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IA0-A125 357 SOCICECONONIC SCENARIOS VOLUMN I JU) ACVUMEN ICS RESEARCH 1/2
0 P~~ND TECHNOLOGY INC 8ETHESDa M FEBUCSIFE SR-RP-11-VL2DTF7M i-3 . /1721N
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MICROCOPY RESOLUTION TEST CHART
NATIONAL BUREAU OF STANDARDS-1963-A
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A e~ ~5iTechnical Report Documentation Pageo1. Report No. 2. Government Accession No. 3. Recipient' Cptalo, No. -
FAA-,APO-81-ll '3 of 6) A [S 3-574. Title and Subtitle 5. Report Date
February 20, 1981Socioeconomic Scenarios, Volume 11 6. Performing Organization Code0
_____________________________________________________________ 8. Performing Organization Report No.7. Author's)
9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 7
Acumenics Research and Technology, Inc.04340 East-West Highway 11. Contract or Grant No.
Suite 808 DOTFA78WAI-932Bethesda, Maryland 20814 13. Type of Report and Period Covered
12. Sponsoring Agency Name and Address
Department of TransportationFederal Aviation AdministrationOffice of Aviation Policy and Plans 14. Sponsoring Agency Code
IWashington, D. C. 20591 APO-21015. Supplementary Notes
t4"C 16. Abstract
DTICEECTE
- 83037 1983D
_ _ _ _ _ _ _ _ _ 04 084117. Key Words 18. Distribution Statement
Document is available to the publicthrough the National TechnicalInformation Service, Sprinpfield,
________________ Virginiaol16 0~~I___19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price
Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
w~~~~~ W w '
.
The contents of this report reflect neither
a position nor an official policy of the
Department of Transportation. This document is
disseminated in the interest of information exchange.
The United States Government assumes no liability
for the contents of this document or use thereof.
Accossion for
- INTIS GPAk&IDTTC TAR flL.-innnounced El
Justificatio
Distribution/SAvailabi11ty Codes
Avail Rnd/orDint Spec I Pl
4 t'
I
~~~~. -. .. . . . . . . . . ..... . . ..- - L. ,j : .. . . . .. ::.......
[ .TABLE OF CONTENTS
[mr Page
Scenario Themes and Overviews. . . . . . . . . . . . . . . . . 3
r Overview of Balanced Growth Scenario . . . . . . . . . . . 5Overview of Rapid Growth .... ..... ... . .. . . 5
_ Overview of Stagflation . .. . ........... 6
I Balanced Growth Scenario . . . . . . ............... . 7
Balanced Growth Economy . . . . . . . . . . . . . . . . . 7Aviation Industry . . . . . . . . . . . . . . . . . . . . 10Demand in Communication Industry......... . . . . 19
[ Rapid Growth Scenario. .. .. ... .. . . . .. .. .. . . 19
Rapid Growth Economy. . . . . . . . . . . . . . . . . . . 19Aviation Industry . . . . . . . . . . . . . .. ...... 20
Demand in Communications Industry . . . .......... 27
Stagflation Scenario . .................... . 27
Stagflation Economy . ......... . . . . . . . . . 27Aviation Industry . . . . . . . ..... . . . . . . . . 28Demand in Communications Industry . . . . . . . . . . . . 34
Pilot Composition ...... . . ........... . . . . 36
StagflationScenario . . . . .:.. .. . 36"Balanced Growth Scenario .. .. .. .. .. .. .. . .. 38
Rapid Growth Scenario . . . . . . . . . . . . . . . . . . 40
Air Carrier Fleet . . . . . . ................... . 42
Balanced Growth Scenario . . . . . . . . . . . . . . . . . 42Rapid Growth Scenario . . . . . . ........... . 42Stagflation Scenario . . . . . . . . . . . . . . . . . . . 42
Summary . . . . . . . . . . . . . . . . . . . . . . . . . .. . 45
Appendix: Forecast Method . . . . ........ . . . . . . A-1
. I iACUMENICS
.- . * , - ..
LIST OF TABLES
Page
1 Forecasted Balanced Growth Economic Variables . . . . . 9
2 Statistical Analysis System . . . . . ......... 12
3 Statistical Analysis System . . . . . ......... 15
4 Statistical Analysis System . . . . . . . . . . . . . . 17
5 Forecasted Rapid Growth Economic Variables . . . . . . . 21
* 6 Forecasted Stagflation Economic Variables . . . . . . . 29
17 Pilot Composition - Stagflation . . . . . . . . . . . . 37
8 Pilot Composition - Balanced Growth . . . . . . . . . . 39
9 Pilot Composition - Rapid Growth. . . . . . . . . . . . 41
10 Aircarrier Fleet - All Scenarios . . . . . . . . . . . . 44
11 Forecasted GNP - Trillion $/1972 . . . . . . . . . . . . 49
12 Forecasted DPI - Trillion $/1972 . . . . . . . .. . . . 50
13 Forecasted Employment - Millions...... . . . . . . 51
A-i Linear Approximations of Official Baseline Forecast, A-71970-1972 . . . . . . . . . . . . . . . . . . . . ..
A-2 List of Forecast Equations...... . . . . . . . . . A-9
A-3 Total Operations . . . . . . . . . . . . . . ... . . . . A-11A-4 Local Operations . . . . . . . . . . . . . . . . . . . . A-12
A-5 Itinerant Operations . . . . .. . . . . . . . . . . . . A-13
A-6 Total Active GA Aircraft . . . . . . . . . . . . . . . . A-14
A-7 Single Engine GA Aircraft . . . . . . . . . . . . . . . A-15A-8 Multiple Engine GA Aircraft . . . . . . . . . . . . . . A-16
g A-9 En Route Total Aircraft Handles . . . . . . . . . . . . A-17
A-10 IFR Departures . . . . . . . . . . . . . ... .. A-18A- f1 Total Overs . . . . . . . . . . . . . . . . . . . . . A19
I A-12 Flight Services . . . . . . . . . . . . . . . . . . . . A-20
A-13 Total Flight Plans Filed .................... A-21
A-14 Pilot Briefing . . . . . . . . . . . . . . . . . . . . . A-22
A-15 Total Pilots . . . . . . . . . . . . . . . . . . . . . . A-23[ A-16 Student Pilots..... . . . . . . . . . . . . . .A-24
ACUMENICS
-I LIST OF TABLES (Continued)
j Page
A-17 Transport Pilots . . . .* .. ... . . . . . . . . A-25
A-18 Private Pilots . . . . . o . . . . . . . . . . . . . . A-26
A-19 Controller Staffing Equations . . . . . . . . . . . . . A-27
A-20 Definition of Terms . . . . . . . . . . . . . . . . . . A-28
ACMNC
ir LIST OF FIGURES
SPage1 1 G.A. Aircraft Balanced Growth . ............ 132 Balanced Growth Operations . ............. . 16
r- 3 En Route Workload Measures Balanced Growth . ...... 184 G.A. Aircraft Rapid Growth ............... 23
5 Rapid Growth Operations ............... . 25
6 En Route Workload Measures Rapid Growth . . . . . . . . 267 G.A. Aircraft Stagflation ............... 31
, 8 Stagflation Operations . ............... . 339 En Route Workload Measures Stagflation . . . . . . . . . 35
10 Forecasted GNP All Scenarios . ......... . 46[ 1 Forecasted DPI All Scenarios .............. 47
12 Employment Forecast All Scenarios . . . . ....... 4813 Total GA Aircraft By Scenario . . . .. .. . . . . . . 5214 Multi-Engine A.C. By Scenario . ............ 53
[ 15 Single Engine A.C. By Scenario .. . . . . . . . . . . . 54
16 Total Operations By Scenario . . . . . . . . .. .. . . 56
17 Itinerant Operations By Scenario . . .......... 57
18 Local operationsBy Scenario ...... . . . . 5819 Total Aircraft Handled By Scenario .. .. .. .. . . . 5920 Total IFR Departures By Scenario ...... . . . . .6021 Total Overs By Scenario . . . . . ..... . 61
A-1 Illustration of Linear and Logistic Forms ....... A-6
Iii!
