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This dissertation has been
microfilmed exactly as received66-13,705
HOGG, Howard Carl, 1935-AN ITERATIVE LINEAR PROGRAMMING PROCEDUREFOR ESTIMATING PATTERNS OF LAND USE.
University of Hawaii, Ph.D., 1966Economics, agricultural
Univemity Microfilms, Inc., Ann Arbor, Michigan
AN ITERATIVE LINE~~ PROGRAMHING PROCEDURE
FOR ESTIMATING PATTERNS OF LAND USE
A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF THE
UNIVERSITY OF HAWAII IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN AGRICULTURAL ECONQ~ICS
JAi'lUARY 1966
By
Howard Carl Hogg
Thesis Committee:
Arnold B. Larson, ChairmanLudwig Auel'"Edmund R. BarmettlerKyohei SasakiFrank S. Scott, Jr.
ACKNOWLEDGMENTS
The method of analysis employed in this investigation is based
upon suggestions made by Arnold Larson. I am very g~ateful for the
assistance and for his continued encouragement throughout the study. I
also want to thank the other members of my thesis committee:
Frank Scott, Jr.; Edmund Barmettler; Kyohei Sasaki; and Lud~g Auer.
In addition, I would like to acknowledge the invaluable contributions
of Tamotsu Sahara, Iwao Kuwahara, Mrs. Faith Fujimura, and Mrs. Barbara
King.
Financial support for part of this work was provided by the
Department of Land and Natural Resources, State of Hawaii. In this
connection, I am especially grateful to Paul Tajima for his efforts in
making funds available. The Statistical and Computing Center of the
University of Hawaii generously allocated several hours of computer time
for program testing and data analysis.
TABLE OF CONTENTSPage
THEORETICAL BASIS OF LAND USE PATTERNS
• • • • • 0 • 0 • 0• 0 • • • • • 0CHAPTER
CHAPTER
10
II.
INTRODUCTION •
Objectives
Procedure •
• • • • 0
• • •
• • • • • •
. . . . . .• • • • • • •
• • • • • • •
• • • • 0 •
1
1
2
4
Linear Programming and Production Allocation
Model Required for This Study
Problems • • • • 0 • • • • • · . . . . . . . .· . . . . . . . .
5
8
Basic Assumptions •••••••• • • • •• 9
Economic Model and Estimating Procedure •• 10
• • • • • • • • • • • •
• • • •
• • • • •
14
22
24
· . . . .· . . . .. .• •• •
• •
Mathematical Model •
Limitations of Model
BASIC DATA •••••III.CHAPTER
Land Productivity Classification •• • • • •• 24
Production Costs and Yields by Land
Productivity Class. • • • • • • • • • • • •• 28
Pineapple • • • • • • • • • • • • • • • •• 28
Supply • • • • • • • • • • • • 0 0 • • • • •
Crop Group I • • • • • • • • • • • • • • • • •
Crop Group II • • • • • • • • • • • • • • • • •
Dernand • 0 • • • • • • • • • • • • • • • 0 •
• • • • • • • • • • • • • • • • • •
ESTllo1ATED MARKET SUPPLY AND DEMAND FUNCTIONS.
29
32
50
64
64
65
66
68
• •
• • • • •
• • • • •. . . . . . .• • • • • • • • • •
Vegetable Crops
Orchard Crops
Pasture
IV.CHAPTER
ii
Page
CHAPTER V. ESTIMATED LAND USE PATTERNS • · • • • • • • • • • 78
Land Use Patterns for the Entire Area • • • • • 78
Land Use Pattern IA • • • • • · • • • · • • 82
Land Use Pattern IB • • • • · • • · • • · · 86
Land Use Pattern IC • • • • • • • • • • · • 88
Land Use Pattern ID • • · · • • · · • · · • 90
Land Use Pattern IE • · • • • • · • · • • • 92
Land Use Patterns for Hoolehua • • · · • • • • 95
Land Use Pattern IIA. · · · • • • • • • · • 95
Land Use Pattern lIB • • • • • • • • • • • · 96
Land Use Pattern IIC. • • • • • • • • • • • 97
Land Use Pattern IID. • • • · • • • • • 98
Stability of the Land Use Patterns • • • • • • 99
Derived Labor Demand Curves for Hoolehua • • · 100
CHAPTER VI. SOME ECONOMIC EFFECTS OF EXPANDED PRODUCTION ON
EXISTING STATE PRODUCERS, THE STATE AS A WHOLE,
AND THE CONSUMER · • . • • · • • • • • • • • • • 104
Changes in Producer and State Output • • • • • 104
Changes in Producer and State Income • • · • • 107
Changes in the Wholesale Price Level ~ • • • · 109
CHAPTER VII. SOME ADDITIONAL CROPS THAT OFFER POTENTIAL FOR
• • • • • • •
Vegetable Crops •
• • •· . . III
III
113
• •• •
• • • •
• • • •• •
· .· .· .· .• •• • •
· . . .
· . .Orchard Crops •
ACREAGE EXPANSION
iii
Page
CHAPTER VIII. S~~1ARY AND CON:LUSIONS ••••••• • • • • •• 116
Surmnary • • • 0 • • • • • • 0 • • • • • • • •• 116
Implications • • • • • • • • • • • • • • • •• 117
Validity of Findings •••••••• • • • 119
Suggestions for Further Research • • • • • •• 121
APPENDIX A.. DESCRIPTION OF LAND TYPES • • • • • • • • • • • 123
APPENDIX B. IP~IGATION REQUIREMENTS • • • • • • • • • • • • • • , "0
.L "'0
Waimanalo. . . • • • • . . . . • • . . . . . • • 128
Waianae Kai and Hoolehua • • • • • • • • • • • • 130
APPENDIX C.
APPENDL'{ D.
DEMAND CURVE TABLES
SUPPLY CURVE TABLES
. . . . . . . . . . . . . . . .• • • • • • • • • • • • • • • •
132
136
APPENDIX E. COMPUTING FACILITIES REQUIRED FOR DATA ANALYSIS •• 140
Computing Time by Phase • • • • • • • • • • • •• 140
Computing Time Required for Estimating Land
Use Patterns • • • • • • • • • • • • • • • • 140
REFERENCES • • • • • • • • • • • 0 • • • • • • • • • • • • • • • 143
CHAPTER I
INTRODUCTION
Development of land resources poses many problems for the planning
agency. From the viewpoint of the economist perhaps the most important
problems are those relating to the desirability of a project in terms
of some income or efficiency objective. Typically, a project objective
is stated as the maximizat!on of individual, regional, or national
income depending upon the jurisdiction of the developing organization.
To effectively evaluate a land development, in terms of its objectives,
it is necessary to anticipate the pattern of land use that will likely
result in the project area. This study presents a quantitative approach
for estimati~g land use patterns when use of the project land is
restricted to agricultur~~ Planning problems concerned with agricul
tural as compared to non-agricultural uses, project financing, condi
tions of repayment, and form of tenure are ignored. The empirical
application of the estimating procedure consists of estimating land use
patterns for a project currently being undertaken by the State of
Hawaii.
Objectives
The primary objective is to develop a procedure for estimating the
perfect competition eqUilibrium production of several crops, on lands
of varying quality, in spatially separated producing areas. Market
supply and demand equations are include~ in the model so that the
patterns of land use ~ll be established by market forces. The model
indicates, by physical land productivity class and proje~t area, the
acreage used to produce each crop. It also gives the equilibrium
2
market price and quantity supplied for each included commodity.
The obj~ceive of the empirical applications of the model was to
estimate patterns of land use based on different wage rate, labor
availability, and unit size assumptions for several tracts of state
owned land that are included in a current development project. These
lands, which are located at Waimanalo and Waianae Kai on the Island of
Oahu and at Hoolehua on the Island of Molokai, make up the three
project areas considered in this study.
Procedure
The first step was to construct cost of production and yield
budgets, by land productivity class, for a group of crops that repre
sent most of the production alternatives faced by prospective farmers
in the project areas. These budgets are based upon existing cost of
production studies supplemented by interviews with crop specialists.
Because of limited resources, only those crops for Which cost studies
are presently available are included in the analysis. This group of
crops includes pineapple, pasture, papaya, apple banana, tomatoes, snap
beans, cantaloupe and Manoa lettuce.
Market supply and demand functions were developed for each crop
and included in the estimating model. This was done in an effort to
duplicate the market forces that actually contribute to the establish
ment of a land use pattern~ For the purposes of this analysis, it is
assumed that all vegetable crop production will be sold on the Honolulu
market 0 This market restriction is imposed because producers will not
export until the Honolulu market price falls to a point Where export
offers the most profitable outlet. This price would probably be some-
what lower than the West Coast price less transportation charges.
Available information suggests that under prevailing management prac
tices, which are assumed, this price would not be sufficient to cover
production costs (39; 49, p. 11). The estimating model is an iterative
linear programming system that allows for adjustments in supply from
existing producers as price changes and does not permit production to
exceed quantity demanded at any given price. This model constructs a
static equilibrium lur a specified number of crops while allowing them
to compete ~th one another for scarce resources as they would in the
market. The scarce resources are allocated to their most profitable
use.
3
4
CHAPTER II
THEORETICAL BASIS OF LAND USE PATTERNS
For the purposes of this study, economic rent is defined as the
difference between production costs, with opportunity costs added, and
total revenue. Opportunity costs in this case equal the level of rent
that could be earned in the next best use. The difference between
production costs and total revenue is defined as net returns. This
procedure varies from the conventional treatment of economic rent which
equates it to net returns (4, p. 159).
Ricardian rent theory relates levels of economic rent (net returns
by the above definition) to land quality. In the Ricardo model, price
is determined by the per unit production cost on the lowest quality
land needed to supply a single market. If this model is generalized to
include several crops, and the land qualities are defined as producing
regions, it is identical to the standard interregional programming model
formulated for multiple producing regions and a single market.
This chapter presents a procedure for estimating the regional
production of several crops to be sold in a single market, that
incorporates certain aspects of both the Ricardo and standard inter
regional models. In this study, unless otherwise specified, each
separate quality of land is considered a distinct producing region.
However, the identity of each land quality found in a project area is
retained so that patterns of land use can be constructed. These use
patterns indicate the acreage, by land quality, devoted to the produc
tion of a particular crop in each of the three project areas described
earlier. A project area may contain more than one quality of land but
must have uniform transportation costs. These use patterns are
5
identical to those implied in Ricardian rent theory if the latter is
generalized to the multiple crop case.
Linear Programming and Production Allocation Problems
Linear programming models relevant to the present investigation
can be classified into three groups. The first of these is the stand
ard interregional competition model of the Egbert-Heady t)ye (18 j
p. 218). This model features spatially separated producing and con
suming regions and fixed regional quantities demanded for each included
commodity. This model can be formulated to maximize net returns or
minimize production and transportation costs while meeting the specified
regional quantities demanded. The cost minimization problem is of
primary interest in the present case. Whittlesey and Skold (66) have
shown that the dual of this model constructs a stepped supply function
for each crop exchanged in a given market. A function of this type is
shown in Figure 1. The solid horizontal segments PIa, P2b, and P3c
represent production and transportation costs for three producing
regions. If a regional quantity demanded of Q3 is specified, market
price would be P3 which is the production cost in the least efficient
producing region supplying this market. With price set at P3 regions
one and two earn a positive net return. Region one, for example, earns
a net return equal to [(P3-Pl)(Ql-QO)].
The formulation of Yaron and Heady (67) represents the second type
of linear programming model relevant to the present study. Their model
accommodates a single producing and consuming region and declining
demand curves for several commodities by approximating the marginal net
revenue function with a step function as shown in Figure 2.
6
Figure 1. F-.coduct Supply Curve for .2 Consulling RegiQn
f~egionsContainin~ T~rce ?j:od~cin~
Po S'I
~_________ ______~ _;,l cIIIIIIIIIIIII
P2 ------ - -~i""'--------'! bIIiI•
Price,cost
Qo Q3Quantity
Figure 2. Step Approximation of rlarginal Net Revenue Function
MNR ::t MR-l'-IG-
$HNR
MNR2 1-----..lJ=====~
QoQuantity
7
Solution is achieved by considering each step of the function as a
separate activity (a sub-activity of the activity in question). Net
revenue equals the final MNR multiplied by the final quantity.
The third type of regional programming model features multiple
producing and consuming regions and a declining demand curve for a
single commodity. An example of this type of model is the beef cattle
feeding study by Schrader and King (55). Their model constructs
regional supply functions which allow market equilibria and correspond
ing regional production and supply patterns to be computed within the
program. The regional supply of carcass beef is a function of feeder
cattle, feed concentrates, and hay or other roughages, all of which can
be shipped between regions. Demand curves are incorporated by varying
the quantity restrictions and the values of the objective function in
successive approximations. These variations are made to be consistent
with estimated market demand curves.
Certain assumptions inherent to the above models limit their
usefulness in the present case. The Egbert-Heady model does not
incorporate downward-sloping demand functions. Inclusion of such func
tions would allow determination of the optimum quantity supplied to each
market, the corresponding market price, and the optimum level of produc
tion for each region rather than merely market price and the optimum
regional production corresponding to a predetermined quantity demanded
(or supplied, as supply equals demand) for each consuming market. The
Yaron-Heady approach fails here because it is not applicable to
multiple producing regions, and the Schrader-King formulation considers
only a single commodity and does not allow alternative uses to compete
for scarce resources as required by the present problem.
Model Required for This Study
A model incorporating multiple producing regions, a single con
suming region, and a downward-sloping demand curve for each of several
commodities is needed for the present investigation. There are two
possible approaches for constructing a model of this type. The first
would be to construct regional supply and demand functions for each
commodity, and determine the equilibrium prices and commodity flows by
quadratic programming. Quadratic programming occurs When the objective
function is non-linear resulting from a downward-sloping linear demand
curve~ A spatial price equilibrium model that could be adapted to this
problem has been formulated by Takeyama and Judge (62). As a second
approach the standard interregional model can be modified so that it
will accommodate a demand function.
The budget data used in this analysis assume constant production
costs on each quality of land. Regional supply curves based on these
budgets would be step functions, with each step representing a land
quality found within a particular project area (Which would correspond
to a producing region in the Takeyama-Judge model). These functions
could then be smoothed for adaptation to the Takeyama-Judge model.
Treating each land quality as Q r~oducing region results in a step
function identical to that shown in Figure 1. Because the product
supply function can be directly related to the step-function of the
standard interr~gionaimodel and because only one consuming region is
included there appears to be no real advantage in using the Takeyama
Judge model. Also, at present no computer program is available for
this purpose at the University of Hawaii and therefore the second
approach, modification of the standard interregional model, is used
8
9
here.
Basic Assumptions
Most interregional programming studies have certain assumptions in
common. These assumptions are listed below.
(a) The basic assumptions of all linear programming problems
apply, viz. (1) additivity of activities; (2) divisibility
of factors and commodities; (3) a finite number of activi
ties; (4) constant input-output coefficients; and (5) one
or more restrictions.
(b) The supply of land within each producing region is of a
uniform quality.
(c) The level of management is uniform, for each crop produced,
within each producing region. That is, all producers in a
given region have the same input-output coefficients.
(d) All inputs except land, and in a single case labor, are
assumed to be available in unrestrictive quantities at
tbeir current market prices.
(e) The system is static and refers to market supply and demand
o£ a single year.
(f) Producers seek to maximize net returns in a competitive
market.
In addition to those listed above, the present model makes the
following assumptions.
(g) The selected crops included in the model represent the
entire range of production choices faced by prospective
farmers in the project areas.
(h) The market demand curves of the model are independent.
10
Economic Model and Estimating Procedure
In this study the programming problem is solved by varying price
in successive program solutions. This procedure requires that prices
be increased just enough in each solution to allow the introduction of
the next best land as, for example, in Figure 1 from Pl to P2 to P3 and
Ql to Q2 to Q3 until mark~t demand is satisfied. The objective function
for this solution consists of the net returns earned by the respective
activities. A solution is obtained in this manner that is identical to
that of the cost minimization problem if the objective function values
are kept current as price is varied.
With multiple crops the following four conditions must hold for an
optimum solution:
(1) Total market supply equals demand simultaneously for all
crops.
(2) Market price is determined by production cost, including
opportunity cost, of the least productive region.
(3) Each producing region earns a net return consistent with a
single product price for each commodity exchanged in the
market.
(4) A single region producing more than one commodity earns the
same net return in each use.
These conditions are identical to those for the cost minimization formu
lation of the standard interregional model. Egbert and Heady (9, p. 4
of supplement) construct, from these conditions, a proof of static
short-run competitive equilibrium. This proof is summarized, and re
lated to the present model, in the next section of this chapter.
Bringing new agricultural land into production can be viewed as
11
moving a market from an existing equilibrium to a new one. The
availability of new land tends to shift the existing supply function,
causing the new equilibrium to be established. This process is illus
trated in Figure 3. The intersection of the existing market supply
curve (5) and market demand curve (D) represents ~he initial ~quilib
rium. When the new land is made available the market supply function
shifts to 51, establishing a new equilibrium. A smooth supply curve
(S) is used to represent the relationship between market price and the
quantity supplied by existing producers of this commodity because the
relationship is estimated by a regression model that results in a con
tinuous function. The new supply curve (51) is approximated by a step
function because production costs are assumed constant for each region.
For example, at a per unit cost of Cll the quantity Qll-QOl could be
gro~ in region one. The total market supply at thi& price is Ql1'
which equals the quantity from the newly developed area (Q11-QOI) plus
the original production (Q01-0) before development.
To establish an optimum solution for multiple crops, the program
first enters crop one wdth price set at Cl1 Which is the production
cost in the most productive producing region. Output at this price
equals Q11' which is less than the quantity demanded at this price,
therefore price is increased to C2l which allows the next best pro
ducing region to enter production. This process continues until supply
equals demand for this crop. Crop one now meets three of the require
ments for an optimum solution: (1) market supply equals demand at C31'
Q31; (2) market price equals the production cost in the least produc
tive region; and (3) net return equals [(C21-Cll)(Qll-POl)] in region
one and [(C3l-C2l)'Q2l-Qll)] in region two.
12
Figure 3. Hypot.hetical Supply and DCiil.:J.nd Functions for Tvlo. Crops
Price,cost
C21
Cll -- --/ir-j;,....----IIIIII
o
1
~sI DIIIIIIII
s
Quantity
Price,cost
Crop T,·;o
s
QuantityQ02
--------~-l SlI~D
------ I
/I II II II II II II I
o
13
The second step in the solution process is to enter crop two. The
net returns earned per acre of crop one are added to the per acre
production costs of crop t~ in regions where crop one was introduced.
This is equivalent to charging an opportunity cost to crop two con
sidering crop one the best alternative use at this point. Crop two is
now entered in the same manner as crop one until supply equals demand.
At this point crop two meets the first three requirements of an optimum
solution. The fourth and final requirement, that each region producing
more than one crop earn the same return in all uses, holds for both
crops. Region one now produces crop two only and earns [(C22-Cll)
(Q12-Q02)] + [(C3l+Cll)(Qll-QOl)] net returns. Region two is used in
the production of both crops earning a net return of [(C3l-C2l) (Q2l-Qu)]
in each case.
Because region one and part of region two have been bid away from
crop one supply is less than demand for this commodity which violates
the first requirement for an optimum solution. Adding the total net
return earned by both crops to the production costs of crop one for
each region in which they were introduced, as an opportunity cost,
allows it to be re-entered as before. The solution process is repeated
entering each crop on land classes of diminishing quality until supply
equals demand. The crops are re-entered until this condition (supply
equals demand) holds simultaneously for both crops. Only at this point
are all of the requirements met.
The objective function consists of the net returns earned by the
respective crops. As each crop is introduced on a particular land
class the objective function is modified so that the accumulated net
return is added to the objective function term of the appropriate
14
activityo The objective function must be constantly updated as the
solution proceeds from one stage of the solution to the next if the
competitive strength of the crop is to be accurately specified.
Under certain circumstances convergence of the system to a final
solution may be slow. The production costs of single crops in each of
the regions differ from one stage of the solution to the next. These
differences, for each region, equal the sum of the net returns earned
in the previous stage by the crop in question, and all crops subse
quently entered before the initial crop is re-entered. If it is
necessary to enter all of the crops a number of times before achieving
a solution, the competitive advantage of the better lands is reduced.
This results from adding subsequent layers of opportunity cost to the
production costs of each crop, which reduces the cost differences
between lands of different qualities. Reducing the cost differences
slows the rate of convergence.
The program includes a counter that is incremented each time the
final crop, of the group being considered, is entered. The solution
can be interrupted and intermediate results obtained by specifying the
number of entries that are to be allowed. This counter acts as a check
that can be used to prevent long machine runs resulting from slow
convergence. A discussion of several methods of forcing solutions in
these cases is discussed in Appendix E.
Mathematical Model
The formal linear programming model used in this study is
summarized below.
Xij • Level of j-th activity in i-th regiono
nrij = Net returns per acre of j-th activity in i-th region.
lij m Land resource required by j-th activity in i-th region.
Wij Q Quarterly labor requirement per acre of j-th activity in
i-th region.
~ij • Per acre yield of j-th activity in i-th region.
LCi • Land ~onstraint in i-th region.
Wi D Labor constraint in i-th region (Pattern IE only).
Qj D Quantity constraint of j-th activity for Honolulu market.
Pj • Market price of j-th activity.
eij ... Production cost, including opportunity rent, of j-th acti
vity in i-th region.
~e objective is to maximize
f(nr) • f1Xij • nrij
with each of j activities subject to the following constraints:
(a) Land constraint
~ li j • Xi j < LCiJ
(b) . Quantity constraint
The non-negativity assumption is:
Xij ~ 0
An iterative procedure was employed for estimating each optimum
land use pattern. This procedure systematically varies Qj and the
associated values of nrij until a final solution is achieved. The
requirements for an optimum solution are:
(a) t Xij • qij ... Qj
15
16
(b) Pj m elj , Where i a the least productive region in which
crop j is produced
... 0, otherwise
(d) Each region producing more than one crop must earn equal
net returns from each crop.
The above conditions must hold simultaneously for all activities.
