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
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States domestic passenger airfares.
Explain the price of airfares through the identification of
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independent variables that have a causal relationship with the
dependent variable.
3. The airline industry (worldwide) consists of:
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⊠2,000 airlines
⊠23,000 aircraft
⊠3,700 airports
The U.S. accounts for 1/3rd of the worldâs total air traffic
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In 2006, U.S. airlines carried 754 million passengers
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compared to the over 2 billion passengers that were carried
worldwide
4. World Economy
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Government regulation
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Global events
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Fuel prices
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Terrorism
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Supply & Demand
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5. Airlines have restructured The result:
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Airlines have the capability
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Increased demand for fuel-
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to carry 20.4% more
efficient aircraft
passengers
Modification of existing
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Aircraft use 3% fewer
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aircraft
gallons of fuel than in 2000
Reduced aircraft weight
ï $5 billion profit in 2007
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6. In 2007, inflation adjusted (real) airfares fell 1.4%
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Growth Rates (1978-present): Unadjusted terms
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⊠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:
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⊠Economic deregulation
⊠Competitive markets
⊠Advances in technology
⊠More efficient operations
7. Deregulation
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⊠Open sky agreements
⊠Elimination of traffic rights restrictions
⊠Competitive air travel market
Demand for fuel-efficient planes
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⊠Due to increased fuel prices
⊠Every $10 increase in a barrel of crude oil = $3.4 billion cost for the
airline industry
Mergers
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⊠To generate value for the airlines, their shareholders, and their
employees
⊠Northwest Airlines and Delta Airlines
8. Dependent Variable: Average U.S. Domestic Passenger Airfares
Based on fares reported from the United States top 100 airports
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o This excludes Alaska, Hawaii, and Puerto Rico
Airfares are measured per ticket and are based on domestic itinerary
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fares, round-trip, or one-way for which no return is purchased
Airfares include taxes and applicable fees but do not include frequent flyer
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fares and unusually high reported fares
Fares are reported on a quarterly basis by the U.S. Department of
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Transportation: Bureau of Transportation Statistics (BTS)
9. Airfares ($)
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
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Food and Beverage Costs
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Fuel Costs
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Other Operating Expenses
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Seasonal Dummy Variables
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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
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For fuel costs, reject Ho because |4.02| > 1.684
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For other operating expenses, reject Ho because |2.63| > 1.684
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For food and beverage costs, reject Ho because |2.61| > 1.684
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For Q1, reject Ho because |3.31| > 1.684
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For Q2, reject Ho because |2.53| > 1.684
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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
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Why?
ï Positive serial correlation exists
There are likely many more independent variables that
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could and should be considered
The airline industry is vulnerable to many external and
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internal factors making it a somewhat unpredictable
industry