iv ACUMENICS
r Introduction
Technology does not evolve in a sterile environment. The nature
and rate of technological change are inexorably bound with socio-
[ economic phenomena. Technology, when introduced, may alter
historic social and economic relationships. At present, the
[ precise factors which induce technological innovation are not
rknown. Such change is indicated by factors which measure economic
* . and social growth. The purpose of technology assessment is to
ridentify and measure the social effects of innovation. As of yet,
the identification has been more successful than measurement of
L effects. It is difficult to measure that which is little under-
stood. The measurement problem exists because effects are often
multifarious. For example, it is clear that the telephone has
L yielded major social change. It has altered the conduct of personal
and business communications. It has brought places and persons
of vast geographical distances together. Yet one cannot fully
Lgrasp or measure the effects of the telephone.
.4L It seems reasonable that the retrospective identification and
measurement of social effects due to technology innovation could
[ be accomplished, as the events that induced such change and the
attendant results are locked in history. Yet, the thought of
measuring the effects of the telephone are bewildering.
I.ACUMEN ICS
im-
Since the problems of measuring the effects of accepted technology
[ are difficult, the problems of estimating impacts of future
technology on distant socio-economic settings require additional
considerations. As the future is not locked in history, variations
of future social settings will change the magnitude and timing of
effects. Since the future is not known, it is reasonable to
posit likely scenarios within which to consider the impact of
technology. A brief review of history indicates that society
does not follow a predictable pattern. However, one may posit
I future scenarios as bounds for which there seems to be a
Ireasonable probability of occurance. The scenarios presented
in this section are such bounds.
The purpose of this section is to present three reasonable future
I societal options within which one may consider the impact of
aviation communications technology. The information contained
in succeeding sections provides only the glimpse of future bounds
I[ necessary for the conduct of the study. Speculation for specu-
lation sake has been eliminated. That is, the scenarios contain
I[ only those factors found necessary to examine the primary impacts
of technology. - ..
I
AC2MENICS2
I
Scenario Themes and Overviews
The following three themes were used to characterize the alternative
future scenarios: "Balanced Growth", "Rapid Growth", and
[! "Stagflation". The official FAA aviation forecasts extrapolate
the present to the year 1992 on the basis of four scenarios:
"Baseline", "High Prosperity", "Energy Conservation", and "Slow
Growth"(1). The socio-economic assumptions underlying the FAA's
scenarios were used as the basis for the construction of the
*1 scenarios used in this study. The alternative scenarios correspond
to the FAA scenarios in the following manner:
TECHNOLOGY FORECAST SCENARIOS FAA SCENARIOS
Balanced Growth ----------------- Baseline
:1 Rapid Growth --------------------- High Prosperity
Stagflatioa ----------------------- Slow Growth
The time period considered in the present study is 1985 to 2020.
Il The historic and forecast data developed in the FAA document have
been taken as fact for the purposes of the present study. Although
a plethora of variables could be used in the construction of the
scenarios, the research in this report demonstrates that only a
select few variables, also used in the FAA forecast need be
considered. These measures included the following three economic
I variables, gross national product (GNP), disposable personal income
I ACUMEN ICS
3
(DPI) and civilian employment. Measures of aviation activity used
in this studV include:
* aircraft operations;
size and composition of the active general aviation fleet;
e size of the air carrier fleet;
" size and composition of the cadre of pilots; and,
a measures of FAA air traffic control measures; e.g. aircrafthandled, IFR departures, pilot briefings, etc.
The measures estimated for the three scenarios included in this
report are consistent with those included in the recent FAA fore-
cast.
Examination of the FAA aviation forecasts indicates that the
,* "Baseline" scenario forecast shows moderate economic growth rates
with a decline in unemployment and inflation. The "High Prosperity"
and "Slow Growth" scenarios werebased on modifications of the
"Baselino" forecast. The "High Prosperity" scenario assumes growth
rates and related economic conditions similar to those experienced
in the U.S. between 1961 and 1966. On the other hand, the "Slow
* Growth" scenario assumes growth rates and related conditions similar
to those that prevailed in the U.S. between 1971 and 1975. The
socio-economic phenomena associated with the FAA scenarios are
expanded in time to develop the alternative scenarios detailed in
.. this report'(2 ).I
ACUMENICS----------
Overview of Balanced Growth Scenario
The Balanced Growth Scenario depicts a society that has deliberately
constrained economic and technological growth in order to allay
- negative social and economic impacts derived from uncontrolled
growth. Contrary to the past, a mutually cooperative relation-
-- ship exists between government and private industry allowing for
the attainment of specific social goals.-- Government intervention
in the affairs of private industry is of a twofold nature. Govern-
ment regulations serve to establish and maintain an increasingly
competitive market structure in all industries. Simultaneously,
the government examines industries' compliance with regulations
*designed to promote social welfare. The latter govermental task
* is executed in a manner that places minimal restrictions on economic
• "-'nd technological development and growth for all industries.
* Population growth continues with a fertility rate equal to the
replacement level. The result is that the U.S. slowly approaches
"zero population growth". The population distribution patterns
for this scenario exhibit an increasing populace in small cities,
towns and rehabilitated inner cities.
Overview of Rapid Growth
The Rapid Growth scenario portrays a society where technological
4 change is the driving force in societal transition. National
policy reflects the attitudes of society, as the government takes
minimal steps to influence the rate and direction of technological
ACUMENICS
5
-4
and economic change. Government intervention in private industry
* is limited to enforcing regulations that allow for maximum compe-
* tition and efficiency within market structures. Therefore, the
development of new technology is limited only by market forces.
The nation's population increases as the fertility rate approaches
- . post World War II levels and the replacement rate remains constant.
Population distribution patterns reveal continual suburban develop-
ment in the Southwest, Eastern and Great Lake Regions.
Overview of Stagflation
In the Stagflation Scenario social goals or objectives are in
conflict with the nature and direction of technological change.
As such, technological innovation is inhibited, since social
objectives include the minimization of the untoward effects of
technology without consideration of the benefits.
I" Attempts to formulate and implement a national policy for control-
led economic and technological growth meet with uniform opposition
from industrial interest. As such, the relationship between
Iindustry and government deteriorates. Government programs result
in gerrymander regulations and laws that retard economic and
I technological growth. Industrial productivity decreases,
unemployment increases, and inflation continues to diminish the
currency. The lack of social progress increases social pressures
to effect changes through increased government activity. One
result of increased government activity is to reverse the deregu-
ACUMENICS1 6
hA
lation trend initiated in the 1970's. Previously regulated
communications industries are subject to new regulation in the
public interest.
Balanced Growth Scenario
In the Balanced Growth Scenario economic and technological growth
is assumed to occur at a slow but constant rate. Government inter-
vention into private industry affairs serves to promote highly
*competitive market structures while simultaneously fostering
social welfare. Inflation and unemployment are reduced as the
general level of affluence rises gradually but steadily.