The conditions given above are nearly identical to those offered
by Egbert and Heady (9, p. 2 of supplement) as proof of a static short-
run competitive equilibrium. Their proof applies to the cost minimiza-
tion formulstion of the standard interregional model. The conditions
for an equilibrium solution to a two product (A and B), single market,
problem are summarized below. Industry supplies for n regions are
given by:i~
(a) Qa" ~ qiaial
wi th industry demand equal to:
The equilibrium conditions are:
i:Sn(b) Qb - ~ qib
i-l
The cost of qia and qib is always less than or equal to the cost of
qi+l,a or qi+l,b Which allows regional returns for A and B to be
specified by:
Solution of the Egbert-Heady model results in the following revenue
conditions: (1) product A will be supplied by a producing region only
if it earns a net return larger than B; (2) only B will be supplied if
17
it earns the largest return; and (3) both A and B ~11 be supplied only
if they earn the same net return. The symbols are defined as follows:
Qa ... Equilibrium quantity of A
QJ,- Equilibrium quantity of B
qia .. Quantity of A supplied by i-th region
qib .. Quantity of B supplied by i-th region
Da .. Demand for A
~. Demand for B
Ka • Per capita consumption of A
Kb • Per capita consumption of B
p. Population
ita .. Net return of A in i-th region
itb .. Net return of B in i-th region
Yia • Yield of A in i -th region
Yib • Yield of B in i-th region
Pa • Market price of A
1b • Market prl ce of B
cia" Cost of producing A in. i-th region
cib ,.. Cost of producing B in i-th region
The major difference between the two models is that in the present
case Qa and Qb' as well as Pa , Ph, qia, qib, Ria, and Rib are deter
mined within the model. Also, in the Egbert-Heady model land rents or
regional returns (Ria and Rib) and product prices are determined in the
dual solution. Solving a two product problem with the present model
would result in a set of values for Qa' Qb' Pa , Pb' qia' qib' Ria' and
Rib- If the resulting Qa and Qb is then used in solving the Egbert
Heady model an identical set of Pa , Pb' qia, qib, Ria' and Rib would be
18
obtained. The following illustration shows the equivalence between the
two methods. This example utilizes two products, tomatoes (A) and
snapbeans (B), that could be grown in two newly developed areas
(Region 1 and Region 2) and are to be sold on a single market. The
symbols used are identical to those defined earlie~ except as indicated.
Given the market supply and demand functions:
Tomatoes Snapbeans
Demand;
Supply;
P m 25.64 - .0008 Qo P • 45.01 - .0142 QD
Qs • 3709.32 + 41.9292 P Qs. 945.12 + 12.7332 P
Where; p. Market price (cents per pound)
Qs • Quantity supplied by existing producers (1000 pounds)
Qo • Quantity demanded (1000 pounds)
Per acre production costs:
Tomatoes
Region 1; $4,243
Region 2; 4,284
Per acre yield (l000 pounds):
Tomatoes
Region 1; 31.2
Region 2; 34.0
Snapbeans
$6,336
3,750
Snapbeans
36.0
30.0
Available land in each region:
Region 1;
Region 2;
680 acres
56 acres
The following results were obtained by the procedure outlined in this
study.
Qa D 10,783,000 pounds
Qb· 1,091,000 pounds
19
Pa a 13.59 cents/pound
Pb = 13.63 cents/pound
qla a 324.3 acres
qlb a 0 acres
q2a - 19.6 acres
q2b· 36.4 acres
RIa. 0 dollars
RIb· 0 dollars
R2a • 340 dollars
R2b a 340 dollars
Total cost • 1,607,796 dollars
The Egbert-Heady version of this model was then solved. The objective
in this case is to minimize production costs while meeting the level of
demand specified by Qa and Qb. The primal solution gave the results
listed below.
Qa a 10,783,000 pounds (given)
Qb· 1,091,000 pounds (given)
q1a· 324.3 acres
o acres
q2a· 19.6 acres
q2b a 36.4 acres
Total cost • 1,607,796 dollars
The dual of this solution was not computed because the sources of value
that determine the imputed rents and product prices can be easily
traced. Product prices must be high enough to allow production costs
to be covered in all producing regions. The minimum per unit prices
that would accomplish this, in the present example, are:
20
Pa c 13.59 cents
Pb = 13.63 cents
The respective product demand curves indiuate that the amount taken off
the market at these prices is just equal to the amount produced (plus
the marketings of existing producers). The imputed rent for tomatoes
(Region 2) is equal to the difference between the per unit production
cost and market price multiplied by the tomato yield. Snapbeans must
match this return or be forced out of Region 2. In other word~, the
rent imputed to tomatoes becomes an opportunity cost to snapbeans.
Therefore, regional per acre net returns become:
Rla = 0 dollars
RIb = 0 dollars
RZa = 340 dollars
R2b = 340 dollars
The only difference in the results of the t~ methods is the inability
of the Egbert-Heady model to determine Qa and Qb.
Table 1 is provided to s~~~ how this model ~uld appear in a con
ventional simplex tableau. It will be noted that the C and Qj entries
have been left blank in Table 1. This was done because these values
are computed within the program and change with each stage of the
solution. The subscripts of the real activities (A) represent region
and crop, respectively. The coefficients corresponding to these activi
ties are the amounts of the respective factors required to produce one
unit of the activity. The other terms have already been defined.
The necessary data for estimating a land use pattern with this
model are listed below.
TABLE 1. BASIC SIHPLEX TABLEAU FOR LAND USE PATTERN IIA
C-4 0 0 0 0 0 0Resource or Activi ty Real Acti vi ties Di S lOsa1 Activities
C Activitv Level .Kj I AL2 AI.3 11.1 4 A2.1 A?? A2 :3 A?!.J. LC, , LC, ? Q1 Q? Q~ Q'~
0 Le1,1 680 1 1 1 1 1
0 LC1,2 219 1 1 1 1 1
0 Q1 31.2 26.6 1
0 Q2 18.3 15.8 I
0 Q3 52.0 47.0 1
0 Q4 36.0 32.0 1
N.....
22
(a) Production cost and yield data, by producing region, for
each crop to be included in the analysis.
(b) Demand functions for all of the included crops with
downward-sloping demand curves. Crops ~nth perfectly
elastic demand are included by entering the appropriate
return in the objective function for th~ activity.
(c) Supply functions for all crops to be included that do
not have perfectly elastic demand.
The program output includes the total market supply, price, and acreage
of newly developed land used for producing each crop.
Limitations of Model
The model used in this study accommodates downward-sloping demand
curves in a particular type of regional programming problem. This
represents some refinement over previous studies of this nature but is
still subject to a number of limitations. The more important limita
tions are listed below:
(a) Not all fanners within a region have the same input-output
coefficients.
(b) Farmers within a region may use different production
methods.
(c) Constant returns to scale may not exist over the entire
production range.
(d) The speed of convergence to a final solution may be slow
under certain conditions
(e) The supply curves of existing producers are assumed to be
independent.
(f) The market demand curves are assumed to be independent.
Thls may not be too important in the present case because
quantities of competing products were included as inde
pendent variables in several preliminary demand equations,
and were found to have no significant influence on price.
23
24
CHAPTER III
BASIC DATA
Most of the data used in this report exist in published form;
others are derived from unpublished manuscripts. The land classifica
tion material and production cost and yield budgets are based upon
existing studies. When these cost of production studies do not
distinguish between lands of different quality, cost and yield adjust
ments were made by utilizing published materials dealing with the
required cultural practices for the several crops. Information obtained
from interviews with Experiment Station, Extension Service, and
industry specialists was also helpful in making these adjustments.
Land Productivity Classification
The land productivity classification used in this study is that
developed by the Land Study Bureau, University of Hawaii. The basic
classification used by the Bureau is land type. "A given land type
includes a group of lands having equivalent physical productivities as
a consequence of similar chemical and physical soil features" (44,
p. 117). In the Bureau classification, land productivity ratings are
the common denominator for suitability classes on a state-wide basis.
These ratings "••• interpret the interacting complex influences of
climate, surface relief, drainage, wind velocities, soil characteris
tics, and cultural practices that are associated with each land type••• "
and relate the physical land quality to levels of output assuming
prevailing management practices (44, p. 127).
Master productivity ratings were first developed by the Bureau to
indicate the over-all suitability of a land type for agricultural
25
production. These ratings were established by a productivity index
that considers the character of the soil profile, texture of the sur
face soil, slope of the land, climate, and miscellaneous factors. This
procedure, which is a modification of the Storie Index Method, can be
summarized by the following formula (44, p. 128):
Land productivity index m A • B • C • X • Y
where:
A Q decimal equivalent of percentage rating for general character
of the soil profile.
B = decimal equivalent of percentage rating for texture of the
surface horizon.
C - decimal equivalent of percentage rating for slope of the
land.
X m decimal equivalent of percentage rating for site conditions
other than those covered by factors A, B, and C (salinity,
soil reaction, ~nd, etc.).
Y - decimal equivalenc of percentage rating for rainfall.
The actual percentage rating for each factor associated ~th a particu
lar land type is based on a state-~de rating scheme developed for
local conditions. Low quality lands would have a low index rating. As
the computed index approaches 100 per cent, land quality increases.
A single land type would not be equally suitable for all crops.
Because of this, single use ratings were developed by the Bureau to
indicate the SUitability of a land type for alternative single uses.
In general, the single use ratings are based on the same factors con
sidered in establishing the master productivity ratings. It was
necessary, however, to consider subjectively the added reqUirements
26
peculiar to individual uses. While the single use ratings are not as
objective as the master ratings, they do allow some control over a
major weakness of the index method. If a single factor has a lo~
percentage rating it could substantially reduce the level of the master
rating. If this over-all rating is then used for single uses it is
likely that the limiting factor will not be as restrictive in some uses
as in others. Slope, for example, is far more important When classify
ing vegetable land than when classifying pasture land.
In this study yields are associated with each individual land
productivity class by assuming levels of inputs that approximate the
modal state-wide level for each land class. The productivity ratings
are used as an indicator of physical quality and as a basis for mapping
areas of uniform quality from parcels containing several productivity
classes.
The Land Study Bureau uses lower case letters to indicate the
productivity of a land type in individual uses with land type and use
designated numerically. In Table 2, for example, land type 23i (i
designates irrigated land) is rated ~ for pineapple, ~ for vegetables,
~ for pasture, and 2 for orchard crops. The possible ratings range
from class a lands with the highest productivity to class ~ lands which
are unsuited for intensive agricultural uses. For the purposes of this
study the productivity ratings for individual uses are of primary
importance; however, the individual land type descriptions are provided
in Appendix A. The characteristics of the land areas utilized in this
analysis are given in Table 2.
27
TABLE 2. LAND TYPES, PRODUCTIVITY RATINGS,
AND ACREAGE OF LANDS UNDER STUDY
Land TypeY Productivity Rating by use~ At;reagetdLocation of Lands
Hoolehua 17i 1a 2a 6a 7a 2
11 1a 2b 6a 7a 678
3i ld 2c 6a 7b 219
7 le 2e 6e 7e 152
Waianae Kai 23i ld 2c 6a 7b 22
56i le 2e 6d 7e 1,008
57 le 2e 6e 7e 56
58 le 2e 6e 7e 410
Waimanalo 3i la 2a 6a 7a 5
4i 1a 2a 6a 7a 4
51 la 2a 6a 7a 47
8i lc 2b 6a 7b 31
9i 1b 2a 6a 7b 62
19i lb 2b 6a 7b 35
321 ld 2d 6b 7c 19
35i ld 2b 6a 7b 20
371 ld 2c 6b 7b 9
4li ld 2d 6b 7c 3
Waimanalo 421 ld 2c 6b 7b 60
47i 1d 2d 6c 7d 6
561 Ie 2e 6d 7e 104
28
TABLE 2. (Continued) LAND TYPES, PRODUCTIVITY RATINGS,
AND ACREAGE OF LANDS UNDER STUDY
Location of Lands Land Type~ Productivity Rating by Use§{ Acreage£!
57
58
le
le
2e
2e
6e
6e
7e
7e
9
8
!V Those lands designated suitable for agricultural production areassumed to be irrigated. Irrigated lands are designated by (i).
B{ Uses 1, 2, 6, and 7 represent pineapple, vegetables, pasture, andorchard crops, respectively. The lower case letters indicate theland productivity class for each use. Class e lands are unsuitedfor intensive agricultural production.
£! Acreages were measured by planimeter from U. S. Geological Surveymaps of a 1:25,000 scale.
Production Costs and Yields by Land Productivity Class
The crop budgets developed in this report are based on existing
cost of production studies. In some cases the data have been modified
to insure comparability between crops and to allow estimation of costs
and yields over a range of land qualities. The budgets are believed to
represent levels of inputs and yields that are now being realized in
the State of Hawaii.
Pineapple
In this study, pineapple is considered a potential crop on only
the Hoolehua lands. Cost of production data are not required as the
State would receive a uniform rental rate per acre for all lands con-
sidered suitable for pineapple production and leased to a plantation.
The rental rate used in this report is 30 dollars per acre per year
which is believed to represent a reliable estimate of the actual rental
should the land be leased.
29
Pasture
In Hawaii, ranches vary from small part-time operations to units
that rank among the nation's largest. Management practices within any
given size group vary substantially between firms.
The practices assumed for this report apply to a hypothetical 250
animal unit. Basic data utilized in constructing this unit were taken
from 11 questionnaires from a large state-wide survey conducted by the
Land Study Bureau in 1963 (20). Only records of respondents with
150-500 animals and Whose ranches had been classified by the Bureau were
used. Selection of the 150-500 animal size group corresponds to average
sized full-time beef operations in Hawaii (21, 22, 23, 24, 2S).
The basic plant and set of equipment for a 2S0-animal Hawaiian
ranch is described in the footnotes of Table 3. Production costs are
presented in Table 4. Because the production costs of the sample
ranches appear to vary with the number of animals, such a relationship
is assumed for the purposes of this study and results in identical per
unit production costs for ranches on all land classes. This assumption
is substantiated, in part, by the evidence presented in Table 4.
The pasture improvement and supplemental feeding expenditures given
in Table 4 should not be viewed as per acre or per animal costs. In
Hawaii, many ranchers practice pasture improvement on selected areas
wi thin their unit (so-called "emergency" or "fattening" pastures) lolhile
others improve limited areas annually as part of a long range program
of development. Supplemental feeci is usually fed for finishing steers
and heifers or to the breeding herd. Seldom, except in emergencies, is
it fed to the entire herd.
30
TABLE 3. ANNUAL COSTS OF PLANT AND EQUUMENT
FOR A 2s0-ANIMAL RANCH - 1963
Item Present Value!! DepreciationlY Interest£! Total
Equipment2./ $ 1,500 $250 $ 90 $ 340
Improvements~ 9,700 850 582 1,432
HerdY 42,100 0 2,525 2,525
Total $4,297
!I The present value is that reported by sample producers and is assumedto equal one-half of their original investment in each categoryexcept herd where it represents the total value.
~ Depreciation values are those reported by sample ranchers.
£! Interest is calculated at 6 per cent of present value.
21 It is assumed that ranch equipment consists of a truck purchased for$2,000, a military jeep purchased for $600, and miscellaneous equipment valued originally at $400. The useful life of these items isassumed to be 12 years which corresponds to producer reports.
~ Improvements consist of a single storage shed which originally cost$920 (present value $460) and fencing valued initially at $18,500(present value $9,250). The useful life of improvements is assumedto be 23 years which corresponds to producer reports. With a fixednumber of animals, ranches operating on poor quality lands ~ll besubstantially larger than those operating on good land. This sizedifference would require more boundary fencing but less crossfencing. For the purposes of this study the single fencing investment is used for all ranches.
£I The herd consists of 81 cows ($16,038), 36 heifers ($5,148), 63steers ($13,680), 66 calves ($5,808) and 4 bulls ($1,232) whichrepresents the sample ranch average as of January 1, 1963 (see 22,p. 12 for the calculation of animal values). Replacement heifersand sale of discarded cows is assumed to offset herd depreciation(2, p. 22).
31
TABLE 4. ANNUAL BEEF PRODUCTION COSTS AND PER ACRE YIELD
BY LAND PRODUCTIVITY CLASS FOR A 250-ANIMAL RANCH - 1963
Cost by Land Productivity ClassItem a b c d
LaborY $ 5,130 $ 5,130 $ 5,130 $ 5,130
Maintenance of Improvements£! 450 450 450 450
Cost of Equipment Operation£! 500 500 500 500
Supplemental FeedE! 1,325 1,325 1,325 1,325
Land Clearing~ 500 500 500 500
Ferti li zationY 200 200 200 200
Weed Control.al 120 120 120 120
Plant, Equipment, and Management!Y 6,697 6,697 6,697 6,697
Real Property Ta~!I 553 513 778 1,767
Gross Income Taxi! 95 49 43 38
Total Cost 15,570 15,484 15,743 16,727
Grazing krestsJ 556 815 1,440 3,840
Cost Per kre 28 19 11 4
Yield Per AcreY 160 53 27 10
Gross Per AcreID! 32 11 5 2
!I Labor is calculated on the basis of 16.4 hours per animal @$1.25 perhour or $20.50 per animal per year (24, p. 12).
B{ Includes materials and contract fence repair. Cost is that reportedby sample producers.
£! Gas, oil, and repairs as reported by sample producers.
E! Figure is that reported by sample producers. At $5.30 per animal itagrees closely with the average for the Land Study Bureau's statewide survey (20).
For the$100 to $150
32
~ Average annual expenditure reported by sample producers.type of clearing usually done in Hawaii, costs vary fromper acre (24, 25, p. 6).
£I Average annual expenditure reported by sample producers. This outlay represents about 2 tons of a complete commercial fertilizer.For example, 10-10-10 fertilizer costs $4.85/cwt.
sf Average annual expenditure reported by sample produpers.
hi A management fee of $2,400 is charged to each unit. Operator incomeis the sum of this fee and the operator's labor income.
!I Based on producer and tax office reports.
jJ Based on ~ per cent of gross sales computed with a five-year averageprice.
~ Average reported acreage for sample ranches operating on landclasses a and b. Acreages for classes c and d were estimated bymultiplying the class carrying capacity-mid-pOint by total animalunits for the ranch (192 animal units). According to the Land StudyBureau classification, the five sample ranches operating on theseland classes are overstocked.
!! Estimated live beef gains per acre per year are based on an assumed200-pound required gain per year per animal and the mid-point of thecarrying capacity range for each land class. The resulting valuesagree closely with Land Study Bureau estimates.
!I Based on the 1963 average price of 20 cents per pound.
The ranch budgets indicate that pasture enjoys a margin of 2.5
cents per pound on class ~ pasture land. However, these budgets do not
allow for breeding herd maintenance, which makes it unlikely that beef
could be grown under any circumstances. If even a minimal adjustment is
made (10 per cent of the gain assigned to herd maintenance) beef could
not be profitably produced on even the class ~ pasture lands. Beef
production is therefore omitted from further consideration.
Vegetable Crops
Detailed cost and yield budgets were prepared for snapbeans,
tomatoes, Manoa lettuce, and cantaloupe. These basic budgets are for
units of four-acres in size, which represent the average size of
33
vegetable farm found in Hawaii. Per acre production costs for a 2S-acre
unit were derived from these budgets by spreading the costs of plant and
equipment and return to management over the larger acreage. This proce-
dure assumes that the level of yields and inputs; e.g., fertilizer,
insecticides, harvesting labor, etc., used for the four-acre units will
prevail on the 2S-acre units.
The set of equipment described in this section is similar to that
found on four- to 10-acre vegetable farms in Hawaii (39, p. 12).
Table 5 gives annual costs of plant, equipment, and management for a
"typical" unit. A suitable irrigation system for an irrigated four-
acre vegetable farm would include the following items (39, p. 13):
Item .Amount ~-6" Aluminum Pipe 726 Feet $982
4" Aluminum Pipe 1200 Feet 818
Sprinklers, Misc. Hardware 385
7~ hp Pump (1800 REM) 473
The other equipment items needed to make up a set of equipment con-
sistent with prevailing management practices in Hawaii are as follows:
Ford 2000 Tractor
2-Bottom Plow
Disc and Spike-Tooth Harrows
6-hp Garden Tiller
Power Sprayer
Light Truck
A single building of 1200 square feet constructed at a cost of $2.20 per
square foot is needed for storage purposes and is included.
An attempt has been made to specify accurately existing production
costs and yields for each of the vegetable crops assuming production on
the designated land classes. Tables 5 through 9 give production costs
and marketable outputs for the crops being considered. The difference
TABLE 5. ANNUAL COSTS OF PLANT AND EQUIPMENT FOR A FOUR-ACRE VEGETABLE FARM - 1963
Item Initial Value!l Life Salvage _Depreciation Interest Insurance Total Costl Acre
Buildings $2,640 20 $264 $118.80 $ 79.20 $13.00 $ 211 53
Irrigation 2,660 20 133 126.35 79.80 - 206 52
Tractor 3,500 12 100 283.33 105.00 - 388 97
Garden TillerlY 715 10 35 68.00 21.45 - 89 22
2-Bottom Plow 530 12 15 42.92 15.90 - 59 15
Disc-HarrOl07 460 12 20 36.67 13.80 - 50 12
Spike-Harro\07 40 12 - 3.33 1.20 - 5 1
Spray 310 10 16 29.40 9.30 - 39 10
Farm Truck (3/4 Ton) 1,000 7 100 128.00 30.00 16.50 332~ 83
Totals $1,379 345
!I All items are new except the spike-harrow and truck. Price data were obtained from local distributorsfor all new items except the bUilding. It is assumed that a suitable building could still be constructed for $2.20 per square foot.
~ Gravely Custom (six hp).
~ Includes 70 per cent of annual operating costs based on 10,000 miles annually. w+'
35
between yield and marketed output, spoilage, is influenced by several
factors; e.g., weather and rate of movement through the market. This
makes it difficult to define a single spoilage rate that would apply to
a given crop produced under diverse conditions. In addition, existing
data are not sufficient to define rates that would apply to a specific
area or season. It is possible with existing information, however, to
estimate an average percentage loss that could be expected throughout
the year (39, pp. 29 and 55; 50, pp. 10 and 17). The portion of total,
harvested output, for which the producer receives payment is the
marketed output.
A procedure developed by the Soil Conservation Service is used to
estimate irrigation requirements and is outlined in Appendix B.
