1. Airport Forecasting
NOTE: for HW, draw cash flow diagram to solve and review engineering economics

2. errata
General Airport website: Master Plan Executive Summary: Master Plan Appendix A (Forecasts): Full Master Plan:
See first two pages of Appendix A

3. Forecasting Demand
Essential to have realistic estimates of the future demand of an airport
Used for developing the airport master plan or aviation system plan

4. Data used to predict future
1. Airport service area
2. Origins and destinations of trips
3. Demographics and population growth of area
4. Economic character of area
5. Trends in existing transportation activities for the movement of people, freight, and mail by various modes
6. Trends in national traffic affecting future development
7. Distance, population, and industrial character of nearby areas having air service
8. Geographic factors influencing transportation requirements
9. Existence and degree of competition between airlines and among other modes of traffic

5. Estimates Needed
1. The volumes and peaking characteristics of passengers, aircraft, vehicles, freight, express, and mail
2. The number and types of aircraft needed to serve the above traffic
3. The number of based general aviation aircraft and the number of movements generated
4. The performance and operating characteristics of ground access systems

6. Forecasting by Judgement
Delphi Method: A panel of experts on different subjects is assembled and asked a series of questions and projections which they take into account to determine a forecast

7. Trend Extrapolation
375000
390000

8. Top-Down Model Extrapolate 1 and 2, multiply to get 3:
Statistical Abstract of the US
Air Carrier Fleet
FAA aviation stats
BTS # of Aircraft, …
Top-Down Model
Extrapolate 1 and 2, multiply to get 3:

9. Cross Classification Model
Cross Classification: examines the behavioral characteristics of travelers
Travelers broken down into classifications based upon these characteristics
Based on the belief that certain socioeconomic characteristics influence the inclination for travel
Market study performed to determine the travel characteristics of the individual groups
By knowing the different groups’ travel patterns, forecasts can be made by projecting the patterns out

10. Factors Income Occupation Age Type and location of residence Education
etc…

11. Market Study
Market Study method does NOT require complex mathematical relationships
uses simple equations to generate a classification table or matrix
Advantage: allows for discrimination between discretionary and non-discretionary travelers and the factors that influence both types
Discretionary = vacationers
Non-discretionary = business traveler

12. Multiple Regression
Econometric Modeling: relates measures of aviation activity to economic and social factors
Multiple Regression is used to determine the relationships between dependent variables and explanatory variables

13. Explanatory Variables
Economic growth
Population growth
Market factors
Travel impedance
Intermodal competition

14. Regression Equations Linear Regression form: Multiple Regression form:
Y = mx + b
Multiple Regression form:
Yest= ao + a1X1 + a2X2 + a3X3 + … + anXn

15. Statistical Testing of Models
Tests performed to determine the validity of econometric models
The analyst needs to consider the reasonableness as well as the statistical significance of the model

16. Coeff. of Mult. Determination
Coefficient of multiple determination, R2 : measures the variation in the dependent variable that is explained by the variation in the independent variables
(e.g. R2 = 1.0 is perfect correlation)
Equation:
R2 =
(Yest - Yavg)2
(Y - Yavg)2

17. Coeff. of Mult. Correlation
Coefficient of multiple correlation, R: measures the correlation between the dependent variable and the independent variables
(e.g. R = 1.0 perfect correlation)
Equation:
R = (R2)1/2

18. [ ] Standard Error y est =
Standard error of the estimate: measure of the dispersion of the data points about the regression line and is used to establish the confidence limits
Equation:
(Y - Yest)2
m - (n+1) [ ]
y est =

19. Equations for Trend Line

21. Elasticity
Elasticity: the percentage change in traffic for a 1% change in fare or travel time
In the past, it was important
Even greater significance today due to a deregulated industry
fare wars
Hub and spoke system

22. ( ) q p p q  = Elasticity
 < -1, Elastic, people likely to change trip behavior
E = 0, Perfectly Inelastic, no effect on trip behavior
-1 < E < 0, Inelastic, less sensitive to price q p p q
 = ( )

23. Elasticity Example
The current fare is 7 with 6000 tourists and 7500 commuters daily.

24. ( ) q p p q  = Calculations Tourists: Commuters:
(-4000/2) (7/6000) =  < -1, Elastic
people likely to change trip behavior
Commuters:
(-1000/2)(7/7500) = < E < 0, Inelastic
less sensitive to price q p p q
 = ( )

25. Engineering Economics

26. Engineering Economics

27. Available forecasts
FAA