APPENDIX A RETURNS TO SCALE
The consequences of proportional input scaling on outputs are
(A.1 ) Definition: If '1xER+, A <: 1 and 0 N < Il ::; 1, 1. (a) POx) c = AP(x); (b) IlP(x) c P(llx), 2. P(Yx) YP(x) , Y > 0,
3. (a) AP(x) c POx) ; (b) P(llx) c IlP(x) ,
the output correspondence is called 1. Subhomogeneous, 2. Homogeneous (of degree +1), and 3. Super homogeneous , respectively.
The effects of proportional output scaling on inputs are
(A.2)
(A.3)
Definition: If '1uER+, e <: 1 and M 0 < 0 ::; 1, 1 . (a) L(eu) c eL(u); (b) oL(u) c L(ou), 2. L(Yu) YL( u), Y > 0,
3. (a) eL(u) c L( eu); (b) L(ou) c oL(u),
the input correspondence is called 1. Subhomogeneous, 2. Homogeneous (of degree +1) and 3. Superhomogeneous, respectively.
Proposition: The output correspondence is subhomogeneous, homogeneous or superhomogeneous if and only if the input correspondence is
subhomogeneous, homogeneous or superhomogeneous, respectively.
Proof: Suppose P is subhomogeneous. The input correspondence L(eu) = {x: eu£P(x)}, e;:; 1, (2.1.4). Thus, L(eu) = {x: uE1/ep(x)}
S
{x: u£P(x/e)} = eL(u). IfL is subhomogeneous and e ;:; 1, p(ex) = {u: 6XEL(u)} = {u: xE1/eL(u)} C {u: x£L(u/e)}
ep(x). Similar arguments apply to complete the proof.
Q.E.D.
The homogeneity notions defined above have obvious geometric interpretations. To elucidate these, introduce the following notions.
(A.4)
(A.S)
(A.6)
150
Definition: A set K C = RG is a Cone if vw£K, Yw£K, Y + > O. A set S C RG is + Starred if vw£S, ~U£S, 0 < ~ S 1. 'A set A C R~ is Areoled if vw£A, lwG£A,
l :i: 1.
Proposition: The output correspondence is subhomogeneous, hcmogeneous (of degree +1) or superhomogeneous if and only if the graph (GR) is starred, a cone or areoled, respectively.
Remark: If VX£RN and l + :i: I, P(lx) C = lP(x) (1.(a», then and only then vx£RN and 0 + < ~ S 1, ~P(x) C = P(~x) (1.(b».
Proof: Suppose X£RN, l + :i: 1 and P(lx) C lP(x). Define y = = (lx), and ~ = (Ill), then y£RN, 0 + < ~ S 1 and ~P(y) C = P(~y). The converse is proved analogously.
Q.E.D.
Proof of Proposition (A.S): Suppose the graph is starred. If (x,u)£GR then
(~x,~u)£GR, 0 < ~ S 1. Thus u£P(x), (2.1.6) and ~u£P(~x). Therefore, P(x) C
I/~P(~x) and ~P(x) C P(~x). To prove the converse, suppose P is subhomogeneous.
Let UEP(X) and 0 < ~ S 1. Then (x,u)EGR, (2.1.5), and ~UE~P(X)
S
P(~x). Thus,(~x,~u)EGR. In view of Remark (A.6), the first part is proved. The remaining parts of the proof are left for the reader.
(A.7)
(A.8)
Q.E.D.
Definition: The production technology exhibits Non Increasing Returns to Scale (NIRS), Constant Returns to Scale (CRS) or Non Decreasing Returns to Scale (NDRS) if and only if the output correspondence is subhomogeneous, homogeneous (of degree +1) or superhomogeneous, respectively.
Definition: The production technology exhibits Increasing Returns to scale (IRS) if it exhibits NDRS and not CRS. It exhibits Decreasing Returns to Scale (DRS) if it exhibits NIRS and not CRS.
The above returns to scale definitions are global. However, sometimes local notions are needed, in particular in finding the source of scale inefficiency (Sections 9.3, 9.4 and 9.5) such local notions are required.