Balanced Growth Economy
The balance-between economic and technological growth and social
needs results in modest economic growth. Industrial production
increases at a slow but constant rate, consistent with national
policy. Throughout the forecast period, GNP rises at an average
annual rate of 2.8%. GNP expressed in 1972 dollars doubles in a
*twenty-four year period from $1740 trillion in 1985 to $3480
trillion by the year 2009. By the year 2020, GNP will increase
170% over the 1985 level to $4700 trillion. Disposable personal
income increases at an average annual rate of 3.01% throughout
the forecast period. Expressed in 1972 dollars, disposable
Ipersonal income doubles in the first twenty-four year period of the
forecast to $2500 trillion. By the year 2020, disposable personal
income will increase 191% from $1250 trillion in 1985 to $3640
I 1 ~ACUMEN ICS
[-.-
trillion. Throughout the forecast period, civilian employment
experiencesl steady increase at an average annual rate of,1.16%.
From 1985 to the year 2020, civilian employment increases 51%
from 104.3 million workers to 158 million workers. Data for the
period 1985 - 2020 for each economic variable are presented in
Table B-i.
The expected values for the economic variables will have a signi-
ficant impact upon the aviation and communication industries.
GINP, a measure of industrial production, constantly increases
during the forecast period. The rise in industrial activity
reveals potential for an increase in the utilization of general
aviation transportation by private industry. Factors increasing
the utilization of general aviation transportation by private
industry include the following:
*Cost saving advantage for some travel distances andgeographical areas;
*Business dispersions and centralized management;
* e Changing air route structures; and,4
* Rapid escalation of fuel prices.
*GNP, a measure of the level of investment, indicates that capital
41 will be available during the forecast period for the development
of sophisticated communciation technology required to control
1. the increasing levels of air traffic.'.4I As indicated previously, disposable personal income, (a measure
of consumer purchasing power) and civilian employment increase
8 ACUMENICS
steadily throughout the forecast period. The increased values
* , of these economic variables implies that more individuals will
become involved with aviation transportation. This phenomena
will occur because of the increasing number of individuals who
will be able to afford air transporation services.
Aviation Industry
* Throughout the forecast period, the demand for air transportation
*is evidenced in the size and composition of the general aviation
fleet mix. The total number of aircraft in the general aviation
fleet increases at an average annual rate of 1.3% throughout
the forecast period. Between 1985 and the year 2020, the general
aviation fleet increases by 62% from 254,000 to 413,.000 aircraft.
Private industry's increased demand for heavier more sophisticated
aircraft accounts for the slow but increasing growth of multi-
v' engine aircraft active in the general aviation fleet. Throughout
the forecast period the number of multiengine aircraft in the
1 general aviation fleet increase at an average annual rate of 1.6%.
* Between 1985 and the year 2020, the number of active multiengine
1. aircraft in the general aviation fleet increases by 82% from28,709 to 52,174 multiengine aircraft. The increase in the number
of single-engine aircraft active in the general aviation fleet
Lis a result of a combination of industrial and public demand forair transportation. The number of single-engine aircraft, used
I primarily for private and instructional flying, increases at an
Iaverage annual rate of 1.2% throughout the forecast period.
10 ACUMENICS
p . ..
Between 1985 and 2020, the number of active single-engine aircraft
in the general aviation fleet rises 56% from 202,481 to 315,264
single-engine aircraft. The numbers and types of aircraft pro-
jected to be active in the general aviation fleet mix is shown
* in Table B-2 for the three alternative scenarios. The general
aviation fleet mix for the Balanced Growth Scenario is presented
in Figure B-i.
The effects of the projected demand levels on air transportation
is reflected also in FAA workload measures. FAA provides the
aviation community with several operational services including the
following two activities: air traffic control at FAA towered
*airports and traffic surveillance and separation at Air Route
Traffic Control Centers. The need for FAA operational services
will increase as a result of growth in aviation activity. Total
aircraft operations at FAA towered airports are projected to
increase at an average annual rate of 1.9% throughout the forecast
period. Between 1985 and 2020, total aircraft operations at
FAA towered airports increase 101% from 83 million to 166 million
aircraft operations. Itinerant aircraft operations rise at an
average annual rate of 1.71 throughout the forecast period.
Between 1985 and the year 2020, itinerant aircraft operations at
FAA towered airports increases 86% from 55.9 million operations to
104.3 million oper; ins. The increase in itinerant operations
reflects both the increases in utilization of general aviation by
business and the increase in demand for air carrier services by
ACUMENICS
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the general public. Local aircraft operations increases at an
average annual rate of 2.3% throughout the forecast period. Between
1985 and the year 2020, local aircraft operations performed at FAA
towered airports increase 131% from 27 million to 62 million. The
* increase in local aircraft operations derives from an increase in
* pilot instruction which will in turn create more air traffic after
students become licensed pilots. The complete tabulations for FAA,
towered airport workload measures are given in Table B-3. The
measures displayed graphically in Figure B-2 are the FAA towered
airport workload measures for the Balanced Growth Scenario.
The growth in the number of aircraft handled by the Air Route
Traffic Control Centers increases at an average annual rate of
1.7% throughout the forecast period. From 1985 to 2020, total
IFR aircraft handled by Air Route Traffic Centers increases 88%
from 36 million to 68 million aircraft. The increases in
operations at Air Route Traffic Control Centers will be a result
of increase in general aviation traffic associated with increases
in pilot capabilities and an increased use of larger more
sophisticated aircraft. The complete tabulations of enroute1 center work measures are given in Table B-4. The enroute work
4 measures for the Balanced. Growth Scenario are displayed graphically
in Figure B-3.
41I I 14ACUMEN ICS
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at fn N N N N in N w) Nr N- Nr on y N- N. N N N N . N N ND N N on N in N N an N Na a,I Z in inP %D PW VN r &nwnnN I 9p N04
N~- V Nn %00 W N w t% m N w0 -04 N m~ " & &A N1a0% N n m m. %- N4 0I a. a. N N
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02 . . . . . .. . .. . .. .. .. . .. 4 6 1 v e .- 41. . an. .
0 60o0AOla N CD 10 N so 106 w N co9 0WN 10 Nso 1 N 0 ON 4.t 10 s "on wl 10
c oo N a4s n o so n "s NO in . in c Nc v, 60opi N o i cy a, IA 10 N , w- N N .w a. -606 NY
f ~ " a- 40 N 106 N pn- N D N N0 N% C1 W- a.0 NP. W wI a.-N 1 W% m 0I WI N 60. .A .n .I . . .. .I .I 60 . .mm 066 V .~ .N .mgn 0 W W; an ;~. .60 CN&I mnW 0 Im m NO&%Dc & 0 rN6NW a, -A0 NIr %& 0 m nC100AI 60.NWIIW
P. Z -6an60a-40m-6 460 an N-'1 an -6an.0a160N a- an P6 an -4 IV-
so %l .6g0C Nan. ,'Y " w WN 10 an C WCDI N m4%& Nl an N so a.- C N 10a W; 0;64 an C1 9;
9% 10 00Na C0"6&0W.-4 P. so km-4 eyW)Iina 0 oNC a. " WITIA N goN a, m W
al10 N an an an aYn a n 101000 N - N Nl N1 Nl 0P 06000. aI"CFnW&. N. o00=0.at 0 00 00 , 0.0 -a ,a ma 4- "0P... yC
O4'aa0 -W aamM M a D*w~ w =~----I0Wa1-------- WI000~aO~a-~m0NO
N0 o~en wU m0 0,m anN M, -A. 0 ~aa- D n F04 a N .m inZ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ o N .0NIIC .1N0I Fn0. 6 01 N10. an O0C N in-
4 II60NC06a.-4WImImmACIN40NCI6m-60I0C170W
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=& a -A U.
