ECO550 Week 3 Scenario Script Using Techniques to Forecast Variab.docx

ECO550 Week 3 Scenario Script: Using Techniques to Forecast
Variables of Interest to Business and Foreign Exchange
Slide #
Scene
Narrations
Slide 1
Scene 1
An older cottage style family run business (Katrina’s Candies)
Slide 2
Scene 2
Herb and Renee are in Renee’s office discussing how to select
and use forecasting techniques to forecast the behavior of
variables Katrina uses to make decisions.
Display:
Regression output for the model.

ECO550_3_2_Herb-1: Good Morning, Renee!
ECO550_3_2_Renee-1: Good Morning, Herb! We should get
started because I have another meeting following our meeting.
What progress did you and Maria make at your session? I saw
your email; however, I’ve been too busy to read it.
ECO550_3_2_Herb-2: No problem, Renee! I will give you an
update now. Maria and I made a lot of progress considering we
had to revise the model you and I developed.
ECO550_3_2_Renee-2: Revise the model, Why?
ECO550_3_2_Herb-3: Let me explain. The first revision
occurred before we estimated the model. Maria was unable to
find prices for bottled-water and unable to get data on the
number of buyers of sugar-free-chocolate. Maria, however,
located proxy data for both of these independent variables; as a
result we estimated the demand model you and I formulated
using some proxy data.
ECO550_3_2_Renee-3: That’s good news; otherwise, we would
have had to reformulate the entire model.
ECO550_3_2_Herb-4: I was quite impressed that Maria made
the extra effort to find proxy data to use in order to estimate the
demand model. However, after estimating the model and
evaluating the significance of regression coefficients, we had to
drop caffeinated coffee and bottled-water from the model; as the
results were insignificant for both variables. We also added a
dummy variable to capture the supply of Katrina’s sugar-free-
chocolate on the demand for Katrina’s regular chocolates.

ECO550_3_2_Renee-4: So, did the modifications that were
made to the model make a difference in estimation results?
ECO550_3_2_Herb-5: Yes, as a matter of fact, the revised
version of the demand model generated significant results for
all of the independent variables including the price of Katrina’s
sugar-free chocolate, median household income, the export of
domestic confectionary merchandise and the dummy variable.
Let me show you the regression output for the model.
Slide 3
Scene 3
Herb and Renee are in Renee’s office discussing the first
forecasting procedure.
Show linear trend model on projector.
Show line graph example on projector.
ECO550_3_3_Renee-1: Herb, this is a great report--this means
we can use the data and the estimated model to forecast the
future demand.
ECO550_3_3_Herb-1: How are we going to forecast the
demand, Renee?

ECO550_3_3_Renee-2: Since we used historical time-series
data to estimate the demand model, we will use forecasting
methods for time series data.
ECO550_3_3_Herb-2: That makes sense but where do we begin?
ECO550_3_3_Renee-3: We’ll begin with a simple forecasting
method, a linear trend model. In a linear trend model, the
dependent variable is regressed against only one independent
variable, which is time. For this model, the quantity of
Katrina’s sugar-free-candy is the dependent variable and the
corresponding year is the independent variable for time.
ECO550_3_3_Herb-3: That’s easy to do, we can use Excel
again. Let me open the Excel file Maria created.
ECO550_3_3_Renee-4: Okay, Herb. When you open the
dataset, make a smaller dataset consisting of just the quantity of
Katrina’s chocolates and year.
ECO550_3_3_Herb-4: Done. That didn’t take long; I just copied
and pasted the data onto a new spreadsheet.
ECO550_3_3_Renee-5: Good. Now, let’s look at a time-series
graph of Katrina’s chocolates and time.
ECO550_3_3_Herb-5: A graph, what type of graph?
ECO550_3_3_Renee-6: A line graph gives the clearest picture
of the relationship between time and a dependent variable.
Excel uses the term “chart” instead of graph so look under the
Charts option.
ECO550_3_3_Herb-6: Okay, found it! I had to select the
“Insert” tab, then the Line option. Please take a look at my

graph.
Slide 4
Scene 4
Renee and Herb are in Renee’s office to analyze the graph
generated for the trend-line forecast
Show the demand function on projector.
ECO550_3_4_Renee-1: The graph reflects what we would
expect; the demand for Katrina’s sugar-free-chocolates is
increasing over time.
ECO550_3_4_Herb-1: It also looks as if demand has grown
during the last four years. Is that right?

