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slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS Dept., Univ. North Texas

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Page 1: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 1

DSCI 5180: Introduction to the Business Decision Process

Case Study 2

Constructing a Demand Curve for Crude Oil

© 2013 Nick Evangelopoulos, ITDS Dept., Univ. North Texas

Page 2: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 2

DSCI 5180Decision Making

Review of Microeconomics/Price Theory

A Demand Curve shows the relationship between price and consumption

Plots Price on the vertical axis and Consumption on the horizontal axis

Page 3: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 3

DSCI 5180Decision Making

Using a Demand Curve

A demand curve can be used in business planning

For example, if a certain accident (spillage, explosion, etc.) results in a temporary reduction of the total quantity of an essential raw material offered for sale in the market, the demand curve can help you estimate the expected price increase so that supply and demand are stabilized

Knowing the expected price increase allows you to adjust your budget

Quantity consumed

Price

A

B

Equilibrium moves from A to B

Page 4: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 4

DSCI 5180Decision Making

Oil consumption data

File USOilDemand1970-2002.xls contains data related to demand for crude oil in the United States in the 1970-2002 period. Data were obtained from the U.S. Dept. of Energy and U.S. Department of Labor Web sites.

Y AdjOilPrice Inflation Adjusted U.S. Crude Oil Price, base year = 2005 (in $)

X1 USPop Total Midyear Resident U.S. Population

X2 USOilCons U.S. Petroleum Consumption in million barrels per day

X3 WorldOilCons World Petroleum Consumption in million barrels per day

Page 5: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 5

DSCI 5180Decision Making

Not a clean demand curve

A preliminary plot of AdjOilPrice versus USOilCons does not provide a clean demand curve!

Page 6: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 6

DSCI 5180Decision Making

Why not a clean demand curve?

This happens because our data spans a number of years during which many things changed, including population and oil consumption habits and needs

The price/quantity equilibrium points need to be adjusted so that they correspond to a single demand curve.

Quantity

Price

Quantity

Price

Page 7: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 7

DSCI 5180Decision Making

Drivers of US Oil Consumption other than Oil Price

If Oil Prices in the US were held constant, US Oil Consumption would be driven by such factors as:

•Oil Availability (World Oil Production)•Population Growth (US Population)•Spending Habits of the US Consumers (Total US Consumption)

Based on these drivers, we fit a regression model that explains US Oil Consumption. The unexplained part (residuals) is a US Oil Consumption Differential.

US Oil Consumption = f(World Oil Production, US Population, US Consumption) + US Oil Consumption Differential

Page 8: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 8

DSCI 5180Decision Making

Drivers of US Oil Consumption other than Oil Price

The regression model has a good fit. All regression assumptions (normality, constant variance, independence of the error term) hold.

Page 9: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 9

DSCI 5180Decision Making

Drivers of Oil Price other than US Oil Consumption

The same drivers may partially affect Inflation-Adjusted Oil Price. We fit a second regression model that explains US Oil Price (adjusted for inflation). The unexplained part (residuals) is a US Oil Price Differential.

Inflation-Adjusted US Oil Price = f(World Oil Production, US Population, US Consumption) + US Oil Price Differential

Page 10: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 10

DSCI 5180Decision Making

Price vs. Consumption after the model adjustments

Plotting Residuals1 (=US Oil Price Differential) vs. Residuals2 (=US Oil Consumption Differential) reveals a shape that is much closer to a demand curve

Page 11: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 11

DSCI 5180Decision Making

Adding a quadratic demand curve

Transfer your data to Excel, plot the scatterplot, and then add a trendline. Change the trendline settings to a second-order polynomial curve

Page 12: Slide 1 DSCI 5180: Introduction to the Business Decision Process Case Study 2 Constructing a Demand Curve for Crude Oil © 2013 Nick Evangelopoulos, ITDS

slide 12

DSCI 5180Decision Making

Final measurement scale adjustment

The plot shown in the previous slide uses “differential” measurement scales. These may be hard to interpret. Adding a constant to all data for the two variables would not alter their relationship or the shape of the curve. Add the average price to all US Oil Price Differential values and add the average consumption value to all US Oil Consumption Differential values

Model-Adjusted US Oil Price = US Oil Price Differential + Average (Price)

Model-Adjusted US Oil Consumption = US Oil Consumption Differential + Average (Consumption)