NBSIR 81-2250

Estimating Area Cost Factors for

Military Construction Projects:

A Computerized Approach

Robert E. Chapman

Bruce E. Thompson

Building Economics and Regulatory

Technology Division

Center for Building Technology

National Engineering Laboratory

U.S. Department of Commerce

National Bureau of Standards

Washington, DC 20234

May 1981

. U56 U S. DEPARTMENT OF COMMERCE

81-2250

1981

NATIONAL BUREAU OF STANDARDS

NBSIR 81-2250

ESTIMATING AREA COST FACTORS FOR

MILITARY CONSTRUCTION PROJECTS:

A COMPUTERIZED APPROACH

ATIOMAL BUBBAU or standards

UBEART

JUN 1 5 1981

r <

/ r

Robert E. Chapman

Bruce E. Thompson

Building Economics and Regulatory

Technology Division

Center for Building Technology

National Engineering Laboratory

U S. Department of Commerce

National Bureau of Standards

Washington, DC 20234

Sponsored by

Directorate of Engineering and Services,

Department of the Air Force

Washington, DC 20330

Naval Facilities Engineering Command,

Department of the Navy

Washington, DC 20390

Office of Chief of Engineers,

U.S. Army

Washington, DC 20314

May 1981

U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director
^ ^

t^oiifiynO *

If

€»:5lr«t'T5ma5 )^ti?lfiomtvRa©<3 S i)

'"’ V|kCS:0$ DO'

yrt

** 9?J'«3 ilA oHt to rij^fia^Q''

oefe^foa <notoma«gw

.hM;&mfnoO odboootgfia

Vyet^ to inofj^KfiqtiO

I

-, f' feOi ;Oa in018A.f)«rW 4 I

• ':‘; '""ll"":: -’ "^:.i I-.^

.

r

9*"' ., t Hv-". -

' ,: P

V ‘i', -

' A- »

•' %•'%.’ -S:.. "S- ::->?'vyv

.' V '-; • -’*' " * -'"' k>^"' -< "••. j^ f

,'" ' „

-.1... ..;w: . .

, _

flu ,iif1

.'

'S' J '.If'.

..T V

" <

‘ #

,«oiibto3^ifoatftM 3afl3Mlii/*iOC) TV3MTf?A«»3q .2,4

<)id«nCi }«#mJ ,^d€in/vOV)AT^ iuMOfTA^ , 'M*

li'V.SW’X :. -
PREFACE

The computerized procedure presented In this report was developed under the

sponsorship of the Department of Defense by the Applied Economics Group of the

Center for Building Technology, National Engineering Laboratory, National

Bureau of Standards. This procedure is an outgrowth of a cooperative project

between the Center for Building Technology and Michigan State University to

develop an economically sound method for estimating area cost factors for

military construction projects. Accurate estimates of area cost factors are of

crucial importance to the military since these factors are used as deflators to

adjust for regional cost differentials among planned projects. Past efforts in

this area have focused on the use of cost indices based primarily on private

market construction activities. Since the type and nature of construction

projects carried out in the private sector often deviates from those carried

out by the military, the use of cost indices based on private sector activities

may complicate the process of planning and implementing a workable budget for

future military construction projects.

iii
ABSTRACT

This report describes a computerized procedure for estimating area cost factors

for military construction projects. The empirical basis for this procedure

rests upon the results of an econometric analysis of over 500 military con- struction projects. Technical and empirical evidence from a wide variety of

published sources were also used to provide supplemental information on wage

rates, material prices and the level of construction activities in the localities where the projects were undertaken. This report is Intended to serve as a user manual for military personnel concerned with the problem of periodically

updating the area cost factors for each service’s installations. A series of

technical appendices are also included which describe the theoretical underpinnings of the econometric models which constitute the core of the computerized

procedure as well as provide samples of computer output and a complete listing

of the computer program.

Key words: Applied economics; construction; cost; estimation; location factors

model building; statistical analysis.

Iv
TABLE OF CONTENTS

Page

PREFACE Hi

ABSTRACT Iv

LIST OF TABLES vl

LIST OF FIGURES vl

LIST OF EXHIBITS vl

SI CONVERSION UNITS vll

1. INTRODUCTION 1 1.1 Purpose 1 1.2 Scope and Approach 2

2. DESCRIPTION OF THE COMPUTER PROGRAM 3

2.1 Method of Approach 3

2.2 Description of Computer Algorithm 7 2.2.1 Data Requirements 7 2.2.2 Applying the Computerized Procedure 11

3. SUMMARY 23

REFERENCES 24

APPENDIX A Theoretical and Empirical Issues in the Formulation of an Area Cost Factor Model 25

APPENDIX B Sample Computer Run 33

APPENDIX C Listing of the Computer Program 64

V
LIST OF TABLES

Page

2.1 Labor Skills for Which Wage Rates Are Required and Weights

Applicable to Each Labor Skill 9

2.2 Material Price Specifications Required for Each Installation 10

2.3 Variables Used in the Computer Program 14

2.4 Illustration of Error in Input Data 17

2.5 Assembling the Input Deck: Data Card Format 20

2.6 Sample Cities Used in the Example 20

2.7 Assembling the Input Deck: Sample Input Stream 21

2.8 Estimates of Area Cost Factors for Sample Cities 21

B.l Thirty Cities for Which Material Price Data are Reported and Their

Corresponding CITY Numbers 36

B.2 Major Cities and Their Corresponding CITY Numbers 37

B.3 Assignment of Military Bases to Cities 39

B.4 Estimates of Area Cost Factors for Selected Military Bases 46

LIST OF FIGURES

2.1 Size/Unit Cost Adjustment Chart 6

2.2 Flowchart for Area Cost Factor Computer Program 13

A. l Graphical Representation of Technical and Allocative Inefficiency

in Producing a Given Level of Output 30

LIST OF EXHIBITS

B. l Input Stream for the Sample Computer Run 53

B.2 Wage Index Printback for the Sample Computer Run 58

B.3 Estimated Area Cost Factors Based on the Sample Input Stream 61

vi
Most Common SI Units and their Equivalent Values In Customary Units

QUANTITY INTERNAITONAL (SI) UNIT U.S. CUSTOMARY UNIT APPROXIMATE CONVERSION

LENGTH meter (m) foot (ft) 1 m 3.2808 ft millimeter (mm) Inch (In) 1 mm 0.039A In

AREA square meter (m ) square yard (yd^) 1 “2

1 m^

- 1.1960 square foot (ft^) 10.764 f square millimeter (mm^) square Inch (In^) 1 mm^ * 1.5500 X 10"3in2

VOLUME cubic meter (m^) cubic yard (yd^) 1 m3 1.3080 cubic foot (ft^) 1 - 25.315 ft3 cubic millimeter (mm^) cubic Inch (In^) 1 * 61.024 X 10“^ln3

CAPACITY liter (L) gallon (gal) 1 L = 0.2642 gal milliliter (mL) fluid ounce (ft oz) 1 mL “ 0.0338 fl oz

VELOCITY, SPEED meter per second (m/s) kilometer per hour (km/h) foot per second (ft/s or f.p.s.) mile per hour (mlle/h or m.p.h.)1 m/s

1 km/h 3.28080.6214

ft/s mlle/h

ACCELERATION meter per second squared (m/s^) foot per second squared (ft/s^) 1 m/s^ =. 3.2808 ft/s3

MASS metric ton (t) [1000 kg] short ton [2000 lb] 1 t S 1.1023 ton kilogram (kg) pound (lb) 1 kg = 2.2046 lb gram (g) ounce (oz) 1 g

= 0.0353 OZ

DENSITY metric ton per cubic meter (t/m^) ton per cubic yard (ton/yd^) 1 t/m3 =r 0,8428 ton/yd3

kilogram per cubic meter (kg/m'^) pound per cubic foot (Ib/ft^) 1 kg/m-^ - 0.0624 lb/ft3

FORCE kllonewton (kN) ton-force (tonf) 1 kN 0.1124 tonf kip [1000 Ibf] 1 kN - 0.2248 kip

newton (N) pound-force (Ibf) 1 N 0.2248 Ibf

MOMENT OF FORCE, TORQUE kllonewton meter (kN*m) newton meter (N*m) ton-force foot (tonf'ft)

pound-force Inch (Ibf* In)

1 kN*m

1 N*m - 0.36888.8508

tonf *f

Ibf* In

PRESSURE, STRESS megapascal (MPa) ton-force per square Inch (tonf/ln^) ton-force per square foot (tonf/ft^)

1 MPa

1 MPa

- 0.0725

10.443 tonf/ln^

tonf/f t^ kllopascal (kPa) pound-force per square Inch (Ibf/ln^) 1 kPa - 0.1450 lbf/ln2

pound-force per square foot (Ibf/ft^) 1 kPa * 20.885 blf/ft^

WORK. ENERGY, QUANTITY OF HEATmega joule (MJ) kilojoule (kJ) kllowatthour (kWh) British thermal unit (Btu)

1 MJ

1 kJ

- 0,2778

0.9478

kWh Btu

joule (J) foot pound-force (ft*lbf) 1 J 0.7376 fflbf

POWER, HEAT FLOW

RATE kilowatt (kW) watt (W) horsepower (hp) British thermal unit per hour (Btu/h)

1 kW

1 W

- 1.3410

3.4121

hp

Btu/h

foot pound-force per second (ft*lbf/s) 1 W 0.7376 ft*lbf/s

COEFFICIENT OF HEAT watt per square meter kelvln Btu per square foot hour degree 1 W/m^*K 0.1761 Btu/ft^’h

TRANSFER [U- value] (W/m^*K) [-(W/m2»"C)] Fahrenheit (Btu/f t^*h**F)

THERMAL CONDUCTIVITY watt per meter kelvln (W/m*K) Btu per square foot degree Fahrenheit

(Btu/ft^'^F)

1 W/m*K > 0.5778 Btu/ft^*"]

[k-value] [-(W/m*"C)]

NOTES: (1) The above conversion factors are shown to three or four places of decimals*

(2) Unpreflxed SI units are underlined. (The kilogram, although prefixed. Is an SI base

unit)

REFERENCES: NBS Guidelines for the Use of the Metric System, LC1056, Revised August 1977; The Metric System of Measurement, Federal Register Notice of October 26, 1977, LC 1078, Revised November 1977; NBS Special Publication 330, "The International System of Units (SI),” 1977 Edition; NBS Technical NOte 938, "Recommended Practice for the use of Metric (SI) Units In Building Design and Construction,” Revised edition June 1977; ASTM Standard E621-78, "Standard Practice for the Use of Metric (SI) Units In Building Design and Construction,” (based on NBS TN 938), March 1978; ANSI Z210 .1-1976, "American National Standard for Metric Practice;” also Issued as ASTM E380-76^, or IEEE Std. 268-1976.

vll
35

\-r>

miwsmp rssLm}jaa^^

St MIS.i • • i ^

ml *«5»0 -* •• <’> ^

'

. i,. L Vlr.< "

*fcf< •*«<. f !*» l4&r.

(Uli) '<<?*«<

’,«tf

iV^ iiU;i[, *}S|f

'

'T'^,

:..:wm

SMtkadtl—

, i.wm.w;,. ,,....*,,1* _

!

! i*W> ssiWkl'U* (W»t»«

' ' '

' "WF:

«*, om7i

i|#r.« •* * a »# •

Ah^#. If

I4lf SMlt4 •

mm n #««> • *

f A • a\jt Mtf.t *

iftaanr -

i)

- » ‘a\l* -

•os Ctotift tsoc.? -

»p trtb-Ji » Ku»^4«'

SiVtft -

t

j /a

^\» t ‘

»l( t

...

I

'iS*

** '*’‘

s* <e«

• fc> , . ^

;F rr'. 1 ..; -^ '‘ ^r -]7.^3!j

{a*«»t ‘*a «Vj- >)

- - -

., ,/ — iteilka'.,

i''-

Bfi,; i,

" •?«»». *

, I.*'**®; liiF

t&Skm

#tej

ba'simv* 'SBWa^ ""H

V. tmttd l»'

ito) W3»mm a

l yj iisoui ’^!>«'''<r' I-.

'' ' ' "(5|i!pPBMIH|HB' "’'''*•* - , "jv-'* tr'

"

-lACil, *^S-»

tool • vU -

wfl mciO »

lU I ?u»

Hk:

\4-

Sl^tM> *fc«.0 - Bl'lfU M<1»«4I •

' afjiiff

' •d 1'

'stVtii*? tPhUl •

CvjAtdi - hi\m y «"• wc •

' atW 1 »tM f SJ i fl"

dSM 1

..oti* -

“ idr*»i - 1 1

, fd 4*^-1 - 4U4I tJaa.e - (TTtt^ -

«ii 4 ¥ 1 V 1

X,

d***ilViid IttMo - ; fSiktf'y

A 4

* '“'•"

..f. «W*5*^«**'

' ,(Mt wpil

tioi*5dO ' TiL

'

^wo vt <w) »*ivai»ajrii'

‘ 'IV "‘"VT^jf" J.

IMJWJ'

t«|tfH''sl#lto'''Mt*Ni<»i' rfai'jasinr (Wi* jV) toot

|^iAin4l> s»%»'< »*5i Jtad ^

CaVlil'stJiWsaa i»a ><»•'

sX*(<<««srtat

IE*

f: «lo

.atoott

(«MT SsMMiMd

t«) iisz

W''-

f

-±j-.: 'i . • 9T

\»< I* mm »l ,Mw4I*^ wif) (nm^ •mUm ,- ^ ‘m idtau

fit - '

,\\ai ,« lartotaO.lo' mrHaVi sos>i>»n ' t»iwHii0t

'

< * ^

- *^ *^ * kAAMAfl .\nf dIA .i=!^

i vj-oifTTirri

i'saw

• . 4 «it4(

t.s

jXWf 'saiCiiavoiJ taatvst' ,»tCI 3A

ml *jW'(uj' la «««•» «i<* lot' {T\tJ flwl. naifttm .,i

.’,l*o.|tsh‘*« 'x«5 'iil«^,lMai(ll .«ii(J)l'i«»4, _^tta

«• WMt 4il<y.j,'’.IW4tS:h a

);v :

• i

* V

4ilMl>o44l(lf .liW( Jilt 004^

''• '^T' V'*
Most Common SI Units and their Equivalent Values In Customary Units

QUANTITY INTERNAITONAL (SI) UNIT U.S. CUSTOMARY UNIT APPROXIMATE CONVERSION

LENGTH meter (m) foot (ft) 1 m 3.2808 ft millimeter (mm) Inch (In) 1 mm 0.0394 in

AREA

p square meter (m ) square yard (yd^) 1 m2

1 m2

- 1.1960 square foot (ft^) • 10.764 ft2 square millimeter (mm^) square Inch (In^) 1 mm2 1.5500 X 10"3in2

VOLUME p cubic meter (m ) cubic yard (yd^) 1 m3 1.3080 cubic foot (ft^) 1 25.315 ft3 cubic millimeter (mm^) cubic Inch (In^) 1 mm3 61.024 X 10”^ln3

CAPACITY liter (L) gallon (gal) 1 L - 0.2642 gal milliliter (mL) fluid ounce (ft oz) 1 mL 0.0338 fl oz

VELOCITY. SPEED meter per second (m/s) kilometer per hour (km/h) foot per second (ft/s or f.p.s.) mile per hour (mlle/h or m.p.h.)1 m/s

1 km/h - 3.2808 0.6214

ft/s mile/h

ACCELERATION meter per second squared (m/s^) foot per second squared (ft/s^) 1 m/s2 z. 3.2808 ftls^

MASS metric ton (t) [1000 kg) short ton [2000 lb] 1 t a 1.1023 ton kilogram (kg) pound (lb) 1 kg = 2.2046 lb gram (g) ounce (oz) 1 8

= 0.0353 OZ

DENSITY metric ton per cubic meter (t/m^)

kilogram per cubic meter (kg/m"*) ton per cubic yard (ton/yd^) 1 t/m3 0.8428 ton/yd3pound per cubic foot (Ib/ff') 1 kg/m3 - 0.0624 lb/ft3

FORCE kllonewton (kN) ton-force (tonf) 1 kN a 0.1124 tonf kip [1000 Ibf) 1 kN - 0.2248 kip

newton (N) pound-force (Ibf) 1 N * 0.2248 Ibf

MOMENT OF FORCE. TORQUE kllonewton meter (kll*m) newton meter (N*m) ton-force foot (tonf'ft)

pound-force Inch (lbf*ln)

1 kN’m

1 N*m

- 0.3688

8.8508

tonf *f

Ibf ‘In

PRESSURE, STRESS megapascal (MPa)

p ton-force per square Inch (tonf/ln^) ton-force per square foot (tonf/ft^)

1 MPa

1 MPa

- 0.0725

10.443 tonf/ln^

tonf/f kllopascal (kPa) pound-force per square Inch (Ibf/ln^) 1 kPa - 0.1450 lbf/ln2

pound-force per square foot (Ibf/ft^) 1 kPa 20.885 blf/ft2

WORK, ENERGY. QUANTITY OF HEATmegajoule (MJ) kilojoule (kJ) kllowatthour (kWh) British thermal unit (Btu)

1 MJ

1 kJ

- 0.2778

0.9478

kWh

Btu

joule (J) foot pound-force (ft'lbf) 1 J 0.7376 fflbf

POWER, HEAT FLOW

RATE kilowatt (kW) watt (W) horsepower (hp) British thermal unit per hour (Btu/h)

1 kW

1 W

- 1.3410

3.4121

hpBtu/h

foot pound-force per second (ft*lbf/s) 1 W ** 0.7376 fflbf/s

COEFFICIENT OF HEAT watt per square meter kelvln Btu per square foot hour degree 1 W/m2*K 0.1761 Btu/f t2*h TRANSFER (U-valuel (W/m^*K) i-(W/m2*°C)] Fahrenheit (Btu/f t^*h*“F)

THERMAL CONDUCTIVITY watt per meter kelvln (W/m*K) Btu per square foot degree Fahrenheit

(Btu/ft2*’F)

1 W/m‘K . 0.5778 Btu/ft2*‘’l [k-value] [-(W/m*”C)]

NOTES: (1) The above conversion factors are shown to three or four places of decimals.

(2) Unpreflxed SI units are underlined. (The kilogram, although prefixed. Is an SI base unit)

REFERENCES: NBS Guidelines for the Use of the Metric System, LC1056, Revised August 1977; The Metric System of Measurement, Federal Register Notice of October 26, 1977,

I.C 1078, Revised November 1977; NBS Special Publication 330, "The International System of Units (SI),” 1977 Edition; NBS Technical NOte 938, "Recommended Practice for the use of Metric (SI) Units In Building Design and Construction,” Revised edition June 1977; ASTM Standard E621-78, "Standard Practice for the Use of Metric (SI) Units In Building Design and Construction,” (based on NBS TN 938), March 1978; ANSI Z210 .1-1976, "American National Standard for Metric Practice;” also Issued as ASTM E380-76'^, or IEEE Std. 268-1976.

vli
«

r.l»4i" •xJMW n itmmeO

mi mtmi»9 itmtrnflmpt

f ij»i ^

•v.f t'l i#»«}6 ‘ it m i Hr 9^t.i - *• t H i Kml

•

^ H* *'f:« - H 1

fAH *

«ti n -

4 i J» f

^Vrt «•*;.« - j\*um • <IVp< 4

*•’4? Irtw.c •

'** W 1

mml ttkI.J • 3 1 II • yci 1 «» •

PJP 8 1 ,^v I

' •'\ifii 4

U#:y fc{U.#» MU 1 y>8 •»>3i.’0 - ht i

)aI AA4r^« • • 1

fi'.tAOi ^MACjiO - •’MjI.