Suppose the graph is known, then define the cone
151
(A.9) K(GR) {(x,u): (x,u) (ly,lv), (y,v)EGR, 1 > OJ
(A.10) Definition: (x,u)EGR exhibits IRS, if So(x,u) > 1, (Si(u,x) < 1) and
* *
(x,uWo(x,u»EK(GR), «xWi(u,x),u)EK(GR». It exhibits DRS, if So(x,u) > 1,
* *
(Si(u,x) < 1) and (x,uWo(x,u»iK(GR), «xWi(u,x),u)iK(GR».
Traditionally, returns to scale is defined in terms of scale elasticity. Suppose a production function F is known, and suppose it is differentiable. The Elasticity of Scale is defined as
(A.11) E(x,u)
To generalize (A.11) note that Do(x,u) ~ u/F(x). Then
DO(X'U) N -aDo(x,u) x
(A.12) E(X,U) 1: n
u n~1 Ox n (Do(X'U» 2
N aDo(x,u) x
1: n
ax Do(X'U)
n~1 n
In light of (A.12), the Primal Output-Based measure of scale elasticity is given by
(A.13) -XVXDO(X'U)
Do(x,u)
The Primal Input-Based measure of scale elasticity is
(A. 14)
(A.15 )
-uV D. (u,x)
( u 1 )-1
D. (u,x)
1
Proposition: If inputs and outputs are proportionally scaled (dxn/xn ) (prop x), vn and (dum/um) ~ (prop u), vm, then EO(U,X) ~ Ei(u,x).
Proof: The output distance function is homogeneous of degree +1 in output, thus x(prop x)VxDo(x,u) + (prop u)Do(x,u) ~ O. The input distance function is homogeneous in inputs, thus u(prop u)VuDi(u,x) + (prop x)Di(u,x) ~ O. The two expressions yield
(prop x) (prop u)
DO(X,U) xV'xDo(x,u)
152
uV' uDi (u,x) Di(u,x)
To characterize the input-based measure of scale elasticity, recall the input conjugate duality
(A.16) px C(U,p)Di(u,x).
where x is chosen optimality.
Differentiation of (A.16) with respect to u yields
Multiply by u to obtain
(A.17) uV'UC(u,p) C(u,p)
UV'UDi (u,x) Di(u,x)
The left hand side is thus a dual, cost representation of Ei(u,x).
From the output conjugate duality (6.6.9) we obtain,
(A.18) xV' xR(x,r) R(x,r)
xV'xDo(x,u) Do(X'U)
as the dual, revenue representation of EO(U,X).
Q.E.D.
(A.19) Definition: (x,u) exhibits IRS if EO(U,X) > 1, CRS if EO(U,X) if EO(U,X) < 1.
1 and DRS
APPENDIX B
STANDARD NOTATIONS AND MATHEMATICAL APPENDIX
Let A and B be two sets, we mean by
£ a£A a is an element in A;
i aU a is not an element in A;
C A C B A is a subset of B;
C A C B A is a proper subset of B;
eJ A III A is an empty set;
{a£A: *} the subset of A formed by the elements satisfying property *;
n A n B {x: x£A and x£B};
u AU B {x: x£A or x£B};
\ A\B {x: x£A, xiB};
Compl. Complement;
+ A + B A + B (z: a£A, b£B, Z a + b);
RN Euclidean space of dimension N;
~ x,y£RN, x ~ Y if and only if xn ~ Yn' n 1,2, ... ,N;
> x ~ Y if and only if x ~ y and x ~ y;
> x > y if and only if xn > Yn' n 1,2, ••• ,N;
*
*
> x > y if and only if xn > Yn or xn Yn 0, n 1,2, ••• ,N;
154 RN + RN + {x: xe:RN, x ii: O};
RN ++ RN
++ {x: xe:RN, x > 0);
RN RN {x: xe:RN, x ~ 0);
R+ R+ R+ U {+"');
2 RN
2 RN
{A: A C RN);
[, ] [a,b] {x: a ~ x :;: b};
[a,b) [a,b) {x: a ~ x < b);
A is convex if for all 0 ~ A ~ 1, x,ye:A, AX + (l-A)ye:A;
3 there exists;
for all;
sum sign;
x product sign;
the sequence x converges to xo; ~
tends to +"';
closure of it;
=> xe:A => xe:B, x belongs to A only if x belongs to B;
<=> if and only if;
gradient of F(x);
s.t. subject to;
positive integers;
px
B.1
B.2 B.3 B.4
B.5
B.6 B.7 B.8
B.9
B.10
B.11
B.12 B.13
px
155
N L P x , p and xeRN, the inner product.
n=1 n n
A set A c RN is bounded <=> sup{lIx-yll! x,yeA}
A set F c RN is closed <=> 'ts 9- -+ so, s9- eF ,'t9-,
< +"'.
sOeF.
