Hypothesis Testing on Environmental Kuznets Curve of Agricultural Sector in Java Island: Panel Data Analysis | Al rosyid | Agro Ekonomi 25703 60081 1 PB

Agro Ekonomi Vol. 28/No. 1, Juni 2017

95

HYPOTHESIS TESTING ON ENVIRONMENTAL KUZNETS CURVE OF
AGRICULTURAL SECTOR IN JAVA ISLAND: PANEL DATA ANALYSIS
Pengujian Hipotesis Kurva Lingkungan Kuznets (Environmental Kuznets
Curve) Sektor Pertanian di Pulau Jawa : Analisis Data Panel
Ali Hasyim Al Rosyid1, Irham1,2, Jangkung Handoyo Mulyo1,3
1
Student of Postgraduate Program of Faculty of Agriculture, Universitas Gadjah Mada
Jl. Flora, Bulaksumur, Kec.Depok, Kabupaten Sleman,
Daerah Istimewa Yogyakarta 55281
2
Asia-Pacific Study Centre (PSAP), Universitas Gadjah Mada
Jl. Tevesia, Bulaksumur B-13, Yogyakarta 55281, Indonesia
3
Population and Policy Studies Center (PSKK), UniversitasGadjahMada
Jl. Tevesia, Bulaksumur, Kec.Depok, Kabupaten Sleman,
Daerah Istimewa Yogyakarta 55281
alihasyimalrosyid@gmail.com; irhamsec2000@yahoo.com;

Diterima tanggal 6 Juni 2017 ; Disetujui tanggal 15 Juni 2017
ABSTRACT
One obstacle in the improvement of community welfare in the agricultural sector, especially in
Java, is the environmental externality which constantly exists in every economic activity. The
objective of this research was to estimate greenhouse gas emission coming from agricultural
sector in Java and identify whether farmers in Java had allocated environmental conservation
costs as the impact of greenhouse gas emission from agricultural activities in Java. The inventory
method of greenhouse gas emission from agricultural sector is based on inventory guidelines
published by IPCC (Intergovernmental Panel on Climate Change) in 2006. As for the analysis to
determine the relationship between greenhouse gas emission and GRDP of agricultural subsector
per agricultural labor, The Environmental Kuznets Curve (EKC) was employed, alongside
greenhouse gas emission indicators representing environmental degradation and GRDP of
agricultural subsector per agricultural worker representing of per capita income of agricultural.
Overall, greenhouse gas emissions, both CH4 methane emissions and carbon dioxide emission
(CO2) - produced from rice cultivation, fertilizer application, livestock enteric fermentation
and poultry manure - are gradually increasing. And the relationship between greenhouse gas
emission and GRDP per worker has inverted-U shape; and it is in line with EKC hypothesis.
Thereby, the role of the entire community elements and government support in implementing
mitigation technology and agricultural adaptation is needed to cope with impacts of greenhouse
gas emission, such as climate change.

Keywords: Agricultural Sector, EKC (Environmental Kuznets Curve), GHG Emission
(Greenhouse Gas)
INTISARI
Salah satu kendala dalam peningkatan kesejahteraan masyarakat di sektor pertanian, khususnya
di Jawa, adalah eksternalitas lingkungan yang selalu ada dalam setiap aktivitas ekonomi. Tujuan
dari penelitian ini adalah untuk memperkirakan emisi gas rumah kaca yang berasal dari sektor
pertanian di Jawa dan mengidentifikasi apakah petani di Jawa telah mengalokasikan biaya

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konservasi lingkungan sebagai dampak emisi gas rumah kaca dari kegiatan pertanian di Jawa.
Metode inventarisasi emisi gas rumah kaca dari sektor pertanian didasarkan pada pedoman
inventarisasi yang diterbitkan oleh IPCC (Intergovernmental Panel on Climate Change) pada
tahun 2006. Sedangkan untuk analisis untuk mengetahui hubungan antara emisi gas rumah
kaca dan PDRB sektor pertanian per tenaga kerja pertanian, menggunakan Environmental
Kuznets Curve (EKC) di samping itu digunakan indikator emisi gas rumah kaca yang mewakili
degradasi lingkungan dan PDRB subsektor pertanian per pekerja pertanian yang merupakan
pendekatan pendapatan per kapita pertanian. Secara keseluruhan, emisi gas rumah kaca, baik

emisi metana CH4 dan emisi karbon dioksida (CO2) yang dihasilkan dari budidaya padi, aplikasi
pupuk, fermentasi enterik ternak dan pupuk unggas meningkat secara bertahap. Hubungan
antara emisi gas rumah kaca dan PDRB sektor pertanian per tenaga kerja pertanian seperti
U-terbalik. sehingga sejalan dengan hipotesis EKC. Dengan demikian, peran seluruh elemen
masyarakat dan dukungan pemerintah dalam menerapkan teknologi mitigasi dan adaptasi
pertanian diperlukan untuk mengatasi dampak emisi gas rumah kaca, seperti perubahan iklim.
Kata Kunci: Emisi GRK (Gas Rumah Kaca), EKC (Environmental Kuznets Curve), Sektor
Pertanian
INTRODUCTION

environmental damage resulted from the

Agriculture in Java remains

production process of goods and services

as the dominant sector, viewed from

have never been considered. As a result, the

its contributions to total GDP and the

price used in the market is way too low in

employment in this sector. If we view the

comparison with the applied price – as the

agricultural sector’s GDP contribution

price does not include ‘environmental costs’.