«!• ll-t * *« 1

»«( 1

(y'WI t iel' ^ilt t/I8U9 «M 1 ‘tiVUrf « a4| 1

'iui i^m.<i tM 4

oiif iu«».o - Ml *91 #«’;.# • W 1 t J

AdfrllC*! - kill 4 iSaM • « 1 «\Hrr> }» ATJ'XvO * ,i M 1 ITvi. gr**«4A.*»r JAti.o - 1

1«**31U»9» - H*mS6 I

ILW.iJ^«iaEJbS

(KfJ 'wf

imn dm h. <«4 Wi

1^) N#t %»«>.

x\

tTX*} J4|»j, (***)w

kn

(JhHJ H»y sf«tir9

'(tool'

<*» J’fcj' V*«w»b

'^.fltil ,-iA «i\jt) twMM t«r*]! im

l,4.<fim id TOfld *»^

>4r»ii*iiIMf liwiiMid **<i *•»*

3as?iL’’2fe

»nsu4if>y'

,(,> ifixll

ti».t) (mmw

t- (*»}' AiStOoM OH'

iwoWd ^•>)N^

[t> ,i*3»»

M (»)r

wifl M>.t <^-») vHmm «<<«>» 3i«wi

le-ii' 9j4«», i*n Wwyo '•mm .9^.

.p !>^l *|4j4 (Mi)

a**9*

( lU,^ W: <*#.«*

(^Ai\llMka) ll3«l V<k«Mt 91MI (“i^lvliwusj ,n»dl ^-'kuW Kd •W!I*4*)'»

ia>f^ iiTTrt-tortMuw

j lliik l*irt»rfi

Cffi) 1ll»4

tiki **v1

'll

fmVff UxmniHipm

(fW rtut**m>4

^''' ' ®

(U»l

(W> *rirt]L»i*4

: (O'lLat

ttf) 5^

IMCrrf.iOfr’l «•»*«*#* T*<| Mjtf dV (y*<d»*3lVvi»») jKiwtaMetut

»•«••(> >d*l *'**««tt **«

,»J(rei.»»*k |ji» itT* m/mim *<flr <l|., n?

(»*w IB nm •! ,k#irtt»9q agiwrfiii* k^lT) j»* dtittP 18

; . ' dB:»(aHw ” "

' 1 V* ^ Ifc

*• jt»»< »4* i** *81>JP'<4 f** MM

tMi ,4» -Jkdoj#0 »i» •Ot'totf' -tkidliM. 'J|A r «* ,vnff

jMilitJI Wi'.VUJ '"'ri’V V« !S' «r #J»iW <l#> a»l*«K y<i 4yu .*f<i ifti (M*3W»T WM

iT)iei''*/nrfe paDjtb.' *n’i*iiM;

lU •i'lBtli (T8V a'la***^ '“•<1 *tnm

1 M

‘

. A ...^ JAAa Ak^. iMij' k ^ iVk y MdL touk « wM.f« I.M *1 rk A d ^AliS IkJAfl'^r t «• i*t8 r ' , (»e8 «er W*' €<• ifti a«*m,i«a

h«iN>»| uk(A •KMlfMti BHodK iot

v< ^‘- * ..49#' k.mM 4UA . mfBA ')(8!t#' kt ltf«k^

iJH".
1.0 INTRODUCTION

Past experience with military construction projects has indicated that large

discrepancies can arise between the amount authorized for a particular project

and the actual cost of the project. Such discrepancies interfere with the

budgeting process in situations of both overestlmatlon and underestimation. In

circumstances where the actual costs are overestimated, the "surplus” amount is

not available for alternative uses. In circumstances where the actual costs are underestimated, either additional funds must be sought, or cost saving design

changes must be Implemented.

The current cost estimating procedures used by the Department of Defense Involve

first estimating the cost of a particular project in a given locale, and then

adjusting the estimated cost through the use of two multiplicative factors.

These factors adjust: (1) the size of the particular project visa-vis the size

of a "standard" project; and (2) the construction costs in the location of the

proposed project relative to construction costs in a "standard" or "base" location. (The standard location or "base city" used in this report is Washington,

D.C.). Errors in the estimation for either of these adjustment factors can result in considerable error in the cost estimate used to facilitate comparisons

among proposed military construction projects prior to the actual allocation of

funds. From a more pragmatic point of view, these errors introduce considerable

uncertainty into the budgeting process for proposed military construction projects. Given that the size of construction projects, in terms of square footage,

is changing less rapidly than the fluctuations in the market place, relatively

more uncertainty is generated by regional cost differentials than by factors

affecting size.

Since the Department of Defense submits proposed projects for annual

appropriations, it would thus be desirable if estimates of area cost factors^

could be updated on an annual basis just prior to Congressional Hearings. Currently, area cost factors are reviewed annually using limited data and often not

in the time period most likely to facilitate budget planning. The accuracy of

area cost factors is extremely important since Congressional statute limitations

on funds available for construction projects are quite stringent and assume that

all area cost factors used have been accurately estimated.

1.1 PURPOSE

The purpose of this report is to describe a computerized procedure for

estimating area cost factors for military construction projects. Identify its

data requirements, show how to run the procedure in a batch mode, and provide

guidelines for Interpreting its output. The procedure described in this report

is based on the results of an econometric analysis of over 500 military

^ The term area cost factor is defined as a multiplicative factor used to

reflect relative geographical cost differentials. They are used in the

development of military construction program projects and/or alternative

basing studies. They are not used, however, to develop construction cost

growth forecasts.

1
construction projects.^ The end result of this econometric analysis was a procedure which explicitly takes into consideration variations in the prices

for labor and materials. This report is intended to serve as a user's manual

for aiilitary personnel concerned with the problem of periodically updating the area cost factors for each service's installations.

1.2 SCOPE AND APPROACH

The general plan of this report is to briefly describe the computer program,

state the requirements of the program, and show how the computer program may be

accessed. Specifically, this user's manual is organized as follows.

Section 2.1 describes the economic theory of cost functions which permitted an economically sound method for estimating area cost factors to be derived from

empirical data on military construction projects. Section 2.2 Includes a discussion of the computer algorithm; Illustrating how a user would actually apply

the program. Step-by-step instructions are then given to; (1) identify the

necessary inputs; (2) facilitate the preparation of the input deck; and (3)

interpret the program's output.

This report also contains three technical appendices.

Appendix A shows how, given an underlying set of technical relationships, a function suitable for estimating area cost factors may be derived.

Appendix B provides examples of what the actual input and output statements from

the computer should look like. A sample computer run is given to show how data

from major metropolitan areas could be used to estimate area cost factors if

information from individual military installations were not available.

Appendix C consists of a listing of the computer program. The program is

written in FORTRAN.

^ Details of the econometric analysis are given in James M. Johannes,

Paul D. Koch and Robert H. Rasche, An Investigation of Factors Affecting

Geographical Cost Differentials on Military Construction Projects, National

Bureau of Standards, NBS-GCR-80-197 , 1980.

^ The guide used in preparing this computer program was Fortran V Level 1 Reference Manual, Interdata Inc., Oceanport, N.J. , November 1975.

2
2.0 DESCRIPTION OF THE COMPUTER PROGRAM

2.1 METHOD OF APPROACH

Past efforts at estimating area cost factors have made use of cost indices

contained within construction cost estimating guidebooks or other published

sources. Most guidebooks also contain detailed cost adjustment indices which

differ not only by region but by labor categories as well. They are usually

applied to average cost figures in order to attain figures which are more

appropriate to local construction market conditions. Although cost indices

serve to control for systematic differences in the structure of construction

costs, they may promote a false sense of security.^ This stems from two factors: (1) the construction project mix; and (2) Federal regulatory

requirements.

Cost indices are really little more than a market basket of cottstructlon labor,

materials, and sometimes equipment. The weights used in computing the index

are based on specific types of construction. Consequently, should the type of

construction being put in place for a particular region differ from that used

to compute the weights for the index, it is quite likely that the index would

introduce a bias into any cost to which it was applied. Unfortunately, there

is no a priori information which can be used to identify the direction and size

of such a bias.

It is almost certain that programs such as the Small Business Set-Aside Program,

Affirmative Action Compliance Program, Davis-Bacon Act, Buy America Act, and

others increase Federal contract construction costs. In particular, the proliferation of competition-limiting programs may have a significant cost Impact.

Federal regulatory requirements may thus Introduce biases which will render

meaningless the weights used in a construction cost index based on private

sector activity.

The purpose of this section is to show how the requirements of having a sound

cost engineering approach can be integrated with economic theory. Combining

both aspects of the problem results in a cost estimating procedure which is

sensitive to the technical considerations of the construction process as well

as to local market conditions.

The approach taken in this study is highly desirable due to the explicit

relationship between construction costs and the production process.^ Stated

another way, once a particular building design is established and a contractor

^ Lawrence Jaqulth, "The Cost Index: Working Tool or Trap," Architectural

Record , February 1969.

^ The presentation in this section aims at providing a non-technical discussion

of the engineering economic techniques used in developing the relationship

between costs and production technology. Those readers who wish a more

technical discussion which states this relationship explicitly are referred

to appendix A.

3
is selected to construct the building, the contractor must decide on how to best

combine the various inputs (labor, equipment, materials) to erect the building.

In making such decisions the firm is constrained by the existing construction

technology. Through the economic concept of the production function, however, an explicit mathematical statement of the construction technology can be made.

The general form of the production function is given as:

Q

= f(L,E,M)

where Q

= the output (square feet of floor area);

L = the labor input into the construction process;

E = the equipment input into the construction process;

M = the materials input into the construction process; and

f = the explicit functional relationship.

It is Important to point out that the production function is a technical

relationship which represents the current "state-of-the-art" method of combining

the construction Inputs to erect the building. It is also a constraint on how

the contractor can substitute among inputs in putting up the building. Given

the productive constraints under which the firm must operate, it becomes possible to overlay the cost structure faced by the contractor in erecting the

building. This structure is based on the rationale that firms attempt to minimize the costs of producing a given output. (Cost minimization is a prerequisite for profit maximization, a concept which has had long standing acceptance

in the field of economics.) Given the constraints of the construction process

and the goal of cost minimization by the contactor, the cost structure faced

by the firm can then be expressed through the use of the economic tool known as the cost function. A general statement of the cost function may be taken as

C* = g(T,S,PL,PE,PM)

where C* = the minimum total cost of erecting the building;

T = a representation of the relevant technical issues;

S = a measure of the size or scale of the project;

Pl = the price per unit of labor;

Pg = the price per unit of equipment;

Pj^ = the price per unit of building materials; and

g = the explicit functional relationship.

Depending on the functional form of the production function, the cost function,

C*, can take on various representations. In this study the cost functions are based on the assumption that the production function underlying the construction

4
process is Cobb-Douglas This assumption is made both because it is consistent

with previous studies of the construction industry^ and for ease of exposition.

The cost function associated with the Cobb-Douglas production function is

particularly attractive since it can be expressed as a product of three factors.

These factors are: (1) a technology factor; (2) a size factor; and (3) a market

factor. The technology factor, TF, is defined by the underlying construction

process. That is, certain basic construction techniques (technologies) interact

with the structure type in defining an approach which is feasible in the

engineering sense. The size factor, SF, may be derived from the size adjustment

chart, where a factor line is used to define a cost relationship factor from a size relationship factor (see figure 2.1). The market factor, MF, reflects the

Influence that supply and demand conditions in the local construction market

for key labor, material and equipment inputs have on the overall cost of the

job. The cost function, C*, may thus be written as:

C* = (TF)x(SF)x(MF) 2.2

The concept of an area cost factor may now be Introduced through reference to

equation 2.2. Suppose a subscript which ties each cost function evaluation to

a given locale is Introduced. For example, the Washington, D.C. locale may

be denoted by a "w" subscript. The "base city" cost function is thus given by

C^. It is then possible to construct an area cost factor for that city by

regionally factoring the two cost functions. In the actual process of regional

factoring, the Washington, D.C. cost function is used as a deflator. That is,

is the denominator of the equation defining the area cost factor. The area

cost factor for a particular city, say Chicago, ACF^., may thus be defined as

ACF^ = C*/C5 .

In general, for any arbitrary city, j, the area cost factor is defined as:

ACFj = eye*. 2.3

Expanding equation 2.3 through reference to equation 2.2 reveals that

ACFj = [(TFj) (SFj) (MFj)]/[(TF^) (SF,,) (MFJ] 2.4

^ The general form of the Cobb-Douglas production function is given as:

Q

= A L“1e“2m«3

where L, E and M are as defined earlier and A, ^1, and “2, and ^3 are positive constants relating the inputs to the output Q. A is frequently

referred to as an efficiency parameter and °^1, °^2, and “3 are referred to as output elasticities.

2 For an authoritative source on this subject see John S. McConnaughey

,

Production Functions in Contract Construction for the United States, 1972

(unpublished), Ph.D. dissertation, Michigan State University, 1976.

5
Figure

2.1

Size/Unit

Cost

Adjustment

Chart

dlHSN0llV13U 1S03

6

AREA

RELATIONSHIP
Since area cost factors reflect the relative cost differentials of erecting an Identical structure in a different locale, the TFj and TF„ terms in equation

2.4 cancel.^ By the same token, holding design constant would imply that the

size factor for Washington, D.C., SF^ would cancel the size factor for Chicago,

SFj., or for any other city. Thus the area cost factor for each city, j, may be

defined as

ACFj = MFj/MF^ 2.5

Equation 2.5, based on empirical estimates of equation 2.2, is the formula

actually used in the computer program described in the next section.

2.2 DESCRIPTION OF COMPUTER ALOGORITHM

The computer program discussed in this section is written is FORTRAN. Although

the program is written in FORTRAN it is not necessary for the user to know how

to use FORTRAN in order to run the program. The program is designed to provide

a maximum amount of flexibility to the user and includes several check mechanisms which significantly reduce the chance of a user error. This section begins

with a discussion of the data required to run the program. Guidelines are also

given as to how these required data can be collected. Section 2.2.2 makes use

of a flowchart to provide a description of the computer algorithm. Several

examples are also used to illustrate some of the safeguards built into the

program and to facilitate the interpretation of the output.

2.2.1 Data Requirements

In order to calculate area cost factors for each installation, information on

10 labor skills and four building materials are required.^ Each of the 10

labor skills are identified in table 2.1. These skills are: (1) common building laborer; (2) bricklayer; (3) carpenter; (4) cement mason; (5) electrician;

(6) operating engineer; (7) painter; (8) plumber; (9) sheet metal worker; and

(10) structural steel worker. These skills represent the bulk of the labor

^ Technology factors may change over time. However, unless one were interested

in comparing the area cost factor in one location at one point in time to the area cost factor for some other location at some different point in time, it

would not be necessary to include the TFj and TF^ terms in the cost function.

The cost functions which were actually estimated did include these terms so that future comparisons among locales could be made. The computer program

discussed in the following sections, however, does not include a technology

factor.

^ Those readers wishing a more detailed example are referred to appendix B,

where a sample runstream is presented, and appendix C, where a complete

listing of the computer program is given.

^ In the event that data from each installation can not be obtained, cost

information from major cities can be used. Installations can then be paired

off with a major city. See appendix B for an example of such an approach.

7
involved in the construction projects used to estimate the cost functions

discussed earlier. Note that the indicated figure for each skill includes the

contractor’s overhead and profit. The figures required for the computer program include additions to the bases due to worker’s compensation and employer’s

liability, U.S. and state unemployment. Social Security, builder’s risk and

public liability, and overhead and profit. Since overhead and profit will vary

as a function of the type of job, the size of the job, the location of the job

and prevailing economic conditions at the locale, some care should also be taken

to insure that it is adequately reflected in the wage data reported. Each of

the four building materials are identified in table 2.2. These four materials

are: (1) common brick; (2) lumber, 2" x A"; (3) ready mix concrete; and (4)

structural steel (light). Additional qualifying information is also given in

table 2.2. For example, the delivered price per cubic yard of concrete assumes

a regular weight mix with a strength of 3000 psl.

It is important to point out that the four building materials listed above do

not affect equally the calculations of the area cost factor. In particular,

for some category codes, one or more of the materials may not be included as a key cost factor. This is because the empirical analysis of that category code

revealed that material to be of minor importance. Furthermore, even if a material is used across all category codes, there may be a difference in the

cost impact associated with a change in the price of that material. The preceding statement can be best explained by noting that the coefficients of the

cost functions described earlier are a type of weight reflecting the relative

importance of that building material. Through the use of econometric methods,

these weights were estimated so as to obtain the best possible fit or measure

of the importance of that key cost factor.

Thus far no mention has been made about how to obtain the data listed in tables

2.1 and 2.2. Two alternative approaches will be pursued in addressing this

topic. These approaches are: (1) obtain all fourteen pieces of data from each

installation; and (2) obtain all data from a single source. As will be shown in

the paragraphs which follow, there are substantial advantages in obtaining all

data from a single source.

Obtaining data from each source is time consuming, and it is likely that

different agents will report different types of information. Unless consistency

checks can be devised to screen these data, some area cost factors may not accurately represent the premium placed on a particular installation’s location.

One crude consistency check is to require each installation to provide the same

set of data for the nearest major city. Since this type of data is often published periodically, it would, at least in theory, be possible to "check” the

figures provided by the Installation against published results. Should one decide to pursue this approach, it is recommended that past records be reviewed

to determine if any meaningful cost figures are included in documents submitted

for progress payments. In the event that recent records are unavailable, it

should be possible to contact local contractors and suppliers to obtain the

Information outlined in tables 2.1 and 2.2.

The second approach, whereby all data are obtained from a single source, is

highly desirable since it saves time both in the field and at the central

8
Table 2.1 Labor Skills for Which Wage Rates are Required and

Weights Applicable to Each Labor Skill®

Labor Skill Weight

Coflunon Building Laborer .05

Bricklayer .08

Carpenter .23

Cement Mason .07

Electrician .14

Operating Engineer .05

Painter .04

Plumber .20

Sheet Metal Worker .04

Structural Steel Worker .10

® Labor skills and weights are based on historical data made

available by the Army Corps of Englners.

9
Building

Material

Unit

Additional

Information

4-1 • • • 33 33 3 M CO • A C 3 P • 04 Pm 3 60 3 •H

4J CO •3 iH 3 3 CO O • 3 •H > 60 *H • 0^ PM r—1 s •H 3 1-1 P 4P

CO CJ I—1

•H 33 3 O

•3 0)

O

C 4M 3 •P 3 •H >~} CO T3 o M 3 O 3 3 3 O •H o U 33 Pm O

iH CO cn 3 3 •3 •H P

iM 3 u

C • ^ Pm' 3 p

CO Mt 4-1 •H vM 3 60 ^ 3 3 60

CJ iM Pm 3 3 3 O 3

04 60 Pm Pm

n •H Pm

OO •H

04

O •H 3 4-1 P<! X) CO 04 •3 3 Pm Mm CM 3 3. C3

CO •4M 12 3 CO 4J 3 O Pm

O 3

iM iMU 3 X Pm « x: P

CJ 3 Pm 3 PC

w

O CO rs CO

H

CO cO >

CM fH •H 3 1—1

/~v So 3 1-M CM CO «CJ- in so

04

a s-x V-M S-M

PiM

(0ao

CO ooo ooo

(U Pm0) c; •H

iM Pm

(U>M

(U>

(U Q

U0) Pm

(UO

•H

»M 4-1 Pm 04

0) T3 Fn

04»M *0

04 >M > to •H O

iH PQ

04 O

>M

04 Pm

04O

>M PmT3

04>M0) >

04 o o

•H

>M PCcoo

CJ

-O’X

CM

>M

04

04MOco

CJX

•H

TS

CO04 PO coH

iM

04 PM

04O

•H

iM PmT3

04

iM

04>

04 O

4J60

04

04 4J CO

CO

iM3

4-1 O3

iM

4-1 CO

10
facility where the area cost factors are being calculated.^ Furthermore, if

all data are obtained from a single source there is less likelihood that different types of data (l.e., non-systematic biases) will be presented for different Installations. The likelihood of systematic biases across the entire

data set being introduced is, however, higher in this mode of operation.