A set Q c RN is compact <=> it is closed and bounded.
A set Q in a topological space is compact <=> every cover of Q has a finite subcover.
A function f: RN + ~ R is upper semi-continuous <=> 'tx9-+ ~ xO, lim sup f(xi ) ~ f(xO) <=) (x: f(x) ~ ~} is closed, 't~eR+ <=>
i~+'"
GR = ((x,~): f(x) ~ ~, 't~eR+} is closed.
f is lower semi-continuous <=> -f is upper semi-continuous.
f is upper semi-continuous, Q compact, max f(x) is achieved.
xeQ
f: R~ ~ R+ is quasi-concave <=> 'tA, 0 ~ A ~ 1, X,yeR~, f(Ax + (1-Aly) ~ min{f(x), fey)}
f is quasi-convex <=> -f is quasi-concave.
f is quasi-concave <=> (x: f(x) ~ ~} is convex 't~eR+.
f is continuous <=> f is upper and lower semi-continuous.
f: R ~ R is strictly increasing if x > u => f(x) > fey).
A continuous strictly increasing function f has an inverse
C 1 .
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Attainability, ~, 21, 44
Congestion, 14, 18, 135 OP-Congestion, 14 OL-Congestion, 14
Cost Function, 83 derivatives, 91-93 duality, 84
properties of, 83, 81
rate of return regulated, 101 ray-homothetic, 88
revenue indirect, 113 short run, 99
Cost Minimization Set, 89
Disposability
strong input,
2,
13, 15-11, 52, 11 strong output, ~, 11, 135weak input,
2,
21, 38, 48 weak output, ~, 34, 48Distance Function
input, 35, 36, 40, 91, 128 duality, 85
properties of, 31-38 ray-homothetic, 56 revenue indireot, 114 output, 29, 36, 31, 40, 41, 128
cos~indirect, 110 duality. 94
properties of, 30-34 ray-homothetic, 52
INDEX
Duality
ccst indirect, 110, 111 ccst-prcducticn, 84, 92 revenue indirect, 114, 115 revenue-prcduction, 94, 197
Efficiency Measures, 127-148 Farrell decompcsiticn, 129-133 input, 128, 129-131
output, 128, 131-133
Efficient Subsets
input,
11,
11-14, 64 dynamic, 122 output,11,
11-14 dynamic, 123Essential, 65, 70 ccngestion, 75 cost, 86
not essential, 66
Graph, ~, 119
Indirect Production ccst indirect, 106
properties of, 106-111 efficiency, 143-144
revenue indirect, ~ prcperties cf, 112-115
Input Correspondence, ~, 36, 38, 39 piecewise linear, 44-49 prcperties of, 8-10 ray-homothetic, 54-56
Input Efficiency Theorem, 89
Input Set, ~, 36, 38, 39 properties of, 14-17
161
Isoquant
input,
.!..l,
36, 39,' 139 output,.!..l,
34, 39, 135Joint Produotion Funotion, 38 properties of, 39-40
Law of Variable Proportions, 79
Limitational strong, 68, 70 weak, 64, 67
Linear Expansion Paths input, 87, 90 output, 96
Maintained Axioms, lQ, 24 independenoe of, 18-20
Null Joint, 77 oongestion, 78
Output Correspondenoe, ~, 23, 25, 31, 39 piecewise linear, 44-49
properties of, 6-8 ray-homothetic, 49-51, 56
Output Set, ~, 17, 31, 39
Plant Capacity,
II
efficiency, 145-146 properties of, 71-73
Product Technology, 118 properties of, 118-122
162
Produotion Funotion, 23 dynami c, 1 22 examples of, 26-29 indirect, 108 properti es of, 23-29 ray-homothetic, 59-60, 69
Profit Function, 100
Pr ices, 82-86 shadow, 97-98
Quantity Index, 41
Returns to Scale, 147-152
efficiency, 134, 137, 140-143
Revenue Function, 93 cost indirect, 109 duali ty of, 94 properties of, 93-95 ray-homothetic, 95
Shephard's Lemma, 92, 102
Time
substitution, 124-126 support, 121
163