ECO550_3_4_Renee-2: Yes, the line is positively sloped so you
correctly interpreted the relationship. Now let’s estimate the
regression for the trend line model.
ECO550_3_4_Herb-2: Okay, it will only take a few seconds.
[PAUSE] There it is now.
ECO550_3_4_Renee-3: Before we can use the results for
forecasting, we have to check for significance.
ECO550_3_4_Herb-3: I’ll do it, Renee. Maria and I performed
the same significance tests when we estimated the demand
model.
ECO550_3_4_Renee-4: Okay! Can we use this estimation to
forecast?
ECO550_3_4_Herb-4: Yes, we can use this trend-line to make
predictions. Let me show you.
ECO550_3_4_Renee-5: You can even use this information to
create a forecast.
ECO550_3_4_Herb-5: How do we do that?
ECO550_3_4_Renee-6: The data we used was from a span of
several years. We can forecast this years demand or even the
demand for upcoming years by substituting this year or other
years for “t” then solve for the quantity. Here let me show you.
ECO550_3_4_Herb-6: Trend-lining is a useful forecasting
methodology, and it’s simple.
ECO550_3_4_Renee-7: Yes it is. Now let’s use the demand
function you and Maria estimated to develop another forecast.

ECO550_3_4_Herb-7: The demand function we estimated is
here, in Excel, here’s the version I created. I am unsure though
of how we will use this function to forecast.
Slide 5
Scene 5
Renee and Herb are in Renee’s office to calculate demand using
hypothetical values
ECO550_3_5_Renee-1: You may have already used this
approach. All we need to do is hypothesize values for the next
year’s independent variables, substitute the hypothetical values
into the model and solve to get the forecasted value of demand.
This method is called a point forecast.
ECO550_3_5_Herb-1: Yes, I actually do recall this approach.
Let’s both solve this problem to make certain I get it correct.
ECO550_3_5_Renee-2: Okay. Use eight-dollars for the price,
since price will probably not change within the next year; then
use fifty-two thousand-seventeen-dollars for income. We will
then have exports measured in pounds per year, so use four
hundred eighty-thousand-eight-hundred twenty-six-point-five as
the hypothetical value. Finally, use one for the dummy variable.
ECO550_3_5_Herb-2: Are you solving by hand without a
calculator? I’m going to use Excel to solve for the predicted
level of demand for this year..
ECO550_3_5_Renee-3: Let’s compare solutions. This is the
solution that derived.
ECO550_3_5_Herb-3: My solution is the same! I’m glad I did
this correctly in Excel.
Slide 6
Scene 6

Renee and Herb are in Renee’s office comparing the results
from the demand function and the trend line
ECO550_3_6_Renee-1: Keep in mind that the demand function
forecast using hypothetical data is larger than the forecast using
the trend-line model. Off-hand, I cannot explain the difference
between the two forecasts, however, both forecasts show some
decrease but are still attractive numbers. Now we will use
smoothing techniques to forecast demand. There are three types
of smoothing techniques and they include: moving averages,
weighted averages and exponential averages.
ECO550_3_6_Herb-1: Is moving average the method where you
combine data points from different time periods then find the
average of those data points to forecast a value?
ECO550_3_6_Renee-2: Yes, that’s correct! The forecasted
value is based upon an average of two or more values. Since we
have only twelve years of data, we will use a two-year moving
average to forecast the demand.
ECO550_3_6_Herb-2: Are we using the data we compiled to
estimate the demand function?
ECO550_3_6_Renee-3: Yes, that’s the data we’ll use.
ECO550_3_6_Herb-3: Take a look on page four of the report I
emailed you, the dataset is there.
ECO550_3_6_Renee-4: I see it now. Make note that since we
are developing a two-period moving average, we start by taking
the average for the first two years of actual data, and then use
each year to forecast the next year.
ECO550_3_6_Herb-4: Ok, I understand! So using two periods, I
would compute ninety-thousand plus one-hundred-thousand

divided by two to get the demand forecast which is ninety-five-
thousand. Then for the next year the demand forecast would be
one-hundred-fifteen-thousand and so on using this method. I
used the Excel Data Analysis, Moving Average function to
finish, let me print the output for you.
ECO550_3_6_Renee-5: Wait; since you’re going to print, we
should compute the forecast error, which is the difference
between the forecasted amount and the actual amount. Just use
Excel to find forecast errors; organize the information into a
table so we can see how it looks.
Slide 7
Scene 7
Renee and Herb are in Renee’s office finishing up their
discussion on weighted average and exponential smoothing
techniques.
ECO550_3_7_Herb-1: According to the moving average
forecast, actual demand values are consistently higher than the
forecast. What does that mean, Renee?
ECO550_3_7_Renee-1: I know the behavior of forecast error
means there is forecast bias. However, other than that I don’t
know. We’ll need to ask Ken about this.
ECO550_3_7_Herb-2: I do have one more question. Can Excel
also calculate the weighted average and exponential smoothing
forecasts?
ECO550_3_7_Renee-2: Let me see if we have anything in the
video library. (Pause, clicking) Okay, I found a couple of videos
that explain and illustrate how to smooth data using weighted
averages and exponential averaging. However, it’s nearly time
for my next meeting. I think you can use the videos to learn
how to use the other two smoothing techniques.

