as a great proxy. Of course, I?ll

 

have to consult with Renee to get her

 

opinion because she?s the one

 

mentoring me on this project. But I?m

 

fairly certain Renee will agree with me.

 

ECO550_2_6_Maria-3:Okay! Here?s

 

the data I compiled from our accounting

 

records.

 

ECO550_2_6_Herb-3: Great! Now,

 

can we create the data set in Excel and

 

then estimate the model?

 

ECO550_2_6_Maria-4:That?s correct!

 

I have some great resources that will

 

help you review how to create datasets

 

in Excel and how to use Excel functions

 

to estimate the model. Please look over

 

these resources and I will get back to

 

you once you are finished.

 

ECO550_2_6_Herb-4:Okay that

 

sounds great! Slide 7 Scene 7

 

Interaction Slide

 

Incorporate iPad to show Videos about

 

Excel and model creation Slide 8 Multiple Linear regression

 

analysis using Microsoft

 

Excel?s Data Analysis

 

toolhttp://www.youtube.com/wa

 

tch?v=ZwtxHXh-ZXU

 

Multiple Regression

 

Interpretation in Excel

 

http://www.youtube.com/watch?

 

v=tlbdkgYz7FM Scene 8

 

Herb?s office to go over the data Maria

 

collected Show regression output table ECO550_2_8_Maria-1: I hope those

 

videos helped you gain a better

 

understanding of using Excel to create

 

data sets. I want you to keep in mind

 

that the procedure we will be using to

 

estimate the model is regression. The

 

model Renee and you formulated is a

 

multiple regression model because there

 

is more than the price of chocolate

 

included as an independent variable.

 

Take a look at the regression output for

 

our estimated model.

 

ECO550_2_8_Herb-1: Wow! That was

 

fast!

 

ECO550_2_8_Maria-2:Yes, Herb,

 

Excel generates results almost

 

instantaneously. Herb shows formula ECO550_2_8_Herb-2: Okay, let?s see

 

what we have. I see the coefficients are

 

presented in a single column. Let me

 

rewrite the model to include the

 

coefficient values.

 

ECO550_2_8_Maria-3: What does all of this mean?

 

ECO550_2_8_Herb-3: Well, the first

 

number, three hundred and forty four

 

thousand and four hundred point five

 

refers to the number of boxes of sugarfree-chocolate demanded if none of the

 

independent variables changed their

 

value. If we assume one of the other

 

variables changes while all of the others

 

remain constant, then we calculate a

 

new number of boxes of chocolate.

 

ECO550_2_8_Maria-4: Could you

 

give me an example for this change? Herb shows Maria the updated formula One more formula for Herb to go over Display on projector: The new quantity

 

demanded is, three hundred seventyfour thousand, three hundred sixty-six

 

point two boxes of sugar-freechocolates. ECO550_2_8_Herb-4: Sure! For my

 

example, let?s assume that the price of

 

Katrina?s sugar-free-chocolates declines

 

by one dollar while none of the other

 

independent variables changes.

 

According to our model, the decrease in

 

price would cause quantity demanded to

 

increase by twenty nine thousand and

 

nine hundred and sixty five point seven

 

boxes. Each of the other coefficients is

 

then interpreted similarly. Here?s the

 

way we calculate the change in quantity

 

demanded, if price was to change.For

 

all of the variables that are constant,

 

that is, those unchanging variables, we

 

substitute a ?zero.?

 

ECO550_2_8_Maria-5: That is very

 

interesting! Is there anything else I

 

should know?

 

ECO550_2_8_Herb-5: There is one

 

more thing I?d like to add. For the price

 

of Katrina?s sugar-free-chocolate,

 

substitute one dollar, with a negative

 

sign in front of it to indicate price

 

declined. Here, I?ll show you how the

 

model determines quantity demanded.

 

After making the changes the new

 

quantity demanded is, three hundred seventy-four thousand, three hundred

 

sixty-six point two boxes of sugar-freechocolates.