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a a0.1m
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-- - - - - - -
Demand on Communicatio: IndustryinGPtruhtte
The slow but steady increases observed in GNP throughout the
Jforecast period, indicate that capital will be available fortechnological development in the communications industry. The
* net effect of increases in the demand for air transportation has
special significance for the communications industry. Throughout* I
the forecast period, aircraft operations and fleet size rise
steadily which also increases the amount of air traffic. In order
' to efficiently handle the increased air traffic, new communications
technology will have to be developed to ensure the safety of the
air routes.
Rapid Growth Scenario
In the Rapid Growth Scenario it is assumed that society makes no
attempt to constrain or channel economic and technological growth.
National policy encourages economic and technological growth as
the government acts to remove or reduce all barriers to such
development.
Rapid Growth Economy
The result of rapid economic and technological growth is reflected
in the GNP statistics for this scenario. Throughout the forecast
1 period, GNP will rise at an average annual rate of 4.2,. Between
1985 and the year 2020, GNP expressed in 1972 dollars increases
3421 from $1900 trillion to $8400 trillion. The average annual rate
I 19 ACUMENICS
Y of increase for Disposable Personal Income is approximately the
same as the rate of growth in the GNP for the same forecast period.
[ However, Disposable Personal Income (also expressed in 1972 dollars)
increases 345% from 1310 trillion in 1985 to $5830 trillion in the
-F year 2020. Civilian Employment rises steadily at an average annual
rate of 10 throughout the forecast period. Between 1985 and the
year 2020, the civilian workforce is projected to increase 55%
from 105.7 million workers to 163.9 million workers. The values
of the economic variables for each year in the 1985-2020 period
[ are included in Table R-1.
The GNP statistics indicate that industrial production increases
I constantly throughout the forecast period. An increase in
industrial activity indicates that there will be a great demand
for general aviation transportation. The GNP measures in this
forecast also indicate that substantial levels of capital will
I be available to develop technology in the aviation and communica-
tions industry. The projected annual rate of increase for
disposable personal income and civilian employment suggest that
an increasing amount of individuals will have available the
resources necessary to utilize air transportation.
Aviation Industry
*The size and composition of the general aviation fleet reflects
society's demand for air transportation. The total general
aviation fleet rises at an average annual rate of 2.41 through-
I out the forecast period. By the year 2020, the total general
1 20 ACUMENICS
-4
.1L4j
an
an
in %r .M CD riD .60 a C, N4 .CYnI wl . so V.~ ' In -A S cC do C2 Cy r c c* ~ A N cy Vc@ r NC'. ' I- N Sri .W Ny Cit 0' Fn N W) Kl W) %tI qr 'ri Ir yi l n ti ViN in wl
* 4
Z 1 CF0. W)2-&M , cy '0 N o nr c " 1 O C CPC-IinCMM Pn'AIN &M 0W ' - .- CY C CY .~ j N .r. N )W O ) onn iAn r)% %r~~A 0'~i in na ao- IAIrf r. 46-do
=rCC-- - N N N N N cm N N m m mn Fn %,P -- wi -r %r %It .4 r LetVM In Si I.0 .01- 4 - -- 4 4 - 444 -4-1 4 4~ -e----1 -1.4 ---. LA:of
49 &MA 400 C -NM~rkf~ol . CN'0C.~ N..?U1'0n %a0'9x 40 00 0 ,0 r '0. a-CP a CCCCC C )C E-4.-
4NN.NNN NlIcCMN NeiNY N NwN N
LU C4P- P-41 P". v4 N N N NN NC~ C\N NV en on W on
21
aviation fleet rises 144% from 264,975 aircraft to 645,874
aircraft. T1roughout the forecast period, the number of multi-
engine aircraft active in the general aviation fleet increases
at an average annual rate of 2.9%. Between 1985 and the year
2020, the number of multiengine aircraft active in the general
aviation fleet increases 185% from 298,456 aircraft to 849,775
aircraft. The increase in multiengine aircraft activity is
attributed to the increasing utilization of general aviation by
private industry. Single-engine airzraft active in the general
aviation fleet rises at an average annual rate of 2.4%. By the
year 2020, active single-engine aircraft in the general aviation
* fleet increase 137% from 209,826 to 497,668 single-engine aircraft.
The increase in the utilization of single-engine aircraft reflects
an increase in instructional and recreational flying. The general
aviation fleet mix for the Rapid Growth Scenario is shown graphi-
cally in Figure R-1. (The complete tabulation for the general
aviation fleet is shown in Table B-2).
As noted previously in the Balanced Growth Scenario presentation,
an increase in demand for air transportation results in an increase
of FAA operational services. In the Rapid Growth Scenario, the
increasing demand for air transportation further intensifies
the utilization of FAA operational services. Total aircraft
operations at FAA towered airports is projected to increase at an
I1 average annual rate of 2.30 throughout the forecast period.
22 ACUMENICS
%Da
02 1 CD E
KU I
EE
S+
Nc I
n E
0 +0
I 0Y
0 4n " toI an
0 cocaI N.
LU M LULLI4ftINan Kn 4nV)
" ====ii
IL fn +0M
De 000
n >-)I ad nK *
eC*LL w.'L n E +
IL CL 4t SE I
- in ~o - in K
+30
4000I.-I
000 23 inI
Between 1985 and the year 2020, total aircraft operations at
airports with FAA towers are forecast to increase by 135% from
- 96 million to 226.3 million operations. Itinerant aircraft
operations at FAA towered airports rises at an average annual
rate of 2.5%. Between 1935 and the year 2020, itinerant aircraft
operations at FAA towered airports increase 149% from 96.249
-* million operations to 226.299 million aircraft operations.
The increasing utilization of general aviation services by industry
and the increasing demand for air carrier services by the general
public will account for the increasing itinerant aircraft operations
at FAA towered airports. Throughout the forecast period, local
aircraft operations at FAA towered airports, increases at an
average annual rate of 1.9%. By the year 2020, local aircraft
operations will increase 103% beyond the 1985 figure of 28.9
million to 58.7 million local aircraft operations. The steady
F increase in local aircraft operations at FAA towerd airports,
implies that the number of pilots undergoing flight training
will increase throughout the forecast period. The complete
tabulations for FAA towered workload measures are given in
Table B-3. Displayed graphically in Figure R-2, are the FAA
I towered airport workload measures for the Rapid Growth Scenario.
The growth in the number of aircraft handled by Air Route Traffic
Control Centers reflects increases in general aviation traffic
associated with increases in pilots capable of IFR flights. The
21 24ACUMENICS
I. III- iI ,-
I
- INoo ,I a-
- -I , o,,aa
I,- ,I...
*,,, I
OO04
Mi4
In
4D
I II
xr
IL IK
9 IxNoILj LL L IN
coo I-
I In
- + 41coon~I
AL CL9
P" Io Ilk
I i
0 InC, n4 v n DII-. t 41 F. LeCD 6
w ty 11 2
1 ai
5 0 4.-
o n.4nmnIm
me IN
46 4ft U) G
IKI +
'n cooI eyw = r- x II
I- I
L e =96 S
1. 49.- .aj
MPI I
0 Ix aKa
ofw coo In
A L Li II-
dc az 9 9It
a = a a6
I* number of aircraft handled by Air Route Traffic Control Centers
increases at an average annual rate of 2.6%. Between 1985 and
the year 2020, IFR aircraft handled by Air Route Traffic Control
Centers increases 156% from 43 million to 110.3 million aircraft.
