Refresh Data  ECO 550: Managerial Economics and Globalization Guidelines for the Final Project Goals The project is meant to complement and reinforce the key concepts from the course lectures, reading assignments, and examinations. The research paper will demonstrate an understanding of supply and demand equilibrium, various price elasticities, and elementary time-series analysis. To accomplish these tasks each group should understand and complete the following steps. 1. Choose a good or service. Examples might include, beef, pork, automobile model, et cetera. a. Collect minimum 30 data points with a regular frequency. Annual data are often the easiest to collect and analyze. b. These data are the quantity of the good sold. For example, beef consumption or number of Camry’s sold. c. This is the left hand (independent variable) for your estimated extended demand equation. 2. Gather the right hand (independent variables) data. a. Collect the (average) price for the good or service; i.e. the price of beef per pound or the sticker price of a Camry. b. Collect the average income for consumers of the product. c. Collect the price of at least one (more is better) of a related good(s). d. Collect any other ‘data’ that your group thinks will ‘explain’ the demand for the good or service. Once the data are collected make sure that the variables are complete, and all span the same time frame; i.e. try to avoid missing values. With an appropriate dataset begin by estimating the extended demand equation. To do this please see the course notes and examples on Blackboard. Also, please feel free to discuss with Professor Nguyen or Mr. Clancy. 3. Evaluate the estimated demand model. a. What is the R2? Is it above 90%? 80%? i. Explain what the R2 means; i.e. how much of the variation in the quantity demanded does the model explain? b. What is the p-level associated with the model’s F-statistic? Is it less than 5%? 10%? What does the significance indicate about the model? c. Inspect the p-levels for all the independent variables. Are they less than 5%? 10%? Interpret the p-levels and explain which variables are statistically significant. d. Omit any insignificant variables and re-run the model. i. Make sure your model has at least the independent variables including, the good’s own price, the price of a related good, and income. e. Re-evaluate steps a) – e) with the (new) model and any subsequent results. 4. Check the signs for the independent variables to determine: a. Does the Law of Demand hold for the model? b. What is the sign for income? What does the sign signify? c. What is the sign for the related good’s price? Positive, negative, or zero? Explain what this means about the relationship between the goods. 5. Compute three elasticities using the arc price formula for elasticity. a. The (own good) price elasticity of demand. Int ...

1. Refresh Data
ECO 550: Managerial Economics and Globalization
Guidelines for the Final Project
Goals
The project is meant to complement and reinforce the key
concepts from the course lectures,
reading assignments, and examinations.
The research paper will demonstrate an understanding of supply
and demand equilibrium,
various price elasticities, and elementary time-series analysis.
To accomplish these tasks each

2. group should understand and complete the following steps.
1. Choose a good or service. Examples might include, beef,
pork, automobile model, et
cetera.
a. Collect minimum 30 data points with a regular frequency.
Annual data are often
the easiest to collect and analyze.
b. These data are the quantity of the good sold. For example,
beef consumption or
number of Camry’s sold.
c. This is the left hand (independent variable) for your
estimated extended demand
equation.
2. Gather the right hand (independent variables) data.
a. Collect the (average) price for the good or service; i.e. the
price of beef per pound
or the sticker price of a Camry.
b. Collect the average income for consumers of the product.
c. Collect the price of at least one (more is better) of a related
good(s).
d. Collect any other ‘data’ that your group thinks will ‘explain’

3. the demand for the
good or service.
Once the data are collected make sure that the variables are
complete, and all span the same
time frame; i.e. try to avoid missing values. With an
appropriate dataset begin by estimating
the extended demand equation. To do this please see the course
notes and examples on
Blackboard. Also, please feel free to discuss with Professor
Nguyen or Mr. Clancy.
3. Evaluate the estimated demand model.
a. What is the R2? Is it above 90%? 80%?
i. Explain what the R2 means; i.e. how much of the variation in
the quantity
demanded does the model explain?
b. What is the p-level associated with the model’s F-statistic?
Is it less than 5%?
10%? What does the significance indicate about the model?
c. Inspect the p-levels for all the independent variables. Are
they less than 5%?
10%? Interpret the p-levels and explain which variables are

4. statistically
significant.
d. Omit any insignificant variables and re-run the model.
i. Make sure your model has at least the independent variables
including, the
good’s own price, the price of a related good, and income.
e. Re-evaluate steps a) – e) with the (new) model and any
subsequent results.
4. Check the signs for the independent variables to determine:
a. Does the Law of Demand hold for the model?
b. What is the sign for income? What does the sign signify?
c. What is the sign for the related good’s price? Positive,
negative, or zero? Explain
what this means about the relationship between the goods.
5. Compute three elasticities using the arc price formula for
elasticity.
a. The (own good) price elasticity of demand. Interpret.
b. The income elasticity of demand. Interpret.
c. The cross-price elasticity of demand. Interpret.

