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[Part 4] 1/25 Stochastic FrontierModels Production and Cost Stochastic Frontier Models William Greene Stern School of Business New York University 0 Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions 7 Panel Data 8 Applications

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 Presentation

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Page 1: Stochastic Frontier Models

[Part 4] 1/25

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

Page 2: Stochastic Frontier Models

[Part 4] 2/25

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.

Page 3: Stochastic Frontier Models

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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

Page 4: Stochastic Frontier Models

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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.

Page 5: Stochastic Frontier Models

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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.

Page 6: Stochastic Frontier Models

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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).

Page 7: Stochastic Frontier Models

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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.

Page 8: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Duality Between Production and Cost

T( ) = min{ : ( ) }C y, f yw w x x

Page 9: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Implied Cost Frontier Function

Page 10: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Stochastic Cost Frontier

Page 11: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Cobb-Douglas Cost Frontier

Page 12: Stochastic Frontier Models

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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

Page 13: Stochastic Frontier Models

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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

Page 14: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Cost Application to C&G Data

Page 15: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Estimates of Economic Efficiency

Page 16: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Duality – Production vs. Cost

Page 17: Stochastic Frontier Models

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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

Page 18: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Banking Application

Page 19: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Economic Efficiency

Page 20: Stochastic Frontier Models

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Stochastic FrontierModels

Production and Cost

Allocative Inefficiency and Economic Inefficiency

Page 21: Stochastic Frontier Models

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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

Page 22: Stochastic Frontier Models

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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

Page 23: Stochastic Frontier Models

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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

Page 24: Stochastic Frontier Models

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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