* [ The complete tabulations of enroute work measures are given in
Table B-3. Displayed graphically in Figure R-3 are the enroute
measures for this scenario.
Demand in Communications Industry
As indicated by the GNP for this scenario, capital will be available
for technological development in the communications industry. All
I measures of aviation activity confirm increases in air traffic
L and in turn, the need for new communications technology to direct
air traffic.
Stagflation Scenario
I This Stagflation Scenario is built upon the theme of acute tension
I between society and technology in the U.S. Government policies
designed to retard technological development results in low
I. economic growth. Poor economic conditions, in turn, impedes
I further technological development.
Stagflation Economy
Throughout the forecast period, GNP and Disposable Personal Income
(both rise at an average annual rate of 1.51. Between 1985 and the
year 2020, GNP expressed in 1972 dollars increases 68% from
SI $1605.1 trillion to $2662.9 trillion. In the forecast period
27 ACUMENICS
• from 1985 to 2020, Disposable Personal Income also increases 68%
I from $1114.6 trillion to $1876.8 trillion. During the forecast
period, Civilian Employment experiences a low average annual
* growth rate of .48%. Between 1985 and the year 2020, Civilian
I Employment increases only by 19% from 103.7 million workers to
123 million workers. The tabulations of the economic variables
Lare given in Table S-1.
I The slu-ggish economic conditions portrayed by the variables
I depicted above, portend grave conseqences for the aviation and
communications industries. The slow increases in GNP imply
low business activity in the stagflation economy. Low business
activity, in turn, suggest a decrease in general aviation trans-
portation demanded by private industry. The minimal increases in
GNP also imply that capital will not be available to advance
technology in the aviation or communications industries. Due to
Isociety's negative attitude towards technological development,economic growth increases at a very low annual rate. The reduced
levels of employment coupled with minimal increases in Disposable
Personal Income suggest a low demand for air transportation by the
general public.
Aviation Industry
I The demand for general aviation transportation decreases as a
result of low business production. Evidence of this phenomena is
shown in the projected number of aircraft active in the general
I aviation fleet. The total number aircraft active in the general
1 28 ACUMENICS
I1
0I L
POI 4 w .4 N 0 r = %D No w~ m~ In b In C an sn CD m = in m m r- mC nC
ft.If ' &n 1 4 ~4 a: ; .4.4 .W 4 ; .4 W ----- 1: 4 1 0 0 C C --
kn o 4 N m sr 'aN- *f 4 O N on .12 In .0 P.e M 6 40 e N on %A@ e. ' D P~. e ago V. CD
o ft
I .49x"IYF %T &td~ln to cm I" C.4.4nr i Mn.0 o CP% -4N W)'T 9 'D . ,C) 44N Lei %
-. 0 in -------.---. 4 CC C C.4 -0 1" N""N NNN NN Ne e
I:29
f I aviation fleet increases at an average annual rate of .44%
throughout the forecast period. Between 1985 and 2020, the total
[ number of active aircraft in the general aviation fleet only
increases 18% from 248,542 to 292,195 aircraft. The demand for
multiengine aircraft by business entities accounts for most
Fof the growth of active aircraft in the general aviation fleet.
Throughout the forecast period, the number of multiengine air-
craft active in the general aviation fleet increases at an
.1 average annual rate of 1.7%. Between 1985 and the year 2020,
the number of multiengine aircraft, increases 86% from 254,538
I to 472,770 aircraft. The number of single-engine aircraft active
l in the general aviation fleet increases at an average annual
rate of .4%. By the year 2020, the number of single-engine air-
I craft active in the general aviation fleet increases 16% from
F197,622 aircraft to 229,459 aircraft. The decrease in the
utilization of single-engine aircraft is attributed to the effects
!i j of low Civilian Employment levels and low Disposable Personal
6 Income levels. As the consumer's purchasing power decreases, so
i ! will the demand for recreational and instructional flying performed
in single-engine aircraft. The general aviation fleet mix for
the Stagflation Scenario is shown graphically in Figure S-I.
[ (The complete tabulation for the general aviation fleet is shown
in Table B-2).. II
ACUMENICS30
a C,
-~ C, C *
P"
U I wU,
in + -44.I C.
CY
I aY
4n to IQ In
-C Malmo e E
-peLW n EQ
U. en EQ>->.1 en n
I I~tI.I- X- enK0%-ae 46n en
0000IV- Ij a 1 A-
IL IIAL4 II PM
+ do
- en go
t- an Ka- enn W1 N I 1P0 -
[ I The decrease in demand for air transportation is reflected in FAA
workload measures. Total aircraft operations at FAA towered air-
[- ports increase at an average annual rate of .89% throughout the
I forecast period. By the year 2020, total aircraft operations
at FAA towered airports increase 39% from 80 million aircraft
j operations in 1985 to 111 million operations.
Itinerant aircraft operations at FAA towered airports increase at
an average annual rate of .87% throughout the forecast period.
Between 1985 and the year 2020, itinerate aircraft operations
at FAA towered airports increase 38% from 53 million operations
to 74 million operations. The general public's inability to
afford aircarrier services because of the low level of Disposal
Personal Income accounts for the lcw annual increase in itinerant
I aircraft operations. Another factor that relates to the low
* levels of itinerant aircraft operations at FAA towered airports,
is the low level of business production associated with a stag-
flation economy. Throughout the forecast period, local aircraft
, operations performed at FAA towered airports increase at an average
I rate of .93%. By the year 2020, local aircraft operations at FAA
towered airports increase by 41% from 26 million operations in
1985 to 37 million. The low growth of local aircraft operations
I imply that fewer pilots will be trained during the forecast period.
This phenomena further suggest a decrease in air traffic due to
the decreases in the pilot population. The complete tabulations
I2 AU ACUMENICS
32
or~ s-IenII
I U
I'D-
41)
4y in
I-
I
* m4a 4N
at I In"i I
-a
00I > Ir.
to o M 14In IL InI4
+ -P
00
00
A6n
Ca~~L + aso a a a
I ~33 II
~4I
F:
for FAA towered airport workload measures are shown in Table B-3.
( I The measures displayed graphically in Figure S-2 are the FAA towered
[ airport workload measures for the Stagflation Scenario.
The growth rate in the number of aircraft handled by Air Route
Traffic Control Centers increases at an average annual rate of .91%.
I By the year 2020, the number of aircraft handled by the Air Route
q Traffic Control Centers increases 40% from 34.9 million air-
craft in 1985 to 48.8 million aircraft. The increasingly low levels
of operations at Air Route Traffic Control Centers results from
decreases in general aviation traffic and the pilot population
level. The complete tabulations of enroute center work measures
are given in Table B-3. The enroute measures for the Stagflation
Scenario are displayed graphically in Figure S-3.
Demand in Communications Industry
The reduced demand for air transportation by all segments of society
will effect the aviation industry's demand for communication
I technology. Throughout the forecast period, aircraft operations,
the pilot population and the general aviation fleet size experience
very minimal growth trends, thereby reducing the need for advanced
I communication technology for the aviation industry.
