ECO550 Week 2 Scenario Script Models of Supply and Demand, and No.docx

ECO550 Week 2 Scenario Script: Models of Supply and
Demand, and Non-Price Determinants of Each
Slide #
Topics
Narration
Slide 1
Scene 1
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.

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_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 sugar-free-chocolate candy is the dependent variable
and there are five independent variables.
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 sugar-free-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-
free-chocolate, 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 sugar-free-chocolate.
Slide 3
Scene 3
In Herb’s office to explain concept of estimation
Shows the model on the projector
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_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?
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-free-chocolate
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-free-
chocolate 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.
Insert the URL for the Census Bureau
Show a pictures of the Strayer Resource Center

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.
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.
ECO550_2_5_Herb-4: Thanks for the clarification on this
subject. We can continue with our updates on the data you
collected.

Scene 6
Herb’s office to go over the data Maria collected.
Show data table of per capita consumption of bottled water.
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
· Multiple Linear regression analysis using Microsoft Excel’s
Data Analysis toolhttp://www.youtube.com/watch?v=ZwtxHXh-
ZXU
· Multiple Regression Interpretation in Excel
http://www.youtube.com/watch?v=tlbdkgYz7FM
Slide 8
Scene 8
Herb’s office to go over the data Maria collected
Show regression output table
Herb shows formula

Herb shows Maria the updated formula
One more formula for Herb to go over
Display on projector: The new quantity demanded is, three
hundred seventy-four thousand, three hundred sixty-six point
two boxes of sugar-free-chocolates.
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.
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 sugar-free-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?
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-free-chocolates.
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 R-square indicates a
better model.
http://wn.com/r-squared_or_coefficient_of_determination
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-free-chocolates 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-point-nine
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 F-value 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 F-calculated value is eleven-point-nine-five-two and is
greater than four-point-one-two, a significant relationship does
exist between the quantity of sugar-free-chocolate 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
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 re-estimate 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-free-
chocolate 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 sugar-free-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
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 decision-making
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
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

sugar-free-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 our model and conducted significance
tests for the model and its coefficients. Lastly, we used these
results to generate an amended regression model to formulate
the demand curve and calculate the price elasticity of demand
coefficient.
ECO550_2_14_Herb-3: Thank you for the recap. I will be sure
to update Renee on what we covered today.
ECO550_2_14_Maria-3: That’s fantastic! I will talk to her as
well when I see her next. That is all for today, I’m now going
back to my office to update Ken on our progress with this
project. Until we meet again,don’t forget to complete your
weekly threaded discussions based on the key concepts we
covered this week.

ECO550_2_14_Herb-4:Thanks,Maria and have a great day!

ECO550 Week 2 Scenario Script Models of Supply and Demand, and No.docx

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