EFFLUENT CHARGE REFORM FOR CONTROLING WATER
POLLUTION IN THE MALAYSIAN CRUDE PALM OIL INDUSTRY
Corresponding Author: AMIR HOSSEIN MONTAZER HOJAT
Faculty of Economics and Management, Department of Economics, Universiti Putra Malaysia,
43400 Serdang, Selangor, Malaysia
Faculty of Economics and Social Sciences, Department of Economics, Shahid Chamran
University (SCU), Ahwaz, Iran
Tel: +60176680936
Email: a.mhojat@gmail.com
KHALID ABDUL RAHIM
Institute of Agricultural and Food Policy Studies, University Putra Malaysia, 43400 Serdang,
Selangor, Malaysia
Email: Khalid@econ.upm.edu.my
LEE CHIN
Faculty of Economics and Management, Department of Economics, Universiti Putra Malaysia,
43400 Serdang, Selangor, Malaysia
Email: leechin@econ.upm.edu.my
1
EFFLUENT CHARGE REFORM FOR CONTROLING WATER
POLLUTION IN THE MALAYSIAN CRUDE PALM OIL INDUSTRY
Abstract
This study analyzes Malaysian palm oil mills’ environmental performance of their water
pollution treatment. The mills are considered according to their cost of abatement in
meeting the mandatory standard. The model is estimated to obtain efficient effluent-related
fees and effluent charge at the mandatory standard level using panel data for the states of
Selangor and Johor in Malaysia over 2006-2008. This study found that the marginal
abatement costs are so much higher than the effluent charge imposed at the mandatory
standard level. Hence, to force palm oil mills to meet the standard the effluent charge must
be set higher equaling the marginal abatement cost. Also, the results reveal that the effluentrelated fees are not sufficiently high to encourage firms to reach the ideal goal of perfectly
treating their pollution. While the results show existence of economies of scale in water
pollution activity, setting effluent-related fee to equal the marginal abatement cost may
encourage mills to further abate their water pollution to reach the ultimate goal.
Keywords: Water pollution, Abatement cost, Palm oil mills, Malaysia
JEL: Q53, C23
Conference category: Economic and finance
1. INTRODUCTION
Industrialization is one of the major goals in many developing countries. Negative externality problem
arises if, due to ignorance and undervaluation of the environment, there is no appropriate regulation
and/or instrument to control it. Government regulations have always played a critical role in protecting
environmental media from further deterioration. To protect the environment and to reach a concordant
economic, social and environmental development, the Malaysian government has enacted Environmental
Quality Act (EQA), and has implemented a set of principles and policies since 1974. Employing various
instruments such as market instruments and command-and-control approach, the Department of
Environment (DOE) forces industries to comply with the EQA. Consequently, assessment of the effects
of the aforementioned instruments is of great interest.
The role of rivers in Malaysia’s economy is vital since these are resources for food and daily water
supply, and also are used as transportation lines. According to DOE reports in 2008, one of the major
pollutants of Malaysian rivers is the Biochemical Oxygen Demand (BOD). Table 1 shows the number of
river basins status based on the BOD parameter. During 2007-2008, number of clean rivers has decreased
from 94 to 79. Consequently, there is a significant increase in the number of slightly polluted rivers in
2008 compared with 2007. The number of slightly polluted rivers increases from 37 to 46. Also, 12
polluted river basins in 2007 has increased to 18 in 2008. It could be caused by untreated or partially
treated wastewater discharged by agro-based and manufacturing industries (DOE, 2008).
Table 1. River basins water quality based on the BOD
Year
2007
2008
DOE, 2008
Clean
94
79
Slightly polluted
37
46
2
Polluted
12
18
The number of polluted river basins was 7 based on Water Quality Index (WQI) in 2006. The number has
not decreased during 2007 and 2008. In 2006, there were 7 polluted river basins, five of which or 72%
were located in the states of Selangor and Johor. This percentage had increased to 85% in 2008. The
Environmental Quality Report of the DOE shows that there are 54 polluted rivers in Malaysia 6 of which
are in Selangor and 20 are in Johor. Totally, 26 (49%) polluted rivers are in the states (Table 2).