I
1 34ACUMENICS
34J
IV
I a~4
* I CC* = a1
1 a,
IN
I C',C
= acc
(n 0fU) + CD
ofa I CF
IIN
+ a,
'4= aL LLLf coC ' ,
I
I-
-. 1~I -. a
+ 4
CD LM LMI nC.M,~~~ -1 C l
= a35
IThePilot Composition
I Stagflation Scenario
The decrease in aviation activity due to the levels of the
* j economy effects the slow increase in pilot populations. Between
1995 and 2020, the total pilot population is expected to increase
at an average annual rate of 1.3% and by the year 2020, the total
I pilot population will increase only 40% from 1.01 million pilots
to 1.5 million pilots. The low levels of business activity
f account for the low levels of increase in private pilots who
pilot general aviation aircraft. Between 1995 and 2020, the
* number of private pilots increases at an average annual rate of
1.2% and by the year 2020, the number of private pilots will
increase 37% from 437,348 pilots to 599,215 pilots. The number
of transport pilots increases at an average annual rate of 2.2%
and by the year 2020, the number of transport pilots will increase
770 from 110,880 pilots to 195,948 pilots. The student pilot
J population will increase at an average annual rate of .97% and
by the year 2020, the student pilot population is expected to
I increase only 29% from 242,912 to 312,202 student pilots. Table S-2
Idisplays the pilot compositions for the Stagflation Scenario.
I3
I
S36 ACUMEN ICS
4
ad
w 00 L"W, n-a%
m= 444 N N " ii4a n na n r an in n m an aun o% uwI.0
0 f~.0 .0 n OV-I 0- , c@ N"M -r WO , 0
o- . w uO4 i.-a n u --a r Zw %an N -.Ia%go "' ,Ww"'- ,
to a, ta I - 0 4 0 -4 .4 -a . - -400 W%4C4 - --- W 4 a
an1-0 InFUc. r% vW .a - o=C 1,a0 0 u .
P.0 o a owP oi n-, u"- Da oP o-
I-1; ;1 Nar4Nn .0; ; .0-a0ea9aN .0 e; 0:
a- al C, a- a, - C, 'M = C-a~n U. C , C, C, I* 10OC. 0 I..- 4 vI
CU o -lC Y MC C y
A.37
.I
Balanced Growth Scenario
The constant.increases in the size of the general aviation fleet
and the air carrier fleet connotes an increase in the pilot
population. Between 1995 and 2020, the total pilot population
[ and the number of private pilots is expected to increase at an
average annual rate of 1.5%. By the year 2020, the total pilot
population will increase 49% from 1.16 million pilots to 1.75
[ million pilots and the number of private pilots will increase
46% from 471,738 to 687,113 pilots. The increase in private
4 pilots is associated with the increase in the size of the general
I aviation fleet. The increase in the number of transportation
pilots reflects the increase in the utilization of air carrier
CI service. Between 1995 and 2020, the number of transport pilots
* increases at an average annual rate of 2.5% and by the year 2020,
the number of transport pilots will increase 88% from 128,899
I pilots to 246,512 pilots. Between 1995 and 2020, the number of
student pilots increases at an average annual rate of 1.2% and
I by the year 2020, the number of student pilots will increase 35%
from 256,187 pilots to 349,847 pilots. The pilot composition
for the Balanced Growth Scenario is shown in Table B-6.
I4,IEl
4 3 ACUMEN ICS
. .. .. ..38
In
Iwo
fU
to 6 a-1 C0 -4 N0 'n w 9 0 r ~0- ~ 0 0
a. Nl CD "00 P. = r M N % D .6 C2, 1? .0 N O NI U.0 4 9%a,
% 0. -rNV %0" 00.O0-NUI..0N%
r. a- 0 0 0 0 II in 00 od .N N, NI V. 0 0 0 In r. D U,'r-j o 0 -a.0 . ca .4 N.UOed 4w w r .I&
N N0NN-a .. t '06.- tv CY 0 N NY .~ . . . W) ", NON wl .
4n .4 4 0 CDoka..0 0 0 soo00 0N 0 F .r.P 0 0 AD %Do. - so n cy w. vi cy r- 4 sowi N0.0%aW m @Ne 4 i
. . . . . . . . . . . . .0.. 0 ~ 0 U 6 . . . . .
Q ag =Nw ?% a0O U ,0%T'00 4 wl ' m = N r ,0WI'o0*cDcinU60 ~ ~ Ww wNg N ~ ? ,,,, ,0000 N
A c in 1,0 0 a- . YFTL NU.NO %0 V 0 0on NI tU,'D P00S- O-
39
I Rapid Growth Scenario
The increase in aviational activity gives rise to the increase in
[" the pilot population. The total pilot population increases at
an average annual rate of 2.1% between 1995 and 2020 and by the
Syear 2020, the total pilot population will increase 72% from 1.48million to 2.55 million pilots. The number of private pilots
I • increases at an average annual rate of 2% and the number of private
pilots is expected to increase 67% from 586,877 pilots to 978,777
*) pilots. The continuing demand for air carrier service is reflected
i in the increase of transport pilots. The number of transport
pilots increases at an average annual rate of 2.9% and by the year
2020, the number of transport pilots will increase 109% from 189,194
to 594,739 pilots. The number of student pilots increases at an
K 1. average annual rate of 1.7% and by 2020, the number of studentpilots is expected to increase 55% from 309,098 pilots to 480,470
I student pilots. The pilot composition for the Rapid Growth Scenario
is presented in Table R-2.
4
I
ACUMENICSK ___40
Ir I T- I- -
4
. soI p Y0 D= )N ftc Df n4 I 4f-I"4;
w' -a i - Ip -iw% nP ,- r ,v
o- w p - )ri ,P oc.cD. 4N"q n% .r w ;.
nCC-',- CC!- .--!!!- '
"-4
No %ir u, ono "4 NV) m. 4p, 4w -v) -4 N w i tn I-o N IA ac. IA E-4 I
D I-. a N4 . n - wl .0 N a. to 0 w 4 %0 IO so Ir CD ND 04 0 N 4D " N)
CL W;00... 'O C; N; 0: N ; N; 604a606060600. a; U .0. U. UP- @.0Iir 4i % D- nc n40C DC l0 )s ~ aC 1o* '0600 IA IA N0. "4 N .0600 4 oII N cy 0 o '6 U)
I .U. N =I IA CNI CO 60. I"4Co UV, N '0Y 1* Col CC,60Y Nl CV, IA"4 060.0 "O N
0 ~4"4NNNNNNNNIAAIAAIAAIIAIIA41A
I
J Air Carrier Fleet
Balanced Growt. Scenario
An increase in disposable personal income and civilian employment
[ suggest that more of the public will become involved in travelling.
Between 1985 and the year 2020, the air carrier fleet is expected
L to increase concurrently with the steady growth in the general
economy. The air carrier fleet increases at an average annual
rate of 1.1% between 1995 and 2020 and by the year 2020 the air
* j carrier fleet will increase 34% from 3338 aircraft to 4488
aircraft. (See Table B-5 for complete tabulation of air carrier
I fleet).
I Rapid Growth Scenario
1 The steady increase in the level of the general economy places
further demands on air carrier service. The effects of this demand
is evidenced in the number of aircraft that comprise the air
carrier fleet. Between 1995 and the year 2020, the air carrier
fleet increases at an average annual rate of 1.8% and by the4.
year 2020 the air carrier fleet will increase 58% from 4288
aircraft to 6759 aircraft. (Refer to Table B-5 for tabulation
Iof air carrier fleet for this scenario).
Stagflation Scenario
Between 1995 and the year 2020, the air carrier fleet decreases
I at an average annual rate of .6% and by the year 2020 the air
carrier fleet will decrease 13% from 2381 aircraft to 2063 aircraft.
ACUMENICS42
I
! i Factors influencing the decrease in demand for air carrier service
I include the ;ow levels of disposable income and civilian employment.
i j associated with a Stagflation economy. The economic variables
indicate that the public's desire to travel will be curtailed
.' because of inflationary prices and the low levels of increase
in consumer purchasing power. (Refer to Table B-5 for tabulations
of air carrier fleet).