Basically, this procedure consists of first using pan evaporation data
(47) and consumptive use requirements to estimate gross water needs.
Secondly, rainfall is adjusted by considering the effects of consumptive
use needs, irrigation in inches, and gross rainfall to estimate effec
tive rainfall. The gross consumptive use less effective rainfall gives
irrigation requirements. An irrigation efficiency of 60% is assumed.
At the present time, the State of Hawaii supplies irrigation water to
Waimanalo farmers at a cost of eight cents per 1000 gallons plus a
monthly assessment of $2.50 per acre. Distribution facilities are being
prepared to deliver water from the Molokai Irrigation Project to the
Hoolehua Lands. The cost of this water will be eight cents per 1000
gallons plus a monthly assessment of $1.10 per acre (Honolulu Advertiser,
Septenber 30, 1964). There is presently no irrigation project in the
Waianae area. As water rates are not available for Waianae, it was
decided to use the Waimanalo costs for these lands.
36
Real property tax rates were supplied by the First and Second
Taxation Divisions of the State Department of Taxation. Hoolehua Farm
Lands are currently assessed at a uniform rate, While the study lands at
Waimanalo are valued at two distinct levels with the higher assessment
corresl~nding to the lands considered suitable for intensive cultiva
tion. In general, the Waianae Kai lands are assessed at a low rate.
This low valuation results from two factors: 1. the lands are, in the
most part, not suited for intensive agricultural uses, and 2. large
parcels are assessed at a uniform rate (small areas of better quality
land are not delineated). Approximately 22 acres of the study lands at
Waianae Kai are classified as £ productivity (land type 23i) Which are
well suited to intensive uses. According to the State Department of
Land and Natural Resources, the study lands, with improvements, will be
assessed at about $700 per acre ($1000 market value) after development.
For the purposes of this study this rate is assumed to apply uniformly
to all study lands except those used for grazing and pineapple. A
management fee of $2,400 per unit ($600 per acre) is charged to each
vegetable farm. This fee plus the operator's labor income equals
operator income.
The State Department of Land and Natural Resources will establish a
system of permanent windbreaks on the Molokai Farm Tract before disposi
tion of the units. It is assumed that wind will be effectively con
trolled for vegetable production before farming begins and that the
established windbreaks will be available l~thout direct cost to
individual farmers (51).
TABLE 6. SNAPBEAN PRODUCTION COSTS AND YIELDS PER ACRE BY LAND CLASS - 1963~
Expenditure by Land ClassItem Amount Price Per Uni t a b c d
Yield (Pounds) 11 ,100 10,000 8,900 7,800
Spoilage (10 per cent) 1,100 1,000 900 800
Marketed (Pounds) 10,000 9,000 8,000 7,000
Per Crop Production Costs Applicable to All Areas:
Seeds 50 Pounds $ .60 Pound $ 30 $ 30 $ 30 $ 30
Fertilizer (5-10-10) 850 Pounds 4.20 100 Pounds 36 36 36 36
Insecticide:
DDT 8 Pounds 1.70 4 Pounds 3 3 3 3
Toxaphene 20 Pounds 3.10 4 Po\lInds 16 16 16 16
Weedicide 20 Gallons 1.90 Gallon 38 38 38 38
Crates .25 Each 56 50 45 39
TractorW 10 Hours .80 Hour 9 9 9 9
Labor:£!
Growing 1.25 Hour 319 319 319 319
Harvesting 1.25 Hour 656 621 580 507 w......
TABLE 6. (Continued) SNAPBEAN PRODUCTION COSTS AND YIELDS PER ACRE BY LAND CLASS - 1963!1
Item Amount
Mi sce11aneaus
Gross Income Tax21
Cornmission~
Total Per Crop Production Costs
Production Costs Peculiar to Area:!!
Water - Waimanalo
Water - Waianae Kai
Water - Hoolehua
Freight from Molokai
Real Property Tax - Waimanalo
Real Property Tax - Waianae Kai
Real Property Tax - Hoolehua
Management Fee
Expenditure by Land ClassPrice Per Unit a b c d
$ 8 $ 8 $ 8 $ 8
12 11 10 9
367 330 293 257
1,550 1,471 1,387 1,271
$140 $140 $140 $140
164 164 164 164
147 147 147 147
$7.00 Ton 155 140 125 109
10 10 10 10
10 10 10 10
10 10 10 10
600 600 600 600
wCIO
TABLE 6. (Continued) SNAPBEAN PRODUCTION COSTS AND YIELDS PER ACRE BY LAND CLASS - 1963!1
Item Itnount Pri ce Per Uni tEXpenditure by Land Classabc d
Total Annual Costs - Waimanalo
Total Annual Costs - \~ai anae Kai
Total Annual Costs - Hoolehua
$5,745
7,319
7,457
$5,508
7,004
7,126
$5,253
6,668
6,775
$4,908
6, 20l~
6,295
!I The cost figures presented in this table are based on studies by Douglas J. McConnell (39).
B1 Tractor operating costs are estimated at $.80 per hour. Fixed costs of ownership are given inTable 3.
£! Harvesting and marketing labor costs are estimated from data presented in McConnell's report (39)and interviews with Experiment Station specialists.
~ Gross income tax is computed as ~ of gross income based on a five-year average price.
!I Wholesale commission is computed as 15% of gross receipts based on a five-year average price.
£! Computation of annual water and freight costs assumes three crops at Waimanalo and four crops atWaianae Kai and Molokai.
VJ\0
TABLE 7. TOMATO PRODUCTION COSTS AND YIELDS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963~
Land Productivity ClassItem /mount Pri ce Per Uni t a b c d
Yield (Pounds) 20,000 18,300 15,600 13,900
Spoilage (15 per cent) 3,000 2,700 2,300 2,100
Marketed (Ibunds) 17,000 15,600 13,300 11,800
Per Crop Production Costs Applicable to All Areas:
Seeds .25 Ounces $30.00 Ounce $ 8 $ 8 $ 8 $ 8
Fertilizer (5-10-10) 1500 Pounds 4.20 100 Ibunds 63 63 63 63
Insecti cides 56 Pounds .85 Pound 48 48 48 48
Fungicides 48 Ibunds 1.30 Ibund 62 62 62 62
Herbicides 15 Gallons 1.90 Gallon 28 28 28 28
Fumigants 8 Gallons 3.35 Gallon 27 27 27 27
Manure 1500 Pounds 3.50 100 Pounds 52 52 52 52
Flats and Crates .30 Each 180 165 140 125
String 45 Pounds 1.00 Pound 45 45 45 45
~o
TABLE 7. (Continued) TCMATO PRODUCTION COSTS AND YIELDS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963!1
Land Productivity ClassItem Pmount Pri ce Per Uni t a b c d
Labor:'2!
Growing 246 Hours $1.25 Hour $ 308 $ 308 $ 308 $ 308
Harvesting 1.25 Hour 569 563 488 438
Tractorf2! 20 Hours .80 Hour 16 16 16 16
Power-Spray2! 6 Hours .25 Hour 2 2 2 2
Power Cultivator£! 10 Hours .25 Hour 2 2 2 2
Stakes 25 25 25 25
Miscellaneous 36 36 36 36
Gross Income TaxY 16 15 13 11
Wholesale CommissionB! 516 473 401 358
Total Per Crop Production Costs 2.003 1,938 1,764 1,654
Production Costs Peculiar to Area:h!
Water - Waimanalo $ 99 $ 99 $ 99 $ 99
Water - Waianae Kai 109 109 109 109
Water - Hoolehua 92 92 92 92 ./:'t-'
TABLE 7. (Continued) TOMATO PRODUCTION COSTS AND YIELDS PER ACRE BY LAND PRODUCTIVITY CLASS· 1963!1
LandEToductrvlty ClassItem /mount Price Per Unit a b c d
Freight from Molokai $ 140 $ 128 $ 109 $ 97
Real Property Tax - Waimanalo 10 10 10 10
Real Property Tax - Waianae Kai 10 10 10 10
Real Property Tax - Hoolehua 10 10 10 10
Management Fee 600 600 600 600
Total Annual Costs - Waimanalo $5,060 $4,930 $4,582 $4,362
Total Annual Costs - Waianae Kai 5,070 4,940 4,592 4,372
Total Annual Costs - Hoolehua 5,192 5,051 4,684 4,107
!I The cost figures presented in the table are based on a study by J. A. Mollett (41).
E1 Harvesting and marketing labor costs are estimated from data presented in Mollett's report (41) andinterviews ~nth Experiment Station specialists.
£! Tractor operating costs are estimated at $.80 per hour. Fixed costs of ownership are given inTable 3.
gj Power spray operating costs are estimated at $.25 per hour. Fixed costs of ownership are given inTable 3.
.l:N
TABLE 7. (Continued) TCMATO PRODUCTION COSTS AND YIELDS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
!I Power cultivator operating costs are estimated at $.25 per hour. Fixed costs of ownership are givenin Table 3.
!! Gross income tax is computed as ~ of gross income based on a five-year average price.
s! Wholesale commission is computed as 157. of gross income based on a five-year average price.
hi Computation of annual wateI' and freight costs assumes two crops in all producing areas.
~w
TABLE 8. MANOA LETTUCE PRODUCTION COSTS AND YIELDS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963!1
Land Productivity ClassItem hnount Price Per Uni t a b c d
Yield 13,300 12,200 11,100 8,900
Spoilage (15 per cent) 2,000 1,800 1,700 1,300
Marketed (POunds) 11,300 10,400 9,400 7,600
Per Crop Production Costs Applicable to All Areas:
Seeds 1 Pound $4.75 Pound $ 5 $ 5 $ 5 $ 5
Fertilizer (10-10-5) 1600 Pounds 4.75 100 Pounds 76 76 76 76
Manure 4 Cubic Yards 6.00 Cubic Yard 24 24 24 24
Fungicides 6 POunds 1.30 Pound 8 8 8 8
Insecticides 6 Pounds .85 Pound 5 5 5 5
Crates .25 Each 92 84 77 61
Labor:!Y
Growing 170 170 170 170
Harvesting 189 185 168 134
Power Cultivator£! 6 Hours .25 Hour 2 2 2 2
Power spray'Y 3 Hours .25 Hour 1 1 1 1~~
TABLE 8. (Continued) MANOA LETTUCE PRODUCTION COSTS AND YIELDS PER ACRE
BY LAND PRODUCTIVITY CLASS - 1963!1
Land Productivity ClassItem !mount Price Per Uni t a b c d
Mi see11aneous $ 18 $ 18 $ 18 $ 18
Gross Income Tax!! 8 8 7 6
Wholesale Commission£! 275 252 229 183
Total Per CrOp Production Costs 873 838 790 693
Production Costs Peculiar to Area:~
Water - Waims~alo $ 132 $ 132 $ 132 $ 132
Water - Waianae Kai 156 156 156 156
Water - Hoolehua 139 139 139 139
Freight from Molokai 233 214 194 156
Real Property Tax - Waimanalo 10 10 10 10
Real Property Tax - Waianae Kai 10 10 10 10
Real Property Tax - Hoolehua 10 10 10 10
Management Fee 600 600 600 600
~V1
TABLE 8. (Continued) MANOA LETTUCE PRODUCTION COSTS AND YIELDS PER ACRE
BY LAND PRODUCTIVITY CLASS - 1963!1
Land Productivity ClassItem Amount Pri ce Per Uni t a b c d
Total Annual Costs - Waimanalo $4,579 $4,439 $4,247 $3,859
Total Annual Costs - Wai anae Kai 5,476 5,301 5,061 4,576
Total Annual Costs - Hoolehua 5,692 5,498 5,238 4,715
!I The cost figures presented in this table are based on a study by J. A. Mollett (40).
~ Harvesting and marketing labor costs are estimated from data presented in Mollett's report (40) andinterviews with Experiment Station specialists.
£! POlver cultivator operating costs are estimated at $.25 per hour. Fixed costs of ownership are givenin Table 3.
~ Power spray operating costs are estimated at $.25 per hour. Fixed costs of ownership are given inTable 3.
!I Gross income tax is computed as ~ of gross income based on a five-year average price.
£! Wholesale commission is computed as 15% of gross income based on a five-year average price.
at Computation of annual water and freight costs assumes four crops at Waimanalo and five crops atWaianae Kai and Molokai.
~0"
TABLE 9. CANTALOUPE PRODUCTION COSTS AND YIELDS PER ACRE
BY LAND PRODUCTIVITY CLASS - 196)!!
Item /mount Price Per Un! tLand Productivity Classabc d
Yield (Pounds)
Spoilage (15 per cent)
Marketed (Pounds)
Per Crop Production Costs Applicable to All Areas:
8,800
1,300
7,500
7,200
1,100
6,100
6,200
900
5,300
5,800
900
4,900
Seeds 2 Pounds $2.85 Pound $ 6 $ 6 $ 6 $ 6
20 Gallons 1.90 Gallon
Fertilizer (5-10-10)
Insecticide: Malathion
vleedicide
Crates
Tractor.JY
Labor:£!
Growing
Harvesting
1000 Pounds
24 Pounds
9 Hours
4.20 100 Pound
3.25 4 Pound
.25 Each
.80 Hour
42
13
38
44
7
290
182
42
13
38
36
7
290
159
42
13
38
31
7
290
137
42
13
38
29
7
290
126
~
"
TABLE 9. (Continued) CANTALOUPE PRODUCTION COSTS AND YIELDS PER ACRE
BY LAND PRODUCTIVITY CLASS - 196J!/
Land Productivity ClassItem Amount Price Per Unit a b c d
Miscellaneous $ 8 $ 8 $ 8 $ 8
Gross Income Tax9! 7 5 5 4
Wholesale CommisSio~ 175 145 125 115
Total Per Crop Production Costs 806 745 698 675
~oduction Costs Peculiar to Area:£!
Water - Waimanalo $ 138 $ 138 $ 138 $ 138
Water - Waianae Kai 176 176 176 176
Water - Hoolehua 160 160 160 160
Freight from Molokai 93 75 66 60
Real Property Tax - Waimanalo 10 10 10 10
Real Property Tax - Waianae Kai 10 10 10 10
Real Property Tax - Hoolehua 10 10 10 10
Management Fee 600 600 600 600
.j:'-(Xl
TABLE 9. (Continued) CANTALOUPE PRODUCTION COSTS AND YIELDS PER ACRE
BY LAND PkODUCTIVITY CLASS - 1963!1
Land Productivity ClassItem hnount Pri ce Per Uni t a b c d
Total Annual Costs - Waimanalo $3,517 $3,332 $3,191 $3,121
Total Annual Costs - Waianae Kai 3,555 3,370 3,229 3,159
Total Annual Costs - Hoolehua 3,632 3,429 3,279 3,203
!I The cost figures presented in this table are based on studies by Douglas J. McCOnnell (39).
£! Tractor operating costs are estimated at $.80 per hour. Fi:ced costs of ownership are given inTable 3.
£I Harvesting and marketing labor costs are estimated from data presented in McCOnnell's report (39)and interviews with EXperiment Station specialists.
2! Gross income tax is computed as ~ of gross income based on a five-year average price.
~ Wholesale commission is computed as 15% of gross income based on a five-year average price.
f! Computation of annual water and freight costs assumes three crops in all producing areas. Whencantaloupe was being produced in Hawaii the prevailing practice was to grow a single crop each yearin rotation with some other crop such as snapbeans or broccoli.
~\0
50
TABLE 10. ANNUAL PER ACRE COST OF PRODUCTION (25-ACRE UNITS)
FOR SELECTED VEGETABLE CROPS BY LAND PRODUCTIVITY CLASS - 1963
Land Productivity ClassItem a b c d
Snapbeans
Waimanalo $4,951 $4,715 $4,459 $4,114
Waianae Kai 6,525 6,209 5,873 5,409
Hoolehua 6,663 6,332 5,981 5,501
Tomato
Waimanalo $4,226 $4,136 $3,788 $3,568
Waianae Kai 4,276 4,146 3,798 3,578
Hoolehua 4,398 4,257 3,890 3,313
Manoa Lettuce
Waimanalo $3,785 $3,645 $3,453 $3,065
Waianae Kai 4,682 4,507 4,267 3,782
Hoolehua 4,898 4,704 4,444 3,921
Cantaloupe
Waimanalo $2,723 $2,538 $2,397 $2,327
Waianae Kai 2,761 2,576 2,435 2,365
Hoolehua 2,838 2,635 2,485 2,409
51
Table 10 gives the per acre cost of production by land class for
the 25-acre units. Yields for these units are the same as those given
earlier for the four-acre farms.
Orchard Crops
Detailed cost and yield budgets were prepared for apple banana and
papaya. The unit sizes represented by these budgets are four and five
acres. respectively. which corresponds to the state average. As in the
case of vegetables. the 25-acre budgets are basically the same as those
of the smaller units ~th plant. equipment. and management costs spread
over more acres. For bananas, however. a used tractor and trailer is
added ~th the larger unit.
The sets of equipment described in Tables 11 and 15 are similar to
those found on four-acre banana farms and five-acre papaya farms in the
State of Hawaii (30. 32). The irrigation plant is the same as that
previously described for vegetable farms.
Cost figures given in Tables 12 and 16 are explai~ed. when
necessary. to ease interpretation. In Table 12. the planting is depre
ciated over a 25-year period and interest is charged at a rate of six
per cent on one-half the original investment. For papayas land clearing
is depreciated over a nine-year period as papayas are usually not grown
more than three crop cycles (of three years each) on a given site. This
results from a substance given off by the papaya root which poisons the
soil. The costs in Table 11 are depreciated over three years and
interest is charged at a rate of six per cent on one-half the original
investment.
The production costs that apply to all producing areas are
explained in detail in the body of Tables 13 and 17. Water requirements
52
were estimated w1th the same procedure outlined for vegetables (see
Appendix B). Irrigation labor cost is determined by using the rate of
one man-hour per 27,000 gallons of water delivered ($1.25 per 27,000
gallons). This rate is based upon a 1958 papaya study for the Waimanalo
area (34, p. 14). The real property tax rates used in the vegetable
budgets are also used for orchard crops. These rates are discussed in
the previous section. Ammlagement fee of $2,400 per unit is charged to
each orchard unit. This rate is equal to $600 per acre for bananas and
$480 per acre for papaya.
Sufficient data to estimate fruit spoilage by area and season are
not available, but it is possible to estimate a gross percentage of
fruit loss that would apply to all producing areas for the entire annual
production. This figure relies heavily on discussions ~th EXperiment
Station specialists.
Table 19 gives the per acre production costs for the 25-acre units.
Yields levels are assumed to be identical to those specified for the
smaller fanns.
TABLE 11. ANNUAL COSTS OF PLANT AND EQUIIMENT FOR A FOUR-ACRE BANANA FARM - 1963
Item Value Years Life Depreciation Interest Total Cost/Acre
Quonset (20 x 50) $ 600 20 $ 30 $ 18 $ 48 $ 12
Truck (l~ ton) 2,000 12 160 60 377Y 94
Irrigation 2,660 20 133 80 213 53
Jeep (Mi 11 tary) 600 6 100 18 118 30
Power Sprayer 600 10 60 18 78 20
l<napsack Sprayers (4) 140 5 28 4 32 8
Tractor and Irai 1erP.! 1,000 25 40 30 70 18
Miscellaneous 200 4 50 6 56 14
~ Includes 70 per cent of operating costs based on 10,000 miles annually.
E! This item to be used for 25-acre unit only and is not to be included in the four-acre budget.
VIu.>
TABLE 12. COST PER ACRE OF ESTABLISHING A BANANA PLANTING - 1963
Operation Cost/Acre
Land clearing (Contract) $100
Pile and burn brush (20 man-hours @$1.25)
Preplanting weed control: Straight aromatic oil, 100 gallons @18 cents • $18;Dalapon, 10 pounds @$1.05 = $10.50; 6 man-hours @$1.25 • $7.50; jeep andpower sprayer, 3 hours operating costs • $3.00
Prepare planting basins: Spacing 15' by 15' or 194 basins per acre, contract @$30;plus 10 man-hours for layout @$1.25 = $12.50
Suckers for planting (194 plants @$.50 each)
Planting: 40 man-hours @$1.25 = $50
Total Per Acre
Cost Per Acre Per Year (25-year life and 6 per cent interest)
25
39
42
97
50
$353
$ 25
VI~
TABLE 13. ANNUAL APPLE BANANA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
_~ ~_ _ _Ope~ation
Per Crop Production Costs Applicable to All Areas:
Land ProductiYity Classabc d
Weed Control: A contact herbicide concentrate containing50 pounds of pentachlorophenal dissolved in50 gallons of aromatic oil will be made at thefarm. Ten gallons of concentrate will beemulsified in 100 gallons of water. Cost pergallon is 6 cents. (55 gallons weedicide •$3,30; 17 man-hours @$1.25 • $21.25; jeep andsprayer 5 hours @$1.00 m $5.00; knapsacksprayer 12 hours, fixed costs only).
$ 30 $ 30 $ 30 $ 30
Ferti 11 zing:
Harvesting:
A balanced fertilizer (10-10-10) or equivalentapplied at the rate of 12 pounds per mat inthree applications. (194 mats x 12 pounds =2,328 pounds @$4.85 per 100 pounds = $112.91;3 applications x 2 man-hours per application@$1.25 • $7.50; jeep 6 hours @$1.00 = $6.00).
Includes time used in pruning suckers, locatingmature fruits, picking, severing old stalks,loading on truck, and packing in tubs. (Class a:360 bunches @30 pounds, 63 man-hours @$1.25 •$78.75, 23 truck hours @$1.00 • $23.00; Class b:250 bunches @30 pounds, 57 man-hours @$1.25 •$71.25, 29 truck hours @$1.00 • $21.00; Class c:183 bunches @30 pounds, 42 man-hours @$1.25 •$52.50, 15 truck hours @$1.00 a $15.00; Class d:150 bunches @30 pounds, 34 man-hours @$1.25 •$42.50; 13 truck hours @$1.00 • $13.00).
$ 126
$ 102
$ 126
$ 92
$ 126
$ -68
$ 126
$ 56
VIVI
TABLE 13. (Continued) ANNUAL A]?PLE BANANA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
Lmld Productivity ClassOperation a b c d
Indi rect Labor: Includes bookkeeping, going after supplies, $ 6 $ 6 $ 6 $ 6repairing equipment, etc. (5 man-hours@$1.25 • $6.25).