ECO550_3_7_Herb-3: Thank you for the videos they should
great learning tools!
ECO550_3_7_Renee-3: Fantastic! Before I head out, once you
finish these videos I would like for you also to participate in a
review activity I put together based on key items we discussed.
Slide 8
Interaction Slide
Incorporate iPad to show Videos about Excel and model
creation
· What is Demand Forecasting?
·
http://www.smetoolkit.org/smetoolkit/en/content/en/416/Deman
d-Forecasting
· Forecasting Using Regression Analysis
· http://www.youtube.com/watch?v=E73AJ73-S6g
· Using Excel for Basic Forecast Smoothing
· http://www.youtube.com/watch?v=sg7Mv54sISQ
Slide 9
Check Your Understanding
Multiple Choice Questions
Question 1: Time-series methods of forecasting are identified
by which of the following characteristics?
a. They are based on the assumption that future events will
follow patterns of past economic behavior. Correct Answer*
Correct feedback: Time-series forecasts are based upon an
analysis of historic data. Therefore, the logical assumption is
that the behavior of the variable will continue, ceteris paribus.
b. They generate data primarily from the opinion(s) of one or
more people.
Incorrect Feedback: Forecasts based upon opinions are known
as “subjective” forecasts. Subjective forecast are common
occurrences yet are considered less reliable than forecasts based

upon data. As an example, a subjective forecast is when a
person who commutes to work daily states, “today is
Wednesday, I know roads will be congested because on
Wednesdays there is always a lot of traffic.
c. They incorporate economic theory with quantitative
techniques to analyze and forecast the movement of some
economic or business variable of interest.
Incorrect Feedback: Economic theory is the basis of some
forecasting techniques but not all forecasting techniques.
d. They make use of inter-industry linkages to forecast how
changes in demand will affect output by various industries.
Incorrect Feedback: Forecasting techniques are intended to
evaluate the behavior of the variable of interest.
Question 2: Which of the following is a qualitative forecasting
method?
a. Expert opinion
b. Consumer surveys
c. Delphi method
d. All of the above are forecasting methods.
Correct Feedback: That is correct; all of the listed choices are
qualitative techniques.
Incorrect Feedback: Yes, this is a qualitative technique;
however, all listed choices are qualitative techniques.
Slide 10
Scene 10
Concluding scene taking place in conference room
ECO550_3_10_Herb-1: Renee, those videos and review
activities were very helpful!
ECO550_3_10_Renee-1: I’m glad to hear that. That is all I have
for today, Do you want to begin our review of what we
accomplished today?
ECO550_3_10_Herb-2: Sure thing! Today we developed
forecasts using the trend-line method and moving average

smoothing technique. We also used the estimated regression
function we formulated for the demand for Katrina’s chocolates.
We then used actual data for the trend-line and moving averages
forecasts. We later hypothesized data for forecast using the
estimated regression model. Based on all of our work, we
concluded that the estimated regression model gave us the best
estimate of our future demand.
ECO550_3_10_Renee-2: That’s a good summary of what we did
today. Remember to document everything we have worked on
so we can respond to any questions Ken may ask.
ECO550_3_10_Herb-3: Okay. Do we need to do anything else
today?
ECO550_3_10_Renee-3: That’s all for today, Herb, but until we
meet again, don’t forget to complete your weekly threaded
discussions based on the key concepts we covered this week.
ECO550_3_10_Herb-4: Thanks, Renee and have a great day!
Quality Analysis Part II
For the company Coca Cola respond to the following in a 3- to
4-page Microsoft Word document:
· Imagining yourself to be the customer, construct a House of
Quality to provide the organization with your perspectives on
what the important dimensions of quality are and how well the
organization is currently meeting your needs.
· Develop a SPC checklist for each dimension of the product
that you believe would be subject to statistical control.

· Evaluate the product using the five-step plan that is associated
with the Kaizen philosophy.
· Determine what elements of the production and delivery of the
product or service would be subject to benchmarking and
describe how you would identify those organizations to which
comparisons could be made in a benchmarking process.
Support your responses with examples.
Cite any sources in APA format.
See Quality Analysis Part 1 below for reference only
For this company, I have selected coca cola as the company of
analysis. Coca-Cola Company is a multinational company whose
parent company is in which was founded in 1886. It is a
company in the foods and beverage industry that manufacturers,
markets and also retails beverages with its main competitor
being PepsiCo. The company has more than 300 brands all
across the globe in more than 200 countries (Pendergrast 2013).