Although both types of biases do pose complications in interpreting the area

cost factors which result from the program, relatively less danger is associated with any systematic biases which may be introduced in this case. This

claim may be supported by noting: (1) these biases are likely to be small;

and (2) the regional factoring process may tend to cause some cancelling of errors

Of the various ways of obtaining the data for each installation, perhaps the

fastest and simplest is to purchase the data directly from a nationally known

cost engineering firm. Many of these firms keep extensive data bases which are

in some cases tabulated at the zip code level. Such geographic detail is more

than sufficient for estimating a set of area cost factors. In such an event,

each installation would be located by zip code and each of the 14 pieces of

information recorded. If such detailed cost Information cannot be easily

obtained, it is still satisfactory to use data from contiguous areas. In these

cases, however, it may be necessary for some engineering judgment to be exercised to determine if any adjustments are called for.^ Although these guidelines

are rather simple and straight forward, it is believed that following them will

permit the data required to exercise the computerized procedure to be obtained

with a minimal amount of effort on the part of the central facility engineering

staff

2.2.2 Applying the Computerized Procedure

The computerized procedure discussed earlier is programmed to determine regional

cost differentials, i.e., area cost factors for either a group of military

installations or cities. The computerized procedure for determining these area

cost factors is outlined in figure 2.2. Figure 2.2 is a flow chart showing the

sequence through which the area cost factors are calculated. For purposes of

^ Potential sources of data for this approach include standard cost manuals

such as McGraw-Hill's Dodge Manual for Building Construction, Pricing and

Scheduling , and R.S. Means, Building Construction Cost Data .

2 Although the results of the computerized procedure for estimating area cost

factors are based on information which can be readily measured or checked,

it is important to point out that some judgmental decisions are inevitable.

There is no substitute for professional experience. The use of this procedure is not intended to do away with the input from experienced individuals

but to complement it. However, the use of this procedure does reduce to a minimum the reliance on decisions which are purely judgmental and hence can neither be confirmed nor denied. Thus, a real strength of this procedure is

being able to identify quickly any discrepancies should they result, determine how serious they are, and take them into consideration in any future any

future calculations.

11
explanation, the flow chart is divided into six sections beginning with the 100s

and ending with the 600s. The designation of each section refers to the numbers

of the statements included within it. For example, in the first section (100s)

the cost data are read, tested for errors, and reproduced. This section contains statements numbered 100, 110, 120, 130, and 140, and is included within

the section of the program having statements numbered in the 100s. The same procedure holds for the remaining five sections.

The 100s section of the program (line number 1 through 57 in the listing which

appears in appendix C) begins with a dimension statement. Variables whose

values are to be stored must first be dimensioned. Table 2.3 lists and defines

the variables used in the computer program. The dimensioned variables are each

alloted 250 rows by one column of storage space. The only exception to this

array size is the ACF variable which is given 250 rows by three columns of storage space. ^ These columns represent storage space and room for calculation of

the area cost factors. It should be noted that the number of rows indicated in

the dimension statement (250) is a somewhat arbitrary upper limit of the number

of military installations or cities for which an area cost factor may be

required as opposed to the actual number for which data are being input. The

actual number of Installations or cities for which cost data are being input is

indicated by the value in integer variable I. (See line number 22 of the computer listing given in appendix C.) Consequently, the dimensions given on each

variable in table 2.3 are Ixl, 1x3, or I rather than 250 x 1, 250 x 3 or

250. If data on more than 250 locations is to be input, the number or rows of

storage space indicated for the variables in the dimension statement should be

changed to reflect the actual number of locations for which data are provided.

For the example presented in appendix B, the variable I is set equal to 145, the

number of cities for which data will be input. In order to provide a ready

reference, the remainder of the discussion will proceed on the assumption that

the example presented in appendix B is the case for which estimates of area cost

factors are desired.

Within the program's first DO loop, ten wage rates, four material costs and two

Identification codes are input. The wage and material factors are read through

a floating point format. The identifiers CITY(J) and ICODE(J) are read through

an integer format. ^ The last statement number under the control of this DO loop

is 100. Hereafter, the DO loops in this program will be referenced according to

^ For those readers referring to the listing of the computer program given in

appendix C, it is important to point out that a 'C in column 6 of the data

card refers to a continuation of the information contained on the previous

card. It does not change the name of the variable. A 'C in column 1 of the

data card indicates an information statement or "comment line." This comment

line serves solely to describe or identify the procedure which follows it.

^ It should be noted that a slash (/) within the format statement indicates

the termination of data reading on the first card applicable to a particular

city or installation and the beginning of data reading on the second card of

that city or Installation (see line number 27 of the computer listing given in

appendix C)

12
2»2 Flowchart for Area Cost Factor CofliputGr Program

13
Table 2.3 Variables Used in the Computer Program

VARIABLE DIMENSION

I 1 X 1

J 1 X 1

ACF I X 3

WCL I X 1

WBR I X 1

WCA I X 1

WCM I X 1

WEL I X 1

WOE I X 1

WPA I X I

WPL I X 1

WSM I X 1

WSW I X 1

AWR I X 1

WP I X 1

SSP I X 1

CBP I X 1

RMCP I X 1

STAWR I X 1

STWP I X 1

STCP I X 1

STSSP I X 1

STCBP I X 1

CITY I X 1

I CODE I X 1

J1 1 X 1

J2 1 X 1

J3 1 X 1

X1-X5 1 X 1 Cl-QO 1 X 1

D1-D12 1 X 1

CONE 1 X 1

CTWO 1 X 1

DESCRIPTION

Number of military installations (or major

cities) for which cost data are being input.

Installation (or major city) number.

Area cost factor matrix

Wage rate: common building laborer

Wage rate: bricklayer

Wage rate: carpenter

Wage rate: cement mason

Wage rate: electrician

Wage rate: operating engineer

Wage rate: painter

Wage rate: plumber

Wage rate: sheet metal worker

Wage rate: structural steel worker

VJage index for each installation (or

city)

Material price; lumber

Material price: structure steel

Material price: common brick

Material price: ready mix concrete

Natural logarithm of AWR

Natural logarithm of WP

Natural logarithm of PUC

Natural logarithm of SSP

Natural logarithm of CBP

Installation ID

Identifier Code 1 = Alaska; 2 = Hawaii;

0 = Otherwise

Leading line space flag

Lagging line space flag

Error flag

Working space

Constants used in computing area cost

factors for SET 1.

Constants used in computing area cost

factors for SET 2.

Cost function for SET 1.

Cost function for SET 2.

14
to the last statement number under their control (e.g., loop 100, loop 200,

etc.)* J is the index of loop 100 and of all other DO loops found in the program. Each loop proceeds from an initial index value of one (1) to a final

index value of I (in this example, I = 145). Each city/installation for which

an area cost factor is to be calculated has two data cards. The first data card

includes the ten wage rates applicable to a particular city/installation. The

second data card includes the four material costs and the ICODE(J) identifier

which corresponds to each city/installation. The final entry on both data cards

is the identification code CITY(J) which is used as a means of keeping track of

the city or installation to which a particular set of cost factors apply. The

cities/installations are given numbers from 1 through I. City 1 is the base

city (Washington, D.C.). The cities/installations are assigned the remaining

mombers (2 through I), in order, alphabetically by the state in which they are located and alphabetically within each state. A complete listing of the 145

cities and their corresponding identification codes used in the Illustrative

example is provided in table B.2. The other identifier, ICODE(J), is used in

determining which locations require special coefficients in the calculation of

their area cost factor. More succinctly, a value of ICODE(J) equal to 1 Implies that the city/installation is in Alaska, a value of 2 implies that the

city/installation is in Hawaii. In all other cases the value of ICODE(J) is

equal to 0.

Several IF statements are Included to check for errors in the input data. These

statements test whether the wage rates or material prices entered into the program are less than or equal to zero. If a value is negative or equal to zero, an error has been encountered.^ The program will highlight this error by double

spacing above and below the lines of the city/installalton containing the incorrect figure when the data are printed. The double spacing is achieved through

the use of the carriage control mechanisms in the variables J1 and J2. In

addition, an error in the input data will change the value of the error flag,

J3, from 0 to 1. Following the completion of loop 100, if an error has been

encountered, this flag triggers a printed message, ERROR IN INPUT DATA. Compilation is then terminated. The input data are reproduced to facilitate verification of input values. Table 2.4 illustrates an example where the price of

common brick for CITY 83 was entered as .00 instead of 95.00. Double spacing

appears above and below the lines containing the Incorrect figure. In the

event that no error is encountered, the program proceeds to the 200s section.

The 200s section of the computer program (line number 58 through 83 in the

listing which appears in appendix C) begins with a DO loop (loop 200) designed

to calculate the wage index, AWR(J), for each city/installation. Wage rates for

ten skills—common building laborer, bricklayer, carpenter, cement mason, electrician, operating engineer, painter, plumber, sheetmetal worker, and structural

steel worker—are weighted and added to get the total wage, TWAGE(J) . The

TWAGE(J) figure for each city is then divided by TWAGE(l), the base city

(Washington, D.C.) total wage rate, and multiplied by 100. The resulting wage

indices are the AWR(J) for each city.

^ Non positive values for wage and material prices are not permitted on technical grounds because the natural logarithm of zero or a negative number

is not defined.

15
Regional variables are computed in the second part of the 200s section. In

loop 250, the log values of the AWR(J) and four material prices are calculated

for each city. The four material price variables are WP(J) (lumber price),

SSP(J) (structural steel price), CBP(J) (common brick price), and RMCP(J)

(ready mix concrete price). The log values of AWR(J), WP(J), SSP(J), CBP(J)

and RMCP(J) are transferred (via XI, X2, X3, X4 and X5) to the variables

STAWR(J), STWP(J), STSSP(J), STCBP(J) and STCP(J), respectively, where they are

stored.

In the 300s section (line number 84 through 109 in the listing which appears in

appendix C), the "SET 1 Structures Routine," the base city cost function for set

1 category codes^ and set 1 category code structures' cost function for each

location are calculated and factored to determine the area cost factors corre- sponding to these category codes. (The base city function city function is

used as a deflator.) The coefficients of the cost functions. Cl, C2, and C3 are multiplied by the log values in STAWR(J), STSSP(J) and STCP(J), respectively. The sum of the products is then exponentiated. When the log values

associated with CITY(l) are used, the resulting value is the base city cost

function for set 1 category (C7). In addition, there is an adjustment factor

for Alaska (C5) and a coefficient corresponding to a dummy variable for Hawaii

(C6). These values estimate the unusual costs of building set 1 category code

structures in such areas; costs which are not captured in the measured input

prices. Loop 300 begins by multiplying Cl through C3 by the log values corresponding to each city/installation in the same manner outlined for the base

city. The sum of the products is set equal to C8. Two IF statements follow

immediately. These statements refer to the ICODE(J) column read previously

from the data cards. ^ A in the ICODE(J) column indicates a city location

in Alaska. A '2' in the column denotes a Hawaii location. A 'O' appears in

the ICODE(J) column for any other city location. If ICODE(J) is equal to 1 it

is referred to a statement which takes the exponential of C8 and assigns that

value to C9. To determine the cost function for set 1 category code structures

(CONE) for cities or installations in Alaska, C9 is multiplied by the Alaska

adjustment factor (C5). The IF statement for ICODE(J) equal to 2 transfers

the applicable data to an equation which adds the Hawaii coefficient (C6) to

C8. The resultant value is put into CIO. The exponential of this value is

set equal to CONE. The other city locations (ICODE(J) = 0) use the standard

procedure. That is. Cl, C2 and C3 are multiplied by STWAG(J), STSSP(J) and

STCP(J), respectively, and summed. The result (C8) is then exponentiated, the

value of which is set equal to CONE. In each case after computing the cost

function, the program proceeds to the calculation of the area cost factors for

set 1 category codes, ACF(J,1). This is accomplished by dividing each city's

cost function by that of the base city (i.e., C0NE/C7).

^ Category codes 74023, 21105, 51010, 4410, 7211, and 72411 compose the "Set

1 Structures." All other category codes are grouped under "Set 2 Structures."

2 The ICODE(J) is the next to last column on the right of the second data

line (card) for each city/installation (see the sample output shown in

table 2.4).

16
Table 2.4 Illustration of Error in Input Data

15.00 19.25 19.45 19.05 22.65 24.35 17.25 22.80 22.75 28.45 80

340.00 700.00 130.00 44.15 0 80

15.00 18.95 19.35 18.75 24.70 24.35 18.30 23.35 22.45 25.95 81

420.00 675.00 100.00 34.50 0 81

14.00 19.60 19.70 18.45 22.20 24.35 17.25 22.35 21.55 24.35 82

420.00 675.00 100.00 34.50 0 82

12.85 17.90 19.30 15.60 20.25 16.70 14.90 21.55 21.40 22.00 83

345.00 815.00 .00 39.85 0 83

16.45 18.30 17.60 18.15 20.80 20.00 16.25 20.20 20.50 20.70 84

340.00 700.00 130.00 44.15 0 84

14.25 16.20 15.20 16.05 19.80 16.75 14.05 17.40 21.30 20.35 85

340.00 700.00 130.00 44.15 0 85

18.10 21.95 21.65 21.20 24.20 22.20 19.05 22.25 22.75 24.35 86

350.00 705.00 160.00 39.55 0 86

17
The 400s section of the program (line number 110 through 136 in the listing

which appears in appendix C), the "SET 2 Structure Routine," follows a plan

very similar to the one used for set 1 structures. The coefficients D1 through

D5 are multiplied by STAWR(l), STWP(l), STSSP(l), STCBP(l) and STCP(l), respectively. The sum of the products with regard to the base city is then put into

D6. The exponential of D6 is set equal to D9, the base city cost function.

The variables D7 and D8 represent the set 2 category codes structures’ coefficient for Alaska and Hawaii, respectively. In loop 400, the variable DIO is

defined as the summation of the D coefficients multiplied by the values of the

transformed variables for each city. The cost function (CTWO) is derived by

taking the exponential of DIO. As in the set 1 structure routine, IF statements

are used to reroute data for installations in either Alaska or Hawaii to a special cost function equation. Both the Alaska and Hawaii sequences begin by

adding the appropriate coefficient (D7 or D8) to DIO. The exponential of the

result. Dll for Alaska and D12 for Hawaii, determines the cost function, CTWO.

The area cost factors for set 2 structures are then calculated by dividing CTWO,

the cost function for each city, by D9 , the Washington, D.C.(base city) cost

function. Set 2 category code area cost factors are stored in column 2 of the

ACF array (i.e., ACF (J,2)).

In the 500s section (line number 137 through 143 in the listing which appear in

appendix C) , the "Integrating Routine," a project weighted average area cost

factor is generated for each installation. The unweighted area cost factors

for set 1 category codes (ACF(J,1)) and set 2 category codes (ACF(J, 2)) are multiplied by 0.26 and 0.74, respectively, to reflect the relative frequency

with which structures within these two sets of category codes occur.

The final portion of the program, the 600s section (line number 144 through 161

in the listing which appears in appendix C), is devoted to the output format for

for the printing of the area cost factors or an error message. Loop 600 begins

with an IF statement which applies to the 1st, 51st, 101st, 151st and 201st

lines of area cost factor data output by the computer. A format statement permits these lines to appear at the top of a new page of the computer printout

under headings ('CITY,' 'ACF,' which describe the city/installation which the area cost factors apply. The area cost factors are printed fifty to a page

through a floating point format. As noted earlier, the message 'ERROR IN INPUT

DATA' indicates that one or more of the values input in the 100s section was

found to be less than or equal to zero. Compilation is terminated following

this printed message.

Preparing an Input Deck and Interpreting the Results of the Program; A

Simplified Example

The purpose of this section is to provide a step-by-step example which will

Illustrate how the procedure would be applied in practice. In order to keep the

example simple, data inputs and outputs on a sample of only 10 cities will be

used. Since these cities are a part of the detailed example illustrated in

appendix B, the reader can use the exposition presented in this section as an overview to test his/her understanding of the procedure prior to turning to the

detailed example in the appendix.

18
The first step in applying the computerized procedure is to specify the number

of cities/installations for which data will be input. This step is accomplished

at line number 22 of the program (See appendix C) where the integer variable I is read. (Note that I must be an integer, i.e., 100 is acceptable whereas 100.0

is not.) For the example presented in this section I is set equal to 10, i.e.,

the statement 1=10 is inserted at line number 22. It is important to point out

that this step is a programming change rather than an input per se. This is

because the integer variable I specifies the count on all DO loops referenced

within the program.

The second step in applying the computerized procedure is to prepare the data

cards. The program is arranged so that wage rate data is entered on the first

card applicable to a particular city/installation, and material price data and

the ICODE(J) identifier are entered on the second card of that city/installation

In order to minimize the likelihood of input error and to facilitate debugging,

the CITY(J) identifier appears as the last number on the right on all data cards

It is extremely important to note the order in which the data are entered on the

cards. For example, interchanging two material prices by accident can cause a completely meaningless estimate of the desired area cost factor to be printed.

As a means of avoiding this problem, reference should be made to table 2.5

prior to the preparation of the data cards. Table 2.5 shows the order in which

the data must be entered on the cards, the variable name as it is referenced

within the program, the format through which the variable will be read and a brief description of what the variable is.

Returning once more to the example, the 10 cities for which data are to be input

are identified in table 2.6. Table 2.7 shows the actual data input for the 10

cities. Note that column 5 on line (card) 2 of city 6 (Anchorage, Alaska) contains a 1 to distinguish it from all non Alaska locations. The first city on

the list, regardless of the number of cities, is always the base city.

The base city may or may not be Washington, D.C. However, in this report the

base city is always assumed to be Washington, D.C. The data, once read by the

program, are manipulated according to the flowchart (figure 2.2) and the discussion presented earlier so as to arrive at ah estimate of the area cost

factors for each city.

The estimates of the area cost factors associated with the data input in table

2.7 are shown in table 2.8. Columns 1 and 2 of table 2.8 are exactly as they

would be output from the program. Column 3 of table 2.8 provides a cross tabulation between the city number and city name; it is provided for convenience

only and would not be a part of the standard computer output. Referring to

table 2.8, it can be seen that the area cost factor for Washington, D.C., is

1.00. This result stems from the fact that Washington, D.C., is the base city

and consequently dividing the Washington, D.C. cost function for each structure

type by the base city cost function will always produce a value of 1.00.

The estimated area cost factors presented in table 2.8 may then be used as a part of the budget process through which the adjusted cost per unit for the

primary facility, ACPUp, is calculated. The adjusted cost per unit is defined

as

19
Table 2.5 Assembling the Input Deck; Data Card Format

ORDER

OF

INPUT

VARIABLE

NAME

FORMAT

FOR

VARIABLE

DESCRIPTION

Card One

1 WCL(J) F6.2 Wage rate In the Jth city/ Installation: Common Laborer

2 WBR(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Bricklayer

3 WCA(J) F6.2 Wage rate In the Jth clty/lnstallatlon: Carpenter

4 WCM(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Cement Mason

5 WEL(J) F6.2 Wage rate In the Jth clty/lnstallatlon: Electrician

6 WOE(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Operating Engineer

7 WPA(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Painter

8 WPL(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Plumber

9 WSM(J) F6.2 Wage rate In the Jth clty/lnstallatlon; Sheetmetal Worker

10 WSS(J) F6.2 Wage rate In the Jth clty/lnstallatlon: Structural Steel Worker

11 CITY(J) 15 Installation ID for the Jth clty/lnstallatlon

Card Two

1 WP(J) F7.2 Material price In the Jth clty/lnstallatlon: Lumber

2 SSP(J) F7.2 Material price in the Jth city/installation: Structural Steel

1 3 CBP(J) F7.2 Material price In the Jth clty/lnstallatlon: Common Brick |r 4 RMCP(J) F6.2 Material price in the Jth city/installation: Ready Mix Concrete

j

i 5 ICODE(J) 13

1 Identifier code for the Jth clty/lnstallatlon i

6 CITY(J) 16 Installation ID for the Jth clty/lnstallatlon 1

Table 2.6 Sample Cities Used In the Example

i

City Number City Name

12

34

56

78

9

10

Washington, D.C.

