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1
FORMULATION OF TECHNICAL, ECONOMIC
AND ENVIRONMENTAL EFFICIENCY
MEASURES THAT ARE CONSISTENT WITH
THE MATERIALS BALANCE CONDITION
byTim COELLI
Centre for Efficiency and Productivity Analysis, University of Queensland, Brisbane, Australia
Ludwig LAUWERSCentre for Agricultural Economics, Brussels, Belgium
Guido VAN HUYLENBROECKDepartment of Agricultural Economics, Ghent University, Belgium
2
Outline
• Introduction
• Literature review and critique
• Proposed environmental efficiency measures
• Implementation using DEA
• Application to Belgian pig farms
• Conclusions
3
Introduction• Traditional efficiency measurement methods do
not include pollution• Some authors proposed methods that include a
pollution variable as an extra variable in the production model – as a “bad output” or an input
• We argue that many of these latter methods are inconsistent with the materials balance condition – which essentially states that “what goes in must come out”
• Plus these methods tend to assume that all pollution reduction must be costly
4
Introduction (continued)
• We propose a new method that is consistent with the materials balance condition
• The method looks at pollution minimisation in an analogous way to the standard cost minimising model
• The method explicitly allows for both cost increasing and cost decreasing pollution reduction
5
Traditional efficiency analysis• Does not account for environmental damage• Only traditional inputs and outputs are included
in the model• E.g., in electric power generation
– Inputs = labour, capital, fuel, other– Output = electricity– Air pollution not considered
• E.g., on a pig fattening farm– Inputs = labour, capital, feed, piglets, other– Output = pig meat– Nutrient pollution in soils and water not considered
6
Traditional efficiency measures
• Normally we estimate the production technology set ( ) by fitting a production frontier over the data (using DEA or SFA methods)
• We then measure the efficiency of each firm as either:– The amount by which it can expand output ( )
using its current inputs ( ) and remain feasible
– or, the amount by which it can reduce inputs while still producing the same output
T),(|max xyx
T)/,(|max xy
y
T
7
Efficiency measures
input
outputfrontier
●A
8
Efficiency measures including pollution
• Färe et al (1989)– Air pollution in paper mills– Included a pollution variable ( ) as a “bad output” in
the production model– Weak disposability was imposed on the pollution
variable to reflect that its disposal was costly– A hyperbolic efficiency measure was used which
sought to simultaneously expand outputs and reduce inputs and bad outputs
z
Tz )/,/,(|max xy
9
Efficiency measures including pollution (2)
• Färe et al (1996)– Air pollution in electricity generation– Included a pollution variable as a “bad output” in the
production model– Weak disposability was imposed on the pollution
variable to reflect that its disposal was costly– Productive efficiency measure sought to reduce
inputs
– Environmental efficiency measure sought to reduce pollution
Tz ),/,(|max xy
Tz )/,,(|max xy
10
Efficiency measures including pollution (3)
• Reinhard et al (2000)– Nitrogen pollution on intensive dairy farms– Included a pollution variable as an input in the
production model– Productive efficiency measures sought to reduce all
inputs
or expand outputs
– Environmental efficiency measure sought to reduce pollution
Tz )/,/,(|max xy
Tz )/,,(|max xy
Tz ),,(|max xy
11
Are these past methods consistent with the materials balance condition?
• Materials balance condition:
a and b are (K1 and M1) vectors of known non-
negative constants • Consider first the Reinhard et al (2000) environmental
efficiency measure
• Can we reduce pollution without changing inputs or outputs? - the answer is no – it will violate the materials balance condition
• The only solution to is =1
ybxa z KM RxRy ,
ybxa /z
Tz )/,,(|max xy
12
Consistency?
• In addition – if we apply the Färe et al (1989) efficiency measure
to the MB condition we obtain
or
so the only solution is =1 again• This applies to the other models as well…
ybxa //z
2ybxa z
Tz )/,/,(|max xy
13
Proposed efficiency measures
• Do not include the pollution variable into the model
• Treat it in an analogous manner to the cost efficiency model
• We first review the cost efficiency case
• Then we introduce the environmental efficiency case
14
Cost efficiency
• Cost minimisation
• Cost efficiency
• Technical efficiency
• Allocative efficiency
• Note
TC yx,xwwy,x
|min)( K Rw
CE = wxc / wx.