It also has a franchised distribution system in many countries
across the world.
Under the many brands that this company has, we are going to
focus on the product that is named after the companies name
that is coca cola. Coca-Cola is a soft drink that is carbonated,
and it is sometimes referred to as coke. When this product was
initially invented, it was invented as a patent medicine. This
company keeps the formula of this product highly protected
under the trade secret rights. The company makes the
concentrate and the sells it to coca cola bottling companies that
are licensed all over the world.
The quality of these products means a lot to the company as
well as for the consumer. This product is very popular and has
been able to retain its popularity for so long majorly due to its
consistent and good quality. The company measures the quality
of this product in terms of the ingredients used as well as others
materials. The company works to ensure that the ingredients for
this product are safe for consumption. The company shows its
commitment to the quality of this product by providing strict
regulations on the manufacturing, bottling as well as the
distribution of the product to ensure that they fulfill the
expectations of the consumer. The regulations are conducted
and governed by the coca cola operating requirements.
Strengths
· • High Consumer loyalty
· • High company valuation
· Large global presence
· Excellent strategies in place for marketing
· Vast and good distribution system
· Enjoys a large market share
· Brand equity
Weaknesses

· • Water management issues
· • High competition from PepsiCo
· Health issues accrued to their products
· Low product diversification as compared to competition
Opportunities
· Product diversification e.g. production of snacks
· High markets in developing countries for carbonated drinks
· Marketing the brands that are not well selling
· Improving their supply chain
Threats
· High indirect competitions from health drink companies.
· Loss of raw material sourcing majorly water
The strategy that can help the organization to focus on
strategy is enhancing and promoting quality right from within
the company. Staffing is a very important process for a
company and for a company to be able to focus on quality they
need to be able to promote it through hiring highly talented
individuals both in management as well as in the manufacturing
sectors. This will help to ensure that they can work according to
the set standards on quality and ensure that they effectively
meet the needs of the consumers.
The organization fails on the element of health. The
products of this company have been associated with health
conditions such as diabetes due to high sugar levels (Hays
2013). Many families and individuals have cultivated a culture
of healthy lifestyles, which is mainly comprised of healthy
eating. The company lacks in this, and that is why it faces a
threat from the indirect competition from health drink
companies.
The company targets a wide ally of consumers of all ages,

genders, religions and ethnicities. The primary consumers
include diverse number retailers all around the world,
supermarkets, hotels and restaurants as well business. The
secondary consumers are the individual people who buy from
the retailers, supermarkets or from the hotels.
The company can implement change by positioning themselves
more in the line of production of healthy drinks. This is majorly
the case in developed countries. They should produce more
healthy drinks to replace the carbonated ones. For example, they
should focus more on brands such as Minute Maid that are
healthier and market the more.
The company can acquire an already established health drink
company or form a merger with one of them. Since coca cola is
already well known, they can easily market these products,
meeting the needs of the consumers and enhancing quality
concerning health implications to consumers.
References
Hays, C. (2013). The real thing truth and power at the Coca-
ColaCompany. New York: Random House.
Pendergrast, M. (2013). For God, country and Coca-Cola: the
definitive history of the great American soft drink and the
company that makes it. New York: Basic Books.

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.

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.
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_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!

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.

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
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.

Summary
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 1 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
Introduction Page
Takes place in Ken’s office
· Ken and Herb
President of Katrina's Candies- Ken Sanders
Grad Student/ Part-time Data Analyst- Herb Jones
ECO550_1_2_Ken-1: Hello, Herb! My name is Kenneth Sanders
and welcome to Katrina's Candies. I can speak for my team and
myself by saying how excited we are to work with you! But
before we begin let me tell you about our company, Katrina's
Candies. We are a small family owned candy-manufacturing
company specializing in a variety of chocolate candies
including a new sugar-free chocolate bar.
ECO550_1_2_Ken-2: We mostly produce candy for domestic
and international markets and we currently employ
approximately three hundred employees in a variety of