Birmingham, Alabeima

Huntsville, Alabama

Mobile, Alabama

Montgomery, Alabama

Anchorage, Alaska

Phoenix, Arizona

Tucson, Arizona

Little Rock, Arkansas

Anaheim, California

20
Table 2.7 Assembling the Input Deck: Sample Input Stream

14.45 20.15 17.70 17.75 20.70 17.65 18.95 21.20 20.85 21.25

400.00 800.00 130.00 30.00 0 1 11.40 17.00 15.75 14.20 19.40 15.65 16.00 20.55 19.45 20.45

288.00 700.00 91.00 34.75 0 2 9.15 15.25 14.00 14.05 19.10 16.60 14.95 18.15 19.45 18.80

325.00 875.00 100.00 35.00 0 3

10.40 16.45 15.15 14.70 20.65 15.00 15.80 19.00 18.55 17.65

300.00 750.00 120.00 43.00 0 4

9.20 15.95 15.60 14.85 16.40 15.65 11.90 18.85 19.45 20.45

288.00 700.00 91.00 34.75 0 5 26.85 30.10 28.70 27.70 36.20 29.25 31.25 32.50 32.40 36.75

380.00 700.00 168.00 39.90 1 6

15.75 20.20 18.90 18.55 26.70 20.80 17.75 23.80 25.10 27.00

325.00 700.00 110.00 39.00 0 7 15.75 20.20 18.90 18.55 24.30 20.80 16.25 23.80 19.90 27.00

325.00 700.00 110.00 39.00 0 8

11.00 15.60 15.15 14.30 18.20 15.10 13.10 19.25 19.10 18.80

320.00 700.00 97.00 35.00 0 9

19.50 24.15 22.85 22.55 26.90 24.90 23.50 27.55 27.20 29.15

300.00 790.00 108.00 40.10 0 10

Table 2.8 Estimate of Area Cost Factors for Sample Cities

(1) (2) (3)

CITY ACF City Name

1 1.00 Washington, D.C.

2 0.90 Birmingham, Alabama

3 0.93 Huntsville, Alabama

4 0.97 Mobile, Alabama

5 0.89 Montgomery, Alabaoia

6 1.84 Anchorage, Alaska

7 1.00 Phoenix, Arizona

8 1.00 Tucson, Arizona

9 0.90 Little Rock, Arkansi

10 1.05 Anaheim, California

1

2

3

4

5

6

7

8

9

10

21
SIOH

ACPU = X _JL X SF X & X 2.9

P SIZE ACF CONT ENR

where PFC = the total cost of the primary portion of the faciity at award

(primary facility cost);

ACF = the area cost factor;

SF = the size factor (see figure 2.1);

SIOH & CONT = SIOH and contingency (1.1017);

ENR = Engineering News Record Index at award; and

2175 = Engineering News Record Index projected to 31 March/April 1982;

An average cost per unit can also be calculated for the support facility cost

ACPUg , by replacing the primary facility cost, PFC, with the support facility

cost, SFC, in equation 2.9. Support facility costs are separated from primary

facility costs since non-market factors such as climate may have a profound

influence on the type of support services needed (e.g., the special HVAC

requirements associated with a base in Alaska).

The ACPUp figure is particularly important because some categories of primary

facilities are subject to statutory limits. Even if the particular category of

structure being considered is not subject to a statutory limit, a wide divergence from the service wide average will reduce the likelihood of approval.

22
3.0 SUMMARY

A coaputerlzed procedure has been used to calculate estimated area cost factors

for military construction projects. The computerized procedure Is based on the

results of a detailed econometric analysis of over 500 military construction

projects located throughout the nation. Variations In the prices of labor and

materials are considered, so that the area cost factors produced are applicable

to a particular city or military Installation.

23
REFERENCES

Aigner, D. J., C. A. K. Lovell and P. J. Schmidt, "Formulation and Estimation

of Stochastic Frontier Production Function Models," Journal of Econometrics

Vol. 6, No. 1, 1977.

Building Construction Cost Data; 1980 , R.S. Means Company, Inc., Kingston,

Mass. , 1979

Farrell, M. J., "The Measurement of Productive Efficiency," Journal of the

Royal Statistical Society , Series A, Vol. 120, Part IV, 1957.

Fortran V Level 1 Reference Manual , Interdata, Inc., Oceanport, N.J.,

November 1975.

Jaquith, Lawrence, "The Cost Index: Working Tool or Trap," Architectural

Record , February 1969.

Johannes, James M., Paul D. Koch and Robert H. Rasche, An Investigation of

Factors Affecting Geographical Cost Differentials on Military Construction

Projects , National Bureau of Standards, NBS-GCR-80-197 , 1980.

Johnston, J., Econometric Methods, McGraw-Hill Publishing Company, New York,

1972.

Kontsylannls , A., Theory of Econometrics: An Introductory Exposition of

Econometric Methods , Barnes and Noble, New York, 1977.

McConnaughey , John S., Production Functions in Contract Construction for the

United States, 1972 (unpublished), Ph. D. dissertation, Michigan State

University, 1976.

McGraw-Hill, 1980 Dodge Manual for Building Construction Pricing and

Scheduling , McGraw-Hill Information Systems, Inc., New York, 1979.

1980 Labor Rates for the Construction Industry , R.S. Means Company, Inc.,

Kingston, Mass., 1979.

Musgrave, Gerald L. and Robert H. Rasche, "Estimation of Cost Functions,"

The Engineering Economist , Vol. 22, No. 3, 1973.

Nicholson, Walter, Microeconomic Theory: Basic Principles and Extensions , The Dryden Press, Inc., Hinsdale, Illinois, 1972.

Sllberberg, Eugene, The Structure of Economics: A Mathematical Analysis , McGraw-Hill Publishing Company, New York, 1978.

24
APPENDIX A

THEORETICAL AND EMPIRICAL ISSUES IN THE FORMULATION

OF AN AREA COST FACTOR MODEL

The purpose of this appendix is to show how the requirements of having a sound cost engineering approach can be integrated with the economic theory

of cost functions. Combining both aspects of the problem results in a cost

estimating procedure which is sensitive to the technical considerations of

the construction process as well as to local market conditions.

The cost function approach is highly desirable due to the duality

relationship between the cost function and the production function associated

with the physical process. (Recall that the term production function as used

in this study refers to an explicit relationship between a set of inputs

(i.e., labor, materials, and capital) and technological factors which taken

together produce a given output, e.g., square floor area provided.) The

duality relationship stems from the fact that the contractor attempts to

minimize costs subject to the technical constraints imposed by the production

function. A simple analytical technique through which this constrained minimization problem can be solved is known as the method of Lagrange multipliers.

The essence of the Lagrange-multiplier method is to convert a constrainedminimization problem into a form such that the necessary conditions for an unconstrained minimization can still be applied. If we assume the constraint

Q

= f(L,E,M) is exactly met (where Q= the output; L = the labor input into

the construction process; E = the equipment input into the construction

process; M = the materials input into the construction process; and f defines

the functional relationship between Q, L, E and M) , then Q

- f(L,E,M) is

equal to zero and may be incorporated into the cost function to form an augmented function with the same value. This function is known as the Lagranglan.

That is, by incorporating the constraint into the Lagranglan function and by

treating the Lagranglan multiplier as an extra variable, it is possible to

solve the constrained minimization problem, C*, by identifying the optimal

values of L, E and M, of the unconstrained minimum. An additional point

worth noting is that the solution value of the Lagrange multiplier provides a measure of the impact of a change in the level of output, Q, on the optimal

value of the cost function.^

^ For a detailed discussion of production functions, cost functions, duality,

and Lagranglan multipliers, the interested reader is referred to Walter

Nicholson, Microeconomic Theory; Basic Principles and Extensions , The Dryden

Press, Inc., Hinsdale, Illinois, 1972.

25
The duality relationship has been documented in numerous economic and

engineering economics art ides. Through reference to the duality relationship it is possible to assert that the cost function tells us the least-cost

way of providing Q square feet of floor area. In an actual empirical study,

the cost function associated with the underlying process would first be theoretically derived from the production function by solving a constrained optimization problem. The theoretical parameters of the cost function would then be

empirically estimated using econometric techniques until a "best fit" model was uncovered

.

The derivation of the cost functions used in this study proceeds on the

assumption that the production function underlying the construction process is

Cobb-Douglas . This assumption is made both because it is consistent with previous studies of the construction industry^ and for ease of exposition. In the

mathematical discussion which follows, it is assumed that the prices of all

inputs are independent. Under this assumption, the quantity of output, Q, the

square feet of floor area provided, and the cost of output, C, may be expressed

as:

Q TtTs

n

( n xct.)

j=i

A.l

n

C = Z X.P.

j=l

where

Q

= total square feet of floor area to be provided;

Tt = basic construction technology factor;

Tg = basic construction scale factor;

Xj = quantity of the j*" input (materials, labor, equipment)

required to perform the job;

A.2

^ Eugene Silberberg, The Structure of Economics: A Mathematical Analysis , McGraw-Hill Publishing Company, New York, 1978.

^ Gerald L. Musgrave and Robert H. Rasche, "Estimation of Cost Functions,"

The Engineering Economist , Vol. 22, No. 3, 1973.

^ For an authoritative source on this subject see John S. McConnaughey

,

Production Functions in Contract Construction in the United States, 1972

(unpublished), Ph.D. dissertation, Michigan State University, 1976.

26
ttj = the percentage change in output associated with a one percent

change in the utilization of the input;

C = the total cost (expected bid price) of the job; and

Pj = the unit cost of the input.

Note also that the summation sign, E, and the product sign, II, are used in

equations A.l and A. 2. They are defined as:

n

Z XjPj = XiPi + X2P2 + ... + X^Pn

j=l

and

n

n X.“. = (Xi“l) ... (Xn“n)

j=l

The constrained optimization problem may then be solved through application

of the method of Lagrange multipliers.

Based on the constrained optimization problem referenced above, it is possible

to assert that the cost minimizing demand curve for each input reduces to:

* 1 /r —1 /r ^ » cxj/R Oj/R

X = (Tt • TS) ( n (aj/a£) J (PA/PJ ^ ) A.

3

A J

n where R = S a-?; and

j=l

A~l, . . .,n.

The minimum cost solution for providing Q square feet of floor area is then

determined by substituting equation A. 3 into equation A. 2. This substitution

yields:

n

C* = Z x*P.

j=l J J

or equivalently:

n

C* = (Tt • Ts)"^/^ ( nj=l

“a ./R

(Pj) J )(R)

n

( nj=i

(“j)

a ./R

J

) A.

4

27
A closer examination of equation A. 4 would reveal that it consists of three

distinct factors. These factors are; (1) a technology factor; (2) a size

factor; and (3) a market factor. The technology factor, TF, is defined by the

underlying construction process. That is, certain basic construction techniques (technologies) interact with the structure type in defining an approach

which is feasible in the engineering sense. The size factor, SF, may be

derived from the size adjustment chart, where a factor line is used to define a cost relationship factor from a size relationship factor (see figure 2.1). The

market factor reflects the Influence that supply and demand conditions in the

local construction market for key labor, material and equipment inputs have on

the overall cost of the job. The market factor, MF, in equation A. 4 is given

as:

^ ~aJR "a./R

MF = ( n (P.) J

) (R) ( n (aj)J ) j=l ^ 3=1

Equation A. 4 may thus be written as;

C* = (TF)x(SF)x(MF) A. 5

The concept of regional factoring may now be introduced through reference to

equation A. 5. Suppose a subscript which ties each cost function evaluation to

a given locale is Introduced. For example, the Washington, D.C. locale may be

denoted by a ”w" subscript. The "base city" cost function is thus given by

C^. It is then possible to construct an area cost factor for that city by

regionally factoring the two cost functions. In the actual process of regional

factoring, the Washington, D.C. cost function is used as a deflator. More

succinctly, is the denominator of the equation defining the area cost

factor. The area cost factor for Chicago, ACF^. , may thus be defined as

' ACF^ = Cc/Cw.

In general, for any arbitrary city, j, the area cost factor is defined as:

ACFj = c}/Cw . A.

Expanding equation A. 6 reveals that

ACFj = [(TFj) (SFj) (MFj)]/[(TF„) (SF„) (MF^)]. A.7

Since area cost factors reflect the relative cost differential of erecting an Identical structure in a different locale, the TFj and TF^ terms of equation

A.7 cancel. By the same token, holding design constant would imply that the

size factor for Washington, D.C., SF^^, would cancel the size factor for Chicago,

SFj. , or for any other city. Thus the area cost factor for each city, j, may be

defined as:

ACFj = MFj/MF„ A.

28
Equation A. 8 based on empirical estimates of A. 4 (presented next) is the formula

actually used in the computer program.

It is important to point out that the theoretical minimum cost curve (equation

A. 4) will not normally be observed in its entirety. The previous statement is

based on the concepts of technical and allocative inefficiency. These two

types of inefficiencies cause the contractor’s costs to be above the envelope

curve which defines the minimum construction cost subject to the technology

constraints. This one-sided error process could cause serious empirical problems where it not for a second error process associated with random shocks both

positive and negative (e.g., weather conditions, labor relations, material and

equipment contracts, etc.) which overlays and dominates it. Since the discussion of productive efficiency serves to highlight some of the empirical Issues,

it will be developed in some detail. Those readers wishing a more comprehensive

treatment of the theoretical and empirical issues associated with productive

efficiency are referred to the articles by Farrell^ and Algner, Lovell and

Schmidt.

In order to make use of a graphical representation to illustrate the two types

of productive inefficiency, a two factor constant returns to scale production

function^ will be utilized. Now if the production function for the "perfectly

efficient firm" is known, by virtue of our constant returns to scale assumption

we can make use of a single isoquant^ (or equal output curve) to illustrate

both types of inefficiency. The single Isoquant in this case is and is

shown on figure A.l as a downward sloping curve. The two axes of figure A.l

reflect the total inputs of Xi and X2 divided by the total output Q. In figure

A.l the perfectly efficient firm faced with a given set of factor prices P]^ and

?2 would produce at point B where the cost curve is tangent to the isoquant

Point B is therefore the minimum cost solution. Technical inefficiency (i.e.,

producing using the wrong quantities of inputs but with the right portions) is

^ M. J. Farrell, "The Measurement of Productive Efficiency," Journal of the

Royal Statistical Society , Series A, Vol. 120, Part III, 1957.

2 D. J. Algner, C. A. K. Lovell and P. J. Schmidt, "Formulation and Estimation

of Stochastic Frontier Production Function Models," Journal of Econometrics,

Vol. 6, No. 4, 1977.

^ A constant returns to scale production function is one in which if all

outputs are Increased/decreased proportionally the output is increased/

decreased by the same proportion. For example, doubling all inputs would

double the output.

^ An Isoquant is a curve giving all the technically feasible ways of providing

a given level of output. For a constant returns to scale production function

all isoquants are just radial blow ups of the unit isoquant. More precisely,

since Q

= f(X]^, X2 ) is the production function, for a given output Q we can write the unit Isoquant as

1 = f(Xi/Q, X2 /Q).

29
Figure A.l. Graphical Representation of Technical anti Allocative

Inefficiency in Producing a Given Level of Output

I

i

f
measured by the difference between one and the ratio of the inputs required to

those actually used. An example of technical inefficinecy would be a firm producing a total output of Q at point A.^ In this case the technical efficiency

is defined as OB/OA; thus the measure of technical Inefficiency is 1-OB/OA. The

measurement of allocative inefficiency (l.e., producing using Inputs in the

wrong proportions but using quantities that are technically correct) is less

straight forward. An example of allocative inefficiency would be a firm producing at C when the factor prices would indicate that production at B was most

efficient. If one constructs a tangent from point C to the ray OB and denotes

the point of Intersection as D, then allocative inefficiency is given as 1-OD/OB.

Total inefficiency may then be defined either as the sum of technical and allocative inefficiency or, as Barrel does it, by 1-OD/OA. Regardless of which

definition is adopted, the total cost of production is higher due to inefficiency. Since firms may not be flexible enough to always use the right quantities (technical efficiency) or right proportions (allocative efficiency) observed

cost will lie above the envelope curve defined by the theoretical minimum cost

curve.

As pointed out earlier, this argument does not address the issue of random

shocks which act as a countervailing mechanism. Thus one can explicitly recognize the constraints placed on the estimation of the relevant cost functions

but safely assert that these "theoretical" constraints are subsumed in a second

random process. This permits the estimation of the relevant cost functions to

be carried out in a straight-forward manner using ordinary least squares.

Several introductory econometrics texts contain excellent descriptions of the

technique and its properties'*^ for the reader who wishes greater detail. In

applying the technique to the data analyzed in this study, it was necessary to

impose two restrictions in order to obtain consistent estimates. First, the

theoretical formulations of the cost functions had to be superimposed as constraints on the empirical formulations actually estimated. Second, to Insure

that all data were internally consistent, some data used in the estimation had

to be scaled to avoid any problems with dimensionality.

Two cost functions are actually used in the program, one for category codes

74023, 21105, 51010, 44110, 72111, and 72411, and one for all other category

codes. The first cost function is referred to as the "SET 1" category code

cost function. This cost function is given as:

InCi(J) = 0.36754*STAWR(J) + 0.211603*STSSP(J) + 0 .239606*STCP(J) A.

9

^ Note that point A lies on the ray from the origin passing through point B.

This is why it was claimed that the firm used the right proportions, since

any point of the ray represents the same proportions of and X£ as at

point B.

2 J. Johnston, Econometric Methods, McGraw-Hill Publishing Company, New York,

1972.

^ A. Kontsoyiannis , Theory of Econometrics: An Introductory Exposition of

Econometric Methods, Barnes and Noble, New York, 1977.

31
where InC^CJ)

STAWR(J)

STSSP(J)

STCP(J)

= the natural logarithm of the minimum total cost solution for the

city;

= the natural logairthm of the average wage rate index;

= the natural logarithm of the cost per ton of structural steel;

= the natural logarithm of the cost per cubic yard of ready mix

concrete.

The second cost function is referred to as the "SET 2" category code cost

function. This cost function is given as:

lnC2(J) = 0.212421*STAWR(J) + 0.0522205*STWP(J) + 0.0861036*STSSP(J)

+ 0.238871*STCBP(J) + 0.0383134*STCP(J) A. 10

where lnC2 (J) = the natural logarith of the minimum total cost solution;

STWP(J) = the natural logarithm of the cost of Iximber; and

STCBP(J) = the natural logarithm of the cost per thousand common brick.

An unweighted area cost factor is then computed for each set, where

ACFi(J) = Ci(J)/Ci(l)

and

ACF2(J) = C2(J)/C2(1)

The project weighted area cost factor, ACF(J), is then computed to reflect the

relative frequency with which structures within the two sets of category codes

occur. The project weighted area cost factor is given as

ACF(J) = 0.26ACFi(J) + 0.74ACF2(J). A. 11

32
APPENDIX B

SAMPLE COMPUTER RUN

In section 2.2, background information was given that identified the inputs

required to use the computerized procedure and provided an example of what a typical output would look like. The purpose of this appendix is to expand on

that example and illustrate, in some detail, how the procedure would be applied

in practice. More specifically, this appendix includes a sample computer run designed to show how data from major metropolitan areas can be used to estimate

area cost factors if information from individual military installations were

not available. This example is based on the set of military construction projects examined in the econometric analysis used to estimate cost functions for

this study.

The first step in this or in any future exercise in actually assigning input

prices to each of the Installations/projects is to construct a list of cities

for which at least some information is available. The R.S. Means Building

Construction Cost Data guide reports material price indices for 30 cities.^

This list of cities is displayed in table B.l along with the identification

number (CITY(J)) for each city. Table B.2 provides a listing of 145 cities for

which input data are available. It is important to point out that for future

projects, cost data from additional cities might be available.

The second step is to assign one of the cities listed in table B.l to each of

the cities listed in table B.2, the complete list of cities for which area cost

factors are sought. This is necessary because the R.S. Means guide reports

material price figures for only 30 cities. Those cities without direct material

price data are assigned the data of the nearest city (geographically) listed in

table B.l. The identification number (CITY(J)) of the city from which material

price figures are taken appears in parentheses following the city name in table

B.2.