Gross Income Tax: Computed as ~ per cent of gross income. $ 4 $ 3 $ 2 $ 2(Gross based on five-year average price).
Wholesale Cammission: Computed as 18 per cent of gross income. $ 151 $ 108 $ 79 $ 65(Gross based on a five-year average price).
Production Costs Peculiar to Area:
Water - Waimanalo $ 222 $ 222 $ 222 $ 222
Water - Waianae Kai 235 235 235 235
Water - Hoolehua 218 218 218 218
Freight from Molokai ($7.00 per ton) 37 26 19 16
Real Property Tax - Waimanalo 10 10 10 10
Real Property Tax - Waianae Kai 10 10 10 10
Real Property Tax - Hoolehua 10 10 10 10
Irrigation Labor Cost - Waimanalo 111 111 111 111V10-.
TABLE 13. (Continued) ANNUAL APPLE BANANA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
Land Productivity ClassOperation a b c d
Irrigation Labor Cost - Waianae Kai $ 119 $ 119 $ 119 $ 119
Irrigation Labor Cost - Hoolehua 119 119 119 119
Management Fee 600 600 600 600
Total Annual Costs - Waimanalo $1,618 $1,564 $1,510 $1,484
Total Annual Costs - Wai anae Kai 1,639 1,585 1,531 1,505
Total Annual Costs - Hoolehua 1,659 1,594 1)533 1,504
VI......
TABLE 14. ANNUAL PER ACRE APPLE BANANA YIELDS AND SPOILAGE RATES BY LAND PRODUCTIVITY CLASS
Land Productivity ClassItem a b c d
Yield (Pounds) 10,500 7,500 5,500 4,500
Spoilage (15 per cent) 1,600 1,100 800 700
Marketed Output (Pounds) 8 ,'~OO 6,400 4,700 3,800
TABLE 15. ANNUAL COSTS OF PLANT AND EQUUMENT FOR A FIVE-ACRE I:'.APAYA FARM - 1963
Item Initial Value Years Life Depreciation Interest Total Cost/Acre-Building (rough wood) $ 600 20 $ 30 $ 18 $ 48 $ 10
Truck (l.!z ton) 2,000 12 167 60 384!1 77
Truck (old used) 1,000 10 100 30 130 26
Irrigation Plant 2,660 20 133 80 213 43
Miscellaneous Equipment (Crates, 975 3 325 29 354 714 knapsack sprayers, hand tools,etc.)
Totals $1,129 $227
!I Includes 70 per cent of operating costs based on 10,000 miles annually.VI<Xl
TABLE 16. ANNUAL COSTS PER ACRE OF ESTABLISHING A PAPAYA PLANTING - 1963
Operation
Land Clearing: $150 for bulldozing, $30 for rolling land after dozing,site has nine-year life (3-3 year cycles)
Layout and dig holes: 25 man-hours @$1.25 = $3l.25!crop (3 years)
Plant and Mulch: 20 man-hours @$1.25 - $25.00!crop (3 years)
Thin Seedlings: 16 man-hours @$1.25 • $20.00!crop (3 years)
Plant Thinning: 8 man-hours @$1.25 • $lO.OO!crop (3 years)
Preplanting weed control: 6 man-hours @$1.25 n $7.50; 50 gallonsaromatic oil @$.19 per gallon a $9.50
Total
Cost!Acre
$180
31
25
20
10
17
Cost!Acre! Year
25
37
$62
VI\0
TABLE 17. ANNUAL PAPAYA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
___ __ Operation
Per Crop Production Costs Applicable to All Areas:
COsfTAiire- by Land PioducfivTIY Classabc d
Weed COntrol: A contact herbicide consisting of 1 pound ofpentachlorophenate (@ $.36 per pound), 8 gallonsof aromatic oil (@ $.19 per gallon) and 1 poundof emulsifier (@ $.40 per pound) in 50 gallonsof water is mixed on the farm. 300 gallons willbe applied annually spraying every 2 months at arate of 50 gallons per acre (300 gallons spray@$4.56 per 100 gallons m $13.68; 37 man-hours@$1.25 a $46.25)
Fertilizing: A complete (10-10-10) fertilizer is appliedmonthly for 33 months. Application is at a rateof 2,900 pounds per year. (49 man-hours @$1.25 m
$61.25; 2,900 pounds fertilizer @$4.85 per100 pounds Q $140.65)
Pest Control: During the three-year life of the planting2,500 gallons of spray are applied per acre.(50 pounds of wettable sulphur @$.15 per poundand 17 pounds of "captan" @ $1.30 per pound ...$29.60; 83 man-hours @$1.25 ... $103.75
Harvesting and Packing Labor: Picking frequency varies from2 to 3 times per week during the year. Sortingand packing is done immediately after picking.(Class a, 205 man-hours @$1.25 ... $256.25;Class b, 176 hours @$1.25 a $220.00; Class c,114 man-hours @$1.25 a $142.00; Class d,66 man-hours @$1.25 a $82.00)
$ 60
202
133
256
$ 60
202
133
220
$ 60
202
133
142
$ 60
202
133
82
~o
TABLE 17. (Continued) ANNUAL PAPAYA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
Cost/Acre by Land Pioductivity ClassOperation a b c d
Other Costs: Minor repairs, maintenance of vehicles, $ 8 $ 8 $ 8 $ 8bookkeeping, etc. (A flat charge of $25per crop cycle)
Gross Income Tax: Computed as ~ per cent of gross income 8 6 4 2(Gross based on five-year average price)
Wholesale Commission: Computed as 18 per cent of gross 273 220 144 84income (Gross based on five-year averageprice)
Production Costs Peculiar to Area:
Water - Waimanalo $ 154 $ 154 $ 154 $ 154
Water - Waianae Kat 165 165 165 165
Water - Hoolehua 148 148 148 148
Freight from Molokai ($7.00 per ton) 63 51 33 19
Real Property Tax - Waimanalo 10 10 10 10
Real Property Tax - Waianae Kai 10 10 10 10
Real Property Tax - Hoolehua 10 10 10 10
0'\I-'
TABLE 17. (Continued) ANNUAL PAPAYA COSTS PER ACRE BY LAND PRODUCTIVITY CLASS - 1963
CostlAcre by Land Productivity Cl~
Operation a b c d
Irrigation Labor Cost - Waimanalo $ 71 $ 71 $ 71 $ 71
Irrigation Labor Cost - Waianae Kai 78 78 78 78
Irrigation Labor Cost - Hoolehua 78 78 78 78
Management Fee 480 480 480 480
Total Annual Costs - Waimanalo $1,944 $1,853 $1,697 $1,575
Total Annual Costs - Waianae Kaf 1,962 1,871 1,715 1,693
Total Annual Costs - Hoolehua 2,008 1,905 1,731 1,595
0'\N
TABLE 18. PER ACRE PAPAYA YIEIDS AND SPOILAGE RATES BY LAND PRODUCTIVITY CLASS - ANNUAL
ItemLand Productivity Classabc d
Yield (Pounds)
Spoilage (15 per cent)
Marketed Output (Pounds)
18,000 14,500
2,700 2,200
15,300 12,300
9,500
1,400
8,100
5,500
800
4,700
TABLE 19. ANNUAL PER ACRE COST OF PRODUCTION (25-ACRE UNITS)
FOR APPLE BANANA AND PAPAYA BY LAND PRODUCTIVITY CLASS - 1963
Item
Apple Banana
Waimanalo
Waianae Kai
Hoolehua
Papaya
Waimanalo
Waianae Kai
Land Productivity Classabc d
$ 923 $ 869 $ 815 $ 789
944 890 836 810
964 899 838 809
$1~258 $1,167 $1,011 $ 889
1,276 1,185 1,029 1,007
Hoolehua 1,322 1,219 1,045 909 0'-W
64
CHAPTER IV
ESTIMATED MARKET SUPPLY AND DEMAND FUNCTIONS
To obtain estimates of market revenue for different output levels,
it was necessary to derive a market demand function for each of the
included crops. As this study deals with bringing new land into produc
tion, it is also necessary to know how existing producers of the various
crops will react to changes in product price. In order to qu~tify this
relationship supply curves were estimated for several of the crops under
study.
Crop Group I
Three crops (pineapple, pasture, and papaya), which either have
perfectly elastic demand or would earn a uniform net return regardless
of output, are included in this group. Pineapple is included because
its rent has been fixed at $30 per acre per year. This rental rate can
be viewed as a constant net return regardless of the acreage devoted to
this use. In the case of beef it was not felt that the additional
production resulting from the relatively small acreages (about 200 acres
on Oahu) considered here would have any appreciable effect on beef
prices. Perfectly elastic demand is assumed over the range of quanti
ties considered in this analysis. For this commodity the 1963 average
annual price is used. The final crop in this group, papaya, presents a
somewhat more problematical situation. During the past four or five
years the papaya industry has developed a substantial export market
which is now believed to determine local price. Although only limited
evidence is available to substantiate this position, it seems evident
from the follo~nng observations:
65
(a) Production is now shifting to the Island of Hawaii
(currently about 80 per cent of the State total).
(b) About 40 per cent of the production on Hawaii is now
being exported to the Mainland.
(c) The Mainland market being much larger than the Hawaii
market could probably absorb much larger quantities
(than current export levels) with little effect on price.
~iven the above observations (and assumptions), an increase in the
Honolulu market price should divert papaya from the export channels to
the Honolulu market, reducing prices. The opposite, increased exports,
would result from a price reduction. This stabilizing action should
cause the Honolulu price to reflect both the local and export price
(the West Coast price would be the local price plus transportation
costs). The 1962-63 average market price is used for this crop.
If a supply increase will not reduce price, as is the case for
these crops, a supply analysis is not needed. In other words, produc
tion from existing producing areas would not be affected by the
increased output.
Crop Group II
The crops included in this group (snapbeans, tomatoes, Manoa
lettuce, cantaloupe, and apple banana) have downward-sloping demand
curves, which means that increased production will reduce price. Demand
and supply equations were computed for each of these crops with the
exception of cantaloupe for which a supply curve was not estimated.
Local cantaloupe production has fallen off to an insignificant amount
(10,000 pounds in 1963), consequently, no local production is assumed.
66
Demand
A graphic multiple regression analysis was conducted for each of
the vegetable and orchard crops. The purpose of this investigation was
to discover what factors had influenced the price of the several
commodities in the past and the general form of these relationships.
This analysis employed quantity, month, population, and time as inde
pendent variables in each case. The results of this analysis indicated
that the best fits were obtained when quantity, month, and time were
included as independent variables. The relationship between the
dependent variable and each independent variable was found to be linear
or nearly linear in every case except for the seasonal pattern.
The second phase of the demand analysis eonsisted of statistically
fitting multiple regression models using a number of different inde
pendent variables. An effort was made at this point to determine which
factors were responsible for the observed seasonal shifts. Foytik (15)
cites studies dealing with over 20 commodities for which seasonally
shifting demand has been observed. These shifts are much more pro
nounced for perishables than for staples, and appear to result from a
combination of influences that are difficult if not impossible to
quantify. In several cases seasonal changes in supplies of competing
products were found to influence commodity prices but in none of these
cases were the B coefficients significant at the five per cent level.
In this study the convention of using month as a "proxy" for the
combined influences of supplies of competing products, intra-year
prefe~ence changes, and other relevant factors is followed. In the
final model the year was divided into t\~ six-month periods (corres
ponding to the seasonal pattern from the graphic analysis) one with
67
higher and one ~nth lower than average prices. Zero-one variables were
then introduced and assigned to each period. The resulting general
model is given by (1).
(1) p m A + B1Q + B2Sl + B3S2 + B4Y
where:
P = Honolulu wholesal~ pri~e (cents/pound)
A = Intercept term
Bi = Regression coefficients
Q = Honolulu market supply (1000 pounds)
51 - High price season (variable equals 1 for months with
higher than average prices and zero for other months)
52 = Low price season (variable equals 1 for months with
lower than average prices and zero for other months)
Y = Year
Direct solution of this model will always result in an indeterminate
solution or a singular matrix (a matrix with no inverse). To avoid
this problem the model can be fitted by simply deleting one of the
seasonal shift variables (64).
The computed demand functions (for 1963), converted to an annual
basis, are given in Table 20. The complete demand equations including
the coefficients for season and year are given in Appendix C.
If the equations given in Table 20 are to represent average annual
prices, 50 per cent of annual production must be sold during each
season. Average marketings of snapbeans, tomatoes, Manoa lettuce, and
apple banana during the high price season accounted for 51, 51, 48 and
44 per cent of the annual average, respectively, for the 1959-63 period
(see Appendix C for the average monthly sales of each crop). Figure 4
68
TABLE 20. ANNUAL DEM~~D EQUATIONS FOR SELECTED CROPS - 1963
Crop A Intercept
Snapbeans 45.01
Tomatoes 25.64
Manoa Lettuce 31034
Cantaloupe£! 25.72
Apple Banana 10.56
B Coefficient(Quantity)
-~(j142
(.00105)
-.0008(.00035)
-.0086(000103)
-.0048(.00057)
-.0002(.00005)
t
.48**
8 **• 2
d~
2.50N•S•
!I Durbin-Watson statistic for serial correlation in the residuals.
** Significant at one per cent level.
£! Test inconclusive.
£! This function was fitted ~thout the seasonal and time variables.
21 Not computed because banana eventually drops out of the analysis(see text).
presents the demand equations for the four vegetable crops in graphic
form. Apple banana eventually drops out of the analysis and is not
included in the final land use patterns so a graph for this crop is not
presented. Apple banana was deleted because the estimated 1963 market
price ~as lower than per unit production costs on all land classes.
Supply
This analysis is confined to the response of local producers to
price change, excluding imports, for the follovnng reasons:
(a) The State of Hawaii is self-sufficient in the production of
all of the crops in question except tomatoes and cantaloupe.
69
Figure 4. Graphic Presentation of Demand and Supply Equations
S
Supply:Xl ~ -77.66 .0785X2R2 =.: .27
Demand:Xl ~ 45.01 - .0142X2R2
=: .70
---------------~f_____. I D
rIIJ
II
~ 40.....l-l
(:l.<
~ 30CI1!/JQ)
....-I
~ 20
:J....-I
~ 10go::r:
70Snapbeans
........"Cl
§ 60o0.-!/J~ 50Q)c:>'-'
o 200 400 600 800 1000 1200 1400 00 1800 2 00Honolulu l'iarket Supply (1000 pounds)
D
SUfll)ly:Xl ~ -644072+ .3791X2R2= .47
D\2m<lnd::·~1 =31034 - .0086X2.,1.\.4= 048
Hanoa Lettuce
-------------------------~
IiIII
3
Q)
~ 15!/JQ).-lo$10:J
....-I:J
'6 5r::S
........]g 30.!/JoWr::~ 25'-'
o 200 400 600 800 1000 1200 1400 1600 1800 2000Honolulu Market Supply (1000 pounds)
Figure 4 (Continued)
70
35
OJ 20u....~0..
OJ 15.-IcoC/)
OJ.-Io 10~::l.-I
.:; 5os:::2
CantaloupeDcr:1c.nd:
Xl 25.72 - .0048X2
R20= .82
D
o 200 400 600 800 1000 1200 1400 1600 1800 2000Honolulu H3".r!<et Supply (1000 pounds)
35Tomatoes
-] 30::l00-......~ 25s::OJu'-"
OJ 20u....~0-
OJ 15o-lcoC/)
OJ
'6 10~-::l
r-l 5::lr-I0s::0::r::
0 1
De;nand::{l = 25.64 - .0008X4R2 = .38
Supply:Xl -88.47 + .0238X2
2R =.25
D
2 3 4 5 6 7 8 9 10Honolulu i'1ari<;et Supply (1,000,000 pounds)
71
(b) The market structure of tomatoes and cantaloupe is of a
form that allows local production to be expanded, without
depressing local price, until all imports are replaced.
This market structure is indicated in Figure 5.
Where:
1. Hawaii is a deficit region importing Q2-Ql from
the West Coast.
2. The West Coast is a surplus region exporting Q2-Ql
to Hawaii. The figures given are approximate 1963
values for tomatoes in Hawaii and California (note
that the quantity axis for the West Coast is of a
much larger scale than that of Hawaii).
3. TIle equilibrium prices are Pw for the West Coast
and Pw + T (transportation cost) for Hawaii. The
West Coast supply curve has shifted from So to SA
because of the exporting activity.
4. Expansion of local supply (SH) could take place with
out significantly depressing price until local supply
equals total market supply (ST).
(c) Given the above assumptions it follows that expansion of
tomato and cantaloupe production would not reduce price until
imports are displaced. Beyond this point (Q2' PH in Figure 2)
price will move down the local demand curve as quantity
i~creases and existing producers will react in accordance
with their respective supply schedules.
Because the effect of price ch~nge on quantity supplied was of
primary interest a relatively simple supply model was selected. Perhaps
Figure 5. Theoretical Market Structure ~
of Tomatoes and Cantaloupe
72
Haviai i Hest Coast
~So
P'l = Pr,; -:- TIP'"r.. t, f ~':
I~ /1 I
I II I I
I I I DI
I I I II I I I
I I II II I I I
I I II I I II I I II I I III I
IT
I II I 54(Ql) 56(Q2)
I II I
6(Q2) 4(Ql)
Quantity (mi llion pounds)
73
the simplest possible supply function is that represented by Equation
(2).
(2) Qs = A + BPS-l
where:
Qs • quantity supplied
Pt-l = lagged market price
Beginning with this model, a graphic multiple regression analysis was
conducted to detennine the most appropriate price lag for each crop and
to test certain other variables. This analysis indicated a seasonally
shifting supply curve and the presence of a trend factor for all of the
crops except apple banana, for which the time variable was not signifi
cant. The most significant price lags for nearly all of the crops were
those corresponding to their respective growing periods. The model was
fitted by employing zero-one variables for the seasonal (quarterly)
shifts. The resulting model is of the form (3).
(3) Qs - A + BlPt-l + B2Ql + B3Q2 + B4Q3 BSQ4 + B6Y
where:
Qs = quantity supplied to Honolulu market by local producers
(1000 pounds)
A • intercept tenn
Bi - regression coefficients
Pt - l = Honolulu wholesale price lagged one time period
Qi ~ zero-one variables for quarters (each variable takes the
value of 1 for the months in that quarter and zero for
the other months)
If all four quarters are treated as zero-one variables a singular matrix
will result. Solution in this case was accomplished by deleting the
74
fourth quarter, ~, then estimating the coefficients with conventional
methods (64).
Supply functions were estimated with the model described earlier,
for all crops except cantaloupe. After estimation, the functions were
simplified to a form compatible with the demand equations. These
functions are given in Table 21.
TABLE 21. ANNUAL SUPPLY EQUATIONS FOR SELECTED CROPS - 1963
B CoefficientdYCrop A Intercept (Price) t R2
12,7332 2.38** .27** *Snapbeans 945.12 1.54( 5.3400)
3,709.32 41.9292 1.46W ** 1.16**Tomatoes .25(28.7664)
1,700.52 2.6376 .40N•S• ** 1.64~Manoa Lettuce .47(6.6480)
.26N•S• ** tYApple Banana 6,205.92 23.7840 .38(90.5112)
~ Durbin-Watson statistic for serial correlation in the residuals.
** Significant at one per cent level.
* Significant at five per cent level.
W Significant at 10 per cent level.
~ Test inconclusive.
tY Not computed because banana eventually drops out of the analysis(see text)¥
Deletion of the seasonal variables is based on the assumption of uniform
marketings by quarter for all of the crops in question, and that this
marketing pattern will continue in the future for any new land brought
into production. Table 22 indicates the quantity marketed in each
quarter for the several crops.
75
TABLE 22. PERCENTAGE MARKETED BY QUARTER FOR SELECTED CROPS 1959-63
Per Cent by QuarterCrop Ql Q2 Q3 ~
Snapbeans 22 27 26 ~
Tomatoes 26 31 22 21
Manoa Lettuce 25 W ~ ~
Apple ~nana 22 20 27 30
The price lags used in estimating these equations differ among the
crops considered. For snapbeans and tomatoes the most suitable lag was
found to equal their respective growing periods, or three and four
months. Manoa lettuce price is lagged one month but it takes two months
to produce a crop. This may result from the relatively high cost of
harvesting labor which could limit harvesting in periods of low price.
For apple banana a lag of six months is used and appears justifiable
from the standpoint of production methods. During low price periods,
fertilizer applications may be reduced and the planting allowed to
deteriorate, in which case about six months would lapse before the
effects are evident in reduced yields. About the same length of time
may be needed to rehabilitate neglected stands.
Figure 4 presents the computed supply equations in graphic form for
all crops in Group II with the exception of cantaloupe and apple banana.
The designated functions for these crops are omitted for reasons
previously given.
Estimated 1963 prices for snapbeans and Manoa lettuce were deter-
mined by simultaneous solution of the supply and demand equations.
Estimates of the 1963 market supply of these crops ~rere made by solving
76
the supply equations with the equilibrium prices. For cantaloupe and
tomatoes, total market supply functions were not computed. In the case
of these crops, the 1963 market price is estimated by first fitting a
simple linear regression to sales over time to estimate the 1963 supply
then solving the demand equations with this quantity. The resulting
functions (sales over time) are given below as equations (4) and (5).
(4) Xl = - 67,806.5 + 35.08X2 (cantaloupe)
(5) Xl = -160,897.2 + 85.37X2 (tomatoes)
where:
Xl :a Honolulu aOO'la1 supply (1000 pounds)
X2 ... Year
The regression coefficients for these equations are significant at t,ro
and one per cent while the R2,s are significant at five and one per
cent, respectively. Table 23 compares the estimated 1963 prices and
quantities with those actually recorded. The material presented in
Figure 4 and Table 23 should, for the most part, be self-explanatory.
However, the graph of tomato supply and demand may require further
clarification. This graph is actually the left-hand side of Figure 5
with the total market supply function missing. Market price, estimated
as outlined above, is indicated by point (a) in Figure 4. The local
supply function (SL) then indicates the quantity supplied by local
producers at this price (4,560,000 pounds as contrasted to the actual
local supply of 4,429,000 pounds). The difference between total market
supply and local supply equals estimated imports (2,130,000 pounds as
compared to 2,338,000 pounds actually recorded).
