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 Dept., Univ. North Texas

2. slide 2 DSCI 5180 Decision 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

3. slide 3 DSCI 5180 Decision 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

4. slide 4 DSCI 5180 Decision 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. YAdjOilPrice Inflation Adjusted U.S. Crude Oil Price, base year = 2005 (in $) X1USPopTotal Midyear Resident U.S. Population X2USOilConsU.S. Petroleum Consumption in million barrels per day X3WorldOilConsWorld Petroleum Consumption in million barrels per day

5. slide 5 DSCI 5180 Decision Making Not a clean demand curve  A preliminary plot of AdjOilPrice versus USOilCons does not provide a clean demand curve!

6. slide 6 DSCI 5180 Decision 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.

7. slide 7 DSCI 5180 Decision 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

8. slide 8 DSCI 5180 Decision 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.

9. slide 9 DSCI 5180 Decision 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

10. slide 10 DSCI 5180 Decision 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

11. slide 11 DSCI 5180 Decision 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

12. slide 12 DSCI 5180 Decision 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)