Q2 Z2,(Q2) Z2(Q2) - Institute for Water Resources - U.S. Army

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A. Total Horsepower TABLE 21 CROSS SECTION INDIRECT COST r 2 = .57 Sample Size = 84 Standard Error of Estimate = 0.11626 Intercept = -1.13876 Variable Name Time Index (times 10 -1) First Calendar Quarter Second Calendar Quarter Third Calendar Quarter log Horsepower (times 10-5 ) lo 0 c, 10 ELM (times 10-7 ) Dependent Variable: log 10 Indirect Cost/EBM (times 10 ° ) B. Number of Towboats r 2 = .61 Sample Size = 84 Standard Error of Estimate = 0.11089 Intercept = -1.22234 _ Variable Name Time Index (times 10-1 ) First Calendar Quarter Second Calendar Quarter , Third Calendar Quarter 1°810 Number of Towboats (times 10-2 -2 ) 1°8 10 EB`i (times 10 -7 ) Dependent Variable: log lo Indirect Cost/EBM (times 10 ° ) Regression Mean Coefficient t-Value • 0.32857 0.04107 0.43167 0.25000 0.09268 2.34259 0.25000 0.05015 1.39720 0.25000 0.04941 1.37036 -0.45576 0.09230 0.49784 -0.19924 -0.70037 -3.35663 -0.44298 Mean 0.32857 0.25000 0.25000 0.25000 -1:02363 -0.96562 -0.44298 130 Regression Coefficient t-Va]ue 0.04862 0.53887 0.06884 1.89323 0.05169 1.50993 0.05424 1.58703 0.23946 2.81235 -0.99916 -0.59324
C. Net Tons of Barge Capacity TABLE 21--Continued CROSS SECTION INDIRECT COST / r- = .65 Sample.Size = 84 . Standard Error of Estimate = 0.10520 Intercept = -0.91246 . Variable Name Time Index (times 10- , 1 ) .First Calendar Quarter Second Calendar Quarter Third Calendar Quarter ' log io Net Tons of Barge Capacity (times 1O, -t ) . . . log io EBM (times 10 -1 ) Dependent Variable: log io Indirect Cost/EBM (times 10 ° ) D. Number of Barges r 2 .64 Sample Size = 84 Standard Error of Estimate = 0.10626 Intercept = 0.10626 Variable Name Time Index (times 10 -1 ) . First Calendar Quarter Second Calendar Quarter Third Calendar Quarter . lor, '3 10 Number of Barges (times 10-3 ) 1oa°10 EBM (times 10 -7 ) Dependent Variable: logio Indirect Cost/EBM (times 10°) Regression Mean Coefficient t-Value 0.32857 0.01911 0.22338 0.25000 0.33510 3.99459 0.25000 0.04656 1.43373 0.25000 0.04145 1.27516 -0.37330 -0.66452 -4.16424 -0.96562 -0.16503 -1.36981 -0.44298 Regression Mean Coefficient t-Value 0.32857 -0.02011 -0.22993 0.25000 0.13822 4.00942 0.25000 0.04630 1.41121 0.25000 0.04095 1.24661 -0.45985 -0.64527 -3.93314 -0.96562 -0.12424 -0.91772 -0.44293 131
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c,q /kao, PROPERTY OF THF H S. GOVE
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INSTITUTE FOR WATER RESOURCES In 19
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NORTHWESTERN UNIVERSITY AN ECONOMET
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ACKNOWLEDGMENTS LIST OF FIGURES •
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Figure FIGURES Page 3.1 Two-Market
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Table Page 4.12 Rail Rate Regressio
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Table 4.A.5 Rate Regression Rail Qu
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This paper presents an economic mod
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All transport modes are designed to
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CHAPTER II REVIEW OF THE LITERATURE
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The first significant generalizatio
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artificially contrived solution met
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trannportnLion, thin neglect ham cP
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to the mode under consideration, cr
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that even if the reasoning is 'corr
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competition, that is where the qual
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His estimating process is divided i
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Table 2.1 COMMODITIES CARRIED ON TH
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- 15 In a recent volume on the de=a
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aggregation over regions for each c
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for each of the modes under the ass
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ail rates, and here he encountered
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had statistical significance; howev
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flows with actual shipments. 21 The
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CHAPTER III THE TWO-MARKET MULTI-MO
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the market price in A it is obvious
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P b P o P a T r 0 Fig. 3.4 -- Equil
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for all quantities, we conceive of
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0 (3.6.A) (3.6.B) Q 2 Fig. 3.6 -- T
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• Q2 Qi Q0 Fig. 3.7 -- Two-Mode M
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preference. He pays money today for
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Situation II: Producer Ownership. T
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little consideration will reveal th
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considered these costs in several f
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Then, to calculate the rate of chan
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(T1) (T2) The effect upon Q of an i
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(3.A.7) (3.A.8) APPENDIX A TO CHAPT
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(3.A.17) (3.A.18) ■FQ 5-(43-- -7,
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term more negative and, since it is
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and its inverse (3.B.8) T c • C(Q
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Now, going back to equation (3.3.7)
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APPENDIX C TO CHAPTER THREE The Two
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product to be transported, Q1 units
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(3.C. 3) ,(3.C.6) The monopolist's
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To obtain the greatest profits, the
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.1., OA The sign of — is only sli
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(4.11) (4.12) (4.13) (4.14) 111 Tc
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(4.26) (4.27) (4.28) (4.29) (4.30)
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The tons figure is the total tonnag
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Since the aim of this study is to e
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Distance ' Quantity Rate Eq. (4.33)
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Distance Quantity Rate Eq. (4.33) (