77
TABLE 23. ACTUAL AND ESTIMATED 1963 WHOLESALE PRICES
AND MARKET SUPPLIES FOR SELECTED CROPS
Crop
Snapbeans 27.2 1,202 26.8 1,286
Tomatoes 20.0 6,767 20.3 6,690
Manoa LettuceY 18.1 1,455 16.3 1,744
Cantaloupe£! 15.0 1,467 20.6 1,059
Apple Banana£! 9.7 5,363 9.3 6,437
~ The 1963 production of Manoa lettuce was abnormally low resulting inan unusually high price. 1962 actual and estimated prices are 15.8and 16.6 cents, respectively.
E{ The actual 1963 price recorded here is that received by localproducers for the 10,000 pounds marketed in 1963. It has littlemeaning for comparative purposes. Cantaloupe price was 17.5 cents,20.4 cents, and 17.3 cents for the years 1960, 1961, and 1962. The1961 and 1962 market supply of cantaloupe was 768 and 880 thousandpounds, respectively.
£! The market supply figures recorded here are for all bananas.
78
CHAPTER V
ESTLMATED LAND USE PATTERNS
In this chapter the estimating procedure developed earlier is used
to estimate patterns of land use for the three project areas being con
sidered. Each of the estimated land use patterns represents a competi
tive equilibrium under a particular set of assumptions and subject to
the limitations of the estimating model.
79
en class a orchard la~d.
Because of the above qualifications, only the vegetable crops need
to be considered within the program for most of the land use patterns.
The other crops that can be profitably grown are pineapple at Hoolehua
and papaya on class ~ orchard land. Both of these crops are assumed to
have perfectly elastic demand which allows them to be dealt with
indirectly by charging an opportunity cost, corresponding to their fixed
net return, to vegetable crops grown on the appropriate land classes.
If the vegetable crops are not at least as profitable the lands would be
allocated to either papaya or pineapple. Vegetable lands ~th the same
productivity rating can now be grouped, ~th identity of the different
lands being retained only when differences in opportunity costs occur.
In view of these considerations, the land class designations indicated
in Table 24 were established. The basic difference between Tables 2 and
24 is that in Table 24 all land types, in a given project area, that
have identical production costs for the uses being considered, have been
combined into a single land class designated Lei. In the case of area
one, additionally, land types one and 17 are combined because of the
small acreage of land type 17 (two acres).
To estimate realistically the land use patterns in the areas under
study, the possibility of encountering other restrictive factors (in
addition to land area and quantity) had to be considered. Preliminary
investigation indicated four factors that could potentially be restric
tive. They were: labor availability at Hoolehua, capital limitations,
freight service from Molokai, and water supply during seasonal peaks at
Hoolehua.
80
TABLE 24. LAND CLASSES USED IN THIS STUDY AND THEIR CHARACTERISTICS
L.S.B.Land Projec, L.S.B. Productivity MeasuredClass Area.! Land Type!Y Ratings£! Acreage
LCl 1 1, 17 la 2b 7a 680
LC2 1 3 ld 2c 219
LC3 2 23 2c 22
LCq. 3 3, 4, 5 2a 7a 56
LC5 3 9 2a 62
LC6 3 8, 19, 35 2b 86
LC7 3 37, 42 2c 69
Lea 3 32, 41, 47 2d 28
!I Pro j ect areasrespectively.
W See Table 2.
£! See Table 2.Hoolehua.
1, 2, and 3 are Hoolehua, Waianae Kai, and Waimanalo,
Pineapple is omitted from all project areas except
The budgets used in this analysis are based upon labor intensive
production methods that would require a large amount of hired labor for
a 25-acre unit. It is assumed that the necessary labor would be avail-
able on Oahu at the $1.25 wage rate. Molokai, however, does not have
the population of Oahu and it is conceivable that a labor shortage
could arise if a sizeable development of 25-acre units were attempted at
Hoolehua. For this reason several alternative use patterns were
estimated that incorporate different labor assumptions. These patterns
utilize wage rates, for Hoolehua, of $1.25 per hour (a common agricul-
tural wage), $1.50 per hour (the wage rate--including fring benefits--
earned by seasonal plantation employees on Molokai), and $2.00 per hour
81
(a wage rate that approximately equals that of permanent plantation
employees on Molokai). An additional pattern (IE) was estimated that
assumes 12 - 25-acre units at Hoolehua and imposes a quarterly labor
restriction on these operations.
Capital, the second potential restriction, was found on closer
investigation to pose no problems. State development programs for
agricultural land have typically included provision for adequate credit
at modest interest rates (48, p. 21).
This analysis assumes that Molokai production will be shipped to
Oahu by barge. Barge service is currently available and the existing
capacity is sufficient to handle the additional output. Air freight is
available but at a substantially higher cost. The problems encountered
with barge service are scheduling and transit time which appear to be
non-optimal for diversified crop production. Analysis of these problems
is beyond the scope of this study, therefore, no transportation restric
tions are imposed in this analysis. Tentative plans for a vacuum
cooling plant at Kaunakakai, Molokai, and increased barge service were
discussed at the Molokai Farm Conference on May 22, 1965. It was con
cluded at this time that if these facilities were needed they would be
provided.
The manager of the Water and Land Development Division, Department
of Land and Natural Resources, assured the Conference participants that
sufficient water would be available throughout the year. He also
indicated that as the need increases additional facilities will be
added. Plans are currently being prepared for a storage reservoir and
feeder lines to tap additional sources of supply.
82
One of the estimated patterns (IA) indicates that a substantial
acreage of papaya could be brought into production at Hoolehua. In
fact, it suggests an increase of nearly 50 per cent in total state
production. It has been assumed in this study that papaya production
could be expanded without depressing its price. While this assumption
is probably true for limited additional quantities it may not hold for
an increase of this magnitude. It was not considered necessary to
develop this possibility any further, however, because of the marginal
nature of this crop at Hoolehua where the cost-return margin on LCI is
.4 cents per pound. It is also doubtful that sufficient labor could be
provided at a wage of $1.25 per hour which, for all practical purposes,
excludes pattern LA from consideration.
Operator income, for all of the patterns discussed in this report,
is the sum of the return to management and labor income. In dollar
terms this would mean a return of $8,650, $9,900, and $12,400 for
patterns IA-IIA ($1.25 wage rate), IB-IIB ($1.50 wage rate), and IC-IIC
($2.00 wage rate), respectively. These income estimates assume 5,000
hours of family labor and a $2,400 return to management in each case.
The difference between the residual (net returns), associated ~th the
more productive land classes in some of the patterns, and contract land
rent would also accrue to the operator.
Land Use Pattern IA
This land use pattern assumes that management practices prevailing
in other producing areas will be used in the areas to be developed,
except in the following cases:
(a) Cantaloupe is treated as a multiple crop rather than being
gro,vn once each year in rotation with some other crop.
83
(b) A 25-acre production unit is assumed.
For the purposes of this pattern it is assumed that all of the required
labor would be available at a wage rate of $1.25 per hour. Under the
25 acre assumption and with a labor cost of $1.25 per hour, papaya can
be profitably grown on LCl end LC4' Because of the earlier assumption
that papaya faces a perfectly elastic demand curve it follows that it
could utilize the entire areas of these lands without reducing price.
The initial per acre opportunity rents for this pattern are Lel = $61
(papaya net return), LC2 = $30 (pineapple net return), and LC4 m $153
(papaya net return). In other words, if the vegetable crop in question
could not earn at least as much on a particular land class the land
would be allocated to the production of papaya or pineapple. Utiliza
tion of the remaining land classes begins with no rental charge.
Tables 25 and 26 summarize this use pattern.
Three acres of LC3 and all of LC7 and LC8 remain idle in this land
use pattern. The net returns figures represent returns over and above
all production costs (except land rent or interest on investment in
land). Economic rent, as defined in this report, occurs on LC2t LC5'
and LC6. TIlis interpretation of economic rent is a little uncomfortable
because it assigns greater rent values to certain lands that are physi
cally poorer than other lands. LC6' for example, enjoys an economic
rent of $164 per acre (the L.S.B. productivity rating is b) while LC4
earns no economic rent (L.S.B. productivity rating is a). This is true
because the $420 economic rent earned by tomatoes on LC4 becomes a
production cost for cantaloupe and subsequently becomes a production
cost for tomatoes because cantaloupe earns a like amount. The net
returns values computed for this pattern follow the traditional
84
TABLE 25. LAND USE PATTERN IA ASSUMING A 25-ACRE UNIT
AND A $1.25 \4AGE RATE2I
LC6Crop 1 2 3 4 5 7 8
Tomatoes
Acres 242 8 86
Net return per acre $61 $420 ($420) $164
Cantaloupe
Acres 48 62
Net return per acre $420 $423
Manoa lettuce
Acres 19
Net return per acre $0
Snapbeans
Acres 21
Net return per acre $61
Papaya
Acres 417
Net return per acre $61
Pineapple
Acres 219
Net return per acre $30
TOTAL ACREAGE 680 219 22 56 62 86 69 28
!I Bracketed values are net returns that would have been earned if thecrop had been produced on that land class.
85
TABLE 26. CHARACTERISTICS OF THE COMPUTED EQUILIBRIUM
CropTomatoes Cantaloupe Manoa Lettuce SnapbeansItem
Equilibrium price(cents/pound) 13.80 13.85 9.02 17.72
Total Market Supply(thousand pounds) 14,800 2,483 2,595 1,922
Production fromnew land(thousand pounds) 10,515 2,483 871 751
(Ricardian) view of economic rent for each single use. Tomatoes, for
example, earn $420 on land of productivity!. (LC4 and LC5) and $164 on
land of productivity ~ (LC6). LCI also has a physical productivity of ~
but has higher costs of production due primarily to location. Net
return on LCI equals the return of papaya ($61). Economic rent for
tomatoes is $267 (LC4)' $164 (LC6), and $0 (LCI) which is the marginal
land class or extensive margin. When multiple crops are considered
each LCi earns the same net return in each use in which it is engaged.
If there is no alternative use, and only one LCi is used; e.g. Manoa
lettuce on LC3 net return and economic rent is $0. Where one crop earns
slightly more than another, on a given LCi , the use earning the highest
return prevails; e.g., tomatoes and cantaloupe on LCS. As discussed
earlier, the conventional treatment of economic rent ignores opportunity
rent when computing production costs in the case of multiple crops. If
the reader prefers the conventional treatment, he can simply interpret
the net returns as economic rent.
86
Land Use Pattern IB
The assumptions of land use pattern IB are identical to those of
IA except that labor is charged $1.50 per hour at Hoolehua. The basis
for using this wage rate was developed earlier. Papaya cannot be grown
at Hoolehua under this wage assumption so an initial opportunity rent
exists only for LCl and LC2 and is determined by pineapple ($30 per acre
per year in each case). Tables 27 and 28 summarize this use pattern.
In this land use pattern only LC8 remains idle. The indicated net
returns values for pattern IB are now influenced by a factor other than
land quality. This is the higher labor cost imposed at Hoolehua which
makes the Oahu lands appear more productive (they are more productive in
an economic sense).
87
TABLE 27. LAND USE PATTERN IB ASSUMING A 25-ACRE UNIT
AND A $1.50 WAGE RATE FOR HOOLEHUA~
LC1 2 3 4 5 6 7 8Crop
Tomatoes
Acres 152 3 86 69
Net return per acre $30 ($137) $722 ($722) $441 $113
Cantaloupe
Acres 35 62
Net return per acre $722 $725
Manoa lettuce
Acres 18
Net return per acre $177
Snapbeans
Acres 4 17
Net return per acre $177 $722
Pineapple
Acres 528 219
Net return per acre $30 $30
TOTAL ACREAGE 680 219 22 56 62 86 69 28
!Y Bracketed values are net returns that would have been earned if thecrop had been produced on that land class.
88
TABLE 28. CHARACTERISTICS OF THE COMPUTED EQUILIBRIUM
ItemCrop
Tomatoes Cantaloupe Manoa Lettuce Snapbeans
Equilibrium price(cents/pound) 14.69 15.19 9.39 18.82
Total market supply(thousand pounds) 13,688 2,194 2,552 1,844
Production on new land(thousand pounds) 9,368 2,194 826 660
Land Use Pattern IC
This pattern is based upon the same assumptions as patterns IA and
IB except that labor at Hoolehua is now charged a wage rate of $2.00
per hour. The reasons for selecting this wage rate were discussed
earlier. The opportunity rent for LCI and LC2 is again determined by
pineapple ($30 per acre per year). This pattern is summarized in
Tables 29 and 30.
In this use pattern none of the lands remain idle. The main
difference between this and previous solutions is that diversified crop
production, on the lands included in this analysis, has shifted entirely
to Oahu. The beginning of this shift was evident with pattern IB but was
not complete until IC was estimated.
89
TABLE 29. LAND USE PATTERN IC ASSUMING A 25-ACRE UNIT
AND A $2.00 WAGE RATE FOR HOOLEHUA!!
Crop
Tomatoes
Acres
LC1 2 3 4
56
5
7
6
86
7
59
8
Net return per acre
Cantaloupe
Acres
Net return per acre
Manoa lettuce
Acres
Net returns per acre
Snapbeans
Acres
Net returns per acre
Pineapple
Acres 680 219
Net returns per acre $30 $30
7
$807
16
$807
$1,164 $1,317 $986 $578
58
($1,164)$1,320
10
$612
28
$319
TOTAL ACREAGE 680 219 22 56 62 86 69 28
~ Bracketed values are net returns that would have been earned if thecrop had been produced on that land class. The acreage and returnsfigures given in this table actually leave approximately 450 thousandpounds of tomatoes (production of 15 acres) in disposal. Thisapproximation was accepted because of the computing time involved inbringing this system to equilibrium.
90
TABLE 30. CHARACTERISTICS OF THE COMPUTED EQUILIBRIUM
CropTomatoes Cantaloupe Manoa lettuce SnapbeansItem
Equilibrium price 16.43 17.82 10.74 20.79(cents!pound)
Total market supply 11,512 1,646 2,395 1,706(thousand pounds)
Production from new land 7,109 1,646 667 496(thousand pounds)
Land Use Pattern ID
This pattern assumes prevailing management practices (except in the
case of cantaloupe which is treated as a multiple crop) and a production
unit of four acres (the prevailing unit size). It is further assumed
that family labor is sufficient to meet the needs of this unit, there-
fore, no restrictions other than land area and quantity are imposed.
The four vegetable crops are treated within the program with pineapple
included, as before, by adding an opportunity rent to the production
costs of the various vegetables On the relevant land classes. Tables 31
and 32 summarize this use pattern.
As indicated in Table 31, the entire areas of LC3, LC7, and LCaremain idle in this pattern. The net returns figures can be interpreted
as before.
91
TABLE 31. LAND USE PATTERN 10 ASSUMING A FOUR-ACRE UNIT
AND A $1025 WAGE RAT"#!
LC 1 2 3 4 5 6 7 8Crop
Tomatoes
Acres 104 42 86
Net return per acre ~~n $450 ($450) $130....oJ"
Cantaloupe
Acres 14 62
Net return per acre $450 $450
Manoa lettuce
Acres 13
Net return per acre $30
Snapbeans
Acres 16
Net return per acre $30
Pineapple
Acres 547 219
Net return per acre $30 $30
TOTAL ACREAGE 680 219 22 56 62 86 69 28
Y Bracketed values are net returns that would have been earned if thecrop had been produced on that land classo
92
TABLE 32. CHARACTERISTICS OF THE COMPUTED EQUILIBRIUM
CropTomatoes Cantaloupe Manoa lettuce SnapbeansItem
Equilibrium price 16.23 17.53 10.61 19.84(cents/pound)
Total market supply 11,763 1,706 2,410 1,772(thousand pounds)
Production from new land 7,367 1,706 682 574(thousand pounds)
Land Use Pattern IE
The assumptions of use pattern IE are similar to those of earlier
patterns except that a quarterly labor restriction is imposed on
diversified crop production at Hoolehua. This pattern assumes a wage
rate of $1.25 per hour.
Quarterly labor requirements for each crop were estimated from the
per acre growing and harvesting requirements and the cropping patterns
presented in Appendix B. Table 33 contains the quarterly labor require-
ments, for the several diversified crops, used in this pattern.
TABLE 33. QUARTERLY PER ACRE LABOR REQUIREMENT FOR DIVERSIFIED CROPS
Cro
Tomatoes 246 451 246 451
Cantaloupe 359 359 359
Manoa lettuce 284 426 426 284
Snapbeans 752 752 752 752
Papaya 108 108 108 108
93
The quantity of labor available during each quarter was estimated
as follows:
(a) The pattern assumes that 12 units ~ll be developed on 300
acres of LCI. This corresponds to the ~tate development
plan announced on May 22, 1965.
(b) It is assumed that each family ~ll be able to supply 5000
hours of labor per year. The basis for this estimate ~11
be discussed in a later section.
(c) The State of Hawaii reported 91 persons unemployed on
Molokai as of April 1, 1965. It is assumed that all of
these workers would b~ willicg to work on the newly
developed lands at $1.25 per hour.
On the basis of the above assumptions, available labor is estimated at
247,200 hours per year or 61,800 hours per quarter. Tables 34 and 35
summarize the pattern of land use resulting.
The net return values given in Table 34 are substantially larger
than those of Table 25. As indicated earlier the only difference
between these patterns is the labor restriction imposed at Hoolehua.
The difference can be attributed to an economic rent accruing to labor
as a factor of production. No effort is made to distinguish between
these land and labor rents because for the purposes of this study these
values can be related to land alone.
Of the 300 acres of LC1 available for diversified crop production,
166 acres shifted to pineapple in this solution. In practice this means
that under the assumptions of this use pattern only 45 per cent or 11
acres of each 25-acre unit would be utilized.
94
TABLE 34. LAND USE PATTERN IE ASSUMING A 25-ACRE UNIT,
A $1.25 WAGE RATE, AND A QUARTERLY LABOR RESTRICTION AT HOOLEHUA!!
LC 1 2 3 4 5 6 7 8Crop
Tomatoes
Acres 130 4 23 86 69
Net returns per acre $310 $113 $691 ($691) $413 $89
Cantaloupe
Acres 33 62
Net returns per acre $787 $790 ($89)
Manoa lettuce
Acres 18
Net returns per acre $154 ($89)
Snapbeans
Acres 4 25
Net returns per acre $383 $0
Pineapple
Acres 546 219
Net returns per acre $30 $30
TOTAL ACREAGE 680 219 22 56 62 86 69 28
Y Bracketed values are net returns that would have been earned if thecrop had been produced on that land class.
95
TABLE 35. CHARACTERISTICS OF THE COMPUTED EQUILIBRIUM
CropTomatoes Cantaloupe Manoa lettuce SnapbeansItem
Equilibrium price 14.60 15.48 9.35 18.62(cents/pound)
Total market supply 13,800 2,133 2,557 1,858(thousand pounds)
Production from new land 9,485 2,133 832 676(thousand pounds)
Land Use Patterns for Hoolehua
All of the land use patterns discussed in this section were esti-
mated by simply determining how much additional production ~uld be
reqUired to force price to the production cost level. This procedure
can be used because the diversified crops considered in this study fail
to use the entire acreage of the best land at Hoolehua. Because of this
simplification it was possible to estimate four land use patterns
wdthout using the program. These use patterns are identical to patterns
LA, IB, IC, and ID discussed earlier except that they apply only to
Hoolehua.
Land Use Pattern IIA
This land use pattern assumes the same per acre input levels as lA,
multiple cropping of cantaloupe, and a 2S-acre production unit. Land
area and quantity demanded are the only restrictions imposed on this
pattern. The assumed wage rate is $1.25 per hour. Table 36 summarizes
use pattern IIA. Table 36 indicates that the entire area of LCl could
be brought into production of the five crops considered.
No economic rent accrues to LCI or LC2 in this pattern. Papaya
could utilize the entire area of Lel at a rental rate of $61 per acre
96
per year and pineapple could utilize LC2 at $30 per acre per year.
These amounts were added to the production costs of the other crops.
This means that at the indicated prices a $61 net return for LCl and a
$30 net return for LC2 exists for the designated uses.
TABLE 36. LAND USE PATTERN IIA ASSUMING A 25-ACRE UNIT
AND A $1.25 WAGE RATE
Production fromCro New Land
(thousand pounds
Tomatoes 13.8 14,800 10,512 337
Cantaloupe 14.6 2,317 2,317 127
Manoa lettuce 9.1 2,585 861 17
Snapbeans 17.7 1,923 753 20
Papaya 9.0 10,525 2,739 179
Pineapple 219
TOTAL 899
~ This price is equal to per unit production costs including a $61 peracre opportunity rent for papaya on LeI.
~ Papaya is grown on the 179 remaining acres of LCl and pineapple onthe 219 acres of LC2•
Land Use Pattern lIB
Use pattern lIB is identical to pattern IIA except that labor is
charged at the rate of $1.50 per hour. The basis for this rate was
discussed earlier. Table 37 summarizes pattern IIB. The interpretation
of the acreage estimates given in Table 37 is identical to that of
pattern IIAc
97
TABLE 37. LAND USE PATTERN IrB ASSUMING A 25-ACRE UNIT
AND A $1.50 WAGE RATE
Equilibr}Uffi Total Market Production fromCrop Price!. Supply New Land AcreageP!
Tomatoes 14.8 13,550 9,220 296
Cantaloupe 15.9 2,046 2,046 112
Manoa lettuce 10.0 2,482 754 14
Snapbeans 19.7 1,782 586 16
Pineapple 461
TOTAL 899
~ This price is equal to per unit production costs including a $30opportunity rent for pineapple on LC1• Papaya cannot be grown iflabor is $1.50 per hour.
E/ Pineapple is grown on the remaining 242 acres of LCl and on the 219acres of LC 2.
Land Use Pattern IIC
Use pattern IIC is identical to both patterns IIA and IIB except
that labor is now charged $2.00 per hour. The basis for using this wage
rate was discussed earlier. Table 38 summarizes pattern IIC.