Approximately all of these rivers are in class three, meaning that extensive treatment is required before
the effluents could be discharged into the rivers.
Table 2. Polluted rivers and river basins status based on the WQI
Rivers
State
Number
6
20
26
54
Selangor
Johor
Both
Malaysia
DOE, 2006
River Basins
Percent
11
38
49
100
Number
1
4
5
7
Percent
15
57
62
100
In 2007, DOE conducted a census country-wide about industrial water pollution sources from agro-based
and manufacturing industries collected by field surveys and questionnaires. A total of 9,204 sources were
identified for the whole of Malaysia. Selangor with 1,956 sources (21.26%) had the largest number of
sources of water pollution. The second largest number was for Johor with 1,789 sources (19.44%).
Totally about 41% of all water pollution is generated in these states. Also the states were reported by
DOE as the major polluted areas in Malaysia (Figure 1).
Figure 1 Number of Polluting Sources in Malaysia
2000
1800
1600
1956
1789
1693
1468
1400
1200
961
1000
800
600
400
200
454
335
159 118
0
3
96
83
36
28
11
1
Based on the DOE reports, palm oil mills are one of the water polluting sources in Malaysia. They are
usually located near rivers from which water is used for their operations and discharge treated or partially
treated wastewater back into the rivers. While there is a special section in EQA to regulate palm oil mills,
a palm oil mill has the highest water pollution problem in comparison with rubber, textile and paper
factories. Table 3 and 4 show the typical concentration and pollution load for the major industries.
Typically, a palm oil mill causes much greater water pollution than that caused by other factories. To
obtain a meaningful comparison, only firms of the same size (above 50 workers) were considered in our
analysis.
Table 3. Concentration of major pollutants for typical medium sized firms
Firm
Palm oil
Rubber
Textile
Food
DOE, 1999
BOD (mg/l)
25,000
4,850
200
242
COD (mg/l)
50,000
3,525
500
484
Table 4. Loads of major pollutants for typical firms (tonnes)
Firm
Palm oil
Rubber
Textile
Food
DOE, 1999
BOD(yearly)
1,379,700
460,750
365
1.65
BOD(daily)
3,780
1,262
1
0.004
COD(yearly)
2,759,400
334,875
912.5
2.11
COD (daily)
7,560
918
2.5
0.005
The seriousness of the effluent discharge from the palm oil mills is measured in terms of the populationequivalent. The population-equivalent load of the raw effluent discharged by a single average-sized palm
oil mill is as much as untreated sewage of a city with 300,000 people.
When palm oil mill effluent (POME) is discharged into a waterbody, which is under natural
decomposition, the dissolved oxygen of the water-body is rapidly depleted as a result of the natural
biochemical processes. Exhaustion of dissolved oxygen leads to anaerobic conditions in which stinking
gases are created. Other negative impacts include the ruin of aquatic life and worsening in the riverine
eco-systems.
Hence, the results of this study may be used to recommend measures for more efficient management of
water pollution. This, in turn, may lead to a decrease in the health hazards of people who live around the
polluted rivers and and improvement in their quality of life. The results may be used to encourage
improvements in aquatic life in the riverine eco-systems. Also, determining optimal charges as an
economic instrument which is in principle cost-effective, can ensure that the palm oils comply with the
standards instead of paying the charges and claim the right to pollute. The optimal effluent-related fees
will also create a strong incentive for technical change to decrease the abatement costs and treating
pollution even beyond the standard.
Next section begins with the theoretical framework of the study followed by the methodology. Finally,
the results are discussed and policy implications and recommendations for future studies are presented.