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Distance Quantity Rate Eq. , Source
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Distance Quantity Rate . Eq. Distan
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where R E average, revenue received
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• Table 4.8 332.42 808.54 478.58
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269.02 931.44 900.75 0.98 0.98 0.97
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Table 4.12 RAIL RATE REGRESSIONS FI
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1. date of the freight bill. 2. ori
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(4.41) Rik ■ 0 30 + 0 31 Mik + 0
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making is usually taken to refer to
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Total 728 79,603 Reduction due to m
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Source of Variance Total Reduction
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there is a wide difference between
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All Commodity Classes. Table 4.20 c
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Source of Variance Total 100 599,25
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Intercept Distance Quantity Density
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Intercept Distance Quantity Density
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stability and density showed very l
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groups into STCC commodity groups,
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The reduced form of this system is
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Exogenous , Changes(X) Transport de
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the quantity of commodity k transpo
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Regression Distance < 200 mi. Rail
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Regression Distance Rail Motor Dist
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increase with distances. This is ra
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Table 4.33 contains the derived rat
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Sample Regression Size Intercept M2
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Mode Int. Mode Sample Size Rate Tab
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Mode Sample Size Table 4.38 STCC 32
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Sample Regression Size Intercept Di
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Table 4.42 STCC 37 - TRANSPORTATION
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the three-mode model. Table 4.43 di
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Summary of the Empirical Results In
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Table 4.45 FREIGHT RATE DATA ANALYS
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Commodity Group II III IV V Total C
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Group Mode . I Truck Rail Water /I
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shipments. After a lengthy analysis
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for Group III is positive, large an
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of the underlying structural parame
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Table 4.49 DEMAND REGRESSIONS FINAL
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• supply The model assumes that t
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Commodity Group Table 4.50 DEMAND A
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APPENDIX A TO CHAPTER FOUR The Effe
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Table 4.A.2 RATE REGRESSION RAIL QU
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Table 4.A.4 RATE REGRESSION RAIL QU
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The overall tendency appears to be
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CHAPTER V SUMMARY AND CONCLUSIONS R
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theoretical basis for their empiric
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competitive industries. Applying th
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in the appendix to that chapter. Th
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BIBLIOGRAPHY Baumol, W. J., "Calcul
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United States Department of Commerc
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NORTHWESTERN UNIVERSITY A MODEL OF
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CHAPTER IV EMPIRICAL RESULTS . Page
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. INTRODUCTION Our goal is to study
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Other studies have been done by the
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. Recently air freight has grown aw
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• For instance, suppose a firm ha
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eceive the same criticisms as above
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Per Cent WA Decrease From Current L
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• Cargo . Brewer's analysis depen
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A different type of approach, is ta
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These substantial estimates of elas
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and the consumption points. These a
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Initially, the determinants of a fi
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axis. Q is the quantity the firm wo
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Arc elasticity of the associated tr
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• same A*es (-p)/-11 Skto 4441.
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Suppose that the range of one choic
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is better than getting P 2 tomorrow
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A, At the kink P . Any_further rais
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market price; or inventory costs ma
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The shipper must pay a transport bi
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quantity transported of Z decreases
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The analysis yields a downward slop
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of each market and calculates each
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If more consumption points ,are add
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or ( 5 1) . 1. Q-14.)4 `("P)EXarg (
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4. 0 -A? 040- Net MR 1 0 so. Ira."