• The third step is to assign one of the cities in table B.2 to each of the

installations/projects. Such a procedure guarantees that the assignment of

input prices will be the best possible for material prices, at least for some

time period, and will be as geographically accurate as possible. In assigning

cities to installations/projects, two rules should be followed. First, if an Installation/project is in a city given in table B.2 that city should be

assigned to the installation/project. Second, if an installation/project is

in a city not given in table B.2, the city geographically closest to the

installation/project should be assigned to it. In the rare case where two or more cities in table B.2 are equidistant from an installation/project, the city

in or nearest the state in which the installation/project is located should be

assigned to it. The actual city assignments for the installations from the

^ Building Construction Cost Data; 1980 , R.S. Means Company, Inc., Kingston,

Mass., 1979. Another widely used guide that can be recommended for this

exercise is McGraw-Hill's 1980 Dodge Manual for Building Construction Pricing

and Scheduling, McGraw-Hill Information Systems, Inc., New York, 1979.

33
military construction projects analyzed in '"^e econometric study are given in

table B.3.

The remainder of this appendix will make use of data from the R.S. Means guide

in putting together a sample input deck to calculate the desired area cost

factors. It is important to point out that the read and format statements given

in table 2.5 and defined on lines 24 through 27 of the computer program (see

appendix C), must be carefully followed. If the format given in table 2.5 is

used, the data from the 145 cities listed in table B.2 would appear (both on

punched cards and as a data input printback) as shown in exhibit B.l. Recall

from Chapter 2 that exhibit B.l is a printback of all the data input. The purpose of this printback is to assist users in finding any obvious errors, such

as negative costs, ^ as well as those which are less easily checked when the user verifies the punched cards.

As discussed in Chapter 2, the program computes a wage index for each

installation/project. These indices are in turn used in the cost function for

that installation/project as a surrogate for labor costs. Since the data actually input are wage rates^, it was felt advisable to printout the calculated

values of the wage index. In this way, the user can compare the wage indices

with each other to determine if they appear to be in the right "ball park." A

sample set of wage Indices, based on the data shown in exhibit B.l, are given

in exhibit B.2. Note that these indices Include wide swings, as much as 100

percent in some cases, so that some care should be exercised in verification.

The final set of outputs are the area cost factors. These estimates are given

in exhibit B.3. Column 1 of exhibit B.3 contains the installation/project ID

number. It is important to point out that the base city always appears on the

first line of output. In this case, the base city is Washington, D.C. The numbers in column 1 may then be cross referenced to table B.2 to detemine the identity of the city. The Installation(s) /pro ject(s) assigned to that city may then

be cross tabulated through reference to table B.3. A sample cross tabulation

for each Installation identified in table B.3 is shown in table B.4. The estimated area cost factor for each installation is also shown in table B.4.

As discussed in section 2.2.2, the area cost factor estimates presented in

exhibit B.3, once paired with the Installation/project, are ready for use in

determining the adjusted cost per unit for the primary facility (see equation

2.9 in section 2.2.2) and/or the adjusted cost per unit for the support facility.

34
^ In the event that a non-positive wage rate or material cost is inadvertently

entered on a data card, the printback is designed to double space before and

after that line to highlight the mistake. A non-positive wage rate on material price will also cause the program to terminate immediately after the

input data have been reproduced. An example in which this safeguard is used

is shown in table 2.4 of section 2.2.2.

2 As indicated in table 2.1, the wage rates are in the form of billing rate per

hour for 10 labor skills. Direct billing rate per hour figures applicable to

cities/installations for which the reader requires area cost factors may not

be readily available. The billing rates listed in exhibit B.l are approximations based on calculations done on data taken from two publications of the

R.S. Means Company; 1980 Labor Rates for the Construction Industry and

Building Construction Cost Data; 1980 . The total wage rate (base wage rate

plus fringe benefit package) for each of the ten labor skills is taken from

Means' Labor Rates . The total hourly wage for a particular skill added to

total subcontractor overhead and profit (expressed as a percentage of the

total hourly wage) equals the billing rate for that labor skill. Subcontractors* average percentage mark-ups are listed in Means' Cost Data . The average

overhead and profit percentages applicable to the 10 labor skills are; 40.7

percent for common building laborers, 38.6 percent for bricklayers, 38.6 percent for carpenters, 37.3 percent for cement masons (finishers), 40.6 percent

for electricians, 43.7 percent for operating engineers (light equipment operators), 38.5 percent for painters (ordinary) 41.3 percent for plumbers, 42.6

percent for sheet metal workers, and 55.8 percent for structural steel workers.

The average percentage for a particular skill is multiplied by the corresponding total wage rate for a given city. The resulting product is then added to

the total wage rate. This sum is rounded to the nearest five cents to arrive

at the approximate billing rate applicable to a particular skill and city.

35
Table B.l

Thirty Cities for Which Material Price Data are Reported and Their

Corresponding CITY Numbers

1 Washington, D.C.

7 Phoenix

13 Los Angeles

17 San Diego

18 San Francisco

22 Denver

32 Atlanta

38 Chicago

45 Indianapolis

53 New Orleans

56 Baltimore

57 Boston

62 Detroit

69 Minneapolis

71 Kansas City

72 St. Louis

86 Buffalo

87 New York City

98 Cincinnati

99 Cleveland

100 Colvimbus

111 Philadelphia

112 Pittsburgh

122 Memphis

123 Nashville

128 Dallas

131 Houston

132 San Antonio

138 Seattle

144 Milwaukee

36
Table B.2

Major Cities and Their Corresponding CITY Numbers

District of Columbia Georgia Massachusetts

1 Washington (1)^ 32 Atlanta (32) 57 Boston (57)

33 Columbus (32) 58 Lawrence (57)

Alabama 34 Macon (32) 59 Springfield (57)

35 Savannah (32) 60 Worcester (57)

2 Birmingham (32)

3 Huntsville (123) Hawaii Michigan

4 Mobile (53)

5 Montgomery (32) 36 Honolulu (13) 61 Ann Arbor (62)

62 Detroit (62)

Alaska Idaho 63 Flint (62)

64 Grand Rapids (62)

6 Anchorage (138) 37 Boise (138) 65 Kalamazoo (62)

66 Lansing (62)

Arizona Illinois 67 Saginaw (62)

7 Phoenix (7) 38 Chicago (38) Minnesota

8 Tucson (7) 39 Peoria (38)

40 Rockford (38) 68 Duluth (69)

Arkansas 41 Springfield (72) 69 Minneapolis (69)

9 Little Rock (122) Indiana Mississippi

California 42 Evansville (45) 70 Jackson (53)

43 Ft. Wayne (45)

10 Anaheim (13) 44 Gary/Hammond (38) Missouri

11 Bakersfield (13) 45 Indianapolis (45)

12 Fresno (18) 46 South Bend (38) 71 Kansas City (71)

13 Los Angeles (13) 72 St. Louis (72)

14 Oxnard (13) Iowa

15 Riverside (13) Montana

16 Sacramento (18) 47 Des Moines (71)

17 San Diego (17) 73 Billings (22)

18 San Francisco (18) Kansas

19 Santa Barbara (13) Nebraska

20 Stockton (18) 48 Topeka (71)

21 Vallejo (18) 49 Wichita (71) 74 Omaha (71)

Colorado Kentucky Nevada

22 Denver (220 50 Lexington (98) 75 Las Vegas (13)

51 Louisville (98) 76 Reno (18)

Connecticut

Louisiana New Hampshire

23 Bridgeport (87) 24 Hartford (57) 52 Baton Rouge (53) 77 Manchester (57)

25 New Haven (87) 53 New Orleans (53)

54 Shreveport (128) New Jersey

Delaware

Maine 78 Camden (111)

26 Wilmington (111) 79 Jersey City (87)

55 Portland (57) 80 Newark (87)

Florida 81 Paterson (87)

Maryland 82 Trenton (111)

27 Ft. Lauderdale (32)

28 Jacksonville (32) 56 Baltimore (56) New Mexico

29 Miami (32)

30 Orlando (32) 83 Albuquerque (22)

31 Tampa (32)

^ The number in parentheses indicates the identification number (CITY(J)) of

the nearest city for which material price data are reported. Cities are assigned material price data from one of the thirty cities reporting such

Information (see table A.l).

37
Table B.2 (contIr>ued)

New York

84 Albany (87)

85 Binghampton (87)

86 Buffalo (86)

87 New York (87)

88 Rochester (86)

89 Syracuse (86)

90 Utica (87)

91 Yonkers (870

North Carolina

92 Charlotte (32)

93 Greensboro (1)

94 Raleigh (1)

North Dakota

95 Bismarck (69)

Ohio

96 Akron (99)

97 Canton (99)

98 Cincinnati (98)

99 Cleveland (99)

100 Columbus (100)

101 Dayton (98)

102 Lorain (99)

103 Toledo (62)

104 Youngstown (99)

Oklahoma

105 Oklahoma City (128)

106 Tulsa (71)

Oregon

107 Portland (138)

Pennsylvania

108 Allentown (111)

109 Erie (86)

110 Harrisburg (56)

111 Philadelphia (11)

112 Pittsburgh (112)

113 Reading (111)

114 Scranton (111)

Rhode Island

115 Providence (57)

South Carolina

116 Charleston (32)

117 Columbia (32)

South Dakota

118 Rapid City (22)

119 Sioux Falls (69)

Tennessee

120 Chattanooga (32)

121 Knoxville (123)

122 Memphis (122)

123 Nashville (123)

Texas

124 Amarillo (128)

125 Austin (132)

126 Beatimont (131)

127 Corpus Christ! (132)

128 Dallas (128)

129 El Paso (7)

130 Ft. Worth U28)

131 Houston (131)

132 San Antonio (132)

Utah

133 Salt Lake City (22)

Vermont

134 Burlington (57)

Virginia

135 Newport News (1)

136 Norfolk (1)

137 Richmond (1)

Washington

138 Seattle (138)

139 Spokane (138)

140 Tacoma (138)

West Virginia

141 Charleston (100)

142 Huntington (100)

Wisconsin

143 Madison (144)

144 Milwaukee (144)

Wyoming

145 Cheyenne (22)

38
Table B.3

Assignonent of Military Bases to Cities

State/Base City Assignment

Alabama

Craig AFB Selma 5 - Montgomery

Ft. McClellan 2 - Birmingham

Ft . Rucker 5 - Montgomery

Jasper 2 - Birmingham

Maxwell AFB 5 Montgomery

Alaska

Adak 6 - Anchorage

Eielson AFB 6 - Anchorage

Elmendorf AFB 6 - Anchorage

Ft. Wainwright 6 - Anchorage

Kokiak Tracking Station 6 - Anchorage

Shemya AFB 6 — Anchorage

Arizona

Ft. Huachucha 8 - Tucson

Luke AFB 7 - Phoenix

Williams AFB 7 - Phoenix

Yuma Proving Ground 7 — Phoenix

Arkansas

Blytheville AFB 122 - Memphis

Jonesboro 122 - Memphis

Pine Bluff Arsenal 9 - Little Rock

USARC Little Rock 9 - Little Rock

California

March AFB 15 - Riverside

Beale AFB 16 - Sacramento

Camp Pendleton (MCR) 17 - San Diego

Coronado 17 - San Diego

Edwards AFB 12 - Fresno

El Toro (MCAS Santa Ana) 10 - Anaheim

Ft. Ord 18 - San Francisco

Fresno 12 - Fresno

George AFB 10 - Anaheim

Hunter-Liggett Military Res 12 - Fresno

Letterman GH San Francisco 18 - San Francisco

Mather AFB 16 - Sacramento

McClellan AFB 16 - Sacramento

MCSC Bar stow 11 - Bakersfield

Miramar San Diego 17 - San Diego

NAS Elcentro 17 - San Diego

NAS Imperial Beach 17 - San Diego

NAS Lemoore 12 - Fresno

NAS Moffett Field 18 - San Francisco

NAS North Is. San Diego 17 - San Diego

Nav Hosp Oakland 18 - San Francisco

Navschcmd Mare Is. Vallejo 21 - Vallejo

NMC Res Ctr San Bruno 18 - San Francisco

39
Table B.3 (continued)

State/Base City Assignment

California (continued)

NS Long Beach 13 - Los Angeles

Norton AFB 15 - Riverside

NS San Diego 17 - San Diego

NWC China Lake 11 - Bakersfield

NWS Seal Beach 10 - Anaheim

Oakland Ca. Army Base 18 - San Francisco

Presidio of Monterey 18 - San Francisco

San Diego 17 - San Diego

San Onofre (Camp Pendleton) 17 - San Diego

Seal Beach 13 - Los Angeles

Sierra Army Depot 16 - Sacremento

Vandenburg AFB 19 — Santa Barbara

Colorado

Air Force Academy 22 - Denver

Air National Guard Denver 22 - Denver

Buckley ANG Base Denver 22 - Denver

Ft. Carson Colorado Springs 22 - Denver

Lowry AFB 22 - Denver

NORAD Colorado Springs 22 - Denver

Peterson Field AFB 22 — Denver

Connecticut

NSMC New London Groton 24 — Hartford

Delaware

Dover AFB 26 — Wilmington

District of Columbia

Walter Reed Hospital 1 — Washington

Florida

Cape Canaveral 30 - Orlando

Corry Field Pensacola 4 - Mobile

Elgin AFB Ft Walton Beach 4 - Mobile

Elgin AFB Valparaiso 4 - tfoblle

Homestead AFB 29 - Miami

Mayport 28 - Jacksonville

MacDlll AFB 31 - Tampa

NAS Jacksonville 28 - Jacksonville

NAS Pensacola 4 - Mobile

NAS Whiting Field 4 - ^toblle

NRMA Jacksonville 28 - Jacksonville

NS Mayfort 28 - Jacksonville

NTC Orlando 30 - Orlando

Orlando 30 - Orlando

Panama City 4 - Mobile

Patrick AFB Melbourne 30 - Orlando

Tyndall AFB Panama City 4 - Mobile

40
Table B.3 (continued)

State/Base City Assignment

Georgia

Atlanta Army Depot 32 - Atlanta

Dobbins AFB 32 - Atlanta

Ft . Bennlng 33 - Columbus

Ft. Gordon 34 - Macon

Ft. Stewart 35 - Savannah

Glynco 28 - Jacksonville

McCollum Kennesaw 32 - Atlanta

Moody AFB 35 - Savannah

NAS Marietta 32 - Atlanta

Robins AFB 34 — Macon

Hawaii

Barbers Pt Oahu (NAS) 36 - Honolulu

Barking Sands 36 - Honolulu

Hickam AFB Oahu 36 - Honolulu

Kaneohe Bay Oahu 36 - Hono lulu

Pearl Harbor 36 - Honolulu

Schofield Barracks 36 — Hono lulu

Idaho

Coeur D Alene 139 - Spokane

Mountain Home AFB 37 — Boise

Illinois

Capital Map ANG Springfield 41 - Springfield

Chanute AFB 39 - Peoria

Glenview 38 - Chicago

Scott AFB Belleville 72 — St. Louis

Indiana

Ft. Ben Harrison Indianapolis 45 - Indianapolis

Kansas

Ft. Riley Junction City 48 - Topeka

McConnell AFB 49 - Wichita

Kentucky

Ft. Campbell Clarksville 123 - Nashville

Ft . Knox 51 - Louisville

Lexington 50 - Lexington

Louisiana

Barksdale AFB 54 - Shreveport

England AFB 54 - Shreveport

Ft. Polk 54 - Shreveport

NAS New Orleans 53 - New Orleans

New Orleans 53 - New Orleans

USARC Monroe 54 - Shreveport

41
Table B.3 (contimied)

State/Base City

Maryland

Bethesda 1 -

Ft. George Meade 56 -

Massachusetts

Ft. Devens Ayer 60 - Westover AFB Chicofee Falls 59 -

Michigan

Klncheloe AFB 62 -

Mississippi

Columbus AFB 2 - Gulfport 4 - Keesler AFB Biloxi 4 - Meridian 70 -

Missouri

Ft. Leonard Wood 72 - Lambert Fid St. Louis 72 - Whiteman AFB 71 -

Montana

Malms trom AFB 73 -

Nebraska

Offutt AFB Omaha 74 -

Nevada

Neills AFB 75 -

New Hampshire

Pease AFB 77 -

New Jersey

Ft. Dlx 82 -

Ft. Monmouth 82 - McGuire AFB Wrlghtstown 82 -

New Mexico

Cannon AFB 83 - Holloman AFB 83 - Klrtland AFB 83 -

New York

USMA West Point 87 -

Assignment

Washington

Baltimore

Worcester

Springfield

Detroit

Birmingham

Mobile

Mobile

Jackson

St . Louis

St. Louis

Kansas City

Billings

Omaha

Las Vegas

Manchester

Trenton

Trenton

Trenton

Albuquerque

Albuquerque

Albuquerque

New York

42
Table B.3 (continued)

State/Base City Assignment

North Carolina

Auxiliary Landing Field 94 - Raleigh

Cherry Point 94 - Raleigh

Ft. Bragg 94 - Raleigh

MCB Camp Lejeune 94 - Raleigh

New River 94 - Raleigh

Pope AFB (Ft Bragg) 94 - Raleigh

Seymour Johnson AFB 94 - Raleigh

Winston-Salem 93 — Greensboro

North Dakota

Hector Fid ANGB Fargo 68 - Duluth

Minot AFB 68 - Duluth

Ohio

Wright Patterson AFB 101 — Dayton

Oklahoma

AFRC Okla City 105 - Oklahoma City

Attus AFB 105 - Oklahoma City

Ft. Sill 105 - Oklahoma City

Tinker AFB 105 - Oklahoma City

Vance AFB Enid 105 — Oklahoma City

Oregon

NMC Portland 107 — Portland

Pennsylvania

Pittsburgh Int Aprt 112 — Pittsburgh

South Carolina

Charleston AFB 116 - Charleston

Ft . Jackson 117 - Columbia

MCAS Beaufort 116 - Charleston

MCRD Parris Island 116 - Charleston

Shaw AFB 117 — Columbia

South Dakota

Ellsworth Rapid City 118 — Rapid City

Tennessee

Army Res Ctr Chattanooga 120 - Chattanooga

NAS Memphis Millington 122 - Memphis

Nav Hosp Memphis 122 — Memphis

Texas

Bergstrom AFB Austin 125 - Austin

Brooks AFB San Antonio 132 - San Antonio

Corpus Christ! (NAS) 127 - Corpus Christ!

43
Table B.3 (continued)

State/Base

Texas (continued)

City Assl gnmen

Dallas (NAS) 128 - Dallas

Ellington AFB Houston 131 - Houston

Ft. Bliss El Paso 129 - El Paso

Ft. Hood 125 - Austin

Ft. Sam Houston 132 - San Antonio

Goodfellow AFB 125 - Austin

Kelly AFB 132 - San Antonio

Lackland AFB San Antonio 132 - San Antonio

Laredo AFB 127 - Corpus Christ!