4V I
w *I
6 t
:4
' I ACUME NICS
C.
C.4N C! C "!r !U
r ~~~~~~~~~~~ ~ ~ ~ ~ ~ ~ in- nr oc * % n&o- ,a 0% 1C 4C or
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44
Summary
Each scenario in this report has been constructed in an internally
consistent manner allowing for comparative analysis. In each
I scenario, society's differing attitudes toward technological
development are reflected in the economic variables projected
I-- for each scenario. A graph for each economic variable is shown
* in Figures C-i, C-2, and C-3. The charts depict the growth trend
corresponding to each alternative scenario. The same informationis supplied in tabular form in Tables C-I, C-2, and C-3. The
future for a society which chooses not to constrain technological
development is illustrated in the growth trends represented by
the Rapid Growth Scenario. On the contrary, national policy
which dictates the rate and direction of economic and technological
development, results in an economy with a low or a moderate
growth rate. This phenomena is illustrated in the growth trends
represented by the Balanced Growth Scenario and Stagflation
Scenario.
The level of industrial activity in each scenario directly affects
the demand for general aviation transportation. Graphs of the
number of component aircraft types that comprise the general4
aviation fleet are shown in Figures C-4, C-5, and C-6. The
growth rates in the utilization of the aircraft for each scenario
are also depicted in the figures. The rise in the level ofI
industrial activity associated with the Rapid Growth Scenario
ACUMENICS
45
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accounts for the increased utilization of the general aviation
fleet for that scenario. As a result of the low levels of
industrial activity associated with the Stagflation Scenario, the
graphs exhibit a low growth rate for the utilization of the
[general aviation fleet in that scenario.It has been demonstrated that FAA workload measures reflect growth
in the aviation activity. A graph for each aircraft operation
performed by the FAA at the FAA towered airports is shown in
[ r Figures C-7, C-8, C-9. The charts depict growth trends corresponding
to each scenario. As indicated previously, the demand for air
:1 transportation by industry and the general public affect the level
of aircraft operations at FAA towered airports. Specifically,
local aircraft operations also indicate the number of pilots
I undergoing flight instruction. The effects of a rapidly expanding
economy versus a moderate and low growth economy is reflected in
the graph for each type of aircraft operations at FAA towered
I aircraft operation airports.
The level of operations at Air Route Traffic Control Centers is
a function of the level of general aviation traffic, the type of
I aircraft in the general aviation fleet, and the number of pilots
capable of conducting IFR flights. A graph for each enroute
center workload measure is shown in Figures C-1O, C-Il, and C-12.
The number of aircraft operations generated by each scenario are
also displayed graphically. An increase in business activity,
ACUMENICSf 55
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which in turn creates a demand for more general aviation trans-
portation, is associated with the Rapid Growth and Balanced
Growth Scenarios. The increased number of operations at Air
Route Traffic Control Centers reflects the phenomena associated
I with the scenarios discussed above. As illustrated in Figures
[C-1O, C-I, and C-12, the curves representing the Rapid and
q " Balanced Growth Scenario assume higher values in comparison to
I the Stagflation Scenario Curve.
I,I
II
I.
I
,IACUMENICS
62
APPENDIX
m FORECAST METHOD
iThe purpose of this section is to describe the method employedto forecast levels of aviation activity. As noted in previous
sections, the purpose of this project is to estimate the nature
and, to the extent possible, the magnitude of primary effects
emanating from the introduction of new aviation communication
[ technology.
The adoption rate of new technology will be in part influenced
by the activity within an industry. In addition, the adoption of
new technology may influence the nature and magnitude of industrial
activity. As such, identification and estimation of future values
SI for typical industry activity measures are necessary to the assess-
* [ ment of technological effects.
[ The aviation industry measures included in the scenario fore-
cast derive from FAA Aviation Forecast Fiscal Years 1981-1992. 1
In particular, parameters that describe aggregate activity levels
for aircarriers and general aviation must be considered. In addi-
I tion, measures that reflect the service provided to the industry
by the FAA must also be included. As such, the measures of import
for this study included:
IlOffice of Aviatir-n Policy (AVA), "FAA Aviation Forecasts
Fiscal Years 1981-1992", U.S. Department of Transportation,Federal Aviation Administration, Washington, D.C. September 1980.
IACUMENICS
A-1
I.
a) total operations
b) lc7cal operations
C) itinerant operations
d) general aviation fleet size and composition
e) aircarrier fleet size and composition
f) FAA workload measures
1) aircraft handles
I 2) IFR departures
" 3) overs
4) flight plans filed
1 5) aircraft contacts.
In addition to the measures identified above other variables of
r import included;
a) controller, flight service, and maintenanceI personnel;
b) FAA investment in traffic control and communications[ investment.
The relationship of each of the preceding factors to the assess-
I ment effort will be described in succeeding sections of the text.
[ I The purpose of this section is to describe the general approach
used to estimate future values for each of the variables.
The present effort required examination of the technology
[induced impacts under three socio-economic scenarios: balanced
growth, rapid growth and stagflation. The analytic differences
among scenarios are measured in terms of economic variables. The
1IA-2 ACUMEN ICS
.1
r economic variables of import for this project are those employed
in the "FAA Aviation Forecast" i.e., Disposable Personal Income[(DPI), Gross National Product (GNP) and Employment (Employ).
2
[ A review of the FAA Forecast indicated the official estimates
represented the balanced growth scenario. The upper and lower
[bound FAA estimates were deemed equivalent to the rapid growth andstagflation scenarios. 3 The economic variables developed used in
the scenarios are shown in the scenario section of the report.
The general method used to forecast aviation activity and
[ FAA workload measures included:
1) examine the official FAA forecast
2) develop linear approximations of activity andworkload measures
3) develop time series estimates of activity andworkload measures
4) forecast aviation and workload measures basedIupon time series estimates.I The official forecast4 is based upon numerous analytic models.
The estimates provided by the analytic models are reviewed by
appropriate agency personnel. The analytic estimates are modified
based upon the expert judgement of the FAA personnel. As such,
~ 2 1bid, page 61.
SI 3 1bid, AVP, pages 28-35.
41bid, AVP.
1I A- ACUMEN ICS
orI
C it was decided that forecast for this project would derive from
analog models, The analog models employ the economic assumptions
I embodied in the FAA forecast as well as the official FAA estimates.
r The use of such analogs allow one to incorporate the expert judgement
of agency personnel embodied in the official estimates. See
V Table 1.
[ Histograms for several of the official estimates (e.g.
operations, pilots, aircraft) were developed by the project team.
A review of the histograms indicated that on surface the time
series relationships were linear. However, further examination
suggested that the historic data as well as the latter portion
j I of the official forecast were non-linear. The most likely analog
form for forecasting was the logistic curve.
An illustration of the difference between a linear and
[ logistic curve approximation is shown in Figure 1. The
general form of a linear approximation is:
Y = At + B
where Y = dependent forecast variable
t = independent time variable
4 I A = slope of the curve
B = intercept
The logistic curve is defined as
'y A
(1 + e(B + Ct))
A-4 ACUMENICS
I where Y = dependent forecast variable
t7= independent time variable, and
A, B, C are empirically determined coefficients.
[ As indicated in Figure 1 the linear and logistic forms may be
congruent for some portion of the forecast period. However, the
[logistic form yields more conservative estimates than the linearform for extended time periods. As such, the logistic function
[ tends to conform with the caution imported by expert judgement.