5. 6. Write the report and follow the style and guidelines provided
in the sample paper found
on Blackboard.
7. Turn in one printed (hard) copy, per group, to Professor
Nguyen by the deadline.
Tip
Experience has shown that collecting the data early is the best
way to ensure success. If your
group is having difficulty collecting a dataset, then please see
Professor Nguyen or Mr.
Clancy as soon as possible. We are here to help.
Elasticities of Demand
Demand elasticity is used to measure the sensitivity of
consumer demand for a product or service based on changes to
variables such as price and income. Applying our data for
Demand of Pork, Price of Pork, Price of Beef and Income we
can calculate these elasticities of demand. In the sections below
we will calculate and interpret the price elasticity of demand,
income elasticity of demand and the cross-price elasticity of
demand.
Our extended demand equation is QD=63.63-
13.01Pp+1.95Pb+.24M, where Pp is the price of pork, Pb is the
price of beef and M is income. Using the data from 2015 we can

6. create a reduced demand equation to estimate the quantity of
pork.
Year
Pork Consumption
Price Pork
Price Beef
Income
2015
47
3.11
4.38
67
QD = 63.63 -13.01Pp + 1.95 (4.38) + .24 (67)
Reduced demand equation = QD = 88.25 – 13.01Pp
When the Price of pork = 3.11, then QD = 47.79
We can now use the elasticity of demand calculation to
determine the effect on demand if we increase the price of pork
by $1. If we input a $1 increase of price, 4.11, into the reduced
demand equation we calculate an estimated quantity demanded
of 34.78. Now we can solve for the price elasticity to observe
the effects of this increase.
Price Elasticity of
Pork Avg/ QD Pork Avg)
E = ((34.78-47.79)/(4.11-
3.11))*((4.11+3.11)/2)/(34.78+47.79)/2)) = -1.14
How do we interpret -1.14? With an elasticity greater than 1 the
demand for this product is elastic. Elastic goods and services
tend to have more substitutes available. As the price increases
the demand can drop dramatically because consumers can
purchase alternative products to replace it. From our
calculations for Pork we find that if the price of pork increases
10% you will see an 11.4% decrease in quantity of pork
demanded, on the other hand if there is a 10% decrease in the

7. price of pork there will be a 11.4% increase in its demand.
Based on our assumptions you can see below that raising the
price of pork by $1 will decrease revenues.
Total Pork revenue with Price of Pork at $3.11 = Q * P = 47.79
* 3.11 = 148.63
Total Pork revenue with Price of Pork at $4.11 = Q * P = 34.78
* 4.11 = 142.95
Next we will focus on the Income elasticity. Income is a
significant variable when analyzing elasticities. Changes in
income levels ultimately change the quantities demanded of
goods all other factors remaining the same. Using the same
2015 data we can create a new reduced demand equation to
calculate elasticity based on a change in income.
QD = 63.63 -13.01 (3.11) + 1.95 (4.38) + .24M
Reduced demand equation = QD = 31.71 + .24M
When the Income is = 67, then QD = 47.79
We can now use the elasticity of demand calculation to
determine the effect on demand if we increase the income by 10.
If we increase income to 77 and input this into the reduced
demand equation, we calculate an estimated quantity demanded
of 50.19. Now we can solve for income elasticity and observe
the effects of this increase.
Income)*(Income Avg/QD Pork Avg)
E = ((50.19-47.79)/(77-67))*((77+67)/2)/(50.19+47.79)/2)) =
.35
With an elasticity greater than 0, the interpretation of .35
elasticity is that this good is a normal good. The fact that the
elasticity is less than 1 also indicates that this good is a
necessity. All other elements held constant a 10% increase in
income will result in quantity demanded increasing by 3.5%.
Displayed below is the affect that this change would have on
revenues.
Total Pork revenue with income at 67 = Q * P = 47.79 * 3.11 =

8. 148.63
Total Pork revenue with income at 77 = Q * P = 50.19 * 3.11 =
156.09
Our final elasticity that we will calculate and interpret is the
cross-price elasticity of demand. This concept is used to
measure the responsiveness of quantity demanded of good X, in
our case pork, to the change in price of a related good Y, in our
case beef.
QD = 63.63 -13.01 (3.11) + 1.95Pb + .24(67)
Reduced demand equation = QD = 39.25 + 1.95Pb
When the Price of Beef is = 4.38, then QD = 47.79
Again using the 2015 data we calculate the quantity demanded
for pork. While holding all other factors constant, an increase in
the price of beef by $1, we can calculate a new estimated
quantity demanded of 49.74. Using these figures, we can
determine the cross-price elasticity of demand.
Cross-
Beef Avg/ QD Pork Avg)
E = ((49.74-47.79)/(5.38-
4.38))*((5.38+4.38)/2)/(49.74+47.79)/2)) = .195
A cross-price elasticity greater than 0 indicates that these are
substitute goods. If the price of good Y increases 10% the
quantity demanded of good X will increase 1.95%. Below we
show the revenue impact for pork when the price of beef
increases by $1.
Total Pork revenue with Price of Beef at $4.38 = Q * P = 47.79
* 3.11 = 148.63
Total Pork revenue with Price of Beef at $5.38 = Q * P = 49.74
* 3.11 = 154.69

