This project was completed as part of my Economic Analysis for Managers MBA class. The purpose of the project was to conduct a regression analysis for the airline industry.
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Economic Regression Analysis Presentation
1. Joseph J. Giarmo III
Economic Analysis for Managers
MBA 679
October 14, 2008
2. Develop an economic regression model for average United
States domestic passenger airfares.
Explain the price of airfares through the identification of
independent variables that have a causal relationship with the
dependent variable.
3. The airline industry (worldwide) consists of:
◦ 2,000 airlines
◦ 23,000 aircraft
◦ 3,700 airports
The U.S. accounts for 1/3rd of the world’s total air traffic
In 2006, U.S. airlines carried 754 million passengers
compared to the over 2 billion passengers that were carried
worldwide
4. World Economy
Government regulation
Global events
Fuel prices
Terrorism
Supply & Demand
5. Airlines have restructured The result:
Airlines have the capability
Increased demand for fuel-
to carry 20.4% more
efficient aircraft
passengers
Modification of existing
Aircraft use 3% fewer
aircraft
gallons of fuel than in 2000
Reduced aircraft weight
$5 billion profit in 2007
6. In 2007, inflation adjusted (real) airfares fell 1.4%
Growth Rates (1978-present): Unadjusted terms
◦ Airfares: 53%
◦ Milk: 154%
◦ New vehicles: 345%
◦ Single-family homes: 345%
◦ Prescription drugs: 499%
◦ Public college tuition: 799%
The decrease in airfares and their low growth rate has been due to:
◦ Economic deregulation
◦ Competitive markets
◦ Advances in technology
◦ More efficient operations
7. Deregulation
◦ Open sky agreements
◦ Elimination of traffic rights restrictions
◦ Competitive air travel market
Demand for fuel-efficient planes
◦ Due to increased fuel prices
◦ Every $10 increase in a barrel of crude oil = $3.4 billion cost for the
airline industry
Mergers
◦ To generate value for the airlines, their shareholders, and their
employees
◦ Northwest Airlines and Delta Airlines
8. Dependent Variable: Average U.S. Domestic Passenger Airfares
Based on fares reported from the United States top 100 airports
o This excludes Alaska, Hawaii, and Puerto Rico
Airfares are measured per ticket and are based on domestic itinerary
fares, round-trip, or one-way for which no return is purchased
Airfares include taxes and applicable fees but do not include frequent flyer
fares and unusually high reported fares
Fares are reported on a quarterly basis by the U.S. Department of
Transportation: Bureau of Transportation Statistics (BTS)
9. Airfares ($)
100
150
200
250
300
350
400
50
0
Mar-95
Sep-95
Mar-96
Sep-96
Mar-97
Sep-97
Mar-98
Sep-98
Mar-99
Sep-99
Mar-00
Sep-00
Mar-01
Sep-01
Date
Mar-02
Sep-02
Mar-03
Sep-03
Mar-04
Sep-04
Mar-05
Sep-05
Average U.S. Domestic Passenger Airfares
Mar-06
Source: Data provided by the U.S. Department of Transportation: Bureau of Transportation Statistics (BTS)
Sep-06
Mar-07
Sep-07
Mar-08
10. Labor Costs
Food and Beverage Costs
Fuel Costs
Other Operating Expenses
Seasonal Dummy Variables
13. Is the model Logical?
Are the slope terms significantly positive or negative?
What is the explanatory power of the model?
Does serial correlation exist?
Does multicollinearity exist?
14. Coefficients Standard Error t Stat P-Value
Intercept 149.472 23.354 6.400 0.000
Labor 0.010 0.002 4.722 0.000
Fuel 0.004 0.001 4.021 0.000
Other Operating 0.009 0.003 2.630 0.012
Exp.
Food/Beverage 0.074 0.028 2.618 0.012
Q1 14.825 4.479 3.310 0.002
Q2 11.147 4.396 2.536 0.015
Source: Data provided by the U.S. Department of Transportation: Bureau of Transportation Statistics (BTS), the Air
Transport Association, and Microsoft Excel
15. For labor costs, reject Ho because |4.72| > 1.684
For fuel costs, reject Ho because |4.02| > 1.684
For other operating expenses, reject Ho because |2.63| > 1.684
For food and beverage costs, reject Ho because |2.61| > 1.684
For Q1, reject Ho because |3.31| > 1.684
For Q2, reject Ho because |2.53| > 1.684
16. Multiple R .763
R Square .583
Adjusted R Square .528
Standard Error 12.896
Durbin Watson .66
Observations 53
Source: Data provided by the U.S. Department of Transportation: Bureau of Transportation
Statistics (BTS), the Air Transport Association, and Microsoft Excel
17. Test Value of the Calculated DW Result Satisfied/Unsatisfied
1 (4-1.175) < .66 < 4 Negative serial Unsatisfied
correlation exists
2 (4-1.854) < .66 < (4-1.175) Result is Unsatisfied
indeterminate
3 2 < .66 < (4-1.854) No serial correlation Unsatisfied
exists
4 1.854 < .66 < 2 No serial correlation Unsatisfied
exists
5 1.175 < .66 < 1.854 Result is Unsatisfied
indeterminate
6 0 < .66 < 1.175 Positive serial Satisfied
correlation exists
Source: Table 4-3 and Table 4-4 from Managerial Economics: An Economic Foundation for Business Decisions
18. Labor Fuel Other Operating Food/Beverage
Exp.
Labor Costs 1
Fuel Costs 0.057 1
Other Operating - 0.106 0.154 1
Exp.
Food/Beverage 0.145 -0.618 0.048 1
Costs
Source: Data provided by the Air Transport Association and Microsoft Excel
19. Actual Airfares ($) vs. Predicted Airfares ($)
400
350
300
250
Airfares ($)
200
150 Actual Airfares ($)
100 Predicted Airfares ($)
50
0
Aug-01
Feb-98
Jun-00
Feb-05
Jun-07
Dec-96
Jul-97
Sep-98
Jan-01
Dec-03
Jul-04
Sep-05
Jan-08
Mar-95
Apr-99
Nov-99
Mar-02
Apr-06
Nov-06
Oct-95
Oct-02
May-96
May-03
Date
Source: Data provided by the U.S. Department of Transportation: Bureau of Transportation Statistics (BTS) and
Microsoft Excel
20. The model is useful but should be used with caution
Why?
Positive serial correlation exists
There are likely many more independent variables that
could and should be considered
The airline industry is vulnerable to many external and
internal factors making it a somewhat unpredictable
industry