capacities. Because of our size, we conduct a significant portion
of our business via the internet. Currently, we have a
management team consisting of a manager, senior data analyst
and financial officer. You will get a chance to meet all of them
soon. So, now tell me a little about yourself; I have been out of
the country for business and didn’t get a chance to review your
new hire file.
ECO550_1_2_Herb-1: Thank you, Mr. Sanders!I am Herb Jones
and I was recently hired to serve as the new part-time data
analyst. Currently, I am a full-time Strayer University student
finishing the last four courses of an MBA management program
through the Global campus. I enrolled full-time in Strayer’s
online program about three years ago.
ECO550_1_2_Ken-3: Yes, I do recall our Management
Department supervisor Gigi Thomas, making a strong case to
convert the position to part-time and hold the full-time position
for you. Gigi told me your educational preparation impressed
her. Do you have work experience, too, Herb?
ECO550_1_2_Herb-2: Yes, I have about four years experience
working as a consultant for several proprietary firms much
smaller than Katrina. Mostly, I served as liaison between the
firms and their clients…verifying task descriptions conducting
quality control reviews, and recording problems with defective
products for sequential follow-ups after tasks were completed.
I was the eyes and ears of my clients outside of their offices.
Interesting jobs-- but I wanted something different.
ECO550_1_2_Ken-4: You’re in the right place to get a new
experience—we’re at the threshold of making a change in our
general mission. As you were talking, I reviewed our
electronic version of your transcript. I see why Gigi was
impressed! Strayer exposed you to the type of skills we need to
round out our management team.

Scene 3
Introduction, continued
Takes place in Ken’s Office
· Ken and Herb
[Herb and Ken proceed towards the conference room]
ECO550_1_3_Ken-1: So, let me tell you about where Katrina's
Candies is heading now; then we can start our meeting with the
rest of the team.
For more than one hundred and fifty years, Katrina's Candies
has primarily concentrated on supplying candy to the U.S.
market; with our largest sales occurring during holiday seasons.
However, our 2012 revenues from a pilot marketing project and
general revenue trends in the first six months of this year
suggest Katrina's Candies should consider broadening its market
base.

ECO550_1_3_Herb-1: That is very interesting!
ECO550_1_3_Ken-2: As the Sanders' fifth generation Katrina's
Candies president, my challenge is to decide whether or not to
expand Katrina's Candies operations to add an international
component that caters to consumers outside of the U.S.
I’m really nervous about making such a venture because the
international arena is unchartered territory for us-- except for
the recent pilot project.
ECO550_1_3_Herb-2: Ken, what was the item Katrina's Candies
piloted in the international market?
ECO550_1_3_Ken-3: Sugar free chocolate candy …it’s been a
big success in a couple of international markets as well as
among health conscious U.S. consumers. I’m just not sure the
success we’re seeing isn’t just a new-kid-on-the-block
phenomenon; as I will need to be completely sure before
directing resources to the product! Anyway, you’re here to help
Renee, our analyst, get me up to speed on the type of
information I need to make a decision. Gigi’s going to give
more details about your role in the project shortly.
ECO550_1_3_Herb-3: Thank you for the update Ken. I look
forward to working on this project and I will do my best to see
this project to completion!
ECO550_1_3_Ken-4: Well, let me get you to the conference
room, the team meeting is scheduled to begin in a few minutes.
Slide 4

Scene 4
Takes place in Conference Room
· Kenneth Sanders
· Herb Jones
· Gigi Thomas
Supervisor of the Management Department- Gigi Thomas
ECO550_1_4_Ken-1: Good Morning, Gigi. I see the team is
here and ready to go.
ECO550_1_4_Gigi-1: Good Morning, Ken. Yes, the team is
ready to go.
ECO550_1_4_Ken-2: Well, here’s Herb, he’s ready, too. I’m
going back to my office—I have a lot of work to do before I
leave tomorrow for China.
ECO550_1_4_Ken-3: Congratulations again on joining Katrina's
Candies, Herb.
ECO550_1_4_Herb-1: Thank you, Ken. (Ken leaves)
ECO550_1_4_Gigi-2: Hi, Herb. Good to see you here. The
management team is really excited about you joining us!
ECO550_1_4_Herb-2: Hello, Gigi. I’m excited to be here as
well!

ECO550_1_4_Gigi-3: [Looks down at her phone… reads, then
says] Ken just texted me. He said your meeting went well and
that he briefed you about Katrina's Candies history and briefly
mentioned changes in our revenues.
ECO550_1_4_Herb-3: Yes, my meeting with Ken went really
well. He’s an interesting person; warm and friendly. I was
nervous about meeting him but he put me at ease right away!
ECO550_1_4_Gigi-4: Good! We want you to feel comfortable
working here at Katrina's Candies. Let’s start off with some
introductions from the rest of the team.
Slide 5
Scene 5
Takes place in Conference Room
· Herb Jones
· Gigi Thomas
· Renee Smith
· Maria Scott
Senior Level Data Analyst- Renee Smith
Supervisor of the Finance and Accounting Department- Maria
Scott
ECO550_1_5_Gigi-1: Good morning, everyone! You remember
Herb Jones, our new part-time analyst who’s going to assist
Renee. Herb was our number one candidate for the full-time
analyst position we advertised. However, since Herb has to
finish his last quarter at Strayer University, where he’s a
graduate student, we decided to convert the position to part-
time until he finishes.
It’s been about a month since Herb has seen either of you so