 

ECO550_2_8_Maria-6:Thank you for

 

sharing that with me! Now that you

 

explained this all to me, things are

 

much clearer.

 

ECO550_2_8_Herb-6: Not a problem

 

at all. As you can see, regression

 

models are useful but only if the results

 

from the model are valid.

 

Slide 9 Scene 9

 

Herb?s office to conduct significance

 

test on the model and coefficients with

 

Maria Display on projector: The coefficient of

 

determination ranges from 0 to 1.

 

Display on projector: A higher adjusted Rsquare indicates a better model. http://wn.com/rsquared_or_coefficient_of_determinatio

 

n ECO550_2_9_Herb-1: Now we need

 

to check the model and coefficients for

 

significance.

 

ECO550_2_9_Maria-1:How do we

 

that?

 

ECO550_2_9_Herb-2: First, we

 

evaluate the adjusted R-square value to

 

see how much of the variation in the

 

quantity demanded of sugar-freechocolates is explained by the

 

independent variables we included in

 

the model. The closer R-square is to

 

one, the better is the explanatory power

 

of the independent variables.The

 

adjusted R-square for our model?s

 

results is point seven, nine, nine which

 

means the model explains seventy-nine

 

point nine percent of the variation in the

 

quantity of sugar-free-chocolates.

 

Maria, I found this video that helps to

 

explain the coefficient of determination

 

from another standpoint.

 

ECO550_2_9_Maria-2:Based upon the

 

explanation you gave about R-square

 

being close to one, seventy-nine-pointnine percent is very good.

 

ECO550_2_9_Herb-3:Yes, it looks as

 

if we included the right set of independent variables.

 

ECO550_2_9_Maria-3:What?s next,

 

Herb?

 

ECO550_2_9_Herb-4:Now we

 

evaluate the overall significance of the

 

independent variable. We are looking

 

for the answer to the question: Can the

 

behavior of the dependent variable, our

 

quantity of sugar-free-chocolates, be

 

explained without relying on the

 

independent variables included in the

 

model? For this test we will evaluate

 

the F-statistic. We first need to state the

 

level of significance, called the

 

?critical-value,? which we will use to

 

test the F-statistic.

 

For our model we are going to use the

 

five-percent level of significance;

 

therefore,the table gives us a critical Fvalue of four-point-one-two.

 

ECO550_2_9_Maria-4:I think I

 

understand how you selected the critical

 

value. I think now we must compare the

 

F-statistic generated for the model to

 

the critical value.

 

ECO550_2_9_Herb-5:Yes, that?s

 

exactly what we will do. Since the Fcalculated value is eleven-point-ninefive-two and is greater than four-pointone-two, a significant relationship does

 

exist between the quantity of sugar-freechocolate and the four independent

 

variables.

 

ECO550_2_9_Maria-5:Great! So

 

we?re done then?

 

ECO550_2_9_Herb-6:No, not quite

 

yet. We still need to evaluate the

 

significance of each coefficient. We can

 

actually use the same method used to

 

find the critical value of F only this time we will conduct a t-test on each

 

coefficient value.

 

Slide 10 Scene 10

 

Herb?s office to conduct significance

 

test on the model and coefficients with

 

Maria ECO550_2_10_Maria-1:So based on

 

the t-test, tell me which independent

 

variables are significant.

 

ECO550_2_10_Herb-1: According to

 

the t-test, only the price per boxand

 

bottled water are significant. The

 

coefficient on median income is

 

marginally significant; however, we

 

cannot use the coefficient for anything.

 

Surprisingly, the caffeinated coffee

 

coefficient is insignificant.

 

ECO550_2_10_Maria-2:I see why you

 

are saying coefficients are insignificant.

 

ECO550_2_10_Herb-2: Yes, this

 

revelation about independent variable

 

significance means we need to drop the

 

caffeinated coffee variable and reestimate the model.

 

ECO550_2_10_Maria-3:Is it okay to

 

drop variables from a model after the

 

model is estimated?