4
2. THEORETICAL FRAMEWORK
Government policies using economic instruments such as an effluent charge affects firms’ environmental
performance. By setting an effluent charge, every polluting firm will abate pollution at different levels:
low-cost abaters will abate more than those high-cost abaters. A uniform standard is inefficient resulting
in high abatement cost for some firms and low abatement costs for others. However, if charges are set at
the highest level for the high cost abaters to meet a mandatory standard, the low cost abaters will abate
further beyond the standard, thus encouraging abatement activity of removing pollution sufficiently.
To determine this effluent-related fee and effluent charge, the marginal cost function for water pollution
abatement should first be estimated. Subsequently, by substituting the value of standard level into this
function it becomes possible to determine abatement cost corresponding to the standard level. Firms have
to abate if the effluent charge is higher than the marginal cost corresponding to the standard level.
According to the existing literature, output of abatement activity could be seen most appropriately as a
service (Goldar et al., 2001). Essentially, a firm reduces pollutants in wastewater. Hence, output of
abatement activity is measured by the amount of pollutant reduction achieved for a certain volume of
wastewater treated. Since the standards have been coded in terms of pollutant concentration in Malaysia,
in this study, pollutant concentration will be used in model to estimate water pollution abatement cost.
Concentration could be considered as a measure of total pollution, which differs from the volume of water
treated (McConnell and Schwarz, 1992). Also, the author has been motivated to include wastewater
volume in the abatement cost function because the effluent fee and charge are load-based in Malaysia.
Including both pollutant concentration and wastewater volume permits computation of marginal
abatement cost based on the pollution load treated at the specific concentration such as standard level
(Goldar et al., 2001). The output of water pollution abatement could be expressed as follows:
Y  W (qi  q e ),
Y / q e  0
(1)
The output of pollution abatement could be interpreted as follows. If q denotes BOD, then (qi – qe)
represents the abatement in BOD mg per liter of wastewater treated so that output Y represents the
reduction in the pollution load. The smaller the qe the bigger is Y. To achieve higher amount of output
higher amount of inputs are required. Hence, the pollutant concentration after treatment, qe, could be
written as follows:
qe = f ( W, qi, X)
(2)
Where W is volume of wastewater, qi is pollutant concentration in wastewater before treatment, and X is
the vector of inputs.
Assuming minimized costs for abatement activities and existence of a competitive market for inputs, the
cost function of abatement could be derived as follows:
C  g ( P, Y )
(3)
Where, C denotes abatement cost and P is the vector of input prices. Substituting equation (1) into
equation (3), the cost function would be obtained as follows:
C  g[ P, W , (qi  qe )]
5
(4)
But qi = (qi - qe) + qe. Thus, equation (4) could be written as follows
C  g[ P,W , (qi  qe ), qe ]
(5)
Simultaneous presence of (qi – qe) and qe in the model could be tested after empirical model have been
specified.
The abatement cost function could be represented in Cobb–Douglas functional form as follows
j
C  BW  (qi  qe )  (qe )  Pj
(6)
Some previous studies have considered cost function based on the proportion of pollutant treated leading
to the equation below
j
C  BW  [( qi  qe ) / qi ] Pj
(7)
This functional form has two disadvantages. First, the cost of abatement is not only a function of the
proportion of pollutant treated, but also the pollutant concentration in the effluent. The latter, however, is
neglected in equation (7). Second, after estimation of the model the value of 𝛿 will be less than unity thus
the second-order partial derivative of C with respect to qe is to be negative. Hence, the marginal
abatement cost curve cannot have the expected shape, i.e. it has maximum instead of minimum.