before we get started, let’s remind him of who we are and our
roles on the team. Let’s start with you, Renee.
ECO550_1_5_Renee-1: Hi, Herb! Welcome to the team!
Thrilled to have you here! I’m Renee Smith, a Senior Level
Data Analyst. I have an MBA –also from Strayer! And have
been at Katrina's Candies for eight years. I’m going to be
directing you on the project Ken discussed with you.
ECO550_1_5_Herb-1: Hi, Renee, I remember you from my
interview. You asked those difficult questions about which tools
to use for analyzing data.
ECO550_1_5_Renee-2: [Laughter] Yep, that was me!
ECO550_1_5_Gigi-2: Maria, you’re next.
ECO550_1_5_Maria-1: Hello, Herb, good to see you again. I’m
Maria Scott; I supervise the Finance and Accounting Office. I
graduated from Strayer too, with an MBA in Accounting
and am also a Certified Public Accountant. I’ve been at
Katrina's Candies for about nine years. For the project you’re
going to work on, I’ll direct you to any data you’ll need. Either
Renee or you can request the data as needed. Do not hesitate to
let me know If I can do anything else as you’re progressing
through the project.
ECO550_1_5_Herb-2: Thank you and nice to meet you again,
Maria.
ECO550_1_5_Gigi-3: Thanks, Maria and Renee! That leaves
me. I’m Gigi Thomas, Senior Manager, and team-manager for
this project. I’ve been with Katrina's Candies for about fifteen
years. My educational background is management and I have an
MBA degree from the College of France- in Paris, France.

ECO550_1_5_Herb-3: That is very neat! I’ve always wanted to
go to Paris and see the sights.
ECO550_1_5_Gigi-4: Yes, Paris is quite the place, no other
place like it! Now that we’ve reintroduced ourselves, let me
explain, again, why Herb was hired and why our team was
formed.
As many of you know, Katrina's Candies Board of Directors has
asked Ken to explore and consider expanding into the
international markets where our new sugar free chocolates are
doing well. Before Ken can respond to the Board, he needs to
know what’s causing the increase in revenue and whether the
increase is sustainable. That’s where we come into the picture.
Does anyone have any questions?
ECO550_1_5_Maria-2: Yes, I have a question about the Board’s
directive to Ken. Is it the board’s responsibility to tell Ken how
Katrina's Candies should operate?
ECO550_1_5_Gigi-5: Good question, Maria. Actually, although
Ken’s family owns Katrina's Candies, as president, Ken is
considered a manager and the Board is considered the owner.
Theoretically, owner’s and manager’s goals diverge. Owners
want managers to act in the best interest of shareholders; while
manager’s act in their own self-interest. This situation is known
as the principal-agent problem. We have a new board that isn’t
aware Ken is an owner. So, the board is just making certain
Ken is considering decisions that are best for shareholders.
ECO550_1_5_Maria-3: Thanks, Gigi. I understand now.
ECO550_1_5_Gigi-6: Any other questions?
ECO550_1_5_Herb-4: Yes, how long do we have to get
something to Ken?

ECO550_1_5_Gigi-7: Renee, you can answer this one.
ECO550_1_5_Renee-3: About the timeline, excluding this
week, it should take us nine weeks at most. Ken is leaving it up
to us to determine the type of information that best tells the
story. At this point, our first tasks are to build a model of the
demand for our sugar free chocolate candy, estimate the model,
and analyze the results. Results from estimating the model will
guide the remainder of our process.
ECO550_1_5_Gigi-8: Fantastic, Renee! So, is everyone ready to
begin? We have a lot to do.
ECO550_1_5_Herb-5: Yes!
ECO550_1_5_Renee-4: Yes!
ECO550_1_5_Maria-4: Yes!
ECO550_1_5_Gigi-9: Well, let’s get going. Herb, go with
Renee, she has things laid-out in her office to get you started.
ECO550_1_5_Herb-6: Okay, sounds great!
ECO550_1_5_Gigi-10: Great, the meeting is adjourned.
Slide 6
Scene 6
Renee’s office to get started on the Ken project

Renee should be writing these five (5) basic categories of
variables that affect consumer purchases.