 

ECO550_2_10_Herb-3: Yes, if an

 

independent variable is not significant,

 

one of the recommended solutions is to

 

drop the variable from the model. In

 

our model, this means sugar-freechocolate and caffeinated coffee are not

 

substitute goods so coffee does not

 

contribute anything to our

 

understanding about demand for

 

Katrina?s sugar-free-coffee.

 

ECO550_2_10_Maria-4:Does

 

dropping the insignificant variable

 

mean we still use the coefficients

 

generated when caffeinated coffee was

 

a variable in the model? ECO550_2_10_Herb-4: That is a good

 

question, Maria! The answer is, no.

 

When we drop a variable like

 

caffeinated coffee from the model, we

 

have to re-estimate the model and then

 

run the Excel regression procedure

 

again to generate new coefficient

 

values.

 

ECO550_2_10_Maria-5:Let?s run the

 

regression without data on caffeinated

 

coffee?I?m anxious to see if there is

 

any difference in the results.

 

ECO550_2_10_Herb-5: Okay, but

 

before we re-estimate the model, I think

 

we should also drop the bottled water

 

variable. After some consideration, the

 

amount of water consumed is not a

 

good proxy for the price of water. Also,

 

the correlation coefficient between

 

bottles of water and income is nearly

 

one. Therefore, there seems to be a

 

problem with their correlation. Keep in

 

mind that we also need to add a Dummy

 

variable to measure the impact of sugarfree-chocolate which Katrina?s

 

introduced into the market last year.

 

Renee and I forgot to include a dummy

 

variable in the first model.

 

ECO550_2_10_Maria-6: Whatever

 

you say, Herb. You know this process

 

better than I do.

 

ECO550_2_10_Herb-6:Let me

 

compute this quick. (pause) Here are the

 

results now. Scene 11 Scene 11

 

Herb?s office to conduct significance

 

test on the model and coefficients with

 

Maria ECO550_2_11_Maria-1:Are these

 

results better, Herb?

 

ECO550_2_11_Herb-1:Yes, everything

 

is now significant. Now we can use the

 

regression equation to derive decisionmaking statistics like elasticity

 

coefficients.

 

ECO550_2_11_Maria-2:How do we

 

go about doing that?

 

ECO550_2_11_Herb-2: Make a note

 

that the point elasticity of demand is

 

calculated as the change in quantity

 

divided by the change in price times

 

price divided by quantity. Here?s how

 

the formula looks.

 

ECO550_2_11_Maria-3:Okay, so

 

where is the data to calculate elasticity?

 

ECO550_2_11_Herb-3:The regression

 

coefficients or the b?s in the model are

 

the change in quantity divided by a

 

change in price, so that part is simple.

 

ECO550_2_11_Maria-4:Do you mean

 

the negative forty-two thousand, one

 

hundred eighty-nine that is the

 

coefficient for the price variable?

 

ECO550_2_11_Herb-4:Yes, however,

 

we have to calculate the ?q? that?s in

 

the elasticity of demand formula.

 

ECO550_2_11_Maria-5:What does the

 

?q? stand for?

 

ECO550_2_11_Herb-5: In the

 

elasticity formula, q, is the quantity

 

demanded at a specific price. For this

 

step, we first find the demand curve.

 

ECO550_2_11_Maria-6:I thought we

 

already have the demand curve. ECO550_2_11_Herb-6: Not quite yet,

 

I was discussing the regression

 

equation which includes all of the

 

independent variables we included in

 

the model. The demand curve is

 

different, as only the price variable is

 

included in the demand curve.For our

 

example we will use some numbers

 

from 2004. We will then use these

 

numbers to showcase how to derive the

 

demand curve. First, go back to the

 

regression equation. Now substitute the

 

data as follows. For income, substitute

 

one-thousand dollars and for exports

 

substitute two-six-three-three-six-six

 

point seven.