3. THE EMPIRICAL MODEL
The Cobb-Douglas functional form is popular and useful, hence many studies have applied it to estimate
cost function of abatement (Goldar, 2001). In comparison with the Translog function, the Cobb-Douglas
is very much easier to estimate and has lesser coefficients. Hence, the results of Cobb-Douglass model
will be more significant especially for samples of relatively small size. Some previous studies such as
Goldar, Bishwanath., Pandey, Rita (2001), Dasgupta et al. (2001) and Khalid (1993) employed CobbDouglas functional form in their studies. In this study, the Cobb-Douglas cost function for abatement is
written as
3
ln C  A   ln W   ln( qi  qe )   ln qe   j ln p j
(8)
j 1
Where, W is the volume of wastewater discharged by a mill, qi and qe are concentration levels of pollutant
before and after treatment respectively, and pj is the price of jth input (labor, capital and electricity).
4. METHODOLOGY
Panel data, with its two-dimensionality, has the advantage that not only makes us able to cross from one
firm to another but to observe the time trends and dynamics of changes in short periods of time (Gujarati,
2009). Employing panel data improves, both quantitatively and qualitatively, observations in as much as
it would not be possible utilizing one dimension only (Gujarati, 2009).
The choice of sample is based on careful consideration of several factors: mandatory standard level set by
DOE, systems of treatment and types of pollutants which vary from one industry to another. For this
6
reason, and also noting the level of pollution, palm oil mills are selected as the industry of interest in this
study. Primary data are collected from 88 palm oil mills in the states of Selangor and Johor using
structured questionnaires. These two states were selected due to their high level of their pollution
compared to other states. The panel data set was used to estimate the abatement cost function for the years
2006 to 2008.
Self-distribution method (visiting mills) for filling up the questionnaires resulted in an increase of
response rates by 51%. In using this method we prevented “pattern answering” which might be straight
down the page or diagonally across the questions (Brace, 2004).
The study utilizes a three-input in the model. Labor is taken as one input, capital and electricity as the
others. Cost of abatement is achieved as the sum total of costs corresponding to these three inputs. For
estimating abatement cost function, price of inputs are required. The price of labor is gotten from wage
bill of the firms (RM/worker). The price of electricity is taken based on the price of one kilo-watt hour
which were recorded in the firms’ documents. Cost of capital is measured by sum of repair and
replacement costs. Whole price index of machinery (WPI) and real interest rate are to be used as a proxy
for capital price, separately. The data are collected from firms on concentration levels of BOD and
wastewater volume in terms of cubic meter and mg/L, respectively.
4.1 PROCEDURE OF ESTIMATION
Choosing the proper type of panel data is the first step in employing panel data set in empirical studies.
Breusch and Pagan (1980) have presented a test, known as LM, to select between random effects and
pooled OLS models. The results of the test are presented in Table 5. We used two proxies for capital price
which are machinery price index and real interest rate. We introduced models which included machinery
price index and real interest rate as Model 1 and 2, respectively. As shown by the p-value, Chi-square for
both models are significant at 1% level and thus, the null hypothesis could be rejected, meaning that
Pooled OLS model is rejected for Panel data model. Then, a proper type of panel model is selected.
Table 5. Breusch and Pagan LM test results
Chi2(1)
P-value
Obtained using Stata 10.0
Model(1)
Model(2)
18.97
0.000
83.63
0.000
To select between two types of panel data, the model was checked using Hausman (1978) test results of
which are presented in Table 6. The random effects model is rejected in favor of fixed effects model. In
most empirical studies, the reason for employing fixed effect model is to permit the unobserved firm
effects to be correlated with the explanatory variables. Hence, it is a useful tool to estimate unobserved
firm effects (Wooldridge, 2009). Also, “in some applications of panel data methods, we cannot treat our
sample as a random sample from a large population, especially when the unit of observation is a large
geographical unit such as a state. Thus, it often makes sense to think of each unobserved effect as a
separate intercept to estimate for each cross-sectional unit. In this case, we use fixed effect method.”
(Wooldridge, J., 2009, p. 493). In our cost model, input prices could be related to unobserved firm effect
not because they interact but because the model consists of a series of the effects that influence input
choice and cost in production decisions (Baltagi, 2008). Therefore, fixed effect model seems to be more
appropriate for estimating abatement cost.