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To determine the demand curve for t
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I • The above equations (1-4) wer
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(I). 1■1 (7). Id. (8). •a 0.0.1
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• goods arrive (so that Q A+Q S g
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k The optimal amounts of QA and Q s
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it has been used in economics. Basi
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An analogous relationship exists fo
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• • (11). Now a probability dis
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--_.—..---...........AawmarA D SA
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, (1). APPENDIX TO CHAPTER III SENS
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decreases. Proper choice of P rA (X
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products, have different cost funct
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The above data falls short of the q
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lower than air rates. It rises more
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One of the objectives of the study
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a. Regression equation TABLE IV-1 r
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significant. 8 It was, therefore, d
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in large tonnages tend to have a lo
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T .A T ° S Highest value per pound
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. In addition, only the smallest qu
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Here the deviations are zero. The r
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certain range, the demand estimates
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expected as goods in the discrimina
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• BIBLIOGRAPHY [1] Air Cargo Maga
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[24] 2 Study of the Possibilities f
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[42] Dawson, Michael, "A Technique
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[62] Gorham, G., Sealy, K.R. 1 and
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■•■•■■•••••
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[100] Richards, Anthony, The Role o
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[120] Traffic World Marketing Study
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! i \ NORTHWESTERN UNIVERSITY FREIG
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While working on this dissertation
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BIBLIOGRAPHY Anderson, T.W. "An Int
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VITA MICHEL VINCENT BEUTHE Born in
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of cost iv iazroduced at once along
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In the present theoretical formulat
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It is possible to generalize this m
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however, because of their nature, t
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ij xo ij ,Diagram 3, . 0 X ij of th
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equal to+ where E is the median of
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CHAPTER II Discrimination With One
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which is,.in this case, the only q
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Notc that the first subscript of a.
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I .' 1) (22) P 1 (X) = (25) Therefo
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(34) P 2 (X) (36) 1 = 1 a b c ' and
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CHAPTER III An Application - Corn T
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time the draft is honored by the co
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2. Critique of the Data. We must no
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made through questionnaires to coun
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we can still hope to obtain satisfa
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common and contract carriers are co
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Table II. Rail Time Regressions: Ti
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3. The Statistical Results. After t
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Table IV gives the discriminant fun
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February non-weighed July weighed T
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the binary problems, when the choic
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Table VII Probabilities that an obs
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Table VIII, Probability of Correct
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significantly different from the 'n
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-X _21 5.15 L4.45 TRUCK RAIL lalm
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CHAPTER IV. A Predictive Model of R
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C ab /C a is smaller than one, the
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II. Rail-Water Competition: One Por
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Until now, no attention has been pa
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9 ) (Z a - kZ b ) = C w /C r Zab +
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shipper. In the reality of competit
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DIAGRAM 5 For the most interesting
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DIAGRAM 7 waterway may be numerous.
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Note the restriction of Y to its ab
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the road-water route. In (24) C t (
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Squaring both sides, one obtains an
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interesting expressions. However, t
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CHAPTER V. This chapter attempts to
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TOTAL . COST D = -(L r - L t ) 2 Th
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2. Two Markets Model. subject --co
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X 0, X 2 - 0. It can readily be see
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the river does not have any --, but
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:sLY: x rail 0 truck 0 rail and tru
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'NLY: K rail 0 truck 0 rail and tru
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Table XI. Rail Rates Regressions: C
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mileages. The reason why this ratio
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Table XIII. Boundary Equations. Wat
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DIAGRAM 21 Figure T shows the actua
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truck sample is small ( 148 origins
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In this application of the spatial
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NORTHWESTERN UNIVERSITY LIBRARY Man
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in the dissertation. In addition, h
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Analysis of Tow in Motion 66 Introd
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Table • TABLES Statistical Result
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deepening or widening the channel,
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lines and isoquants. This locus is
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limited to the cost and production
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problem because engineers also atte
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are ignored. Making sure that the r
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variables, the form of the basic re
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family of cost curves obtained in t
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economies of scale exist in ihe tra
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in which R = resistance, in taw-rop
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(2)marginal productivity of the boa
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conditions are not always met in pr
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production relationship, e.g., a ma
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Howe's production and planning mode