Laughlin AFB Del Rio 132 - San Antonio

NAS Kingsville 127 - Corpus Christl

Perrin AFB Sherman 128 - Dallas

Randolph AFB San Antonio 132 - San Antonio

Reese AFB Lubbock 124 - Amarillo

Sheppard AFB Wichita Falls 128 - Dallas

Webb AFB Big Spring 132 — San Antonio

Utah

Hill AFB 133 - Salt Lake City

NMCC Salt Lake City 133 — Salt Lake City

Virginia

Air Nat Guard Henrico 137 - Richmond

Amphib Base Little Creek 136 - Norfolk

Ft. Belvoir 1 - Washington

Ft. Eustis 135 - Newport News

Ft . Lee 137 - Richmond

Ft. Myer 1 - Washington

Langley AFB Hampton 135 - Newport News

NMCRTC Richmond 137 - Richmond

Norfolk 136 - Norfolk

NS Norfolk 136 - Norfolk

NS Portsmouth 136 - Norfolk

NW Chesapeake 136 - Norfolk

NWS Yorktown 135 - Newport News

Roanoke 93 — Greensboro

Washington

Ft. Lewis 140 - Tacoma

McChord AFB 140 - Tacoma

NAS Whidbey 138 - Seattle

NTS Bangor Annex 138 - Seattle

Trentwood 139 - Spokane

Yakima 140 - Tacoma

44
Table B.3 (continued)

State/Base City Assignment

Wisconsin

Mitchell Field Milwaukee 144 - Milwaukee

Wyoaiing

Warren AFB Cheyenne 145 - Cheyenne

45
Table B.4 Estimates of Area Cost Factors for Selected Military Bases

State/Base AREA COST FACTOR

Alabama

Craig AFB Selma .89

Ft. McClellan .90

Ft . Rucker . 89

Jasper .90

Maxwell AFB .89

Alaska

Adak 1.84

Eielson AFB 1.84

Elmendorf AFB 1.84

Ft. Wainwright 1.84

Kodiak Tracking Station 1.84

Shemya AFB 1.84

Arizona

Ft. Huachucha 1.00

Luke AFB 1.00

Williams AFB 1.00

Yuma Proving Ground 1.00

Arkansas

Blythevllle AFB .92

Jonesboro .92

Pine Bluff Arsenal .90

USARC Little Rock .90

California

March AFB 1.05

Beale AFB 1.17

Camp Pendleton (MCR) 1.07

Coronado 1.07

Edwards AFB 1.16

El Toro (MCAS Santa Ana) 1.05

Ft. Ord 1.18

Fresno 1.16

George AFB 1.05

Hunter-Llggett Military Res 1.16

Letterman GH San Francisco 1.18

Mather AFB 1.17

McClellan AFB 1.17

MCSC Barstow 1.05

Miramar San Diego 1.07

NAS Elcentro 1.07

NAS Imperial Beach 1.07

NAS Lemoore 1.16

NAS Moffett Field 1.18

NAS North Is. San Diego 1.07

Nav Hosp Oakland 1.18

Navschcmd Mare Is. Vallejo 1.17

NMC Res Ctr San Bruno 1.18

46
Table B.4 (continued)

State/Base AREA COST FACTOR

California (continued)

NS Long Beach 1.05

Norton AFB 1.05

NS San Diego 1.07

NWC China Lake 1.05

NWS Seal Beach 1.05

Oakland Ca. Army Base 1.18

Presidio of Monterey 1.18

San Diego 1.07

San Onofre (Camp Pendleton) 1.07

Seal Beach 1.05

Sierra Army Depot 1.17

Vandenburg AFB 1.05

Colorado

Air Force Academy 0.97

Air National Guard Denver 0.97

Buckley ANG Base Denver 0.97

Ft. Carson Colorado Springs 0.97

Lowry AFB 0.97

NORAD Colorado Springs 0.97

Peterson Field AFB 0.97

Connecticut

NSMC New London Groton 1.06

Delaware

Dover AFB .96

District of Columbia

Walter Reed Hospital 1.00

Florida

Cape Canaveral .89

Corry Field Pensacola .97

Elgin AFB Ft. Walton Beach .97

Elgin AFB Valparaiso .97

Homestead AFB .90

Mayport .88

MacDill AFB .90

NAS Jacksonville .88

NAS Pensacola .97

NAS Whiting Field .97

NRMA Jacksonville .88

NS Mayfort .88

NTC Orlando .89

Orlando .89

Panama City .97

Patrick AFB Melbourne .89

Tyndall AFB Panama City .97

47
Table B.4 (continued)

State/Base AREA COST FACTOR

Georgia

Atlanta Army Depot .90

Dobbins AFB .90

Ft . Benning .86

Ft . Gordon .86

Ft. Stewart .87

Glynco .88

McCollum Kennesaw .90

Moody AFB .87

NAS Marietta .90

Robins AFB .86

Hawaii

Barbers Ft Oahu (NAS) 1.52

Barking Sands 1.52

Hickam AFB Oahu 1.52

Kaneohe Bay Oahu 1.52

Pearl Harbor 1.52

Schofield Barracks 1.52

Idaho

Coeur D Alene 1.09

Mountain Home AFB 1.06

Illinois

Capital Map ANG Springfield .96

Chanute AFB 1.06

Glenview 1.08

Scott AFB Belleville .97

Indiana

Ft. Ben Harrison Indianapolis O'. 00 •

Kansas

Ft. Riley Junction City 1.03

McConnell AFB 1.01

Kentucky

Ft. Campbell Clarksville .93

Ft. Knox .98

Lexington .97

Louisiana

Barksdale AFB .98

England AFB .98

Ft. Polk .98

NAS New Orleans .98

New Orleans .98

USARC Monroe .98

48
Table B.4 (continued)

State/Base AREA COST FACTOR

Maryland

Bethesda

Ft. George Meade

1.00

.93

Massachusetts

Ft. Devens Ayer

Westover AFB Chlcofee Falls

1.06

1.05

Michigan

Klncheloe AFB 1.14

Mississippi

Columbus AFB

Gulfport

Keesler AFB Biloxi

Meridian

.90

.97

.97

.95

Missouri

Ft. Leonard Wood

Lambert Fid St. Louis

Whiteman AFB

.97

.97

1.06

Montana

Malms tron AFB .96

Nebraska

Offutt AFB Omaha 1.04

Nevada

Nellis AFB 1.03

New Hamp$hlr’e

Pease AFB 1.02

New Jersey

Ft. Dlx

Ft. Monmouth

McGuire AFB Wrightstown

.97

.97

.97

New Mexico

Cannon AFB

Holloman AFB

Kirtland AFB

.97

.97

.97

New York

USMA West Point 1.07

49
Table B.4 (continued) I

State/Base AREA COST FACTOR

North Carolina

Auxiliary Landing Field .93

Cherry Point .93

Ft. Bragg .93

MCB Camp Lejeune .93

New River .93

Pope AFB (Ft. Bragg) .93

Seymour Johnson AFB .93

Winston-Salem .93

North Dakota

Hector Fid ANGB Fargo .99

Minot AFB .99

Ohio

Wright Patterson AFB .99

Oklahoma

AFRC Okla City .99

Attus AFB .99

Ft. Sill .99

Tinker AFB .99

Vance AFB Enid .99

Oregon

NMC Portland 1.11

Pennsylvania

Pittsburgh Int Aprt 1.02

South Carolina

Charleston AFB .84

Ft . Jackson .85

MCAS Beaufort .84

MCRD Parris Island .84

Shaw AFB .85

South Dakota

Ellsworth Rapid City .93

Tennessee

Army Res Ctr Chattanooga .89

NAS Memphis Millington .92

Nav Hosp Memphis .92

Texas

I

Bergstrom AFB Austin

Brooks AFB San Antonio

Corpus Christi (NAS)

50

91

91

88
p

ll

I

j

i State/Base

!

I Texas (continued)

! Dallas (NAS) .98

I Ellington AFB Houston .97

Ft. Bliss El Paso .90

j Ft. Hood .91

Ft. Sam Houston .91

Goodfellow AFB .91

Kelly AFB .91

Lackland AFB San Antonio .91

Laredo AFB .88

I Laughlin AFB Del Rio .91

j NAS Kingsville .88

I Perrin AFB Sherman .98

Randolph AFB San Antonio .91

Reese AFB Lubbock .97

Sheppard AFB Wichita Falls .98

Webb AFB Big Spring .91

! Utah

Hill AFB .97

NMCC Salt Lake City .97

Virginia

Air Nat Guard Henrico .95

Amphib Base Little Creek .94

Ft. Belvoir 1.00

Ft. Eustis .94

Ft. Lee .95

Ft. Myer 1.00

Langley AFB Hampton .94

NMCRTC Richmond .95

Norfolk .94

NS Norfolk .94

|! NS Portsmouth .94

)i NW Chesapeake .94

NWS Yorktown .94

Roanoke .93

Washington

Ft. Lewis 1.10

McChord AFB 1.10

NAS Whidbey 1.11

NTS Bangor Annex 1.11

I Trentwood 1.09

I Yakima 1.10

1

Table B.4 (continued)

AREA COST FACTOR

51
Table B.4 (continued)

State/Base AREA COST FACTOR

Wisconsin

Mitchell Field Milwaukee 1.03

Wyoailng

Warren AFB Cheyenne .96

52
Exhibit B.l

Input Stream for the Sample

Computer Run

14 • 45 20 • 15 17.70 1 7.75 20..70 1 7 • 65 18 .95 21* 20 20. 65 21 • 25 1 4C0 • 00 800 • 00 130.00 30. 00 0 1

1 1 • 40 17 , 00 15.75 1 4.20 19.>40 15 • 65 16 • 00 20. 55 19. 45 20 • 45 2

268 • 00 700 • 00 91.00 34. 75 0 2

9 • 15 15^ 25 14.00 1 4.05 19.>10 16 • 60 14 • 95 18. 15 19. 45 13 .80 3

325 • 00 875 • 00 100.00 35. 00 0 3

10 • 40 16. 45 15.15 1 4.70 20.>65 15 • 00 15 • 80 19. 00 18. 55 17 • 65 4

300 • 00 750 • 00 120.00 43. 00 0 4

9 • 20 15* 95 15.60 1 4.85 16.>40 15 • 65 1

1

• 90 18. 85 19. 45 20 • 45 5

286 • 00 700 • 00 91.00 34. 75 0 5

26 • 85 30* 10 28.70 2 7.70 36.>20 29 • 25 31 • 25 32. 50 32. 40 36 .75 6

360 • 00 700 • 00 168.00 39. 90 1 6

15 • 75 20^ 20 18.90 1 8.55 26.>70 20 • 80 17 .75 23. 80 25. 10 27 • 00 7

325 • 00 700 • 00 110.00 39. 00 0 7

15 • 75 20* 20 18.90 1 6.55 24.>30 20 • 80 16 • 25 23. 80 19. 90 27 • 00 8

325 • 00 700 • 00 1 10.00 39. 00 0 8

1 1 • 00 15« 60 15.15 1 4.30 18.>20 15 • 10 13 • 10 19. 25 19. 10 18 • 80 9

320 • 00 700 • 00 97.00 35. 00 0 9

19 • 50 24* 15 22.85 22.55 26.>90 24 • 90 23 • 50 27. 55 27. 20 29 • 15 10

300 • 00 790 • 00 108.00 40. 10 0 10

19 • 50 25. 60 22.85 2 2.55 27.>00 24 • 90 18 • 65 26. 85 25. 15 29 .15 1 1 300 • 00 790 • 00 108.00 40. 10 0 1