7
Inter-firm and inter-temporal standard deviations are devoted for choosing between one- or two-way fixed
effects models. Expectedly, the standard deviations across units are larger than that within each unit for
most of the variables. Hence, one-way fix effect model (between cross sectional units) was chosen as the
most appropriate one.
Table 6. Hausman test results
Chi2(1)
p-value
Obtained from Eviews 7.0
Model(1)
26.11
0.000
Model(2)
33.19
0.000
5. RESULTS
Based on the Hausman test our proper panel model for abatement cost is one-way fixed effect. The
estimated parameters for model (1) and model (2) are presented in Table 7. All input prices are in real
value using producer price index (PPI) as the deflater. The results of model (1) are discussed first.
Table 7. Results for water pollution abatement cost for Malaysian Palm Oil Mills
Variables
INT
W
qi-qe
qe
PL
PE
PC
Coefficients
Model (1)
0.840
(2.109)
0.148
(16.595)
0.574
(11.513)
-0.029
(-7.097)
0.112
(4.585)
0.881
(33.172)
0.288
(30.222)
DUM2008
-
R-square
F-statistics(prob)
0.993
239.81(0.000)
Model (2)
3.155
(6.992)
0.217
(16.336)
0.340
(7.525)
-0.023
(-26.774)
0.194
(25.967)
0.547
(119.962)
0.461
(1.690)
0.068
(4.698)
0.971
56.895(0.000)
As the R2 suggests, the model satisfactorily fits through the data. All parameters were found to be
statistically significant. The sign of partial derivatives of cost function with respect to every explanatory
variable was checked in order to interpret the results and verifying that all coefficients are of the signs
anticipated. The coefficient of W which indicates the elasticity of cost with respect wastewater volume
was estimated to be less than unity, meaning the existence of economies of scale in abatement activity.
The coefficient of (qi - qe) which indicates the level of abatement of BOD is positive, implying that the
more the abatement the higher is its cost. The estimated coefficient of qe, the BOD concentration in
effluent, was found to be negative. This suggests that the lesser the BOD concentration in the effluent the
8
greater will be the abatement cost. The coefficient of factor prices were found to be positive, that is a rise
in factor prices increases the abatement cost.
In model (2), the estimated coefficients are statistically significant. The estimated coefficients for W and
(qi- qe) are found to be positive but that of qe was found to be negative. The estimated coefficients are of
signs in accordance with theory and comply with the results of model (1). As could be seen, the two
models yield almost the same estimates of the same parameters. Likewise, the difference in the value of
R2 between the two models was found to be nearly negligible. In addition, its value was larger for model
(1) than for model (2). As the above results suggest, advantages of either model over the other could not
be fully captured by econometric tests in that both models perform satisfactorily in a statistical sense.
Furthermore, in light of their identical framework, they are theoretically of the same validity. The
similarity of the estimated parameters is another evidence of the equal capabilities of the two models.
Pollutant concentrations in effluent qe, and abatement in pollutant (qi - qe) are included in the model
simultaneously. One may choose to test if (qi - qe) could be omitted from the model. In other words, if the
models are to be found nested models it could be concluded that (qi- qe) could not be omitted from the
analysis. To test the null hypothesis α3 = 0 (α3 is coefficient of (qi- qe)), F-statistics was used. This test
was conducted and the related null hypothesis was rejected at 1% level of significance. It could be
concluded that these two models are nested and the cost function depends on BOD concentration in
effluent and abating level in BOD.
6. MARGINAL ABATEMENT COST
Shown in Table 8 are the estimated marginal costs of abatement at various levels of BOD concentration in
the effluents (on the basis of marginal cost of abatement obtained from the cost function estimated).
These estimates are based on the mean values of all variables except qe. The marginal cost of abatement
varies inversely with BOD concentration in the effluent.
In Malaysia palm oil mills use two methods of discharge, namely watercourse and land disposals.