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of the barge coefficient seemed to
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1962 counterparts. However, only (1
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A 10 peicont increase in all inputs
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proportion of constant costs. Typic
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In short, cost was estimated as a f
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o f cars, etc.). Each is then multi
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haul. The variable (Z/X) was used i
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In the switching process--which con
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defined to be the percentage change
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other production analysis of rail i
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of transportation, the inputs contr
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It will be convenient to define T f
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vchicles, is considered to be a poi
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F t (v) = B/v. 6 Therefore, the equ
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The graphical expression of Equatio
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And the distance traveled, D c , du
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CHAPTER IV LINEHAUL PROCESS FUNCTIO
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Form of Process Function The proces
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particular . trip', that tonnage ma
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ostimated from a capacity cable for
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The function was originaliy fit by
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were greater than 11 miles per hour
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effective-push functions will be ex
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ilotilla. These assumptions will no
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Upon testing the hypotheses indicat
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for in the first case tows were sem
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a 0 / V I HP 3000 - 12 - 225 • H
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3.5 3.0 1.5 5.. 2.0 7, 4.0 ■•
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A final note concerning the effect
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predict the time required for trave
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Given the tonnage, 0, to be carried
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existence. For example, the locks o
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If all locks on the waterway arc tr
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loaded ones in 1950; therefore p is
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T L -2; Single Double Locking Locki
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u T L 1 Table 4.7 INDIVIDUAL AND SY
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it would leave the system. Alternat
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The government should incur the cos
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I si,:e was 3.1 bares. The small av
Page 543 and 544:
To simplify the analysis all delay-
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characteristics and delays. Therefo
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Equation (4.37) divides the total :
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Xore confidence may be attached to
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Recapitulation of Tow Linehaul Proc
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function. The difference beiween th
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S -, speed of water, in miles per h
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y the above analysis, but for more
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econoinic analysis of the rail linc
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deceleration, Equation (3.8). Moreo
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Then the cargo weight of the ith ca
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(4, 6, or 8), the weight of the loc
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Analysis of Train in Motion Introdu
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and F(v) = 1.3w c + 29a 0.045w c v
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Adiustment for Grade and Curvature.
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Curve resistance, like grade resist
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F . 0 VI Fd(v) F (v) t Fig. 5.1 --
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and (5.26), and 2-miles-per-hour sp
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per trip into several components, e
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N t = number of trains on a given r
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Table 5.1 STATISTICAL ANALYSIS OF T
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Each of the terms V f and C represe
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nowever, in the case of the rail li
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-, 1 9, D 0 ,- ._ 200 ! i 175 '—
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Horsepowe r ( in t hou sa n ds ) 3
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exceeded 6,000 horsepower, for at p
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Curvatures of greater than 5 degree
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hohavior of rail costs. First, the
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eing charged at the higher rate. Th
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2. If train speed is greater than o
Page 603 and 604:
maximula attainable horsepower of t
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price for each locomotive unit from
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I L' is given by (0.5)($94HP L - $4
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Figure 5.4 displays a set of short-
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Economics of scale, in fact, seem t
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Tab1e 5.8 LONG-RUN MARGINAL COST OF
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obtained this way may then be added
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The estimating methods for each of
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Cos t per ton -mi le (m ;1 1s ) 7.2
Page 621 and 622:
CHAPTER VI SUMMARY AND CONCLUSIONS
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eached for acceleration, which take
Page 625 and 626:
wide range of output would have to
Page 627 and 628:
Isoquants between car and locomotiv
Page 629 and 630:
eported in the dissertation will in
Page 631 and 632:
10. M. Bronfenbrenner and P. H. Dou
Page 633 and 634:
13. A. V.ctor Cabot and Arthur P. H
Page 635 and 636:
7. There are in fact three differen
Page 637 and 638:
26. Eric Bottoms, "Practical Tonnag
Page 639 and 640:
19. Hay, An Introduction to Transpo
Page 641 and 642:
BIBLIOGRAPHY American Railway Engin
Page 643 and 644:
Howe, Charles M... "Methods for Equ
Page 645 and 646:
Soberman, Richard. "A Railway Perfo
Page 647 and 648:
NORTHWESTERN UNIVERSITY ESTIMATION
Page 649 and 650:
TABLE OF COIMETS Page Chapter I. In
Page 651 and 652:
CHAPTER I INTRODUCTION AND REVIEW O
Page 653 and 654:
On the other hand, the statistical
Page 655 and 656:
and capital Outlays are also treate
Page 657 and 658:
TABLE 1 SUMMARY ESTIMATES OF RAILRO
Page 659 and 660:
C (X) FIGURE • ■ 9
Page 661 and 662:
The effects of two types of classif
Page 663 and 664:
egression equations will produce bi
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S = speed in miles per hour W = wid
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(6) S = h(HP, L, B, H, D, W) The ac
Page 669 and 670:
stock which remains idle. Under the
Page 671 and 672:
The planning function also exhibite
Page 673 and 674:
Of the production functions, (13, 1
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sources of data. Despite the use of
Page 677 and 678:
The reader should note several them
Page 679 and 680:
from variations in rates based on v
Page 681 and 682:
service the firm would want to set
Page 683 and 684:
oat output, or effort, is not propo
Page 685 and 686:
this level of disaggregation are ex
Page 687 and 688:
CHAPTER III A STATISTICAL PRODUCTIO
Page 689 and 690:
A second way of generating data inv
Page 691 and 692:
variables, even if it is not accura
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Three major inland waterway firms p
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from changing depth or stream flow.