98
TABLE 38. LAND USE PATTERN rIC ASSUMING A 25-ACRE UNIT
AND A $2.00 WAGE RATE
Equilibr;um Total Market Production fromAcreageE!Crop Price! Supply New Land
Tomatoes 17.1 10,675 6,249 200
Cantaloupe 18.8 1,442 1,442 79
Manoa lettuce 11.1 2,353 623 12
Snapbeans 23.9 1,487 238 7
Pineapple 601
TOTAL 899
!I This price equals per unit production costs including a $30 opportunity rent for pineapple on LC1.
~ Pineapple is grown on 382 acres of LCl and 219 acres of LC2.
Land Use Pattern lID
This land use pattern assumes prevailing management practices
(except in the case of cantaloupe which is again treated as a multiple
crop) and a four-acre unit. It is further assumed that family labor is
sufficient to meet the needs of this unit, therefore, no restrictions
other than land area and quantity demanded are imposed. The assumed
wage rate is $1.25 per hour. Table 39 summarizes pattern lID. Inter-
pretation of the data given in Table 39 is identical to that of earlier
use patterns. The only difference between the assumptions of this
pattern and IIA is that unit size has been changed (from 25 to four
acres).
99
TABLE 39. LAND USE PATTERN IID ASSUMING A FOUR-ACRE UNIT
AND A $1.25 WAGE RATE
Equi 11 br}um Total Market Production fromAcreageP.!Crop Pricea Supply New Land
Tomatoes 16.2 11,800 7,411 238
Cantaloupe 18.7 1,462 1,462 80
Manoa lettuce 10.6 2,412 684 13
Snapbeans 19.8 1,775 578 16
Pineapple 552
TOTAL 899
!I This price equals per unit production costs including a $30 opportunity rent for pineapple.
~ Pineapple acreage includes 333 acres of LeI and 219 acres of LC2•
Stability of the Land Use Patterns
It would have been possible to re-run each final land use pattern
with a linear programming system that ranges the restrictions and
objective function. This is usually done to indicate the range over
which these values could vary without changing the basis or solution.
It appears that this procedure would give some idea of the tolerance or
allowable error that could occur in the cost budgets or demand and
supply functions. Such an interpretation must be approached with some
caution. The quantity restrictions at the equilibrium position are
established by the intersection of the market demand function and the
newly generated supply function for each crop. A change in quantity
must be accompanied by a shift of either the supply or demand curve,
which would also change price. A change in price would, in turn, change
the level of net return. Because these values are inseparably related,
100
ranging them individually ~uld have little meaning. The objective
function supplies a certain amount of information about the computed
equilibrium. Referring to Table 27 it is obvious that if cantaloupe net
returns fell (due to a cost or demand shift) from $725 to $721 per acre,
a basis change would occur. Similarly, a cantaloupe price rise would
cause tomato to be displaced from LC40 The objective function, because
of the way it is computed, is in effect already ranged. The land areas,
in a particular application, are fixed, which eliminates the need for
ranging these restrictions.
Solutions would need to be tested for stability whenever additional
restrictions have been imposed (other than land area and quantity). In
this study only pattern IE, with quarterly labor restrictions, is in
this category. It was decided not to rearun this pattern because of the
time involved and the limited value of the additional information.
Derived Labor Demand Curves for Hoolehua
An interesting by-product of land use patterns A, B, and C are the
labor demand curves that can be constructed from them. Using per acre
per year labor requirements data for the five diversified crops, a
total requirement can be estimated for each pattern. For the purposes
of thib study the relationship of primary interest is the quantity of
labor that can be hired at each wage rate. Estimated available family
labor is deducted from the total requirement to obtain the quantity of
labor that could be hired at each wage.
Available family labor can be estimated directly from the cost of
production budgets. It is generally assumed that family labor is
sufficient to operate a four-acre diversified crop unit. If these
101
family operated farms produced single commodities, the following
quantities of family labor \~uld be required:
Tomatoes 5,576 hours per year per farm
Cantaloupe 4,308 hours per ~~ per farm
Manoa lettuce 5,680 hours per year per farm
Snapbeans 12,032 hours per year per farm
Papaya 2,500 hours per year per farm
Tomatoes and cantaloupe are the largest land users, among the diversi
fied crops, in most of the patterns considered in this study. For this
reason and due to a lack of data family labor is assumed to be 5,000
hours per family per year. With this amount of labor available, a
family operated unit producing only snapbeans would not be possible.
It is necessary to establish the number of diversified crop units
that could be developed under each use pattern. This must be done for
patterns A, B, and C under both I and II development plans. Table 40
gives these values.
Figure 6 shows the relationship between the hourly wage rate and
the difference between required labor and available family labor
(converted to annual worker units). The resulting functional relations
can be interpreted as derived labor demand CU4ves for Hoolehua under the
assumptions of patterns rA, IB, IC and lIA, lIB, IIC, respectively. The
function representing these relationships is of the form (6).
(6) Xl = a - bX2
where: Xl = hourly wage rate
X2 = number of hired workers
As would be expected, the curves shown in FigurE~ 6 are quite different.
102
If only the Hoolehua lands are developed (II) labor commands a much
higher wage than if the entire area being studied (I) is developed.
There are currently 91 unemployed persons on Molokai that could be
given full-time work at wages in excess of $1.50 per hour under either
plan.
TABLE 40. LABOR REQUIREMENT FOR SELECTED LAND USE PATTERNS
Entire Area Developed
PatternRequired
Units Labor(hours/year)
FamilyLabor(hoursyear)
Worker a/uivalent-
IA ($1.25 wage)
IB ($1.50Hoolehua wage)
IC ($2.00Hoolehua wage)
Hoolehua Only
27
6
o
581,494
211,888
o
135,000
30,000
o
446,494
181,888
o
215
87
o
IIA ($1.25 wage) 27
IIB ($1.50 wage) 18
IIC ($2.00 wage) 12
768,543
601,256
401,979
135,000
90,000
60,000
633,543
511,256
341,979
305
246
164
~ Represents hired labor divided by 2,080 hours which is taken to beone full-time employee.
-. 3.001Ill-lC\l 2.75.-l
.-l0"0
2050'-'
(lJuell 2.25""'(!)00C\l 2.00~
>..-l 1.75""'::J,Q""~.I
....~ 1.50~-<
1.25
1.00
.75
.50
.25
Figure 6. Derived Demana Curves for Hired Labor at Hoolehua
(I) Xl C 1092 - .003X2
(II) Xl = x.77 - .005X2
on1" (II)...... Hoolehua __ .'.1
---------------- . "' d8velop,d (I)-------- En ti 2.'2 en: cd
I
o 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400
X2 Hi red ','Orkers
.....ow
104
CHAPTER VI
SOME ECON~~IC EFFECTS OF EXPANDED PRODUCTION
ON EKISTING STATE PRODUCERS, THE STATE AS A WHOLE, AND THE CONSUMER
It is obvious that development of new agricultural land under any
of the patterns discussed in this report would work to the disadvantage
of existing state producers. What is not so obvious is that the
consumer and the state as a whole may benefit, perhaps greatly, from
such a development. The purpose of this chapter is to examine some of
the measurable changes that would be expected to occur under selected
land use patterns. The land use patterns estimated for the entire study
area, that assume 25-acre units and Hoolehua wage rates of $1.25 and
$1.50 per hour, and that pattern assuming a four-acre unit with a $1.25
wage rate will be analyzed in this context. Similar results would be
obtained for the corresponding Hoolehua patterns because the final
product prices are nearly identical in each case. Pattern ID (25-acre
unit and a $2.00 wage rate) is omitted because it was not considered
likely to result in the study area.
Changes in Producer and State Output
Table 41 gives the expected change in output for existing state
producers and the expected change in total state production, for
pattern ~ The indicated changes occurring in existing producer out
put are very small. Total state output on the other hand has increased
sUbstantially in every case.
Table 42 indicates the expected change in output for existing state
producers and the state as a whole, for pattern lB.
In general, the results of this development plan are nea~ly
identical to those presented in Table 41. It will be recalled that the
105
TABLE 41. CHANGES IN OUTPUT RESULTING FR~i L~ID USE PATTERN LA
THAT ASSUMES A 25-ACRE UNIT p~D A $1.25 WAGE RATE
Change in OutputExisting State Projected State For Existing Producers
Cro Production Production Amount Acres!!thousand pounds thousand pounds (thousand pounds
Tomatoes 4,560 14,800 -275 9
Cantaloupe 0 2,483 0 0
Manoa lettuce 1,744 2,595 - 20 .5
Snapbeans 1,286 1,922 -115 4
Papaya 10,525 15,654 0 0
~ The acreage estimates were made by dividing pounds by the product ofclass b yield multiplied by the number of crops that can be grown atWaimanalo.
TABLE 42. CHANGES IN OUTPUT RESULTING FROM LAND USE PATTERN IB
THAT ASSUMES A 25-ACRE UNIT AND A $1.50 WAGE RATE FOR HOOLEHUA
CroExisting State Projected State
Production Production(thousand pounds (thousand pounds
Change in OutputFor Existing ProducersAmount Acres!!
thousand pounds
Tomatoes 4,560 13,688 -240 8
Cantaloupe 0 2,194 0 0
Manoa lettuce 1,744 2,552 - 18 .4
Snapbeans 1,286 1,844 -102 4
~ See footnote a, Table 41.
only assumption difference between these patterns is in the wage rate at
Hoolehua. The effect of this difference was to increase all of the
prices slightly, which iu turn reduced total market supply. Existing
106
state producers would find that they are slightly better off under IB
a~d their production would decline less than in the case of IA.
Table 43 presents the output changes associated with land use
pattern ID. This pattern is based upon the prevailing (diversified
crop) unit size of four acres. Because of this it would be expected to
have a smaller effect on existing producers than either of the
previously discussed patterns.
TABLE 43. CHANGES IN OUTPUT RESULTING FROM LAND USE PATTERN ID
THAT ASSUMES A FOUR-ACRE UNIT AND A $1.25 WAGE RATE
Change in OutputExisting State Projected State For Existing Producers
Cro Production Production }mount Acres!!(thousand pounds (thousand pounds (thousand pounds)
Tomatoes 4,560 11,763 -164 5
Cantaloupe 0 1,706 0 0
Manoa lettuce 1,744 2,410 - 16 .4
Snapbeans 1,286 1,772 - 88 3
Y See footnote a, Table 41.
Of the three patterns only IA allows papaya to be produced. The
reasons for increased production not affecting existing papaya producers
have been discussed previously. The reduction in output of existing
producers is very small for the other crops, because of the highly
inelastic nature of the computed supply functions. In terms of fa~
units, none of these patterns would force more than the equivalent of
three producers out of the production of these crops. In reality this
change ~~uld probably t&<e the form of shifting to the production of
crops other than those included in the analysis. Another likely outcome
107
of any development plan would be for some of the existing producers to
move to the newly developed land. A shift of this type is not only
possible but encouraged by the state as part of the development program.
An analysis of the ramifications of this possibility is beyond the scope
of the present study.
Changes in Producer and State Income
Even though the output of existing producers does not appear to
change significantly under the different patterns, their income does.
For the purposes of this comparison only changes in gross income will be
considered. Gross income is defined as the Honolulu ~olesale price
multiplied by marketable output. Total state income is computed in the
same manner. Table 44 indicates the estimated income changes associated
with land use pattern IA.
TABLE 44. CHANGES IN INCCME RESULTING FRCM LAND USE PATTERN IA
THAT ASSUMES A 25-ACRE UNIT AND A $1.25 WAGE RATE
EKisting Gross Projected Gross Projected Income ofCrop State Income State Income EKisting Producers
Tomatoes $ 925,680 $2,042,400 $ 591,330
Cantaloupe 0 343,896 0
Manoa lettuce 284,272 234,069 155,505
Snapbeans 344,648 340,578 207,501
Papaya 947,250 l~408 ,860 947,250
TOTALS $2,501,850 $4,369,803 $1,901,586
It is apparent from Table 44 th~t development of the study lands
according to pattern IA would reduce the income of existing producers by
nearly 25 per cent (39 per cent if papaya is excluded). Total state
108income, on the other hand, rose by approximately 75 per cent (90 per
cent if papaya is excluded). This income increase is actually under-
stated because it does not include the value added between Wholesale
and retail. These values are used here for purposes of comparison only,
and should not be considered measures of state income attributable to
the various crops. The multiplier effect has also been ignored in this
discussion. Some of the increase in expenditure for diversified crops
would doubtlessly be at the expense of impo~ted produce. The plugging
of this income "leak ll would tend to increase state income and would be
subject to a multiplier effect. In general, the amount of state income
thus created would depend upon how much leaked to the mainland on each
round of subsequent spenJing.
Table 45 indicates the income changes associated ~th land use
pattern IB. For pattern IB the income of existing producers fell by
34 per cent while total state income rose 88 per cent. Interpretation
of the results is subject to the same limitations as pattern IA.
TABLE 45. CHANGES IN INCCME RESULTING FRCM LAND USE PATTERN IB
THAT ASSUMES A 25-ACRE UNIT AND A $1.50 WAGE RATE FOR HOOLEHUA
Existing Gross Projected Gross Projected Income ofCrop State Income State Income Existing Producers
Tomatoes $ 925,680 $2,010,767 $ 634,608
Cantaloupe ° 333,269 °Manoa lettuce 284,272 239,633 162,071
Snapbeans 344,648 347,041 222,829
TOTALS $1,554,600 $2,930,710 $1,019,508
109
Table 46 indicates the income changes associated with land use
pattern ID.
TABLE 46. CHANGES IN INCOME RESULTING FROM LAND USE PATTERN ID
THAT ASSUMES A FOUR-ACRE UNIT AND A $1.25 WAGE RATE
Existing Gross Projected Gross Projected Income ofCrop State Income State Income Existing Producers
Tomatoes $ 925,680 $1,909,135 $ 713,471
Cantaloupe 0 299,062 0
Manoa lettuce 284,272 255,701 183,341
Snapbeans 344,648 351,565 237,683
TOTALS $1,554,600 $2,815,463 $1,134,495
Pattern ID, as expected, has the smallest effect on existing vegetable
producer income. In this case, existing producer income falls 28 per
cent While total state income increases 81 per cent. Again, interpreta-
tion of these results is subject to the same limitations as for pattern
IA.
Changes in the Wholesale Price Level
Each of the land use patterns considered in this report would cause
reductions in the wholesale price level for most of the included crops.
Although a consideration of how these changes might effect retail prices
and consequently the consumer is beyond the scope of this study, an
approximation can be made. For convenience it is assumed that the
retail margin is constant. That is, a one cent drop in the price at
wholesale would reduce retail price by a like amount. For patterns lA,
IB, and IC, the vegetable price changes given in Table 47 occurred.
110
TABLE 47. ESTIMATED WHOLESALE PRICES FOR SELECTED LAND USE PATTERNS
era
Tomatoes
Cantaloupe
Manoa lettuce
Snapbeans
20.3
20.6
16.3
26.8
13.80
13.85
9.02
17.72
14.69
15.19
9.39
18.82
16.23
17.53
10.61
19.84
It is evident from Table 47 that the expected price reductions are
substantial. Pattern IB, for example, would reduce wholesale price by
5.6, 5.4, 6.9, and 8.0 cents per pound for tomatoes, cantaloupe, Manoa
lettuce, and snapbeans, respectively. If the assumption of a constant
retail margin holds a similar decline would occur at the retail level.
111
CHAPTER VII
Sili~E ADDITIONAL CROPS THAT APPEAR TO OFFER POTENTIAL
FOR ACREAGE EXPANSION
This study has considered in some detail the possibility of
expanding the production of a relatively small number of crops. In this
chapter expansion of several additional crops (zucchini squash, eggplant,
Irish potatoes, passion fruit, and macadamia nuts) ~ll be discussed in
a more general manner. Some major limitations are inherent in the
approach used here. First, a demand curve was not constructed for any
of these crops. In fact, only for zucchini squash and eggplant is
sufficient data available from which to estimate a demand relationship.
Secondly, only limited cost of production and yield data are available.
Within these limitations, the following discussion will attempt to
point out some of the relevant factors influencing the possibility of
expanding the production of these crops in the areas under study.
Vegetable Crops
One objective of this study was to discover what the effect of
bringing new vegetable land into production would be on crop prices. A
selected group of four crops was used to provide a basis from which to
consider vegetable production in general. It can be argued that such a
small number of crops is not an adequate basis upon which to make
generalizations. While this may be true, it is also true that the vast
majority of vegetables that could be grown in these areas could utilize
only very small acreages as long as the Honolulu market must absorb all
additional production. During the 1963-64 season the Hawaii Agricul
tural EKperiment Station Demonstration Farm at Eoolehua conducted trials
112
(on 1/5 acre plots) for eggplant, cucumbers, zucchini squash, bell
peppers (two plots), and tomatoes (t\~ plots). From this group of five
crops eggplant, zucchini squash, and tomatoes appeared to be promising
(35). Eggplant returned over $1,400 per 1/5 acre plot based on actual
sales in the Honolulu market (35). The test plot upon which this is
based is small, therefore any error is compounded when stated in per
acre terms. The state is nearly self-supporting in this crop \~.th a
supply of slightly over 700,000 pounds per year. With the yield level
recorded by the Demonstration Farm, Which represents above average
management, the total existing market supply could be grown on 11 acres
with one crop or 5.5 acres with two crops per year. On this basis, it
appears safe to assume that additional production would affect price
markedly and that only limited acreage could be brought into production
without reducing price below per unit cost. Zucchini squash indicated a
return of nearly $500 per 1/5 acre (35) but again it appears that this
crop could profitably utilize only a limited acreage. The total
Honolulu supply of all squash could be grown on 10 acres (at the
reported 28,300 pound yield per acre) with one crop, or five acres with
two crops per year.
There are three vegetable crops, potatoes, dry onions, and carrots,
for which production could be expanded without reducing price. This is
true because most of the market supply is currently imported from the
U. S. mainland. Of the three, cost of production and yield estimates
are available only for potatoes (12). This material is based on planta
tion yield experience during WOrld War II and synthesized cost data.
According to this study the cost of producing potatoes in Hawaii is
nearly three times as high as the California cost but because of high
113
yields (potentially high, as current yield levels are far below those
assumed) and lower transportation cost a net return of from $12 to $728
per acre appears possible. This return level depends upon wholesale
price, yield, and cost structure, and does not include costs for such
items as transportation from Molokai and real property tax, which should
total about $60. The study cited uses wholesale prices of $6.04 and
$8.33 per cwt. and defines a high and low cost unit. The acreage
required to supply the Honolulu market by 1965 was estimated at from
1,400 to 2,000 acres based upon a 15-20,000 pound per acre yield, one
crop per year, and population and consumption estimates. If the price
and cost data upon Which this discussion is based are reliable, the
expansion of potato production in Hawaii is feasible.
The three crops discussed here are generally suited to the areas
being considered. Potato production in Hawaii or at least in the areas
of study may be restricted to one crop per year because of the summer
heat.
Orchard Crops
Two orchard crops which appear to have a future in Hawaii as export
crops, and that could be grown in the areas under study, are passion
fruit and macadamia nuts. The discussion in this section is based upon
cost and return budgets prepared by Joseph T. Keeler (29, 31).
Converting the passion fruit budget to a base comparable to that
used in this study; i.e., $1.25 per hour for labor; $2,400 return to
management; a 25-acre unit; and $330 for water, irrigation labor, and
transportation expenses, allows it to be considered in comparison with
the other crops. Assuming a 30,000 pound yield per year, the price per
pound could drop from the current 5.5 to 4.8 cents per pound and still
114
cover production costs. Data on wholesale price and quantity sold are
not available for this crop so it is nOw known how many additional acres
could be brought into production before price wouid fall to this level.
Scott (56) shows that a market could be developed for the production of
2,250 acres (assuming a 30,000 pound yield which is sUbstantially higher
than average) with a comprehensive promotional campaign. It is probably
realistic to assume that the acreage could be expanded gradually, with
sufficient promotion, without adversely affecting price. The immediate
concern, however, is with the effect on price of a current increase in
output and this cannot be determined from available data.
Macadamia nuts offer another orchard crop possibility for these
lands. Converting the budget prepared by Keeler to a comparable base,
using the procedure outlined for passion fruit, indicates that with a
marketable yield of 5,865 pounds (in shell - 2500 pounds shelled) and a
price of around 20 cents per pound, macadamia nuts could be profitably
grown. Scott (57) provides an estimate, for 10 years hence, of 20
million pounds, or the production of 13,300 acres (assuming a 1500 pound
yield - shelled). This level of sales could be achieved by the time
current plantings reach maturity.
The two orchard crops discussed here are not equally suited to the
study areas. The HAES Demonstration Farm at Hoolehua uses passion fruit
windbreaks that yield well and show no wind damage, this crop appears to
be equally suited to the other areas. Macadamia nuts on the other hand
can be grown in all of the areas but are susceptible to wind damage and
are not gro\~ to best advantage under irrigated conditions. Current
acreages of both crops are far below the estimated requirements. In
January 1963 there were 4,420 acres in macadamia nuts and 290 acres in
115
passion fruit.
It is possible to include any crop in the program for which the
necessary demand, sup~ly, and budget data are available. Of the five
crops discussed in this section only eggplant and zucchini squash are in
this r ~gory. These crops could utilize such a small acreage that it
was not ~.'nsidered worthwhile to include them in the detailed analysis.
\
116
CHAPTER VIII
SUMMARY AND CONCLUSIONS
Summary
Evaluation of a land development project necessitates estimation
of the land use pattern that will probably result in the project area.
Ideally, this estimation would include all of the production alterna
tives faced by the producer. In practice, however, a complete analysis
of this type would seldom be possible. The present study considers a
selected group of crops that includes those most likely to be grown in
important quantities.
The estimating procedure utilizes an iterative linear programming
model to allocate lands of varying quality among uses in such a way as
to assure that each physical land class is being utilized in its best
agricultural use. The best agricultural use is defined as that use
earning the highest net return. Market demand functions for each crop
were incorporated in the solution procedure because the level of return
changes with quantity for all crops with a downward-sloping demand.
Market supply functions were also included for these crops, as it was
necessary to measure the effects of expanded production on existing
produce~s.