1

21 • 00 23^ 90 25.50 23.60 24.>90 26 • 85 19 • 65 27. 20 23. 85 29 • 15 12

3 10 • 00 735 • 00 180.00 46. 30 0 12

19 • 50 23* 45 22.85 22.40 27,>45 24 • 90 22 • 10 27. 55 26. 45 29 • 15 13

300 • 00 790 • 00 108.00 40. 10 0 13

19 • 50 23. 75 22.85 2 2.55 27.55 24 • 90 23 • 05 27. 55 25. 75 29 • 15 14

300 • 00 790 • 00 108.00 40. 10 0 14

19 • 50 23. 15 22.85 2 2.55 26.>75 24 • 90 22 • 30 27. 55 24. 15 29 • 15 15

53
Exhibit B.l (cont inued)

^ 00*00 790.00 108.00 40.10 0 15

21.00 25.35 25.50 23.60 29.30 26.85 25.35 28.50 27 . 40 29 . 15 16

2 10.00 735.00 180.00 46.30 0 16

19.50 23.35 21.90 21.40 25.95 25.00 22.30 27.55 26 . 00 29 . 15 17

310.00 715.00 130.00 41.00 0 17

21.00 25.80 25.55 23.60 30.90 26.85 22.65 33.20 27 . 25 29 . 15 18

3 10.00 735.00 180.00 46.30 0 18

19.50 23.65 22.85 22.55 27.75 24.90 21.85 27.55 27 . 75 29 . 15 19

300.00 790.00 108.00 40.10 0 19

21.00 23.90 25.50 23.60 28.10 26.85 23 . 10 27.20 25 . 20 29 . 15 20

3 10.00 735.00 180.00 46.30 0 20

21 .00 25.80 25.50 23.60 28.15 26.85 25.35 29.40 26 . 35 29 . 15 21

310.00 735.00 180.00 46.30 0 21

13.50 18.90 18.60 18.20 21.80 17.80 19.50 21 .55 21 . 95 21 . 65 22

345.00 815.00 95.00 39.85 0 22

14.05 17.10 17.00 16.95 20.30 19.15 15.25 18.65 22 . 40 24 . 10 23

340.00 700.00 130.00 44.15 0 23

14.05 17.65 17.20 16.60 22.15 19.15 17.95 22.40 19 . 60 24 . 10 24

2es.oo 750.00 181.00 36.25 0 24

14.05 17.40 17.10 17.25 19.95 19.10 15.05 20.15 19 . 60 24 . 10 25

340.00 700.00 130.00 44.15 0 25

14.75 17.95 18.85 16.80 21.10 18.60 16.40 22.75 19 . 55 23 . 80 26

420.00 675.00 100.00 34.50 0 26

12.70 17.50 15.90 16.35 18.40 14.60 15.30 18.15 20 . 00 21 . 95 27

2 S 8.00 700.00 91 .00 34.75 0 27

8.90 14.95 14.25 12.80 17.70 14.35 14.45 19.45 17 . 95 17 . 50 28

288.00 700.00 91.00 34.75 0 28

12.60 17.55 15.90 17.35 20.30 15.50 15.30 18.05 20 . 00 20 . 40 29

268.00 700.00 91.00 34.75 0 29

10.40 14.40 15.20 14.30 17.45 14 .35 12.60 19.45 19 . 05 19 . 60 30

288.00 700.00 91.00 34.75 0 30

1.35 16.35 15.30 15.35 19.90 15.05 15.20 19.85 17 . 15 20 . 30 31

288.00 700.00 91.00 34.75 0 31

10.95 16.95 15.95 15.85 20.60 13.15 16.20 19.35 18 . 35 19 . 60 32

288.00 700.00 91.00 34.75 0 32

8.60 11.10 13.80 10.50 15.10 13.15 11.95 15.95 15 . 60 19 . 60 33

288.00 700.00 91.00 34.75 0 33

3.25 12.25 13.30 11.20 16.10 13.15 14.25 17.30 14 . 35 19 . 60 34

288.00 700.00 91.00 34.75 0 34

9.20 15.10 14.70 11.00 16.90 13.70 12.60 18.25 15 . 80 18 . 60 35

288.00 700.00 91.00 34.75 0 35

16.05 20.15 21.15 19.55 26.45 22.50 21.25 24.05 26 . 15 22 . 65 36

300.00 790.00 108.00 40.10 2 36

15.95 19.40 18.15 17.60 20.60 19.30 15.95 22.00 20 . 75 22 . 05 37

380.00 700.00 168.00 39.90 0 37

16.70 20.95 20.70 20.60 23.65 19.60 16.85 22 . 15 21 . 60 26 . 55 38

322.00 730.00 150.00 46.00 0 38

17.85 19.80 19.85 19.15 20.90 19.90 18.15 21.55 21 . 30 22 . 55 39

322.00 730.00 150.00 46.00 0 39

16.80 19.05 18.90 18.35 20.15 19.60 15.95 21.75 20 . 95 26 . 60 40

322.00 730.00 150.00 46.00 0 40

17.40 17.90 18.30 16.15 21.10 17.95 16.70 21 . 10 20 . 75 21 . 55 41

344.00 725.00 105.00 36.00 0 41

14.95 18.80 18.05 17.60 21.00 18.15 16.40 22.65 21 . 90 23 . 60 42

3 .90.00 700.00 110.00 36.25 0 42

14.00 18.25 17.65 17.10 20.65 16.45 15.95 21.70 21 . 15 23 . 50 43

390.00 700.00 1 10.00 36.25 0 43

15.80 21.10 21.00 20.70 21.95 19.25 19.50 22.80 22 . 75 25 . 40 44

5 A
Exhibit B.l (continued)

222.00 720.00 150.00 46 . 00 0 44

14.50 19.80 20.60 17.50 21 .65 15.75 17.30 21 .65 21 • SO 23.60 45

3 S 0.00 700.00 110.00 26 . 25 0 45

14.75 19.75 18.55 17.80 20.40 18.75 15.00 21.50 20 • 65 23.40 46

222.00 720.00 150.00 46 . 00 0 46

16.10 19.40 17.55 17.05 21 .40 17.05 17.15 21.40 20 • 55 20.80 47

280.00 795.00 148.00 26 . 50 0 47

12.85 16.85 15.40 15.70 21.65 19.40 16.30 20.55 20 • 20 23.15 48

280.00 795.00 148.00 26 . 50 0 48

12.15 17.00 15.10 15.85 19.10 19.40 15.50 19.30 20 • 25 19.10 49

280.00 795.00 148.00 26 . 50 0 49

12.00 17.95 17.00 16.75 20.15 14.65 14.20 20.55 23 • 10 23.25 50

280.00 700.00 110.00 40 . 95 0 50

12.05 17.25 16.50 15.95 22.55 14.65 14.40 22.70 23 • 10 23.25 51

280.00 700.00 110.00 40 . 95 0 51

11.65 19.15 17.70 14.70 22.10 15.20 14.05 19.35 20 • 05 20.15 52

200.00 750.00 120.00 42 . 00 0 52

12.60 17.25 16.90 16.20 19.85 15.65 16.30 18.70 19 • E 5 19.75 53

200.00 750.00 120.00 42 . 00 0 53

10.70 16.40 15.80 14.10 20.55 15.55 15.25 19.75 18 • 60 20.55 54

295.00 640.00 140.00 42 . 80 0 54

12.05 14.05 14.20 12.95 18.70 18.65 10.10 17.40 16 • 95 20.20 55

265.00 750.00 181.00 28 . 25 0 55

12.50 17.25 17.15 17.00 19.40 17.05 15.70 18.75 17 • 25 21.25 56

410.00 700.00 100.00 22 . 40 0 56

15.25 18.75 16.95 18.70 22.50 18.65 19.55 22.45 22 # 05 23.90 57

265.00 750.00 181.00 28 . 25 0 57

15.25 18.70 19.45 18.55 19.75 18.65 19.55 19.90 22 • 05 23.90 58

2€ 5.00 750.00 181.00 28 . 25 0 58

15.25 18.05 17.25 17.90 19.40 17.95 15.80 19.35 1 9 • 70 23.90 59

265.00 750.00 181.00 28 . 25 0 59

15.25 18.20 19.10 18.15 19.85 18.65 19.40 19.20 19 • 00 23.90 60

265.00 750.00 181.00 28 . 25 0 60

17.20 22.55 19.90 22.20 22.80 25.20 17.95 23.30 25 • 40 28.80 61

288.00 945.00 175.00 26 . 80 0 61

18.55 23.55 22.10 21.45 25.15 25.20 21.60 25.10 25 • 40 29.80 62

288.00 945.00 175.00 26 . 80 0 62

15.45 20.25 18.60 19.10 22.15 22.00 16.75 22.35 21 • 05 29.80 63

288.00 945.00 175.00 26 . 80 0 63

12.10 16.55 16.90 15.45 21.65 22.00 12.35 21.85 19 • 70 23.05 64

288.00 945.00 175.00 26 . 80 0 64

14.00 17.75 17.70 16.60 21.65 22.00 15.85 21.85 21 • 45 23.05 65

288.00 945.00 175.00 26 . 80 0 65

16.80 18.45 19.90 17.20 21 .65 22.00 18.00 21.85 21 • 45 29.80 66

288.00 945.00 175.00 26 . 80 0 66

14.80 18.75 18.60 17.55 21 .95 22.00 16.20 22.10 21 • 75 29.80 67

288.00 945.00 175.00 26 . 80 0 67

15.00 18.10 17.05 16.95 20.25 18.30 17.25 20.45 20 • 05 21.60 68

270.00 685.00 125.00 26 . 00 0 66

15.25 18.45 17.85 17.60 21 .40 18.30 17.25 20.30 20 • 75 21.65 69

270.00 685.00 125.00 26 . 00 0 69

9.25 14.60 14.05 12.40 18.05 14.05 11.90 18.25 17 • 85 18.85 70

200.00 750.00 120.00 42 . 00 0 70

15.75 19.40 19.05 17.80 23.05 21 .00 17.85 22.75 21 • 40 23.15 71

280.00 795.00 148.00 26 . 50 0 71

17.20 19.95 18.95 19.45 22.50 18.30 18.40 22.00 21 • 10 21.45 72

244.00 725.00 105.00 26 . 00 0 72

14.40 18.45 16.60 17.20 19.90 19.35 14.70 21.60 19 • 70 22.30 73

55
Exhibit B.l (continued)

345.00 815 .00 95.00 39 . 85 0 73

14 . £5 19.35 18.75 17 . 15 22.70 16.40 18.15 21.70 19 . 70 19.85 74

380.00 795 .00 148.00 36 . 50 0 74

16.20 20 . 45 22.10 19 .30 25.85 24.90 21.20 26.05 25 . 75 29.15 75

300.00 790 .00 108.00 40 . 10 0 75

16.25 21 . 60 22.35 20 .75 27.45 27.65 23.15 26 . 15 24 . 15 29.15 76

310.00 735 .00 180.00 46 . 30 0 76

13.10 15 . 05 14.85 14 .90 17.80 18.65 12.05 18.60 16 . 20 20.40 77

265.00 750 .00 181.00 38 . 25 0 77

14.40 20 . 45 19.40 19 .45 25 . 10 24.35 16.90 22.90 22 . 05 28.45 78

340.00 700 .00 130 .00 44 . 15 0 78

15.05 20 . 85 20.35 19 .70 23.40 24.35 21.75 23 . 10 22 . 25 26.45 79

340.00 700 .00 130.00 44 . 15 0 79

15.00 19 . 25 19.45 19 .05 22.65 24.35 17.25 22.80 22 . 75 28.45 80

340.00 700 .00 130 .00 44 . 1 5 0 80

15.00 1 8 . 95 19.35 18 .75 24.70 24.35 18.30 23.35 22 . 45 25.95 81

420.00 675 .00 100.00 34 . 50 0 81

14.05 19 . 60 19.70 18 . 45 22.20 24.35 17.25 22.35 21 . 55 24.35 82

420.00 675 .00 100.00 34 . 50 0 82

12.85 17 . 90 19.30 15 .60 20.25 16.70 14.90 21.55 21 . 40 22.00 83

345.00 815 .00 95.00 39 . 85 0 83

16.45 18 . 30 17.60 18 . 15 20.80 20.00 16. 25 20.20 20 . 50 20.70 84

340.00 700 .00 130.00 44 . 15 0 84

14.25 16 . 20 15.20 16 .05 19.80 16.75 14.05 17.40 21 . 30 20.35 85

340.00 700 .00 130.00 44 . 15 0 85

18.10 21 . 95 21.65 21 .20 24.20 22.20 19.05 22.25 22 . 75 24.35 86

350.00 705 .00 160.00 39 . 55 0 86

17.25 23 . 70 23.80 23 .20 23.50 21 .85 18.75 26.70 25 . 95 30.30 87

340.00 700 .00 130 .00 44 . 15 0 87

16.80 20 . 00 19.45 19 .80 22.35 18.45 17.40 24.30 2 1 . 60 22.35 88

350.00 705 .00 160.00 39 . 5 5 0 88

15.60 18 . 15 18.25 17 .70 22.15 20.30 17.05 20.55 23 . 10 22.30 89

350.00 705 .00 160.00 39 . 55 0 89

14.35 17 . 20 15.65 16 .05 20.65 20.30 14.35 20.85 23 . 10 20.40 90

340.00 700 .00 130.00 44 . 15 0 90

16.05 22 . 45 20.40 22.25 24.15 25.70 16.25 23.40 23 . 05 30.30 91

340.00 700 .00 130.00 44 . 15 0 91

7 .75 1 1 . 40 14.15 10 .10 16.10 12.80 1 1 .75 17.30 14 . 15 17.70 92

288.00 700 .00 91.00 34 . 75 0 92

7.75 1 1 . 25 14.15 10 . 10 16.10 12.80 11.75 17.30 14 . 15 18.15 93

400.00 800 .00 130.00 30 . 00 0 93

7.75 1 1 . 40 14.15 10 .10 16.10 12.80 1 1 .75 17.30 14 . 15 16.15 94

400.00 800 .00 130.00 30 . 00 0 94

11.10 15 . 65 14.70 15 . 10 18.25 15.25 12.90 20.60 18 . 70 20.90 95

370.00 685 .00 135.00 36 . 00 0 95

17.85 20 . 35 20.15 18 .95 22.00 20.60 18.25 21 . 85 20 . 15 25.35 96

. o o 375 .00 144.00 39 . 50 0 96

15.85 19 . 40 18.35 18 . 95 19.70 20.60 18.10 20.30 20 . 15 22.30 97

394.00 875 .00 144.00 39 . 50 0 97

18.15 20 . 65 20.65 20 .90 22.25 20.15 19.45 22.95 22 . 65 24.30 98

380.00 700 .00 110.00 40 . 95 0 98

20.50 22 . c a 22.60 2 1 .80 23.40 21.00 21.00 22.95 23 . 15 25.35 99

394.00 875 .00 144.00 39 . 50 0 99

15.10 19 . 80 18.25 17.35 22.05 20.10 17.65 22.25 20 . 95 23.95 100

385.00 950 .00 155.00 38 . 00 0 100

15.75 18 . 95 19.20 17 .45 22.00 20.15 18.65 21 .50 21 . 55 23.50 101

380.00 700 .00 1 10.00 40 . 95 0 101

16.50 20 . 00 22.05 19 .80 23.05 21.00 21.00 21.95 23 . 15 25.35 102

56
Exhibit B.l (continued)

394.00 875.00 144.00 39 . 50 0 102

18.55 21.65 21.85 21 .60 23.50 20.55 19.85 23 65 22 . 90 25 . 10 103

288.00 945.00 175.00 36 . 80 0 103

17.50 20.00 19.85 16 .90 21 .45 20.05 19.65 20 90 2 1 . 30 3 .45 104

394.00 875.00 144.00 39 . 50 0 104

12.40 18.75 16.20 17 .65 19.70 17.10 15.30 19 60 19 . 45 19 .95 105

295.00 640.00 140 . CO 43 . 60 0 105

12.40 17.80 16.20 16 .70 19.40 17.10 16.15 19 55 19 . 30 19 .95 106

380.00 795.00 148.00 36 . 50 0 106

17.35 23.40 20.25 20 .05 28.80 22.65 19.85 27 35 25 . 05 25 .05 107

380.00 700.00 168.00 39 . 90 0 107

13.25 18.15 17,75 17 . 90 19.20 18.70 16.15 21 50 20 . 55 24 • 55 108

420.00 675.00 ICO .00 34 . 50 0 108

16.30 20.05 18.70 18 • 40 23.40 20.00 15.90 21 05 22 . 15 25 • 05 109

350.00 705.00 160.00 39 . 55 0 109

12.95 16.40 16.95 16 .55 18.15 18.70 14.30 19 60 20 . 55 23 • 60 110

410.00 700.00 100.00 33 . 40 0 1 10

15.65 19.55 20.45 20 • 40 22.25 20.25 18.65 22 05 22 . 05 24 • 65 1

1

1 420.00 675.00 100 .00 34 . 50 0 1 1

1

17.00 21.45 20.35 20 .70 21.95 18.95 18.70 21 95 22 . 15 24 • 10 112

360.00 750.00 120.00 39 . 35 0 112

12.65 16.90 16.65 16 .55 19.05 18.70 15.80 21 50 20 . 55 23 .35 113

420.00 675.00 100.00 34 . 50 0 113

15.35 18.45 17.20 17 .30 19.50 18.70 14.95 19 95 19 . 40 24 .25 114

420.00 675.00 100.00 34 . 50 0 1 14

15.10 18.80 16.45 17 . 55 19.90 19.75 16.90 20 30 22 . 05 22 .95 115

285.00 750.00 181 .00 38 . 25 0 115

7.05 1 1 .00 12.45 10 • 65 15.25 12.55 11.75 15 40 14 . 95 17 .00 116

268.00 700.00 91 .00 34 . 75 0 1 16

7.05 15.40 12.45 14 • 30 13.70 12.05 1 1 .75 15 70 14 . 95 17 .00 117

288.00 700.00 91 .00 34 . 75 0 1 17

11.10 15.40 15.80 14 .30 18.25 15.30 12,45 18 35 17 , 95 20 . 15 118

345.00 815.00 95.00 39 . 85 0 1 18

11.25 18.15 15.55 17 • 05 18.30 15.30 12.45 17 30 16 . 90 20 . 15 119

370.00 685.00 135.00 36 . 00 0 119

10.80 17.20 15.75 14 .05 18.60 13.55 13.65 1 8 35 18 . CO 18 ,45 120

268.00 700.00 91.00 34 . 75 0 120

9.70 15.75 14.05 12 .20 17.00 13.55 13.95 17 65 18 . 00 1 6 .70 121

325.00 875 .00 100.00 35 . 00 0 121

11.55 18.15 16.25 16 .25 20.00 16.00 15.95 20 40 20 . 30 19 .60 122

320.00 700.00 97.00 35 . 00 0 122

11.05 15.75 15.45 12 .45 18.00 14.55 13.90 17 70 17 . 00 19 .35 123

in . o o 875.00 100.00 35 . 00 0 123

9.80 16.40 15.90 13 .45 18.55 16.90 14.45 17 70 16 . 35 19 .80 124

295.00 640 .00 140.00 43 . 80 0 124

10.35 16.85 16.60 15 .15 19.10 14.90 13,35 18 70 19 . 15 19 .25 125

285.00 700 .00 109.00 28 . 00 0 125

12.40 20.20 17.70 16 .30 21 .80 15.55 16.70 19 40 21 . 50 20 .55 126

285.00 705.00 1 10.00 36 . 00 0 126

9.00 14.90 13.50 13 .25 17.50 13.70 14.00 16 20 15 . 75 16 .80 127

285.00 700.00 109.00 26 . 00 0 127

10.65 17,50 17.00 16 .55 19.05 16.90 15.90 17 95 18 . 15 19 . 15 128

295.00 640 .00 140.00 43 . 80 0 128

9.60 12.95 13.20 11 • 90 15.50 15.20 11.65 15 40 17 . 30 1 8 .40 129

325.00 700.00 1 10.00 39 . 00 0 129

10.65 17.40 17.00 16 .55 19.25 16.90 16.00 17 95 IS . 15 1 9 . 15 130

295.00 640 .00 140.00 43 . 80 0 130

13.85 19.35 16.75 17 • 80 21 .95 17.10 18.50 21 10 21 . 50 21 .75 131

57
Exhibit B.l (continued)

285 • 00 705 • 00 1 10^00 38 ^ 00 0

10 • 20 16 . 50 15^90 15 • 60 18 • 45

285 • 00 700 • 00 109^00 28 ^ 00 0

13 • 25 19 « 40 17^30 16 • 75 21 • 60

345 • 00 815 • 00 95^00 39 ^ 85 0

13 • 00 14 * 85 14^85 14 • 70 15 • 45

285 • 00 750 • 00 181 •OO 38 ^ 25 0

9 • 30 13 . 85 14^60 12 • 35 16 • 85

400 • 00 800 • 00 130^00 30 ^ 00 0

9 • 30 14 * 05 14^60 12 • 35 17 • 15

400 • 00 800 • 00 130^00 30 ^ 00 0

S • 30 16 ^ 75 14^60 12 • 35 18 • 10

4 C 0 • 00 800 • 00 130 •OO 30 ^ 00 0

18 • 80 22 ^ 30 20^30 20 • 80 27 • 05

380 • 00 700 • 00 168^00 39 ^ 90 0

17 • 00 19 . 55 19^65 18 • 70 24 • 50

380 • 00 700 • 00 168^00 39 ^ 90 0

18 • 80 21 • 35 19^80 19 • 90 26 • 85

380 • 00 700 • 00 168^00 39 ^ 90 0

14 • 60 19 * 55 19^40 18 • 25 21 •35

385 • 00 950 • 00 155^00 38 ^ 00 0

14 • 70 19 . 60 18^50 18 • 45 21 • 90

385 • 00 950 • 00 155^00 3 e » 00 0

15 • 40 1 7 . 40 17^00 16 • 25 20 • 05

350 • 00 755 • 00 140^00 32 ^ 60 0

18 • 40 21 • 35 20^25 19 • 45 22 • 55

350 • 00 755 • 00 140^00 32 ^ 60 0

13 • 85 19 . 40 17^90 16 • 20 19 • 40

345 • 00 815 • 00 95^00 39 ^ 85 0

31

• 25 14^00 19^80 19 * 15 18*45 132

32

• 75 16^00 20^70 20*30 22*05 133

33

• 95 12^05 15^65 15*20 20*90 134

34

• 95 11^90 16*65 16 * 10 18«10 135

35

• 95 12^10 16*90 15,75 18*10 136

36

• 95 12^55 17,85 17,25 18*85 137

37

• 35 19^65 27,70 26 * t0 25*05 138

38

• 30 18^60 24*95 25*20 25*05 139

39

• 35 19^65 24*95 25,80 25*05 140

40

• 70 15^40 20*45 20*30 23*05 141

41

• 70 16^00 21*90 20*95 23*35 142

42

• 15 16^55 20*85 20,45 21*20 143

43

• 15 18^85 22*30 22*45 25*00 144

44

• 40 19^50 19*50 19*25 22,35 145

45

1 15

1 22

1 17

1 10

1 10

1 10

1 21

1 20

1 21

1 18

1 18

1 20

1 20

1 20

1

58
Wage Index Prlntback for

the Sample Computer Run

30 84*83

31 89.25

32 89.94

33 73.51

34 75.89

35 80.04

36 115.89

37 101*51

38 111.57

39 105.47

40 104*73

41 100.62

42 102*68

43 99.58

44 111*33

1 loe.oo 45 104.89

2 90*88 46 101.57

3 83.93 47 99.58

4 87.33 48 95.52

c 85.17 49 89.73

6 162.71 50 96*20

7 113.49 51 99*04

6 1 10.38 52 94.49

S 85.65 53 91*60

10 130.02 54 90*18

1

1

128.54 55 83.06

12 121.04 56 92.38

13 129.63 57 106.04

14 129.93 58 101 .94

15 128.62 59 96.57

16 138.06 60 99.91

17 126.99 61 1 16.95

18 143.73 62 125.28

19 130.20 63 109.21

20 134.34 64 98.19

21 138.13 65 101.37

22 102.21 66 109.17

23 96.01 67 107.49

24 101.53 68 96.97

25 97.03 69 99.21

26 102.84 70 80.91

27 89.65 71 106.67

28 82.26 72 105.08

29 90.71 73 97.52

74 101.26

75 122.50

76 125.85

77 86.21

78 1 12.94

79 1 14.53

80 110.86

81 111.42

82 1 07.69

83 99.24

84 98.51

85 88.55

86 114.41

87 125.85
Exhibit B.2 (continued)

88 1 u ‘J • 36

89 101.78

90 95.07

91 117.59

92 74.39

93 74.56

94 74.62

95 87.88

96 108.50

97 100.59

98 111.42

99 117.46

100 104.37

101 104.65

102 112.72

103 115.97

104 95.60

105 93.06

106 91.99

107 122.44

108 99.54

109 105.86

110 93.71

111 108.89

112 109.10

113 96.28

1 14 97.31

115 100.17

116 69.39

117 71.59

118 85.85

119 86.46

120 85.55

121 79.27

122 92.82

123 83.55

124 86.02

125 88.35

126 96.67

127 76.96

128 89.65

129 74.25

130 89.78

131 101 .74

132 87.98

133 99.69

134 80.75

135 77.18

136 77.71

137 81.30

138 121.61

1 39 113.15

140 117.28

141 102.04

142 103.39

143 96.95

144 110.51

145 9 7.58

60
Estimated Area Cost Factors

Based on the Sample Input

Stream

ITY ACF

1 1.00

2 • 90

3 • 93

4 • 97

5 • 89

6 U34

7 l^OO

8 UOO

9 • 90

10 1 •05

1

1

1^05

12 !• 16

13 1^05

14 UOS

15 1 •OS

16 1^17

17 1^07

18 !• 18

19 1.05

20 !• 16

21 1^17

22 • 97

23 l^OO

24 U06

25 l^Ol

26 • 96

27 • 90

28 • 88

29 • 90

30 • 89

31 • 90

32 • 90

33 • 86

34 • 86

35 • 87

36 1^52

37 1^06

38 1^08

39 1^06

40 1^06

41 • 96

42 • 98

43 • 97

44 1.08

45 • 98

46 1.05

47 1.04

48 1.03

49 1.01

50 • 97

61
Exhibit B.3 (contin-.'ed)

CITY ACF

51 • 98

52 • 99

53 • 98

54 •9 8

55 l^Ol

56 • 93

57 l»07

58 l»06

59 l»05

60 1 ^06

61 !• 13

62 1^14

63 l^ll

64 1^08

65 1^09

66 !•! 1 67 1^10

68 • 99

69 1.00

70 • 95

71 1.06

72 .97

73 .96

74 1.04

75 1.03

76 1.14

77 1.02

78 1.05

79 1.05

80 1.04

81 .98

82 .97

83 .97

84 1.01

85 .98

86 1 .08

87 1.07

88 1.06

89 1.05

90 1.00

91 1.06

92 .86

93 .93

94 .93

95 .97

96 1.08

97 1.06

98 1.01

99 1.10

100 1.09

62
Exhibit B.3 (continued)

CITY ACF

101 • 99

102 1.09

103 1.12

104 1*04

105 • 99

106 1.02

107 !• 1

1

106 • 95

109 1^06

110 • 93

111 • 97

112 1^02

1 13 • 94

114 • 94

115 1^06

116 • 84

117 • 85

lie • 93

119 • 97

120 • 89

121 • 92

122 • 92

123 • 93

124 • 97

125 • 91

126 • 96

127 • 88

128 • 98

129 • 90

130 • 98

131 • 97

132 • 91

133 • 97

134 l^OO

135 • 94

136 • 94

137 • 95

138 !•! 1 139 1^09

140 I^IO

141 1^08

142 1.08

143 1.00

144 1.03

145 • 96

63
APPENDIX C

listing of the comfuter program

< <

HI * a OC. a < o

u. in • • X CM

a. u w o O

o M a in in I u CM (VI u 3 z w

< a 0. <

u. QC • a

a h* 3

H u. o V) •

tn in • o in (M O

u z w O in o a in (VI < M HI (VI w

HI I- u HI ««

O' < • 0. O o

< J A CQ 3 in

-J o O • (VI z < in H w

< cu in O HI

in w • in (9 UJ z a (VI <

K •>4 in o 3

D in in J »- a H. •> (VI HI • z O «« w 3

o o a • O

u (X. in in in

UJ (VI in O (VI a (D w H in H Z 0. in (VI UJ D o 3 • w a

V) Z HJ • Z a

1- o u u

J D O in 3

z < a in (VI • • < in z (VI (£ z o o w a O O

O o H u (X 3 in in 3 K" (VI (VI a H UJ UJ < in w

a < I m • • < in J H ij in

W) -1 o ro o 3 3 M < (X * in • • X 1" a o (VI H in IL UJ in w O O

z ac (VI (X in in

U. M z < w 3 (VI (VI a a u. < w w

u. M U) <-» H (X z

HI a 1- a. < in m in U> < a • 3 3 19 o H N h- z a • <

Q. UJ U u o

(X, V) J < M in O O U. D < u. V) (VI in in a z z (VI (VI IX HI 1- K HJ > w w o

HI > M in z 1- -1 _l (X X M z o M u a ex K H KJ Q u 3 3 HI u U u

O u c c o O u u

64
15* J3=0

le*

17*

18*

19*

20 * 21 * 22 * 23*

24*

25*

26*

27*

49*

50*

51*

52*

53*

54*

55*

56*

57*

58*

59*

60*

61*

62*

63*

64*

65*

66 * 67*

68 * 69*

70*

71*

72*

C

C

C

c

c

c

INPUT POUTINE FOR KEY FACTORS

INPUT NUMBER OF INSTALLATIONS FOR WHICH AREA COST FACTORS ARE TO BE

COMPUTED

1 10

1=145

DO 100

REA0(5t

CWPL( J).