Computed effluent fees for both are presented in Table 8. At the standard level set by DOE (100 mg/l) for
watercourse disposal, the corresponding marginal abatement cost is found to be RM30.78 (RM1 =
US$0.33, August 2010)and RM23.77 per mg/l of BOD based on models (1) and (2) respectively. The
effluent fee is load-based in Malaysia. Accordingly, to investigate whether the effluent fee is effective, the
marginal abatement cost per ton BOD of 100 and 5000 mg/l concentrations must be computed. Table 9
suggests that marginal abatement cost per ton of BOD of 100mg/l concentration is RM196 and RM151
using models (1) and (2) respectively. It could be observed in the Table 10 that the marginal abatement
cost per ton of BOD of 5000 mg/l concentration (which is standard level set by DOE for watercourse) is
RM3.50 and RM2.77 based on the models (1) and (2) respectively. The marginal abatement cost is too
much lower for land disposal method than that of watercourse disposal method. This, in our opinion, may
increase pollution in groundwater.
The results indicate one nuance between findings obtained from two models. In our opinion, due to
absence of any exaggeration in estimation of marginal abatement cost, those two models may be used by
policy makers for revising the effluent fee.
It could be seen in Table 8 that at a BOD concentration of 50 mg/l (which is less than the standard level
determined by DOE), the marginal abatement cost is found to be RM62.82 and 48.31 per mg/l of BOD
based on models (1) and model (2) respectively. Table 11 suggests that marginal abatement cost per ton
of BOD of 50 mg/l concentration is RM400.51 and RM308.05 using models (1) and (2) respectively.
Should the policy makers choose to improve the current standards, they may find the above results useful.
9
However, our findings show that the palm oil mills are using old ponding system to treat their water
pollution and bear high cost of abatement. Setting new standard may increase their abatement cost and
reduces their profit. It could lead to a decrease in their competitive power. New technologies should be
employed by firms to reduce their cost of abatement before changing the current standard.
Table 9 presents various levels of BOD load which could be compared with effluent fees at the standard
level. Based on model (2), the effluent fee is roughly equal to marginal abatement cost only for one ton of
BOD. With an annual average wastewater discharge of 156848 m3, a palm oil mill could produce 15.68
tons BOD with a concentration of 100 mg/l. However, according to Table 9, the marginal abatement cost
for 15 ton of BOD is RM2943.9 and 2273.85 based on models (1) and (2) respectively, while effluent fee
is only RM150. Marginal abatement cost for 20 ton of BOD is RM 3925.2 and 3031.8 based on the
models (1) and (2), respectively, while effluent fee is only RM200. It can be concluded that the effluent
fee is not sufficiently high enough to encourage firms to achieve zero pollution.
This conclusion holds for land disposal method that the marginal abatement cost is so much higher than
effluent fee at the standard (see Table 10). At 5000 mg/l BOD concentration, effluent fees do not exceed
marginal abatement cost for various BOD loads. With an annual average wastewater discharge of 156848
m3, a palm oil mill could produce 785 tons BOD with a concentration of 5000 mg/l. However, according
to Table 10, the marginal abatement cost for 785 ton of BOD is RM 2260 and RM 1923 based on models
(1) and (2) respectively, while effluent fee is only RM39.25. This result is consistent for 1 th and 1000th ton
of BOD load meaning that the marginal abatement cost is above effluent fees. It means that the effluent
fee for land disposal method is not sufficiently high enough to encourage firms to treat pollution
perfectly. With an annual average wastewater discharge of 156848 m3, a palm oil mill could produce 7.5
tons BOD with a concentration of 50 mg/l. According to Table 11 marginal abatement cost for 7.5th ton of
BOD is RM 3003.82 and RM 2310.37 based on models (1) and (2) respectively. To be comparable,
marginal abatement cost was obtained for 15th of BOD with a concentration of 50 mg/l. It was RM
6007.64 and RM 6161 based on models (1) and (2) respectively while it was only RM2943.9 and
RM2273.85 for 15th tons of BOD with 100mg/l concentration. It could be deduced that if the standard is
changed to 50mg/l, firms will bear high cost.