Land use patterns were estimated for four- and 25-acre units, two
different development plans, and for various labor assumptions. These
patterns indicate that with 25-acre units, and assuming that the entire
area will be developed, the announced first increment at Hoolehua
(Honolulu Advertiser, May 24, 1965) can be utilized only if a $1.25 per
hour wage rate prevails. There is some doubt that sufficient labor
would be available on Molokai at this wage. If Hoolehua only were
117
developed, the producers could pay as much as $2.00 per hour and utilize
the entire area (300 acres). Hired labor demand curves, derived for
Hoolehua under both development plans, indicate that the 91 persons
currently unemployed on Molokai could be given work at $1.50 per hour.
Under the several development plans, the output of existing
producers changes only slightly. Total state output, on the other hand,
increases greatly (40 to 200 per cent). The gross income earned by
existing producers is reduced by 25-30 per cent while total gross state
income after development increases by 75-90 per cent. Wholesale prices
are reduced substantially in each case.
Most crops not considered in the study could utilize only a limited
acreage. Notable exceptions to this were carrots, potatoes, and dry
onions which could be expanded greatly without reducing price. These
crops can only be grown as one crop per year, during the winter.
Certain orchard crops appear to offer some potential, but expansion
depends upon the level of market promotion.
Emplications
Differences between the several land use patterns occur as the
result of wage rate variations, changes in assumed unit size, imposed
labor restrictions, and modification of the assumed area to be develope~
The State Department of Land and Natural Resources, as the planning
agency in this venture, can control only two of these variables, unit
size and area to be developed. Even in the case of unit size the degree
of control is not absolute because a farmer with a 25-acre unit, for
example, may choose to utilize only part of it in actual production.
Recent evidence (Honolulu Advertiser, May 24, 1965) seems to
indicate that the state is committed to an initial development plan for
118
the Hoolehua lands only. The first increment of this development is to
be composed of l2-25-acre units. For immediate planning needs, those
patterns estimated for the Hoolehua lands only and based on a 25-acre
unit appear to be the most appropriate. The only difference between
these patterns is the wage rate. Selection of the pattern that would
most closely approximate reality depends upon the wage that would have
to be paid to obtain the required labor. The author feels that plan IIB
($1.50 wage rate) probably comes the nearest to accomplishing this.
Labor would not be restrictive if the wage was sufficiently high to
attract workers to Molokai. On the basis of pineapple company expe
rience, a wage of $1.50 per hour is sufficient to do this. It should be
restated, however, that if only the Hoolehua lands are developed for
diversified crop production, the new faDners could pay up to $2.00 per
hour for labor, while still utilizing the 300 acres of LCI (see pattern
IIC). Pattern IIB could utilize over 400 acres of LCI while paying
$1.50 per hour for all labor. Another approach to estimating a land use
pattern for Hoolehua would be to assume a fixed amount of available
labor and then compute the use pattern. This was done for the entire
area, ~th the labor restriction imposed only at Hoolehua (pattern IE),
but could not be computed for Hoolehua alone because the programming
model will not accept problems involving a single land class and more
than one restriction. It is possible to anticipate what would happen if
a corresponding pattern were computed for Hoolehua. To begin with,
papaya drops out of the pattern IE because it cannot compete for scarce
labor. Tomatoes are grown on 130 acres and Manoa lettuce on four acres
of LCI. If only Hoolehua were developed, with the same labor restric
tions used in pattern IE, more crops, probably all of the vegetable
119
crops, would be grown at Hoolehua but total acreage would not increase.
Actually fewer acres would probably be utilized because the labor
requirement for tomatoes is one of the lowest of the vegetable crops
being considered. This means that approximately 50 per cent of each
unit would remain idle. Obviously, this idle land results from labor
becoming restrictive. In the case of pattern IE, labor is restrictive
in the second and fourth quarters only, with about 27,000 hours left
unused in each remaining quarter. If the assumption of prevailing
management practices is relaxed, in reference to the prevailing cropping
patterns used in this study, it would be possible to reconstruct the
budgets and demand curves on a quarterly basis, thus allowing quarterly
patterns to be estimated.
Validity of Findings
Production costs were estimated, for the various land classes,
from existing cost of production studies and are assumed to accurately
represent conditions in Hawaii. If these costs are in error it would,
of course, effect the land use patterns. All known existing data, as
well as materials based upon personal interviews with Experiment Station
and Extension Service specialists, have been incorporated in the cost
budgets. IE in the future conflicting but more reliable data should be
made available or if costs should change, the land use ~atterns can be
recomputed utilizing the new cost structure.
The yield estimates used in this study probably tend to be conser
vative for high quality irrigated land. It was felt, however, that
because of the lack of information regarding the effects of ~~nd and the
difficulty in ~ssessing the contribution of management in those
instances where high yields have been recorded, it would be better to
120
retain the above yield estimates. Two of the study crops in particular
(tomatoes and bananas) appear to offer potentially higher yields.
Tomatoes have yielded 30-50 tons per acre on an annual (2-crop) basis
(varieties N-52 and N-55) under irrigated conditions. One of the
highest recorded yields was on the Molokai Demonstration Farm at
Hoolehua. The level of management on this farm is quite different from
the prevailing levels assumed in this study. Irrigated bananas have
also recorded yields several times larger than those used here, but
these yields were in sheltered areas. ~indbreaks at Hoolehua that are
sufficient to protect bananas will not be available for some time, if
at all (51).
The estimated demand functions, for ~ich some statistical tests
of reliability are provided in Appendix C, have been previously
discussed in some detail. If even one of these equations is in error
the computed land use patterns would indicate incorrect acreages and
returns for all crops. In this analysis no attempt has been made to
quantify the changes that would occur from variations in these functions.
The supply functions used in this study were estimated with a
relatively simple model. Although the fits obtained ~th this model
leave much to be desired statistically, there did not appear to be a
practical alternative to the procedure employed. Errors in these func
tions would influence the acreage that could be brought into production
at a given price. The more inelastic the true relationship is, the less
significant this source of error becomes. The elasticity of supply
measured over the range of price change associated with land use
pattern IA (~ich reduces price more than any of the other patterns)
indicates inelastic supply for all crops for which supply was estimated.
121
The coefficients of elasticity are .16, .25, and .02 for tomatoes,
3napbeans, and Manoa lettuce, respectively.
The computed land use patterns are only as reliable as the data
used in the programming model. In this section an attempt has been made
to establish the type of error that would occur in the estimated land
use patterns as a result of errors in the input data. It should be
re-emphasized at this point that computed net return levels would be in
error if the factors influencing their measurement are not adequately
controlled. As the actual level of return does not enter in the evalua
tion of the respective'patterns, this possibility should not pose a
serious problem. Far more important than the actual level of returns is
the relative level between uses.
Suggestions for Further Research
The land use patterns estimated in this study are based'on data for
a single year, 1963. Amore satisfactory planning approach would be to
project levels of demand and production costs to some future period,
computing land use patterns for each intervening year, so that a land
development scheme could be devised. This scheme should represent
changes in population, income, competitiveness of the several crops, and
any other factor that might significantly affect one or more of the
crops.
There are a number of other areas that could easily justify
additional research. In terms of the input data a logical next step
would be to const);llct a set of budgets for better than average or
perhaps optimum input levels. The possibility of export markets for
winter vegetables should be explored more fully, perhaps to the extent
of estimating demand curves for selected export markets. With these
122
data, the patterns could be recomputed.
The programming procedure developed for this study should be
tested on other types of problems. For example, estimating a land use
pattern for an entire state or region would be a good test of the
efficiency of the program in handling larger problems.
123
APPENDIX A
DESCRIPTION OF LAND TYPES
The following land type descriptions are from the detailed land
classification reports (3, 44) published by the Land Study Bureau,
University of Hawaii.
Molokai
Land Type
1
Description
Deep, red (Molokai) soils; nonstony to slightlystony; slopes less than 10%; average annualrainfall (AAR) less than 20 inches; moderate tostrong winds.
3 Moderately deep, red (Molokai) soils; stony;slopes less than 10%; AAR less than 25"; moderateto strong winds.
7 Moderately deep, red (Molokai and Lahaina) soils;slopes less than 40%; eroded; AAR less than 25".
17 Moderately deep; nonstony to slightly stony, dark(Kawaihapai and Hanalei) soils; nearly levelcoastal flat areas.
Oahu 3 Included are nonstony, moderately deep to deep,well-drained, moderately fine to fine-texturedlands having brownish-red to red surface soil overred subsoil. The soils have developed on uplandpositions from residuum of basic igneous rocks andfrom old alluvium. Soil reaction is slightly acidto mildly alkaline. Slopes range from 0 to 10 percent. Soil series include Maliko, Mamala (greaterthan 20 inches deep), Molokai, and Lahaina. Landsare easily worked. Median annual rainfall variesfrom 15 to 40 inches. Elevations range from 0 to1000 feet.
4 Included are non-stony, deep, well-drained, mediumto moderately fine-textured lands having brownsurface soil over yellowish-brown subsoil. Thesoils have developed from volcanic ash and cinderswashed from adjacent uplands. Soil reaction isneutral to mildly alkaline. Slopes range from 0 to10 per cent. Included is the Koko soil series.Lands are easily worked. Median annual rainfallvaries from 10 to 20 inches. Elevations rangefrom 0 to 200 feet.
O~u
Land TYEe
5
l~
Description
Included are ncnstony, deep, well-drained, mediumto fine-textured lands having brown to darkreddish-brown surface soil over dark brovm subsoil.These young soils are derived from recent alluvium.Soil reaction is slightly acid to neutral~ Slopesrange from 0 to 10 per cent. Soil series includedare the Kawaihapai and Pulehu. Lands are easilyworked. Median annual rainfall varies from 10 to40 inches. Elevations range from 0 to 600 feet.
8 Included are nonstony (except for Kaena),moderately deep, moderately well to imperfectlydrained, fine-textured lands having dark grayishbrown to grayish-black surface soil over subsoilin which gray and brown colors are often mottledwith tints of yellows, browns, and reds. The soilshave developed from old alluvium and residuum ofbasic igneous rocks under the influence ofrestricted drainage. Soil reaction is neutral tomildly alkaline. Slopes range from 0 to 10 percent. Soil series and complexes included areHonouliuli, Honouliuli-Mamala Complex, Kaena,Kalihi, Keaau, Kokokahi, Lualualei, Makalapa,Papaa, and Waimanalo. Lands are difficult to workbecause the soils are very plastic and sticky whenwet and very hard when dry. In localized areas,the impeded internal drainage restricts growth ofcrops that require good drainage. Median annualrainfall varies from 15 to 60 inches. Elevationsrange from 0 to 500 feet.
9 Included are nonstony, deep, well-drained, finetextured lands having dark reddish-brown to brownsurface soil over red subsoil. The soils havedeveloped on upland positions (including highterraces) from old alluvium or residuum from basicigneous rocks. Soil reaction is strongly to slightly acid. Slopes range from 0 to 10 per cent.Included are the Alaeloa, Kaneohe, and Lolekaaseries. Lands are easily worked. Median annualrainfall varies from 40 to 100 inches. Elevationsrange from 0 to 800 feet.
19 Included are nonstony, deep, well-drained,moderately fine to fine-textured lands having darkreddish-brown surface soil over red subsoil. Thesoils have developed on upland positions fromresiduum of basic igneous rocks. Soil reaction ismedium acid. Slopes range from 11 to 20 per cent.Included are the Alaeloa, Kaneohe, and Lolekaaseries. Lands are difficult to work because of
125
Land Type Description
Oahu slope. Median annual rainfall varies from 40 to80 inches. Elevations range from 10 to 1000 feet.
23 Included are stony, deep, well-drained, moderatelyfine to fine-textured lands having red to reddishbrown surface soil over red to brown subsoil. Thesoils have developed from recent and old a11uviunl.Soil reaction is slightly acid to neutral. Slopesrange from 0 to 10 per cent. Soil series includedare Ewa, Kahuku, Kamananui, Pu1ehu, and Waialua.Lands are difficult to work because of stoniness.Median annual rainfall varies from 15 to 40 inches.Elevations range from 0 to 400 feet.
32 Included are nonstony, deep, well-drained,moderately fine to fine-textured lands havingreddish-brown to dark red surface soil and redsubsoil. They have developed on upland positionsfrom residual lava or old alluvium. Soil reactionis strongly acid. Slopes range from 21 to 35 percent. Soil series included are Kahana, Kunia, andWahiawa. Lands are difficult to work because ofslope. Median annual rainfall varies from 30 to60 inches. Elevations range from 250 to 1200 feet.
35 Included are stony, deep, imperfectly to welldrained, medium to fine-textured lands having darkreddish-brown to dark grayish-brown surface soilover brown subsoil. The soils have developed onbottomland positions from recent alluvium. Soilreaction varies from medium acid to neutral.Slopes range from 0 to 10 per cent. Soil seriesincluded are Hanalei and Kawaihapai. Lands aredifficult to ,~rk because of the stoniness. TheHanalei soils are subject to occasional flooding.Median annual rainfall varies from 30 to 80 inches.Elevations ranges from 0 to 300 feet.
37 Included are stony, deep, well-drained, moderatelyfine to fine-textured lands having dark reddishbrown surface soil over brown subsoil. The soilshave developed on old alluvial terraces. Soilreaction is very strongly acid to strongly acid.Slopes range from 0 to 10 per cent. Included isthe Lokekaa soil series. Lands are difficult towork because of the stoniness. Median annual rainfall varies from 40 t~ 90 inches. Elevations rangefrom 20 to 500 feet.
Oahu
Land Type
41
126
Description
Included are stony, deep, vrell-drained, medium tofine-textured lands having dark reddish-brownsurface soil over reddish-brown subsoil. The soilshave developed on old alluvial terraces or volcaniccinder deposits. Soil reaction is very strongly tostrongly acid. Slopes range from 11 to 20 percent. Included are the Lolekaa and Ualakaa soilseries. Lands are difficult to work because of theslope and stoniness. The layer of soil materialover cinders may be rather thin in the case of theUalaka~ soils. The Lolekaa soils are usuallydeficient in bases including potassium and calcium,and phosphorus fixation is high. Median annualrainfall varies from 40 to 90 inches. Elevationsrange from 20 to 500 feet.
42 Included are stony, moderately deep, imperfectly-drained, fine-textured lands having very dark graysurface soil over brown, gray, yellowish-brown, andolive, mottled subsoil. The soils have developedOn upland positions from old alluvium or lavasweathered in place, under conditions of restrictedinternal drainage. Soil reaction is neutral tomildly alkaline. Slopes range from 11 to 20 percent. Soil series and complexes included areHonouliuli, Kaena, Lualualei, Lualualei-Ewa Complex,Makalapa, and Papaa. Lands are difficult to workbecause of the slope, stoniness, and stickinesswhen wet. Median annual rainfall varies from 15 to40 inches. Elevations range from 0 to 500 feet.
47 Included are nonstony, deep, well-drained moderatelyfine to fine-textured lands with dark reddish-brownsurface soil over reddish-brown to red subsoil.The soils have developed on upland positions fromlava weathered in place. Soil reaction is mediumacid. Slopes range from 21 to 35 per cent. Soilseries included are Alaeloa, Kaneohe, Lolekaa,Nakalele, and Paaloa. Lands are difficult to workbecause of slope. Special problems range fromacidity to erodibility. Median annual rainfallvaries from 40 to 80 inches. Elevations range from10 to 1000 feet.
56 Included are rocky, deep, imperfectly to welldrained, medium to fine-textured l&;ds having darkred to very dark brown surface soil and red to graysubsoil. The soils have developed on uplands,upland talus positions, or alluvial flats fromresiduum of basic igneous rocks or from alluvium.Soil reaction ranges from slightly acid to neutral.
127
Land Type Description
Oahu Slopes range from 0 to 35 per cent. Soil seriesand complexes included are the Ewa, Hanalei,Honouliuli, Kaena, Kahana, Kahuku, Kawaihapai,Kawaihapai-Lualualei Complex, Koko, Lahaina,Lualualei, Lualualei-Ewa Complex, Mahana, Makalapa,Mamala, Molokai, Nakalele, Pulehu, Rockland Coral,Rocky lands, Stony lands, and Rough Broken LandSoil Complexes. Lands are virtually impossible towork because of the rocks, and in some cases,slope. Median annual rainfall varies from 25 to80 inches. Elevations range from 0 to 1500 feet.
57 Included are stony or rocky, shallow, well-drained,medium to fine-textured lands having variablesurface and subsoil colors. The soils havedeveloped on uplands or upland alluvial positionsfrom residuum of basic igneous rocks or fromalluvium. Soil reaction is quite variable. Slopesrange from 36 to 80 per cent. Soil series andcomplexes included are Ewa, Ewa-Lualualei Complex,Kaena, Kunia, Lahaina, Lolekaa, Lualualei, Lualualei -Ewa Comple."<:, r.1ahana, Manana, Molokai, Waikapu,and the (Rough Broken Land) Soil Complexes. Landsare virtually impossible to work because of theslope. In some cases, erosion is a serious problem.Median annual rainfall varies from 15 to 100 inches.Elevations range from nearly sea level to 1500 feet.
58 Included are generally steep pali lands havinglittle o~ no soil mantle over the rock material.Drainage is usually good because of the slope.Color varies with the rock composition and degreeof weathering. Slopes generally do not ~xceed
35 per cent, although some inclusions may be moresteep. Many of these lands occur on the sides ofgulches which dissect the open cultivated lands,but large areas belonging to this unit are found inthe Waianae and Koolau mountain ranges. Because ofthe slope and the lack of soil materials, theselands are not suited for agricultural uses. Amountand distribution of rainfall are highly variablethroughout the area of occurrence. Median annualrainfall varies from 15 to about 250 inches.Elevations range from 150 to 4000 feet.
128
APPENDIX B
IRRIGATION REQUIREMENTS
Waimanalo
Irrigation requirements for the study crops produced at Waimanalo
were estimated by multiplying inches of pan evaporation by an average
growing period consumptive use coefficient then deducting effective
rainfall. This procedure is based upon materials supplied by the Soil
Conservation Service. Table B-1 illustrates the calculation of these
requirements for the Waimanalo area. To complete the estimation of
water requirements for this area it was necessary to know during Which
months the "typical" vegetable farmer would grow the various crops. The
follo~ng cropping pattern was established from interviews with
EXperiment Station specialists (Horticulture):
Manoa lettuce (4 crops) April-May, June-July,
August-September, October-November
Snapbeans (3 crops) February-March-April, May-June-July,
August-September-October
Tomatoes (2 crops) February-March-April-May,
September-October-November-December
Cantaloupe (3 crops) February-March-April, May-June-July,
August-September-October
TABLE B-1. IRRIGATION REQUIR~1ENTS FOR STUDY CROPS AT WAIMANALO
Pan Evaporation Average Growing Period Rainfall Irrigation bl~ Inches per Month~(E) Consumptive Use (K) (E)·(K) Total Effective Requirement--Other Other Other Other
Bananas crops£! Bananas Crops£! Bananas Crops£! Bananas crops£!
January 4.5 .85 .58 3.82 2.61 2.0 1.34 1.09 2.48 1.52
February 4.6 .85 .58 3.90 2.66 1.4 1.00 .70 2.90 1.96
March 4.9 .85 .58 4.19 2.86 1.9 1.34 1.15 2.85 1.71
April 6.0 .85 .58 5.08 3.l~7 1.2 1.05 .70 4.03 2.77
Hay 7.3 .85 .58 6.24 4.26 .8 .70 .60 5.54 3.56
June 8.9 .85 .58 7.54 5.14 .5 .50 .40 7.04 4.74
July 9.0 .85 .58 7.61 5.19 .6 .50 .45 7.11 4.74
August 7.8 .85 .58 6.60 4.50 .6 .50 .35 6.10 4.15
September 7.3 .85 .58 6.20 4.23 .8 .72 .70 5.48 3.53
October 6.6 .85 .58 5.59 3.82 1.1 .80 .68 4.79 3.14
November 4.3 .85 .58 3.68 2.51 1.8 1.30 1.10 2.38 1.41Decembei:' 4.3 .85 .58 3.68 2.51 2.5 1.70 1.50 1.98 1.01
-~ Pan (!vaporation data obtained from reference (l~7).
£I There are 27,154 gallons of water in one acre inch.
£! Other crops consist of snapbeans, Manoa Lettuce, tomatoes, cantaloupe and papaya.
.....N\0
130
Waianae Kai and Hoolehua
Pan evaporation data are not available for Hoolehua. However,
Soil Conservation Service and Experiment Station specialists felt that
conditions at Hoolehua were similar to those found at Waianae Kai;
consequently, Waianae Kei data are used for both areas. Estimating
procedures are similar to those described above for Waimanalo and are
summarized in Table B-2. The Waianae Kai-Hoolehua cropping patterns
were established through interview with Experiment Station specialists
(Horticulture):
Manoa lettuce (5 crops) February-March, April-May,
JUne-July, August-September, October-November
Snapbeans (4 crops) January-February-March, April~ay-June,
July-August-September, October-November-December
Tomatoes (2 crops) February-March-April-May,
September-October-November-December
Cantaloupe (3 crops) January-February-March,
April-May-June, July-August-September
APPENDIX C
DEMAND CURVE TABLES
The average monthly sales for each of the included crops are given in Table C-l. Tables C-2 through
C-6 present the vegetable and orchard crop dem~.d functions used in this study. The interpretations of
these equations is discussed in the text under Demand Analysis~
TABLE C-l. AVERAGE MONTHLY SALES FOR SELECTED CROPS 1959-63~
Month Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. DecoCrop
Snapbeans 100 91 114 l24E! 13oE1 117E! ll~ 116 119 122 lO~ 98E1
Tomatoes 433E! 31~ 367E! 45lE! 440 422 395 358 274 297 307'E1 446E!-..
Manoa lettuce 131 112 151 151 152 140 126E1 133£/ 124E! 125E! 117£/ 134E1
Apple banana 564 448 453E1 42o'E! 444E1 443E! 523E! 612£1 641 709 644 630
~ The demand curve for cantaloupe is fitted without a seasonal shift.
£! High price months.