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made for each. (In the log-linear r
Page 699 and 700:
•Ps Variable Name Riven Districts
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Variable Name River Districts Port
Page 703 and 704:
La Variable Name River Districts TA
Page 705 and 706:
Variable Name River Districts TABLE
Page 707 and 708:
t..n .....1 TABLE 6 . . VARIABLE ME
Page 709 and 710:
A. Linear Regression (Arithi.etic M
Page 711 and 712:
are roughly comparable across all c
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termed "labor embodied technologica
Page 715 and 716:
TABLE 8 COMPANY ONE LINEAR REGRESSI
Page 717 and 718:
the other monthly coefficients indi
Page 719 and 720:
CHAPTER IV AN ANALYSIS OF DIRECT TO
Page 721 and 722:
with the use of dummy variables. To
Page 723 and 724:
A more direct method, and the one e
Page 725 and 726:
. cost In using; for example, , cro
Page 727 and 728:
• ,,, • .. -Excluded Variables
Page 729 and 730: 200,000 EBM per year) comes to abou
Page 731 and 732: Form C weights have limited accurac
Page 733 and 734: study as to the level of output to
Page 735 and 736: The firm in the sample operates a l
Page 737 and 738: would tend to be slightly higher co
Page 739 and 740: 3. other bulk 4. petroleum products
Page 741 and 742: In addition, river districts with s
Page 743 and 744: where: Cost = annual total direct b
Page 745 and 746: 1964 1965 Variable Name Barge Type
Page 747 and 748: TABLE 13 F-TESTS FOR BARGE COST REG
Page 749 and 750: tend to rise with increases in barg
Page 751 and 752: ing is quite consistent with a prio
Page 753 and 754: TABLE 16 PERCENT COMMODITY REGRESSI
Page 755 and 756: arge was to ship one more commodity
Page 757 and 758: 1 are the costs of operating and ma
Page 759 and 760: preparation of barges is necessary
Page 761 and 762: estimated was the same for all thre
Page 763 and 764: TABLE 17 DIRECT BARGE EXPENSE r 2 =
Page 765 and 766: Variable Name TABLE 19 TERMINAL EXP
Page 767 and 768: considerable growth in the past twe
Page 769 and 770: also be used in conjunction with di
Page 771 and 772: to an already scheduled tow). Two k
Page 773 and 774: The terminal results are quite tent
Page 775 and 776: The five firms in the sample repres
Page 777 and 778: sure the extent of this activity, a
Page 779: 1 linear form of- the functions hav
Page 783 and 784: Indirect cost is the same for towbo
Page 785 and 786: A. Total Horsepower TABLE 22 CROSS
Page 787 and 788: 1 .‘ A. Total Horsepower TABLE 23
Page 789 and 790: to scheduling. In addition, we obse
Page 791 and 792: :CHAPTER VII SUMMARY AND CONCLUSION
Page 793 and 794: the coefficients of the dummy varia
Page 795 and 796: . The coefficients of the dummy var
Page 797 and 798: Supporting results for neutral tech
Page 799 and 800: port agencies. A considerable amoun
Page 801 and 802: I to inland waterway operators, sin
Page 803 and 804: Footnotes--Continued 7 Howe, Jan.,
Page 805 and 806: Footnotes--Continued This is also w
Page 807 and 808: Bibliography--Continued Interstate
Page 809 and 810: UNCLASSIFIED Security Classificatio
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Q2 Z2,(Q2) Z2(Q2) - Institute for Water Resources - U.S. Army

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