Price of substitute goods
Price of complementary goods
Income
Preference or tastes, advertising expenditures
Number of buyers
ECO550_1_6_Renee-1: Are you ready to begin?
ECO550_1_6_Herb-1: As ready as one can be. (laughing) It’s
great to be here and have the opportunity to learn how a firm
conducts an analysis.
ECO550_1_6_Renee-2: Did you study managerial economics in
your graduate program at Strayer?
ECO550_1_6_Herb-2: Yes, I did. So, now I want to apply what
I have learned.
ECO550_1_6_Renee-3: Actually, you’ll find there isn’t much
difference between what you learned theoretically and what
Katrina's Candies does in reality. We do want to observe some
best practices when it comes to analyzing our data. We first and
foremost want to make certain our approach is consistent with
our rivals. In fact, we pretty much follow what economic theory
recommends as the best way to evaluate changes in revenue.
ECO550_1_6_Herb-3: Oh, I see. I can understand that by using
economic theory it can really make things a little easier on us.
ECO550_1_6_Renee-4: It definitely makes things a lot more
simplified when investigating these changes. Let’s get started.
Do you recall studying supply and demand theories?
ECO550_1_6_Herb-4: Yes, I remember studying both theories.
ECO550_1_6_Renee-5: Good. Tell me, what do you remember
about demand theory?

ECO550_1_6_Herb-5: I recall that the law of demand states that
price and quantity demanded are is inversely related. Meaning,
if Katrina's Candies was to lower the price of one of its
chocolate products, consumers would purchase more. However,
if Katrina's Candies increased the price of one of its chocolate
products, the amount of chocolate consumers would purchase
would decline.
ECO550_1_6_Renee-6: Yes, that’s right! We certainly
understand the law of demand. A few years back, after posting
losses for a few months, our management team voted to raise
prices. Well, what a mess that was! Our sales declined within
days! We really had to scramble to inform the public that the
price would return to its original price. But in the current case,
where our revenue is increasing, Katrina's Candies didn’t lower
the price of existing products. Also, for our new sugar free
chocolate candy, we’ve sold that product at the same price as
one of our other chocolates.
ECO550_1_6_Herb-6: Since price doesn’t explain the revenue
trends you’ve seen recently, that’s the reason you want to build
the demand model to see what other factors might explain
demand for Katrina's Candies new candy.
ECO550_1_6_Renee-7: Yes, absolutely. Managers make better
decisions when the decisions are based upon the results of
formalized models. My thinking is that we need to build a
model of the demand for our sugar free chocolate.
Let’s review the list of other determinants that might explain
the demand for Katrina's Candies sugar-free chocolate. Can you
identify those determinant categories?
ECO550_1_6_Herb-7: Sure, according to theories I studied,
there are five basic categories of variables that affect consumer

purchases.
ECO550_1_6_Renee-8: Let me write down the determinants as
you say them. I want to make certain we don’t forget something
later.
ECO550_1_6_Herb-8: Good thinking! These five categories
consist of the price, income, prices of related goods, preference
or tastes, and the number of buyers.
ECO550_1_6_Renee-9: Let’s see if there’s something on the
internet we can use to verify that we selected the correct terms.
Just in case our memories are fuzzy. (laughs)
ECO550_1_6_Herb-9: That sounds good to me. Let’s check it
out!
ECO550_1_6_Renee-10: I’m still looking, did you find
something?
ECO550_1_6_Herb-10: Yes, I think I found a YouTube video
that’s pretty informative. Check it out on your iPad! Here’s the
link.
Slide 7
Scene 7
Ipad image with video embedded with in
Determinants of Demand
Slide 8
Scene 8
Renee’s office to get started on the Ken project
ECO550_1_8_Herb-1: I thought the video was very informative.

I think we got all of the demand determinants correct.
ECO550_1_8_Renee-1: I agree, the video was great and we got
the verification for the demand determinants. Now we can put
our demand model together.
ECO550_1_8_Herb-2: Here’s what I have for the demand
model. I have the quantity demanded of Katrina's Candies new
sugar-free chocolate being determined by:
The price of the sugar-free chocolate;
The price of caffeinated coffee;
The price of water;
The median income of consumers; and
The number of buyers in the market.
ECO550_1_8_Renee-2: That’s a great model! We can even add
or delete determinants, if necessary.
ECO550_1_8_Herb-3: Thank you, I’m glad my training from
Strayer really came in handy working on this model.
ECO550_1_8_Renee-3: All right, I think this is a good place to
stop for today. I need to go to my office to review the model to
make certain we’ve properly prepared everything. Then I need
to speak with Maria, to let her know which data we need. Can
you and I set a follow-up meeting for next week, same day and
time?
ECO550_1_8_Herb-4: Sounds good to me!
ECO550_1_8_Renee-4: Before we go I would like for you to go
through some review materials that will really reinforce the key
concepts we discussed this morning.
Slide 9
Slide 9