....WI-.:>
TABLE C-2. MULTIPLE REGRESSION OF SNAPBEAN PRICES
Source DF SS MS F R Sguare-Regression 3 0.463920E 04 O. 154640E 04 0.918705E 02 O. 703788 E 00
Residual 116 0.195256E 04 0.168324E 02
Source ~ Coefficient Standard Error Mean Std. Dev. R T
X( 1) Snafbeanpr ce -0.130279E 04 0.266521E 03 0.217817E 02 0.410273E 01
X( 2) Snapbeansupply -0. 170272E-00 0.125671E-01 0.1l7800E 03 0.308762E 02 -0.782468E 00 -0.135490E 02
X( 3) Year +o.686561E 00 0.135946E-00 0.195850E 04 0.281652E 01 0.390582E-00 0.505024E 01X(lO) Season !0.127980E 01 0.759452E 00 0.500000E 00 0.502096E 00 -0. 287164E-00 -0.337034E 01
TABLE C-3. MULTIPLE REGRESSION OF TOMATO PRICES
Source OF SS MS F R Square- -Regression 3 0.891258E 03 0.297086E 03 0.242024E 02 00 384965E-00
Residual 116 0.142391E 04 0.122751E 02
Source ~ Coefficient Standard Error Mean ~d. Dev. R T-X( 1) Tomato
price -0.975692E 03 0.230460E 03 0.179683E 02 0.350358E 01x( 4) Total
tomatosupply -0.100688E-01 0.423231E-02 0.525508E 03 0.839358E 02 -00 276l79E-00 -0.237902E 01
X( 7) Year +O.510700E 00 0.117940E-OO 0.195850E 04 0.281652E 01 0.279957E-00 Oo432473E 01X( 9) Season to.201171E 01 0.68 7060E 00 0.500000E 00 0.502096E 00 -0.525909E 00 -0.585599E 01
....\.oJW
TABLE C-4. MULTIPLE REGRESSION OF MANOA LETTUCE PRICES
Source OF SS MS F R Square
Regression 3 0.972885E 03 0.324295E 03 0.353622E 02 00477681E-00
Residual 116 0.106380E 04 0.917067E 01
Source Name Coefficient Standard Error Mean Std. Oevo R T- -X( 1) Manoa
lettuceprice -O.216604E 04 00251244E 03 00142208E 02 0.302831E 01
X( 2) Manoalettucesupply -0.103198E-00 0.124034E-Ol 0.1l6592E 03 0.293697E 02 -0. 264500E-00 -0.832014E 01
X( S) Year +0.111937E 01 0.128769 E-OO 0.195850E 04 0.281652E 01 00 292692E-00 0.869289E 01X(ll) Season ±0.088456E-00 0.557059E-Ol O.SOOOOOE 01 0.502096E 01 00283391E-00 0.317585E 01
TABLE C-5. SIMPLE REGRESSION OF CANTALOUPE PRICES
Source OF SS MS F R SquareRegression 1 0.405046E 03 0.405046E 03 0.714851E 02 0.817112E 00Residual 16 0.906585E 02 0.5666l6E 01
Source Name Coeffi cient Standard Error Mean Std. Oev. R T-X( 1) Cantaloupe
price 0.257213E 02 0.105730E 01 0.18l444E 02 0.238037E 01
X( 2) Cantaloupesupply -0.579616E-01 0.685540E-02 0.D0722E 03 0.842146E 02 -00903942E 00 -O.845489E 01
l-'W~
TABLE C-6. MULTIPLE REGRESSION OF APPLE BANANA PRICES
Source DF SS MS F !L2.suare
Regression 3 0.971206E 02 0.323735E 02 0.853634E 02 0.688248E 00
Residual 116 0.439923E 02 0.379244E-00
Source Name Coefficient Standard Error Mean Std. Dev. R T-X( 1) Apple
bananaprice -0.571858E 03 0.391831E 02 0.770833E 01 0.615828 E 00
X( 2) Bananasupply -00285318E-02 0.645183E-03 0.531167E 03 0.982895E 02 -0. 270148E-OO -0.442228E 01
X( 6) Year +0. 296703E-00 0.200205E-Ol 0.195847E 04 0.282843E 01 0.750378E 00 0.148200E 02X( 8) Season ;to.166684E-00 O.125964E-00 O.SOOOOOE 00 0.502096E 00 O.262817E-00 00264653E 01
I-'WVI
APPENDIX D
SUPPLY CURVE TABLES
The vegetable and orchard crop supply functions used in this study are presented in Tables 0-1
through D-4. The interpretation of these equations is discussed in the text under Supply Analysis.
TABLE D-l. MULTIPLE REGRESSION OF SNAPBEAN SUPPLY
~:!. DF SS MS F ~uare
Regression 5 0.306112E 05 0.612225E 04 0.832160E 01 0.267390E-00
Residual 114 0.838705E 05 0.735706E 03
Source Name Coefficient Standard Error Mean Std. Dev. R T-X( 2) Snapbean
supply 0.108516E 03 0.923215E 01 0.118450E 03 00271239E 02
X( 3) Year -0.354848E 01 0.101126E 01 0.525000E 01 0.291692E 01 -0. 198908E-00 -0.350899E 01
X( 6) Price L3 0.106113E 01 0.445023E-00 0.215267E 02 0.756999E 01 0.124484E-00 0.238444E 01
X(24) Q1 -0.124097E 02 0.705645E 01 0.250000E-00 0.434828E-00 -0.354218E-00 -0.175863E 01
X(25) Q2 0.178070E 02 0.747482E 01 0.250000E-00 0.4348 28 E-OO 0.323065E-00 0.238227E 01
X(26) Q3 0.174843E 02 0.7.39757E 01 0.250000E-00 0.434828E-00 0.108104E-00 0.236352E 01
I-'Lv~
TABLE D-2. MULTIPLE REGRESSION OF TOMATO SUPPLY
Source DF SS MS F R Square-Regression 5 O.321132E 06 0.642263E 05 0.756745E 01 0.249196E-00
Residual 114 0.967538E 06 0.848718E 04
Source Name Coefficient Standard Error Mecm Std. Dev. R T
X( 1) Tomatosupply O.322263E 03 0.384%7E 02 0.390650E 03 O.921259E 02
X( 2) Price I.4 O.349411E 01 0.239723E 01 0.177458E 02 O.446624E 01 0.239857E-00 0.145756E 01
X( 4) Year -0.433861E 01 O.314590E 01 0.550000E 01 0.288432E 01 -0. 737721E-01 -0.1379l3E 01
X( 5) Q1 0.222650E 02 0.237868E 02 0.250000E-00 0.434828 E-OO -0.8979l3E-Ol 0.936024E 00
X( 6) Q2 0.105257E 03 0.268256E 02 0.250000E-00 0.434828 E-OO 0.473099E-00 0.392375E 01
X( 7) Q3 -0.654879E 01 0.2580S1E 02 0.250000E-00 0.434828 E-OO -0.169276E-00 -0. 253779E-OO
t-'W'-I
TABLE 0-3. MULTIPLE REGRESSION OF MANOA LETTUCE SUPPLY
Source OF SS MS F !LSquare
Regression 5 0.481190E OS 0.962381E 04 0.201202E 02 0.468782E-00
Residual 114 0.s4s280E OS 0.478316E 03
Source ~ Coeffi ci ent . Standard Error ~ Std. Oev. R T
X( 1) Manoalettucesupply 0.717328E 02 0.949723E 01 0.116s92E 03 0.218704E 02
X( 2) Price L1 0.219835E-00 0.s54011E 00 0.141950E 02 0.414117E 01 0.112576E-00 0.396807E-OO
X( 4) Q1 -0. 22s937E-00 0.s68900E 01 0.2s0000E-:00 0.43413 28 E-OO -0.143283E-00 -0. 397147E-01
X( 5) Q2 0.204013E 02 0.608664E 01 0.250000E-00 0.434828E-00 0.251526E-00 0.335182E 01
X( 6) Q3 0.870310E 01 0.589378E 01 0.2s0000E-00 0.4348 28 E-OO 0.2s1691E-01 0.147666E 01
X( 8) Year 0.627612E 01 0.734415E 00 0.550000E 01 0.288432E 01 0.625601E 00 0.854573E 01
....W0:>
TABLE D-4. MULTIPLE REGRESSION OF BANANA SUPPLY
Source DF SS MS F !L29.uare
Regression 4 0.444118E 06 0.111029E 06 0.175244E 02 0.378707E-00
Residual 115 0.728604E 06 0.633569E 04
Source Name Coefficient Standard Error Mean Std. Coeff. R T-X( 1) Banana
supply 0.596352E 03 0.627750E 02 0.532000E 03
X( 2) Price 1.6 0.198201E 01 0.754258E 01 0.748417E 01 0.208938E-01 0.244394E-00 0.262777E-00
X( 4) Q1 -0.110807E 03 0.213367E 02 0.250000E-00 -0.485357E-00 -0.186499E-00 -0.518840E 01
X( 5) Q2 -0.157833E 03 0.221446E 02 0.250000E-00 -0.691340E 00 -0.464885E-00 -0.712737E 01
X( 6) Q3 -0.481039E 02 0.210228E 02 0.250000E-00 -0. 210705E-00 0.181827E-00 -0.228817E 01
I-"W-0
140
APPENDIX E
CC»IPUTING FACILITIES REQUIRED FOR DATA ANALYSIS
The Statistical and Computing Center at the University of Hawaii
is presently equipped vnth an IBM 7040 computer. This installation was
used for all of the data analysis included in this study.
Computing Time by Phase
The approximate computing time required for each phase of the
investigation is as follows:
Regression analysis • • • • • • • • • • • • • • • 1.5 hours
De-bugging the linear programming system •••• 2.5 hours
Estimation of land use patterns • • • • • • • • • 1.0 hours
In addition to this machine time a substantial amount of programmer time
was supplied by the Center to assist in writing and de-bugging the
linear programming system.
Computing Time Required for Estimating Land Use Patterns
Computing time required for the different land use patterns varied
from two to 10 minutes depending upon the nature of the problem. The
longest runs occurred with patterns IB, IC, and IE where either the high
cost or restrictiveness of Hoolehua labor forced the crops to compete
for the limited Oahu lands. In patterns IA and ID the large acreage of
high quality land (680 acres of Lel) at Hoolehua entered early allovnng
rapid convergence. The approximate computing times for the several
patterns are listed below.
141
Pattern
IA ($1.25 ~vage; 25-acre units) • • 0 • • • • • • 0 • • •
IB ($1.50 wage at Hoolehua; 25-acre units) • • • • • • •
IC ($2.00 ~vage at Hoolehua; 25-acre units) • • • • • • •
ID ($1.25 wage; four-acre units) • • • • • · • • · • • •
Computing Time(minutes)
2
3
10
2
IE ($1.25 wage; 25-acre units; quarterly laborrestrictions at Hoolehua ••••••••• • • • • • 7
In cases of slow convergence it is possible to obtain preliminary
results by interrupting the solution process. Frequently, these results
will contain sufficient data for deleting one or more of the crops
before attempting a subsequent run. Crops could be deleted if they are
entering on insignificant acreages or if their acreages change little
from one stage of the solution to the next. If they are deleted for the
latter reason the acreage in the regions where they are to be grown must
be reduced appropriately. It may also be found that the system is close
enough to a solution for the intermediate results to be used as they
are. To reduce the likelihood of slow convergence the program could be
modified as follows:
(a) Price need not be modified according to the production
costs of the several producing regions as was done in this
study. If price is changed by a uni'form amount at each
step of the solution process the major cause of slow
convergence is removed. However, this modification of
the procedure will affect the accuracy of the results as
the final price for each crop may be higher or lower than
the actual price.
(b) An approximate solution could be accepted by writing a
degree of allowable error into the program. There are a
number of ways of doing this; perhaps the most obvious is
to accept a solution that is ~thin a given range of the
required market supply.
142
143
REFERENCES
1. Adams, R. L. Farm Management Crop M~. Universi ty ofCalifornia Press, 1953.
2. • Farm Managemant Livestock Manual. University ofCalifornia Press, 1954.
3. Baker, H. L. Molokai: Present and Potential Land Use. L.S.B.Bulletin No.1. University of Hawaii, August, 1960.
4. Barlowe, Raleigh. Land Resource Economics. Prentice-Hall, Inc.,1958.
5. Bembo1:ver, William. Banana Production in Hawaii. CooperativeEXtension Service, University of Hawaii, June, 1962.
6~ Case, Frederick Eo Real Estate. Allyn and Bacon, Inc., 1962.
Civilian Population, Births Deaths, and Migration Data of Hawaiiby Geographic Area, 1950-l9~3. Hawaii Department of Health, April,1963.
8.
9.
Dorfman, Robert, Paul A. Samuelson and Robert M. Solow. LinearProgramming and Economic Analysis. New York: McGraw-Hill Book Co.,Inc., 1958.
Egbert, Alvin C. and E. O. Heady. Regional Adjustments in GrainProduction. U. S. Department of Agriculture in Cooperation withIowa Agricultural EXperiment Station, Technical Bulletin No. 1241and Supplement, June 1961.
10. Ely, Richard T. and George S. wehrwein~ Land Economics. TheMacmillan Co., 1940.
11. Ezekiel, Mordecal and Karl A. Fox. Methods of Correlation andRegression Analysis. New York: John Wiley & Sons, Inc., 1961.
12. Feasibility Study on Potatoes. Unpublished report from the filesof the Hawaii State Department of Agriculture, November, 1964.
13. Foytik, Jerry. Demand Characteristics for Vine Vegetables inHonolulu, Hawaii, 1947-61. Agricultural Economics Bulletin No. 23,University of Hawaii, December, 1964.
14. • Demand Characteristics for Selected Fruits in Honolulu,Hawaii, 1947=61. Agricultural Economics Bulletin No. 24, Unive;';si ty of Haws~ i:- December, 1964.
15. • Intraseasonal Demand Shifts for Fruits and Vegetables.Paper presented at the annual meeting of the Western Farm EconomicsAssociation, San Luis Obispo, July 15-17, 1964.
144
16. Hamilton, Richard A. Papayas Grown on Shallow Clay Soil. HawaiiFarm Science, Agricultural Experiment Station, University o£Hawaii, January, 1954.
17. Heady, Earl O. Economics o~ ~ricultura1 Production and Resource~. Prentice-Hall, Inc., 1964,.
18. Heady, Earl 0., et...!l. Agricultural Supply Functions. Ames, Iowa:Iowa State University Press, 1961.
19. Heady, Earl O. and Yalfred candler. Linear Programming Methods.Ames, Iowa: Iowa State University Press, 1960.
20. Hogg, Howard C. ''Returns to Land and Gross State Income FromRanching Operations in Hawaii." L.S.B. Unpublished Report, June,1964.
21. Hogg, Howard C. and Harold L. Baker. Ranching Costs and Returns Maui. L.S.B. Miscellaneous Report No.1, University of Hawaii,NOV'einber, 1961.
22. • Ranching Costs and Returns - Kauai. L.S.B. Miscella-neous Report No.2, University of Hawaii, February, 1962.
23. Ran~hing Costs and Returns - Hawaii. L.S.B. Miscella-neous Report No.3, University of Hawaii, March, 1962.
24. Ranching Costs and Returns - Oahu. L.S.B. MiscellaneousReport No.4, University of Hawaii, June, 1962.
25. • Ranching Costs and Returns - Mo1okai. L.S.B. Miscella-neous Report No.5, University of Hawaii, September, 1962.
26. Honolulu Unloads. United States Department of Agriculture, MarketNews Service Cooperating with Hawaii Department of Agriculture.Annual. 1954-63.
27. Johnston, J. Econometric Methods. New York: McGraw-Hill BookCo., Inc., 1963.
28. Judge, G. G. and T. D. Wallace. Estimation of Spatial PriceEqUilibrium Models. Journal of Farm Economics, Vol. XL, No.4.November, 1958.
29. Kee~er, Joseph T. Cost and Returns Budget for Macadamia Nuts.Department of ~gricultural Economics, University of Hawaii. Unpublished Report, 1964.
\\
Department of AgriculUnpublished Report, 1964.
30. Cost and Returns for Bananas.tural Economics, University of Hawaii.
145
31. Keeler, Joseph T. Cost and Returns for Passion Fruit. Departmentof Agricultural Economics, University of Hawaii. UnpublishedReport, 1964.
32. Cultural Methods and Costs in Growing Puna Papayas.Department of Agricultural Economics, University of Hawaii. Unpublished Report, 1964.
33. Keeler, Joseph T. and Donald M. Kinch. Diesel Versus Gasoline inSmall Wheel Tractors. Agricultural Economics Report No. 43,University of Hawaii, January, 1960.
34. Keeler, Joseph T., K. Mihata and W. Nakashima. Economic FactorsAffecting the Production of Papayas in Waimanalo, Oahu. Agricultural Economics Report No. 49, University of Hawaii, June, 1961.
35. Larson, A. B. and L. B. Rankine. Report on Molokai DemonstrationFarm for 1963-64. Agricultural Economics Progress Report, University of Hawaii. In process.
36. Lefeber, Louis. Allocation in Space: Production, Transport, andIndustrial Location. Amsterdam: North-Holland Publishing Co.,1958.
37. Long-Term Projections of Demand and Supply for Selected Agricultural Commodities. New De1.hi: National Council of AppliedEconomic Research, 1962.
38. Lucas, E. C. Demand and Price Structure of Tomato in Hawaii andIts Implication for Control of Market Supply. Department ofAgricultural Economics, University of Hawaii. Unpublished Paper,January, 1965.
39. McCOnnell, Douglas J. Preliminary Studies on the Feasibility ofProducing Vegetables on Mo1okai. Hawaii Agricultural ExperimentStation Report. Progress Report Nos. 1, 2, and 3, University ofHawaii, March, 196~.
40. Mollett, J. ~ Cost of Producing Lettuce in Hawaii. AgriculturalEconomics Report No. 54, University of Hawaii, July, 1961.
41. Cost of Producing Tomatoes in Hawaii. AgriculturalEconomics Report No. 61, University of Hawaii, January, 1963.
42. Nakagawa, Yukio. Gro~~ng Tomatoes in Hawaii. Extension Circular374, University of Hawaii, April, 1957.
43. • Growing Lettuce in Hawaii. Extension Circular 376,University of Hawaii, April, 1957.
44. Nelson, L. A. Detailed Land Classification - Island of Oahu. L.S.&Eulletin No.3, University of Hawaii, January, 1963.
45. Nerlove, Marc. Distributed Lags and Estimation of Long-Run Supplyand Demand Elasticities: Theoretical Considerations. Journal ofFarm Economics, Vol. XL, No.2. May 1958.
46. Nerlove, Marc and William Addison. Statistical Estimation of LongRun Elasticities of Supply and Demand. Journal of Farm Economics,Vol. XL, No.4. November, 1958.
47. Pan Evaporation Data - State of Hawaii. Department of Land andNatural Resources, State of Hawaii, September, 1961.
48. Panaewa Farm Development. Panaewa Farm Development Committee.Hilo, Hawaii. March, 1964.
49. Peters, C. W., J. A. Mollett, and WOodrow Y. Nakashima. Mainland~rkets for Hawaiian Winter Vegetables. Agricultural EconomicsReport No. 51, University of Hawaii. June, 1961.
50. Peters, C. W., Robert H. Reed, and C. Richard Creek. Margins,Shrinkage, and Pricing of Certain Fresh Vegetables in Honolulu.Agricultural Economics Bulletin No.7) University of Hawaii. June,1954.
51. Preliminary Plan for Establishment of Windbreaks at Molokai FarmLots. Department of Land and Natural Resources, State of Hawaii.Unpublished Report~ Jul~ 1964.
52. Ratcliff, Richard U. A Restatement of Appraisal Theory. University of Wisconsin, 1963.
53. Renne, Roland R. Land Economics. Harper and Brothels, 1947.
54. P~jko, Anthony S. Time Series Anal sis in Measurement of Demand.Agricultural Economics Research, Vol. XIII, No.2. April, 19 1.
55. Schrader, Lee F. &ld Gordon A. King. Regional Location of BeefCattle Feeding. Journal of Farm Economics, Vol. XLIV, No.1.February, 1962.
56. Scott, F. S., Jr. An Analysis of Market DevelOpment for FrozenPassion Fruit Juice. Agricultural Economics Bulletin No. 11,University of Hawaii, June, 1958.
57. Sales Potentials and Methods and Costs of MarketDevelOpment for Macadamia Nuts. Paper presented at conference onMacadamia Nuts sponsored by the Honolulu Chamber of Commerce andThe Hawaii Macadamia Producers Association.
58 0 Shoji, Kobe, Masao Nakamura and Mitsuo Matsumura. Growth and Yieldof Papaya in Relation to Fertilizer Application. AgriculturalExperiment Station, University of Hawaii, July, 1958.
59. Smi th, V. L.?qui libri Ulll.
Minimization of Economic Rent in §patlal PriceReview of Economic Science, Vol. 30, 1963.
147
60. Soil Survey - Territory of Hawaii. U. S. Department of Agricultureand Hawaii Agricultural EKperiment Station, 1955.
61. Statistics of Hawaiian Agriculture. Hawaii Crop and LivestockReporting Service Cooperating with United States Department ofAgriculture. Annual 1954-63.
62. Takeyama, T. and G. G. Judge.Programming. Journal of Farm1964.
63. Tallaferro, W. J. Rainfall of the Hawaiian Islands. Hawaii ~ater
Authority, State of Hawaii.
64. Tomek, ~lliam G. Using Zero-One Variables with Time Series Datain Regression Equations. Journal of Farm Economics, Vol. 45, No.4.November, 1963.
65. Tramel, Thomas E. and A. D. Seale, Jr. Reactive Programming of- Supply and Demand Relations--Application to Fresh Vegetables.
Journal of Farm Economics, Vol. XLI, No.5. December, 1959.
66. Whittlesey, Norman K. and Melvin D. Skold. Production Quotas andLand Values: Dmportance of the Dual in a Spatial LinearProgramming Problem. Journal of Farm Economics, Vol. 46, No.5.December, 1964.
67. Yeron, Dan and E. O. Heady. Approximate and Exact Solution to Non~
Linear Programming Problem with Separable Objective Function.Journal of Farm Economics, Vol. XLIII, No.1. February, 1961.
68. Yee, ~alter S. Mu1reg-A General Multiple Regression Program for the}BM 7040. Hawaii Institute of Geophysics, University of Hawaii,June, 1964.
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