Based on the completed questionnaires, some of the palm oil mills have not met the standard determined
by DOE. Our data collected revealed that 38 mills i.e. 83% of the whole sample were violating the
standard. This percentage was 80% and 86% for Selangor and Johor, respectively.
According to Environmental Quality for Crude Palm oil Regulation, 1977, the mills violating from the
standard level are required to pay an effluent charge of RM100 per ton of BOD. In our sample, annual
average concentrations of BOD (in the wastewater after treatment) were 131.39 mg/L for watercourse
disposal method. Therefore, on the average, every palm oil mill exceeds the BOD standard for 31 mg/L
annually. With an annual average wastewater discharge of 156848m3, a palm oil mill could produce 4.86
tons BOD beyond the standard. They gain economic welfare from current charges. This problem have
probably incurred as a result of low effluent charges. Marginal abatement cost for treating this load of
BOD is to be RM953.82 and RM736.72, while effluent charge is only RM486. Effluent charges should,
consequently, be increased to a level preventing the mills from further polluting. Efficient level should be
equal
to
the
marginal
abatement
cost
or
higher.
10
Table 8. Marginal abatement cost
Post-abatement
BOD
concentration level (mg/l)
50
100
5000
Average wastewater
treated(m3)
156848
156848
156848
Marginal abatement cost for 1 mg/l
BOD treated in average of
wastewater(RM)
Model (1)
Model (2)
62.82
48.31
30.78
23.77
0.549
0.434
Marginal abatement cost for BOD
load (RM/ton)
Model (1)
400.51
196.26
3.50
Model (2)
308.05
151.59
2.77
Table 9. Marginal abatement cost and effluent fees at the standard of watercourse disposal method
Post-abatement BOD
concentration level(mg/l)
Marginal abatement aost for BOD
treated load (RM)
Model (1)
Model (2)
196.26
151.59
2943.9
2273.85
3925.2
3031.8
BOD treated load (ton)
100
100
100
1
15
20
Effluent fee in term of BOD
load (RM)
DOE
150
150
200
Table 10. Marginal abatement cost and effluent fees at the standard of land disposal method
Post-abatement
concentration
level(mg/l)
5000
5000
5000
BOD
BOD treated load
(ton)
1
785
1000
Marginal abatement cost for BOD treated
load (RM)
Model (1)
Model (2)
3.50
2.77
2260
1923
2880
2450
Effluent fee in term of BOD
load (RM)
DOE
0.05
39.25
50
Table 11. Marginal abatement cost and effluent fees at the standard of land disposal
Post-abatement
BOD
concentration level(mg/l)
50
50
50
BOD treated load (ton)
1
7.5
15
11
Marginal abatement cost for BOD treated
load (RM)
Model (1)
Model (2)
400.51
308.05
3003.82
2310.37
6007.64
6161.00
7. ANALYZING WELFARE EFFECTS
Our results are used to evaluate the welfare of the palm oil mills. As shown in Figure 2, since the
effluent charges are less than the marginal abatement cost at the standard level, palm oil mills have
gained private economic welfare. But as aforementioned, annual average concentrations of BOD (in
the wastewater after treatment) were 131.39 mg/L for watercourse disposal method. With 4.86 tons of
BOD produced beyond the standard as estimated a palm oil mill gains a welfare value around
RM96.26 per ton of its BOD load. This value is represented by dashed line EI in the figure.
Accordingly, a palm oil mill with average 4.86 tons of extra load of BOD has RM467.82 to gain for
4.86th unit of its BOD load. Total welfare is obtained by subtracting the total imposed effluent charge
from the total abatement cost. On the graph it is represented by the difference between the areas under
the MC curve which is above the horizontal dashed line MB. It could be calculated as follows:
Total cost of abatement – Total imposed effluent charge = 48818.958 - 486 = RM48332.958
As shown, palm oil mills gain economic welfare from current charges. This problem have incurred as
a result of the low effluent charges. Effluent charges should, consequently, be increased to a level
preventing the mills from further polluting.