 

Slide 12 Scene 12

 

Herb?s office to conduct significance

 

test on the model and coefficients with

 

Maria ECO550_2_12_Maria-1:Okay, I did

 

that. What about the price variable,

 

should I substitute for price?

 

ECO550_2_12_Herb-1:No, not yet.

 

Just solve what you have as this will

 

give the demand curve.

 

ECO550_2_12_Maria-2:Is that all

 

there is to finding the demand curve

 

from the regression model?

 

ECO550_2_12_Herb-2: Yes, that?s it!

 

We?re nearly finished as we have only

 

two more steps to calculate elasticity.

 

Again using the data from 2004

 

substitute twenty-four dollars for price

 

variable into thedemand curve and solve

 

to get a quantity equal to two-million,

 

ninety-six thousand, seven-hundred

 

eight-point eight-eight. The elasticity

 

coefficient is then negative zero point

 

four-eight-two-nine. We can then round

 

to negative zero point four-eight-three.

 

ECO550_2_12_Maria-3:Thank you for

 

going over this with me. Since you

 

showed me how to do this, things seem

 

clearer. Does this mean we are finished with this stage of the process to create

 

information for Ken to use when he

 

considers the decision to expand into

 

international markets?

 

ECO550_2_12_Herb-3: Yes, we have

 

completed this stage. We just need to

 

update Renee on our progress.

 

ECO550_2_12_Maria-4: I will update

 

Renee on our findings. While I

 

complete this task could you complete

 

this review activity based on what we

 

just discussed?

 

Slide 13 Scene 13

 

Check Your Understanding

 

Scenario-based and will use folder

 

structure to present scenario, then have

 

tabs to represent options for answers

 

Narrations will be provided for scenario

 

overview and choices (feedback

 

included as well) ECO550_2_13_Maria-1: Based upon

 

the result that the price elasticity of

 

demand coefficient is -0.483 for

 

Katrina?s sugar-free-chocolate, Herb

 

can advise Ken that Katrina?s should

 

never use price as a tool for increasing

 

total revenue?

 

ECO550_2_13_Maria, Agree,

 

Response 1-2:Agreed, that?s correct

 

since price elasticity of demand is less

 

than one it means demand is elastic. As

 

a result of this, the increasing price

 

would lower total revenue because

 

customers would react very strongly to

 

an increase in price by changing their

 

purchases by a greater percentage than

 

the percentage change in price.

 

Therefore, Herb is giving Ken the

 

appropriate advice.

 

ECO550_2_13_Maria Incorrect

 

response-3:

 

We should expect the percentage

 

change in quantity demanded to

 

change by less than the percentage

 

change in price.

 

ECO550_2_13_Maria, Disagree,

 

Option 2-4: When the absolute value of the price elasticity of demand

 

coefficient is less than one it means

 

demand is inelastic, so if price is

 

increased by a certain percentage, say

 

ten percent, demand will change by a

 

lower percentage, such as eight percent.

 

Therefore, when demand is price

 

inelastic, increasing the price actually

 

results in higher total revenue. For

 

Katrina?s, this means demand for sugarfree-chocolate is price inelastic and the

 

company could increase total revenue

 

by increasing price.

 

Slide 14 Summary

 

Concluding scene taking place in

 

conference room ECO550_2_14_Herb-1: Maria, we

 

have discussed and analyzed a lot today.

 

ECO550_2_14_Maria-1: We sure

 

have. Let?s outline the tasks we

 

completed to make certain we

 

remember everything. First, you

 

explained the demand model that you

 

and Renee formulated. I then described

 

the data and its sources for the data that

 

I compiled. We later discussed proxy

 

data and agreed it was okay to use this

 

kind of data for two of the variables.

 

ECO550_2_14_Herb-2: Let?s not

 

forget about our creation of the data set

 

in Excel along with the creation of our

 

estimation model.

 

ECO550_2_14_Maria-2: I?m glad you

 

brought that up! Next, we discussed the

 

results of...

 


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