As noted above the development of forecast equations was
a three step process. The first step was the development of
linear approximations for aviation activity and agency workload
measures. In as much as the differences among scenarios are
measured in terms of economic variables, the initial linear
I approximations were of the form
aviation activity orworkload measure = function (economic variables)
Linear regression equations for the official baseline forecast
data were developed using a stepwise regression program. The
linear approximations were obtained for the appropriate historic
data period to fiscal 1992. The relationships developed using the
I stepwise procedure and the attendant statistics are shown in
Tables 3-19. Table 20 defines the terms used throughout this
section. Based upon the equations developed in this step and
the scenario economic variables, estimates were prepared of future
aviation activity and workload measure. That is, the values for
A' ] A-5ACUMEN ICS
Table A-i
r- LINEAR APPROXIMATIONS OF OFFICIAL BASELINE FORECAST 1970-1972r [ A. Number of Aircraft
TOTGA = -319.5067 + 5.5072 Employ
(t) (-17.94) (31.49) R2 = .984
U SEGA = -226.2078 + 4.1067 Employ[ (t) (-18.00) (33.27) R2 = .986
MEGA = -30.4632 + .5690 EmployI (t) (-10.32) (19.63) R2 = .960
B. Operations
TOPS = - 7o4334 + .0549 GNP(t) (-2.57) (28.79) R 2 = .975
LOPS = 5.4211 + .0133 GNP
(t) (5.96) (22.12) R2 = .959
I ITOPS = -12.8037 + .0416 GNP(t) (-6.06) (29.85) R2 = .977
C. FAA Air Route Traffic Control Centers
I TAIRHAND = -10.3391 + .0283 GNP
(t) (-8.12) (33.64) R2 = .982
TOVERS = - 3.8307 + .1072 Employ(-9.30) (25.43) R2 = .968
IFRDEP = - 5.0314 + .0171 DPI(-9.41) (33.56) R2 = .982
I*iA-
Table A-1- (Continued)
F [D. Flight Service Station (FSS)
r PLTBRF = -10.1438 + .0297 DPI(t) (-15.42) (47.56) R2 - .991
TOTFSS = -25.3077 + .0660 GNPF (-11.75) (46.41) R2 .990
TOTFLTPL = -17.0895 + .2879 Employ(-14.93) (24.60) R- = .966
E. Pilots
TOTPLT = 68.0713 + .7568 DPI(t) (3.24) (40.06) R2 = .990
I PRIVPLT = 64.3252 + .1951 GNP
(t) (6.80) (32.96) R2 = .985
TRANPLT = -85.2893 + .1024 GNP[ (t) (-16.05) (30.84) R2 = .983
STUPLT = 82.4102 + .1203 DPI(t) (10.80) (17.51) R2 = .950
II A-8
Table A- 2
.1 LIST OF FOPECASP EUATIONS
NAME BG RG SF
Total Operations Logistic LIN Logistic
Local Operations LIN LIN LIN
" Itinerant Operations Logistic LIN Logistic
Total Active GA Aircraft Logistic Logistic Logisticr Single Engine GA Aircraft Logistic Logistic Logistic
Mitiple Engine GA Aircraft Logistic Logistic LIN
[ Enroute Aircraft Handles Logistic Logistic LIN
IFR Departures Logistic LIN Logistic
Total Overs Logistic LIN Logistic
[ Flight Services LIN LIN LIN
Flight Plans Filed LIN LIN LIN
Pilot Briefing Logistic LIN LIN
Total Pilots LIN LIN LN
* Student Pilots LIN LIN LIN
Transport Pilot LIN LIN LIN
Private Pilot LIN LIN LIN
[ Linear Approximations 1970-1992
Number of Aircraft LIN LIN LIN
Operations LIN LIN LIN
j FAA Air Route Traffic Control Centers LIN LIN LIN
Flight Service Station LIN LIN LIN
[ Pilots LIN LIN LIN
Controller Staffing
Center Controllers LIN LIN LIN
Terminal LIN LIN LIN
Total Aircraft LIN LIN LIN
I Dployment Logistic
Note: BG = Balanced GrowthI1 RG = Rapid GrowthSF = Stagflation
A-9
C r the economic variables for the stagflation and rapid growth scenarios
were substituted in the equations to calculate appropriate values
I [ for activity and workload measures under each social scheme. The
r forecast for aviation activity and workload measures for each
scenario is presented in Volume 2.
In summary, the effort under this step provided estimates
r of aviation activity and workload fiscal measures for each scenario
for the period 1981 to 1992. The estimates of independent variables
I obtained in the preceding element were used to develop the long
range time series forecast equations for each scenario. It was
assumed initially that all long range forecast equations would be
I [ logistic in form. Time series logistic equations were developed
for aviation activity measures under each scenario using a non-
linear regression program.5 In the event a logistic form could
not be developed for a specific variable, linear time series were
constructed.
The variables forecast and attendant form of the equation
are shown in Table 2. The specific forecast equations for each
variable under each scenario, as well as the appropriate forms of
[ the equations, and the statistics are shown in Tables 3 to 18. The4
equations for controller staffing are shown in Table 19.
5 SAS/ETS User's Guide, Economitric and Time Series Library,1980 Edition. (SAS Institute, Inc. Box 8000, Cary, North
AI ACUJMEN ICS
I A- 10
4[r
I __ ___ ___ ____ ___ ___ ____ ___ ___ ____ ___ ___ ____ _ _ ___ ____ __C%3_
CDO
4 I-
C.' 00LO vI S -4
-4 _ _ _
1 00
I C LM
A- 1
Si L Si
Er 0
IETr _ _ _ _ _ _ _
El 0)
v-4)
0Ii _o
I _____________ ___________C)
4Lt1 29C
CC
II
'I A-22
~cr Table A-l9
!CONTROLLER STAFFING EQUATIONS
S A. Center Controllers
(1) CENT = -5215.64 + 6.3305TAC(t) (-7.09) (24.43) R 2 = .973
(2) TERM = 5204.604 + 34.790 TOTGA
(t) (6.67) (8.19) R2 = .9437
B. Total Air Carrier Aircraft
1TAC = 1216.9761 + 1.4659 DPI(t) (14.05) (18.80) R2 = .957
C. Employment
I Employ = A R2 = .9944
[1 + e(B + Ct)]
A = .140.17 (t = 23.00)B -. 204435 (t =-2.32)
C = -. 0580251 (t =-9.78)
L
,I
I
! 1 A-27
AD-Ai25 357 SOCIOECONOMIC SCENARIOS VOLUME 11(U) ACUMENICS RESEARCH 2/2AND TECHNOLOGY INC BETHESDA MD 26 FEB SIFAA-PO-S-ii-YOL-2 DOT-FR78WRI-932
UNCLASSIFIED *F/G 17/2.1£ NI
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I .Table A-20
DEFINITION OF TERMS
r TERM DEFINITION
I EMPLOY Employment
TOTGA Active total general aircraftSEGA Single engine general aircraftMEGA Multiple engine general aircraft
TOPS °Total operationsLOPS Local operationsITOPS Itinerant operations
GNP Gross National ProductDPI Disposable Personal Income
TAIRHAND Total enroute air handlesTOVERS Total oversIFRDEP IFR departures
PLTBRF Pilot briefingTOTFSS Flight servicesTOTFLTPL Flight plans filed
I TOTPLT Total pilotsPRIUPLT Private pilotsTRANPLT Transport pilotsSTUPLT Student pilotsCENT Center staffTAC Tactical Air CommandTERM Terminal staffFSS Flight service center
41!
01A-2P