stochastic frontier models
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William Greene Stern School of Business New York University. Stochastic Frontier Models. 0Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions 7 Panel Data 8 Applications. - PowerPoint PPT PresentationTRANSCRIPT
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Stochastic FrontierModels
Production and Cost
Stochastic Frontier Models
William GreeneStern School of BusinessNew York University
0 Introduction1 Efficiency Measurement2 Frontier Functions3 Stochastic Frontiers4 Production and Cost5 Heterogeneity6 Model Extensions7 Panel Data8 Applications
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Stochastic FrontierModels
Production and Cost
Single Output Stochastic Frontier ( )
ln + = + .
iviii
i i ii
i i
= fy eTE = + v uy
+
xxx
ui > 0, but vi may take any value. A symmetric distribution, such as the normal distribution, is usually assumed for vi. Thus, the stochastic frontier is
+’xi+vi
and, as before, ui represents the inefficiency.
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Stochastic FrontierModels
Production and Cost
The Normal-Half Normal Model
2
2
ln
1Normal component: ~ [0, ]; ( ) , .
Half normal component: | |, ~ [0, ]
1 Underlying normal: ( ) ,
Half
i i i i
i i
ii v i i
v v
i i i u
ii i
u u
y v u
vv N f v v
u U U N
Uf U v
xx
1 1normal ( ) ,0(0)
ii i
u u
uf u v
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Stochastic FrontierModels
Production and Cost
Estimating ui
No direct estimate of ui
Data permit estimation of yi – β’xi. Can this be used? εi = yi – β’xi = vi – ui Indirect estimate of ui, using
E[ui|vi – ui] = E[ui|yi,xi]
vi – ui is estimable with ei = yi – b’xi.
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Stochastic FrontierModels
Production and Cost
Fundamental Tool - JLMS
2
( )[ | ] , 1 ( )
i ii it i i
i
E u
We can insert our maximum likelihood estimates of all parameters.Note: This estimates E[u|vi – ui], not ui.
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Stochastic FrontierModels
Production and Cost
Multiple Output Frontier The formal theory of production departs from the
transformation function that links the vector of outputs, y to the vector of inputs, x;
T(y,x) = 0.
As it stands, some further assumptions are obviously needed to produce the framework for an empirical model. By assuming homothetic separability, the function may be written in the form
A(y) = f(x).
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Stochastic FrontierModels
Production and Cost
Multiple Output Production Function
1/ q T1 xM q q
m i,t,m it it itmy v u
Inefficiency in this setting reflects the failure of the firm to achieve the maximum aggregate output attainable. Note that the model does not address the economic question of whether the chosen output mix is optimal with respect to the output prices and input costs. That would require a profit function approach. Berger (1993) and Adams et al. (1999) apply the method to a panel of U.S. banks – 798 banks, ten years.
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Stochastic FrontierModels
Production and Cost
Duality Between Production and Cost
T( ) = min{ : ( ) }C y, f yw w x x
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Stochastic FrontierModels
Production and Cost
Implied Cost Frontier Function
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Stochastic FrontierModels
Production and Cost
Stochastic Cost Frontier
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Stochastic FrontierModels
Production and Cost
Cobb-Douglas Cost Frontier
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Stochastic FrontierModels
Production and Cost
Translog Cost Frontier
2 21 1 1kl yy2 2 2
Cost frontier with K variable inputs, one fixed input (F) andoutput, y.ln ln ln ln ln ln ln ln ln ln ln ln
F Kk=1 k k F y
K Kk=1 l=1 k l FF
K Kk=1 kF k k=1 ky k
C w F y
w w F y
w F w y
Kk=1
k
ln lnCost functions fit subject to theoretical homogeneity in prices
lnCrestriction: 1. Imposed by dividing C and all butlnwone of the input prices by the "last" (numeraire) price.
Fy i iF y v u
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Stochastic FrontierModels
Production and Cost
Restricted Translog Cost Function
212
2 21 12 2
ln ln ln ln ln
ln ln ln ln
ln ln ln l
K L y yy
KK LL KL
yK yL
C PK PL y yPF PF PF
PK PL PK PLPF PF PF PF
PKy yPF
n PL v uPF
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Stochastic FrontierModels
Production and Cost
Cost Application to C&G Data
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Stochastic FrontierModels
Production and Cost
Estimates of Economic Efficiency
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Stochastic FrontierModels
Production and Cost
Duality – Production vs. Cost
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Stochastic FrontierModels
Production and Cost
Multiple Output Cost Frontier
1 1 1
1
1
1
1 1
1
1
1ln ln ln ln2
ln
ln ln
1 ln ln2
M M Mmy m lm l mm l m
K
K kkk
K
M K kmk mm k
K
K k lklk l
K K
C y y yw
ww
wyw
w ww w
1
1 + K v u
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Stochastic FrontierModels
Production and Cost
Banking Application
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Stochastic FrontierModels
Production and Cost
Economic Efficiency
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Stochastic FrontierModels
Production and Cost
Allocative Inefficiency and Economic Inefficiency
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Stochastic FrontierModels
Production and Cost
Cost Structure – Demand System
Cost FunctionCost = f(output, input prices) = C(y, )Shephard's Lemma Produces Input Demands
C*(y, ) = Cost minimizing demands =
w
x w w
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Stochastic FrontierModels
Production and Cost
Cost Frontier Model
k kk
k
Stochastic cost frontierlnC(y, ) = g(lny,ln ) + v + u u = cost inefficiencyFactor demands in the form of cost shares
lnC(y, )s h(lny,ln ) + elnwe allocative inefficiency
w w
w w
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Stochastic FrontierModels
Production and Cost
The Greene Problem Factor shares are derived from the cost function by
differentiation. Where does ek come from? Any nonzero value of ek, which can be positive or negative,
must translate into higher costs. Thus, u must be a function of e1,…,eK such that ∂u/∂ek > 0
Noone had derived a complete, internally consistent equation system the Greene problem.
Solution: Kumbhakar in several papers. (E.g., JE 1997) Very complicated – near to impractical Apparently of relatively limited interest to practitioners Requires data on input shares typically not available
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Stochastic FrontierModels
Production and Cost
A Less Direct Solution(Sauer,Frohberg JPA, 27,1, 2/07)
Symmetric generalized McFadden cost function – quadratic in levels
System of demands, xw/y = * + v, E[v]=0. Average input demand functions are estimated to avoid
the ‘Greene problem.’ Corrected wrt a group of firms in the sample. Not directly a demand system Errors are decoupled from cost by the ‘averaging.’
Application to rural water suppliers in Germany