9. Results and Discussion
We begin with the equation we are trying to fill or build.
QDx = a – b(Pp) + c(Pb) + d(M)
Where
“a” equals some number
“Pp” equals coefficient of US pork price
“Pb” equals coefficient of US beef price
“M” equals coefficient of US household income
Using a multiple linear regression model (REFERENCE
EXHIBIT NUMBER), we can estimate the demand equation as
follows:
QDx = 63.63 - 13.01(Pp) + 1.95(Pb) + 0.24(M)
“QDx” equals per capita consumption of pork
“Pp” equals US average price per pound of pork
“Pb” equals US average price per pound of beef
“M” equals US household income
Interpret Results:
To interpret this data, we will first discuss the coefficients we
found using regression analysis.
First, the coefficient of negative “Pp” (-13.01) means that there
is an inverse relationship between the price of pork and the
consumption of pork. This is expected given the law of
demand. To explain further, if all other factors are held
constant and the price of pork increases $0.10, then the quantity
of pork demanded will decrease by 1.301 pounds. Conversely,
if the price of pork decreases by $0.10, the then quantity of

10. pork demanded will increase by 1.301 pounds.
The coefficient of “Pb” is positive (1.95) which means that if
all other factors are held constant the quantity demanded of
work will move in the same direction as the price of beef. For
instance, if the price of beef increases by $1.00, then the
quantity demanded of pork increases by 1.95 pounds. If the
price of beef decreases by $1.00, then the quantity demanded of
pork decreases by 1.95 pounds.
When looking at the coefficient of income “M”, it is a positive
(0.24). Like beef, this means that the quantity demanded of
pork will move in the same direction as household income,
when holding all other factors constant. Using this
interpretation, we know that if household income increases by
$1,000.00, then the quantity of pork demanded will increase
0.24 pounds. Additionally, because there is a positive
relationship between the 2 variables, we know that pork is a
normal good.
Raw DataYearPork Consumption
dpc: Pounds per CapitaPrice Pork
dpc: $/poundPrice Beef
dpc: $/poundIncome
dpc: Average Household in
$1000s1985571.482.34211986541.612.35231987491.862.38241
988511.802.34251989511.712.35271990511.712.29291991491.8

11. 92.27311992491.992.38321993521.942.50341994521.932.66371
995492.252.81371996502.242.88381997522.092.85391998522.0
92.93411999522.102.83432000512.062.84452001482.342.80472
002482.452.80502003512.432.77522004532.412.88552005512.5
83.06572006502.693.38582007512.663.32582008522.663.75592
009512.794.07602010502.834.09632011492.813.97672012502.8
74.16682013492.944.33682014502.924.26682015473.114.38672
016453.434.81702017453.474.9971
ResultsSUMMARY OUTPUTRegression StatisticsMultiple
R0.8351852186R Square0.6975343494Adjusted R
Square0.6662447993Standard
Error1.3522944836Observations33ANOVAdfSSMSFSignificanc
e
FRegression3122.301022590440.767007530122.29288525830.0
000001101Residual2953.0323107431.8287003704Total32175.3
333333333CoefficientsStandard Errort StatP-valueLower
95%Upper 95%Lower 95.0%Upper
95.0%Intercept63.63397180571.700773270237.4147294764.251
79713655048E-
2660.155499898967.112443712660.155499898967.1124437126
Price Pork-13.01455293762.1390789273-
6.08418547430.0000012646-17.3894605665-8.6396453087-
17.3894605665-8.6396453087Price
Beef1.95841679110.93915885812.08528810040.04595357210.0
3762125593.87921232620.03762125593.8792123262Income0.2
3833430240.05411606124.40413247340.00013229420.1276545
2990.34901407480.12765452990.3490140748Q=63.63-
13.01Pp+1.95Pb+.24MwherePp = Price of PorkPb = Price of
BeefM = Income
elasticitiesYearPork Consumption
dpc: Pounds per CapitaPrice Pork
dpc: $/poundPrice Beef
dpc: $/poundIncome

12. dpc: Average Household in
$1000s1997522.092.85392017453.474.9971price
elasticityQ2017-Q1997XP AVG-7X2.78=-19.46=-
0.2907515315inelasticof demandP2017-P1997Q
AVG1.3848.566.93income elasticityQ2017-Q1997XM AVG-
7X55=-385=-0.2480670103inferiorof demandM2017-M1997Q
AVG32.0048.51552Cross price elasticityQp2017-Qp1997XP
AVG Beef-7X3.92=-27.44=-0.2643799981complimentaryof
demandPb2017-Pb1997Q AVG Pork2.1448.5103.79