CICOOE(

J

FORMAT!

J= 1 . I 110) WCL( J) «WBR(J ) .WCA( J) .WCM! J ) •WEL( J)«WOE( J) «MPA( J)

WSM( J) .WSS(J) tCITY( J) •UfP( J)«SSP( J) .CBP! J) .RMCPI J)t

)tCITY( J)

10F6.2* 15/3F7.2tF6.2. 13. 16)

28* Jl=* • 29* J2=* • 30* IF!WCL! J) .LE.O) GO TO 120

31* IF!WER! J) .LE.O) GO TO 120

32* IF!WCA! J) .LE.O) GO TO 120

33* IF!WCM! J) .LE«0) GO TO 120

34* IF! WEL! J) .LE.O) GO TO 120

35* IF!WOE! J) .LE.O) GO TO 120

36* IF! WPA! J) .LE.O) GO TO 120

37* 1F!WPL! J) •LE.O) GO TO 120

38* 1F!WSM! J) .LE.O) GO TO 120

39* 1F!WSS! J) .LE.O) GO TO 120

40* 1F!WP!J)«LE*0) GO TO 120

41* IF!SSP! J) .LE.O) GO TO 120

42* IF!CEP! J) .LE.O) GO TO 120

43* IF!RMCP !J) .LE.O) GO TO 120

44* GO TO 150

45* 120 J1=»0

•

46* J2=*/»

47* ^3=1

48* 130 WRITE!6.140) Jl. WCL! J ) • WBR!

C

C

C

CWPL( J)« V«SM( J )• WSS(J ) •C1TY(J )t UP( J) tSSPC J) vCBPC J ) •RMCP ( J ) • ICOOE < J ) t CCITY( J) #J2

140 FORMAT! A1 «10X,10F6.2tl5/10X.3F7.2 tF6»2 t I3fl6/Al

)

CO TO 100

150 WRITE! 6» 1 60 ) J 1 • WCL! J ) • WBR ! J ) • MCA ! J ) • WCM ! J ) • WEL ! J ) • WOE ! J ) • MP A ! J )

CWPL! J) tWSM! J) ,WSS!J) .CITY! J) • IftP! J ) • SSP ! J ) «CBP! J ) «RMCP! J)t ICODE! J)t

CCITY! J) tJ2

160 FORMAT! A1 1 10X« 10F6.2t 15/1 OX# 3F7.2tF6.2t I3t 16tAl

)

100 CONTINUE

IF!J3.EC.l) GO TO 660

CALCULATION OF WAGE INDEX

CO 200 J=ltl

TWAGE! J ) = WCL! J)*0«054-WBR ! J)*0«08-t-WCA! J)*0«234-WCM! J)*0«07*WEL! J) * CO .14*WOE! J )*0.05^WPA! J)*0.04>WPL! J)*0«20*WSM! J)*0.04*WSS! J)*0. 10

AWR!J)=!TWAGE!J)/TWAGE! 1 ))*100

WR1TE!6 *210) J.AWR! J ) 210 FORMAT! 20XtI10«F10«2)

200 CONTINUE

INITIALIZATION OF CITY FACTORS FOR COMPUTING AREA COST FACTORS

CO 250 J=ltl

65
73* )(lsALCIG(AMR( Ji ) 74* X2=ALCGCWP( J)

75* X3=ALCG(SSP( J)

It* X4=ALCG(CBP( J))

77* X5=ALCG(RMCP( J)

78* STAWR( J ) = X1

79* STI«P( J)=X2

80* £TSSP( J)=X3

81* STCBP(J)=X4

82* £TCP( J)=X5

83* 250 CCNTINUE

84* C

85* c CCNSTANIS USED IN COMPUTING SET 1 AREA COST FACTORS

ee* c 87* Cl=. 367540

88* C2=.211603

89* C3=.239606

90* C4=C1*STA»»R( 1 }^C2*STSSP( 1 )+C3*STCP( 1 ) 91* C5=l .46

92* C6= .426809

93* C7=EXP(C4)

94* c 95* c ROUTINE FCR COMPUTING SET 1 AREA COST FACTORS

95* c 97* 00 300 J=ltl

98* C8=C 1 *STAI«R ( J )-t-C2*STSSP ( J )-fC3*STCP< J ) 99* IFC ICOOEI J) .EQ.l ) GO TO 310

100* IF( ICCOEi J).EQ.2) GO TO 320

101* CCNEsEXP(C8)

1C2* GO TO 330

103* 310 C9sEXP(C8)

1C4* CCNE=C9*C5

105* C-C TC 330

106* 320 C10=C8+C6

107* CCNE=EXP(C10)

108* 330 ACFIJ.l )=CCNE/C7

109* 300 CCNTINUE

110* c 111* c CONSTANTS USED IN COMPUTING SET 2 AREA COST FACTORS

112* c

1 13* Cl=.212421

114* 02=.0522205

115* C3=. 0861036

116* C4=.238£7

1 17* 05=.0383134

118* 06=01*STAMR( 1 )-t-D2*STWP( 1 )+03*STSSP< 1 ) •f04*STCBP( 1 }•»05*STCP ( 1 119* C6=.386239

120* D9=EXP<D6)

12 1* c 122* c ROUTINE FCR COMPUTING SET 2 AREA COST FACTORS

123* c 124* 00 400 J=l.l

125* 0 10=D1*STA*R( J)-t-D2*STWP( J)-fD3*STSSP( J )-f04*STCBP( J)*-05*STCP(

126* IF( 1C0CE< J) .EQ.l ) GO TO 410

127* IF( ICOCEI J) .EQ.2} GO TO 420

128* CT*0=EXP(C10)

129* CO TO 430

130* 410 0 11=010407

66
31*

CTWO=EXF(Ol

1

1

32*

C-0

TC

430

33*

420

C12=D104>D€

344

CTW0=EXP(D12)

o

vOo

o

>4N

O

*

CM

U.yj

<

<¥

O

CM

•O

UJ

•->

O'o

ina

UJ

•a

a

•

o

UJ

u.yj

<

X

vO Q •

CM • ro m ro o

• —

• CM > • (VJ in •

UJ o in • - • vO z * • w o M w o

o u. u U. o

O' K UJ u U. m u u. H

o D • • < • • < •

N. “» H -> • o X • o

o (Z w < • VO *7 a U. Z t-t cz " C5 • u GC • Q .O • O m o • o

yj z <u < U mt • CM X ri 4 X •H r*

II M VJt II II LL II O o o VO X VO o • vO UJ CO lU "> • m o t> » UJ UJ •

CM 3 < in m D H" o «o w <n vO w VO w D z vO * Z cc in o • Z 3 o UJ w H «« H w H Z • w

-) M O 4 o M a o • UJ 4 o UJ < UJ 4 n UJ w H UJ • in 1” 1- o H Z H H Z K Z 1- H

u. Z H 11 u. z o w M CZ M CZ M CZ Z M

u u Z N o u u o o u. cz o a o CZ a u u. (Z yj »-• a u 4 yj o a u. Vtf a IL a u. u iS o o o o o O o o o

n o o CM n 4 o VO 4 4 in '0 vO vO VO VO vO u u u u u o

************************

m'w^(uc^o>^cM(')'9U)^ur>cou'o*^(Ml^'9’U)^ur•cu mr')nr)i»)'M-'?r^'0-^^’4<r'»^ininininmininu)in

67

594

670

FORMAK

lOX,

'ERROR

IN

INPUT

DATA*)

604

650

J3s0

614

END
I'

f/ '

I,

r i- *

i'f \

I

•

W-i

Pr

rv

f

tis

n

t€^

7 t»

f««

eo4

•i«

S44

a«4

He#

fT4

t6« «««

f*a

44

V*-*

• t*

C

c

c

f T-^e^tJ- HA* F* ,U'f|

HWi.i'itit# »:v-v «eo ccKiri»*u><F ^ ^

'i-' ,*'

I'T"* ,..

1«€

44i'' i4<

< » **•

f)<»4f:xt»ii)<6

4 . \ 'ill ., * -^ COMStlikIS 1»4 CO^tlMt 8tt I ’<»••

KJf^m »l H' <>3 « . ,v, r. t ^ , 'V-X r ||40*^t0>u I C*4» .4^ .,

‘•"^ ,

^ -

' CA« r , ,. , a i'T»eMl^i€4 i t) ... 1 2

6 • .

, -v» tcuTf^f cc«»»ohn{L I ADS^cqrr ^4CTOft«

>- *• 2

^' ^

io 3a0 4' . 4 , . H'4 • I3«*< 1 tStA'*i’V>»*'Ct4«i» «p»t J»4C*fSWy‘'<4l ?!

CTJ ifCU3ffi2l«£«^Z| ftcHQ w

j^nffvRXPicef " ^

TO • j; p g

ji» s«*4'’» 05^ •< »*- u. «CN(»c«4cr 4 r f4 2 ^ £Q^in T.O o • » i wiTji^ * 2^JI U *" Jt O ^ *5 «

-f* ^2?

» ^ ^ -O' 30iJ 0« O •- O, O . .K- 204* 0 4 U.

c >C -4 »• X XV>* ^

o ir t? Ifl i ^3uO^

c i^'? ««a ikn€ 8^>&«iw 4«S feS ^ ?«AS^E 5 Sq? 5 ?S S Hi* rs ^j: 6 Si!l

-4 SR^.3«S*SSoS 5 £o V S 5 $g- 2 i SSJ-o

wi r u» m i» ^ y 4» « - P u > u « •- Jf ^ ” tsT *

j

n ^A»04C.'U3Ao o O ^ O ' O O.. ' O

' ‘'\ -J « S ^Sot <35k4ftn4^aoMi/iM»U t4t>3#igas»'4 U404*!it|^u(fo»tft€.'aii

U u i>

rc» co»4'UT<H« self «caIW!a cost fAcr^Aft

> J B

# V k «' \ i i > «»*2 r <»<? : TO

* ' •H, >

Td

:. 'l£- __
Yr. Mo. Day

1 0 1 1 2

04. Software date

Yr. Mo. D ay

FEDERAL INFORMATION PROCESSING STANDARD SOFTWARE SUMMARY

01. Summary date

06. Short title NA

02. Summary prepared by (Name and Phone)

Robert E . Chaponan 301/921-3855

05. Software title Area Cost Factor Estimation Procedure

08. Software type 09. Processing mode

03. Sum^^ary action New Replacement Deletion 0

Previous Internal Software ID

07. Internal Software ID NA

10. General

Application area

Specific Automated Data Q

System

Computer Program

Q

Subroutine/Module

[~~| Interactive Batch

] I Combination

11. Submitting organization and address Operations Research Division

Center for Applied Mathematics

National Bureau of Standards

Washington, D. C. 20234

a

13.

Narrative

Computer Systems

Support/Utility

Scientific/Engineering

Bibliographic/Textual

Management/

Business military construction

Process Control prOT ectS

Other

12. Technical contact(s) and phone

Robert E. Chapman

301/921-3855

Program will estimate a geographical cost index, area cost factor, for each military

installation and/or major city in the United States for which data are input. Two

sets of area cost factors, one for each major set of military category codes, are

estinated and then weighted to reflect the relative frequency with vdiich structures

within each set have occurred historically.

14.

Keywords

15.

Computer manufr and model

UNIVAC 1108A

16.

Computer operating system

NBS Computer

Services Division

17.

Programing language(s)

FORTRAN V

18. Number of source program state- ments

19. Computer memory requirements 20. Tape drives None

21. Disk/Drum units None

22. Terminals None

23.

Other operational requirements

24.

Software availability

Available Limited 0 ^ Operations Research Division

Center for Applied Mathematics

National Bureau of Standards

Washington, D. C. 20234

In-house only

25.

Documentation availability

Available Inadequate 3

Operations Research Division

Center for Applied Mathematics

National Bureau of Standards

Washington, D. C. 20234

In-house only

26.

FOR SUBMITTING ORGANIZATION USE

Standard Form 185

1974 July

U.S. Dept, of Commerce—NBS

(FIPS. Pub. 30)

185-101
, ,r^' v,i.';"-' ^ ® ,, ^ «“ ® ^ ^ . - YWAMMU8 35IAWnO«jaflAaHAT8 0HI883DO5W MOITAMBOWI iAHiOa^J «

;c., 2^

-4

aaHKm ipvn<fiwt .CO ®Q D b ^ ''«' CH nmdioe i^aiatp< iu(iic»ii»>^

,'^^i:

01 "hmS3^

m

itl4li.i .> «Ti

; 'elag;4tg\i:0€v niyt^BfO'

sai/tiooo^ . milaax

•fiM ' f^wi iiiii>iy^

mitDiJTJisrtdo

g

. t «f

- A*M4g«TKaaMsM

imihO **iew?f%

" ||

«<M0“

A- -*A-

!'be» ..St I'

Nn«^iii-W' \c»^\':p>r)u5^ IBOO- :,3cai£«l' jhaoa^Xe^^ W»f

cnttT iKfssb ffcthfe; neol sa^crfS^ bsthilj adf rii ^{fio r[otJ^'io\t^ aoifi

&IB "kf im •jotm rfejeat 'ribi: &m Vsnsalsii^ ?*/

ti

3

ttXMfa vs'MAsrrw

iL.

39f»{i 'Fjb

' MbaM intCIVMICI '.K ^ ©fioM

«d>i» «4k«(MI

- D

9hnapiKb»(a

'-'^- o

vSttliMinr* twWwwwwtilPO ~.CS,

9t/k cMtaHovA

mlajp^U ^

ad'-stefed^ '^ci u^eroB tjencxl^^^

i^.

"^sr.W”'*

’‘-•srwjwr’-*'' .,
INSTRUCTIONS

01. Summary Date. Enter date summary prepared. Use Year, Month, Day format: YYMMDD.

02. Summary Prepared 3y. Enter name and phone number (including area code) of individual who prepared this summary.

03. Summary Action. Mark the appropriate box for new summary, replacement summary or deletioii of summary. If this software summary is a replace- ment, enter under “Previous Internal Software ID’’ the internal softvrare identification as reported in item 07 of the originai summary, and enter the new internal software identification in item 07 of this form; complete all other items as for a new summary. If a software summary is to be deleted, enter under "Previous Internal Software ID’’ the internal software identification as reported in item 07 of the original summary; complete only items

01, 02, 03 and 11 on this form.

04. Software Date. Enter date software was completed or last updated. Use Year, Month, Day format: YYMMDD.

05. Software Title. Make title as descriptive as possible.

06. Short Title. (Optional) Enter commonly used abbreviation or acronym which identifies the software.

07. Internal Software ID. Enter a unique identification number or code.

08. Software Type. Mark the appropriate box for an Automated Data System (set of computer programs). Computer Program, or Subroutine/Module,

whichever best describes the software.

09. Processing Mode. Mark the appropriate box for an Interactive, Batch, or Combination mode, whichever best describes the software.

10. Application Area. General: Mark the appropriate box which best describes the general area of application from among:

(^mputer Systems Support/Utility Process Control Management/Business Bibliographic/Textual

Scientific/Engineering Other

Specific; Specify the sub-area of application; e.g.: “COBOL optimizer” if the general area is “Computer Systems Support/ Utility”; “Payroll” if the

general area is “Management/Business”; etc. Elaborate here if the general area is “Other.”

11. Submitting Organization and Address, identify the organization responsible for the software as completely as possible, to the Branch or Division level, but including Agency, Department (Bureau/Administration), Service, Corporation, Commission, or Council. Fill in complete mailing address, including mail code, street address, city, state, and ZIP code.

12. Technical Contact(s) and Phone: Enter person(s) or office(s) to be contacted for technical information on subject matter and/or operational aspects

of software. Include telephone area code. Provide organization name and mailing address, if different from that in item 11.

13. Narrative. Describe concisely the problem addressed and methods of solution. Include significant factors such as special operating system modifications, security concerns, relationships to other software, input and output media, virtual memory requirements, and unique hardware features.

Cite references, if appropriate.

14. Keywords. List significant words or phrases which reflect the functions, applications and features of the software. Separate entries with semicolons.

15. Computer Manufacturer and Model. Identify mainframe computer(s) on which software is operational.

16. Computer Operating System. Enter name, number, and release under which software is operating. Identify enhancements in the Narrative (item 13).

17. Programing Language(s). Identify the language(s) in which the software is written, including version; e.g., ANSI COBOL, FORTRAN V, SIMSCRIPT 11.5, SLEUTH II.

18. Number of Source Program Statements. Include statements in this software, separate macros, called subroutines, etc.

19. Computer Memory Requirements. Enter minimum internal memory necessary to execute software, exclusive of memory required for the operating system. Specify words, bytes, characters, etc., and number of bits per unit. Identify virtual memory requirements in the Narrative (item 13).

20. Tape Drives. Identify number needed to operate software. Specify, if critical, manufacturer, model, tracks, recording density, etc.

21. Disk/Drum Units. Identify number and size (in same units as “Memory”—item 19) needed to operate software. Specify, if critical, manufacturer,

model, etc.

I 22. Terminals. Identify number of terminals required. Specify, if critical, type, speed, character set, screen/line size, etc.

23 Other Operational Requirements. Identify peripheral devices, support software, or related equipment not indicated above, e.g., optical character devices,

facsimile, computer-output microfilm, graphic plotters.

24. Software Availability. Mark the appropriate box which best describes the software availability from among; Available to the Public, Limited Availability

(e.g.: for government use only), and For-ln-house Use Only. If the software is “Available”, include a mail or phone contact point, as well as the price and form in which the software is available, if possible.

25. Documentation Availability. Mark the appropriate box which best describes the documentation availability from among: Available to the Public, In- adequate for Distribution, and For In-house Use Only. If documentation is “Available”, include a mail or phone contact point, as well as the price and

form in which the documentation is available, if possible. If documentation is presently “Inadequate”, show the expected availability date.

,26. For Submitting Organization Use. This area is provided for the use of the organization submitting this summary. It may contain any information

^ deemed useful for internal operation.

GPO ; 1974 O - 554-665
NBS-114A (REV. i-sci

3. Pui)lication Date

May 1981

U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET (See instructions)

1 . PUBLICATION OR

REPORT NO.

NBSIR 81-2250

2. Performing Organ, Report No,

4. TITLE AND SUBTITLE

Estimating Area Cost Factors for Military Construction Projects;

Computerized Approach

5. AUTHOR(S)

Eobert E. Chapman and Bruce E. Thompson

6. PERFORMING ORGANIZATION (If joint or other than NBS. see instructions)

national bureau of standards

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

7. Contract/Grant No.

8. Type of Report & Period Covered

9.

SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

Directorate of Engineering and Services Naval Facilities Engineering C<2nimand

Department of the Air Force Department of the Navy

Washington, D. C. 20330 Washington, D. C. 20390

10.

SUPPLEMENTARY NOTES

Office of Chief of Engineers

U . S . Amy

Washington, D. C. 20314

[j^ Document describes a computer program; SF-185, FIPS Software Summary, is attached.

11.

ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bi bliography or literature survey, mention it here) This report describes a computerized procedure for estimating area cost factors

for military construction projects. The empirical basis for this procedure rests

upon the results of an econometric analysis of over 500 military construction

projects. Technical and empirical evidence from a wide variety of published

sources were also used to provide supplemental information on wage rates, material

prices, and the level of construction activities in the localities where the

projects were undertaken. This report is intended to serve as a user manual for

military personnel concerned with the problem of periodically updating the ama

cost factors for each service ’ s installations . A series of technical appendices

are also included which describe the theoretical underpinnings of the econometric

models which constitute the core of the computerized procedure as well as provide

samples of computer output and a complete listing of the computer program.

12.

KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolons)

Applied economics; construction; cost; estimation; location factors;

model building; statistical analysis.

13. AVAILABILITY

Unlimited

I I For Official Distribution. Do Not Release to NTIS nn Order From Superintendent of Documents, U.S. Government Printing Office, Washington, D.C.

20402.

Ey] Order From National Technical Information Service (NTIS), Springfield, VA. 22161

14. NO. OF

PRINTED PAGES

76

15. Price $9.50

USCOMM-DC 6043-P80 '