TTE yx,xy
|min),(
= wxt / wx = w(x) / wx =
AE = wxc / wxt
CE = TE AE
15
Cost minimisation
x1
x2 0
isoquant
iso-cost line wx
iso-cost line wxt
iso-cost line wxc
(x1t, x2t)
(x1, x2)
(x1c, x2c)
16
Environmental efficiency• For a fixed output level, minimisation of the surplus
means minimisation of the nutrient content of the inputs
• Surplus minimisation
• Environmental efficiency
• Technical efficiency is the same as before
• Environmental allocative efficiency
• Note
TTE yx,xy
|min),(
ybxa S
xaN
TN yx,xaay,x
|min)(
EE = axe / ax
EAE = axe / axt
EE = TE EAE
17
Surplus minimisation
x1
x2
isoquant
0
iso-nutrient line ax
iso-nutrient line axt
iso-nutrient line axe
(x1t, x2t)
(x1, x2)
(x1e, x2e)
18
Costs and benefits
x1
x2
isoquant
0
iso-nutrient line axc
iso-nutrient line axe
(x1t, x2t)
(x1, x2)
(x1e, x2e)
iso-cost line wxe
iso-cost line wxc
(x1c, x2c)
19
Summary figure
x1
x2
unit isoquant
iso-cost line
iso-nutrient line
0
nutrient minimising point
cost minimising point
I
II
III
20
Generalisations• More than one pollutant
– Identify optimal point for each, or– Specify weights and identify a single
“environmental” optimal point
• An “overall” optimal point – Include measures of the social costs of
pollution
• Pollution abatement activities– Involves the explicit use of extra inputs– Include a “pollution abatement” (good) output
variable
21
Data envelopment analysis implementation
min, ,
st -yi + Y 0,
xi - X 0,
0
min ,xi* (aixi*),
st -yi + Y 0,
xi* - X 0,
0
Technical efficiency
Environmental efficiency
22
Application to Belgian intensive pig-fattening farms
• Nutrient pollution (mostly phosphorous) from manure causes eutrophication and acidification of soils and water in Flanders
• Output = pig meat• Inputs = feed, piglets, labour, capital and other• Preliminary regression analysis:
– Latter 3 inputs are statistically insignificant (and minor in terms of costs)
– Constant returns to scale (CRS)
• Hence simple DEA model with two inputs and CRS
23
DEA results
Efficiency measure Mean Stdev. Min Max
Technical efficiency (TE) 0.897 0.055 0.727 1.000
Environmental allocative efficiency (EAE) 0.940 0.046 0.763 1.000
Environmental efficiency (EE) 0.843 0.065 0.670 1.000
Allocative efficiency (AE) 0.985 0.021 0.877 1.000
Cost efficiency (CE) 0.883 0.057 0.722 1.000
24
Reduction in pollution?
• Total phosphorous in inputs on Flanders pig fattening farms is 38.1 million kg P2O5 per year
• In pig meat output it is 13.6 million kg P2O5
• Thus the surplus is 24.5 million kg P2O5
• Potential reduction is 15.7% of 38.1 = 6.0 million kg P2O5
• This is approximately ¼ of current surplus
25
DEA for pig farms
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00
feed/output
pig
let/
ou
tpu
t
isoquant
iso-cost line
iso-nutrient line
26
Implied shadow cost?
• The two optimal points differ– in costs by 4.6% and – in nutrient surplus by 5.3%
• Implied cost of phosphorous reduction is 27 Euros per kg P2O5
• Current manure treatment cost is 6 Euros per kg
• So aim for cost min point (in this case)
27
Conclusions
• New environmental efficiency measure– Consistent with materials balance condition– Can be decomposed into technical and
allocative components– Emphasizes that pollution reduction need not
be always costly
• Application to Belgian pig farms– One quarter of phosphorous surplus can be
reduced before abatement activities considered