Interaction Slide (tabbed interaction with videos included for
selected topics)
· Revenue – the amount a firm receives from selling products;
known formally as Total Revenue (TR) and calculated as price
times quantity demanded (TR = PxQd)
· Demand: http://www.youtube.com/watch?v=ZMYLgoCdZB4
· Supply:http://www.youtube.com/watch?v=6Q_XxwqtwxY
· Principal-Agent Problem:
http://www.youtube.com/watch?v=uzS3F8MgbK0
Slide 10
Scene 10
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_1_10_Renee-1: Herb, to help us review what we have
covered today, let's think through the following scenario.
Joe Smith, CEO of LG Gardner Apple-butter Company (ABC)
recently received a letter from ABC’s Board of Directors
requesting that he reduce the jar size for cranberry flavored
apple-butter. Joe was offended by the Board’s venture into the
arena where he solely controlled and made decisions about
company ventures. As a consequence, Joe ignored the Board’s
request.
On the way to the office about six months later, Joe heard a
news report that 12 months into the future, twenty Fortune 500
companies were expected to expand executive personnel by an
estimated 35 percent. During the next week, Joe implemented
plans to reduce the jar size as ABC’s Board had directed.
ECO550_1_10_Renee-2 (Option 1): In the provided scenario,
Joe’s attitude about and disregard of the Board’s request was

appropriate. CEO’s have complete responsibility for decision-
making. So although the Board oversees the CEO’s action, the
Board over-stepped its authority by making the request.
Furthermore, Joe must have felt that maintaining the status quo
of the company would not directly harm him in either the short
or long run so he delayed implementing the request to show the
Board who was actually in charge.
ECO550_1_10_Renee-3 (Incorrect feedback for Option 1): Keep
in mind that the Board does hold authority over Joe. Please try
again.
ECO550_1_10_Renee-4 (Option 2): In the provided scenario,
inappropriate. Although Joe has more knowledge about market
situations and superior decision-making skills, as CEO, Joe still
had an obligation to follow the Board’s directive since the
requested change would have improved ABC’s profits. Joe’s
decision to implement the request late was made without regard
to personal impact.
ECO550_1_10_Renee-5 (Incorrect feedback for Option 2): Keep
in mind that Joe considered the personal impact of ignoring the
directive and six months later when he finally implemented the
directive. Please try again.
ECO550_1_10_Renee-6 (Option 3):In the provided scenario,
inappropriate. Although Joe has more knowledge about market
situations and superior decision-making skills, as CEO, Joe still
had an obligation to follow the Board’s directive since the
requested change would have improved ABC’s profits.
Although Joe may not have fully understood his role vis-à-vis
the Board and ABC, Joe recognized that it was in his best
interest to implement the request, after learning about the
anticipated changes in the Fortune500’s demand for executives.
ECO550_1_10_Renee-7 (Correct feedback): Yes, Joe had an
obligation to pursue strategies that would improve profits since
he does report to the Board and is only an agent who is to act on
behalf of ABC.

Additionally, Joe decided to implement the request because he
had always wanted to work for a bigger Fortune 500 company
and realized after hearing the news report that he needed ABC
to be more profitable so he could include the successful
outcome on his resume as an example of outstanding managerial
skills.
Slide 11
Scene 11
ECO550_1_11_Renee-1: Thank you for going over the review
materials, I hope they helped solidify things for you! Let’s now
go over some of the key concepts we discussed today. After
receiving our task to provide Ken with information to make a
decision about expanding Katrina's Candies, we created a model
of demand for Katrina's Candies new sugar-free chocolate
candy. We then talked about the different types of determinants
to include in our demand model.
ECO550_1_11_Herb-1: I then helped out by selecting five
determinants to use for our demand model and we began
developing data to assist Ken with his decision.
ECO550_1_11_Renee-2: You did a great job today Herb! I think
we are definitely making progress on this project. I know Ken
will be very happy with our results thus far. Until we meet
again, don’t forget to complete your weekly threaded discussion
questions based on the key concepts we covered this week. I’m
now on my way to meet with Maria; we need to discuss our data
needs.
ECO550_1_11_Herb-2: Thanks for working with me today
Renee! You were very helpful and I’m excited to work on other
parts of this project with you.
Take care!

ECO550 Week 3 Scenario Script Using Techniques to Forecast Variab.docx

ECO550 Week 3 Scenario Script Using Techniques to Forecast Variab.docx

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