Figure 2 Economic Welfare for Mills with Watercourse Disposal Method
For the mills which used land disposal method, the effluent charge is higher than the marginal
abatement cost. However, they gain from easier standard which could be measured by the dashed line
AB in Figure 3. As shown, an increase in BOD concentration from 100 mg/L to 5000 mg/L leads to a
decrease in marginal abatement cost. In other words, marginal abatement cost for 1 mg BOD in
wastewater with 100 mg/L concentration is RM30.23 which is higher than those for 5000 mg/L
concentration. In comparison with mills which use watercourse method, total cost for meeting the
standard is lesser for mills which used land disposal. It could be measured by the difference between
the total abatement costs as:
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Difference total welfare = Total abatement cost for 100 mg/L - Total abatement cost for 5000 mg/L =
106153.24 – 44767.80 = RM61385.2
As a result, total welfare for mills which used land disposal method is greater than the other category.
It is also greater than the gains which mills with watercourse disposal method gained from low
effluent charge.
Figure 3 Economic Welfare for Mills with land Disposal Method
8. CONCLUSION AND POLICY IMPLICATIONS
We explored the influence of economic instruments through testing whether effluent fees are
sufficiently high to encourage Malaysian palm oil mills to reach ultimate goal of abatement activities
that is treating pollution perfectly. As stated in the results, the effluent fees, for watercourse and land
disposal methods, are much lower than the marginal abatement cost of the firms. Our study also
analyzed whether effluent charges are sufficiently high to force Malaysian palm oil mills to meet the
mandatory standard. The results revealed that the effluent charge is lower than the marginal abatement
cost for firms which use watercourse disposal method. This causes firms not to abate to the standard
level leading to the more polluted surface water resources. Thus, it is recommended here that effluentrelated fees be increased to an effective level equaling the firm’s marginal costs.
Every year the Department of Environment (DOE) issues licenses for firms, which determine the
permissible system of discharge (watercourse and land disposal methods) based on the firm’s
geographical location, and the environment’s self-purification capability in the firm’s locality. Our
findings prove that the land disposal method has been less regarded in comparison with the
watercourse one. In fact, the latitude that the standard level (100 mg/L in contrast to 5000 mg/L for
watercourse disposal method) entitles the firms has led to extensive pollution of the land and
groundwater resources. From an economics standpoint, pollution raises the community’s costs and
affects the social welfare in the long run. Thus, it is recommended that effluent fees be increased to an
effective level equaling and/or above firm’s marginal costs.
Results of our study also proposes a standard for BOD concentration, which should be revised
upwards to that level the firms’ costs will increase, notwithstanding the economies of scale in
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pollution abatement activities. The current standard should be revised to 50 mg/l. The welfare analysis
performed in this study should be the basis for implementing the revision. Our results reveal that, in
view of the low charge and high abatement costs, firms are benefiting from them. Consequently, firms
prefer to pay the charges rather than lowering their pollution to the mandatory standard level.
Noticing the marginal benefit of firms is essential in improving the standards. In fact, if the standards
are improved disregarding the incurring costs, the competitiveness of firms – specially, that of the
smaller ones -- is affected. A 2-stage program is recommended. In the first stage, charges should be
increased to the marginal cost associated with the present standard level. Doing so, takes from the
firms their extra surplus. In the second stage, new standards should be introduced (but not
compulsorily), and the income resulting from increased charges is granted to the firms accepting the
standards as long term loans with negligible interests so that they could make use of new technologies
and reduce their abatement costs. Once a considerable number of firms have adopted the standard, the
standard must be enforced such that the remaining firms to join the program too. It is noteworthy that
this program should be executed for all firms simultaneously so that a significant earning could be
made from the increase in the charges.
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