in Indonesia, the agricultural sector

As a key sector in the fulfillment of

contributes to Rp.441.601.433,4 (Billion)

food needs, emissions generated from the

or equal to 36.50% out of total GDP of

agricultural sector are expected to continue

Indonesian agriculture sector.

to keep rising until 2030, alongside

One of the obstacles in the improvement

increasing food demand. In order to handle

of community welfare in the agricultural

this Indonesian Government has committed

sector, especially in Java, is the environmental

to reduce GHG emission by 26% by 2020.

externality which constantly exists in every

(Ariani et.al., 2016).

economic activity, and it should be addressed

Dasgupta et.al. (2002) proposes the

in the economic development by means of

hypothesis used in this EKC: at the early

improving the agricultural development

stage of the industrialization process,

performance. In reality, the environmental

pollution grows real swiftly because the

externalities in the agricultural sector are

main priority is to increase output, and the

rarely considered, particularly in Indonesia.

community tends to be more interested in

As proposed by Irham, (2002), the costs of

getting jobs and having higher income,

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97

rather than getting good environmental

undertook a research to estimate the

quality. According to Everett et al. (2010)

Kuznets Environment Curve hypothesis for

the reversed-U curve illustrates the degree

4 countries. The use of OLS in this research

of environmental degradation will go

is capable of proving the EKC hypotheses

together with increasing per capita national

in countries with low income and rather low

income. De Brunye, et al., (1998) believes

income. Wang et.al., (2016) performed a

that EKC does not happen in the long

research to investigate impacts of economic

run. It is, therefore, the U-Shape will only

growth and urbanization on level of sulfur

happen at the early stage of the relationship

dioxide in the air of China. The research

between environmental damage level and

results suggest the evidence of inverted-U

per-capita income. In the condition above,

relationship between economic growth

a certain level of income will have a new

and sulfur dioxide emissions. However,

turning point. Dinda (2004) and Song,

the relationship between urbanization and

et.al. (2008) develop EKC relationship

sulfur dioxide emission does not show

in the form of cubic polynomials, where

relationship similar to inverted-U.

such model can be used to examine several

Apergis and Ozturk (2015) tested the

relationship forms between environmental

hypothesis (Environmental Kuznets Curve)

indicators and economic growth.

in 14 countries in Asia in 1990-2011. The

Environmental degradation becomes

results of the analysis show that per capita

a hotly debated issue between economic

income has a significant and positive

experts and environmental experts. Lau et

influence on CO2 emissions in 14 Asian

al. (2014) empirically tested the hypothesis

countries studied, as well as population

of the Kuznets Environment Curve in

density also have an effect on emissions

Malaysia by looking at the relationship

increase. In addition, the average economic

between Foreign Direct Investment and

growth in 14 countries in Asia is still in the

free trade system with CO 2 emissions,

early stages so that the increase in income

viewed for its short and long term. Farhani

per capita still has an impact on the increase

et al., (2014) carried out a research to

of environmental pollution.

examine the hypothesis of Kuznets

The objective of this research is to

environmental curve in Middle East and

estimate greenhouse gas emissions coming

North Africa countries using panel data

from the agricultural sector in Java, in order

from 1990-2010. The results demonstrate

to identify whether farmers in Java have

that the EKC model obtains inverted-U

allocated environmental conservation costs

between environmental degradation and

as impacts of greenhouse gas emission

income per capita. Azam and Khan (2016)

from agricultural activities in Java.

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METHODS
The selection of research site was

Panel on Climate Change) in 2006. The
measurement methods are as follows:

conducted purposively, taking locationspecific condition into consideration. The

a. Agriculture (Food Crops, Horticultures,

reason for selecting Java for this research

and Plantations)

was based on the roles of agricultural sector,

Emissions from agricultural sector

employment rate and its contribution to the

especially food crops, horticultures and

national GDP. The provinces in Java have

plantations can be approximated from CH4

large percentage.

emission from rice paddy cultivation and

The data was collected by

carbon dioxide resulted from urea fertilizers

documentation: the data used was recorded

application. CH4 emissions are calculated by

from the data sources or existing documents

multiplying the daily emission factor by the

from 2001-2015 in five province of Java

length of rice cultivation and harvest area

Island. The documents were people’s notes

using the following equation (IPPC, 2006):

or works on events in the past. The data

ECH4=LT x HT x EFflooded land x 10-3

employed in this research were those resulted

Where:

from recordings in government agencies,

E CH4 = CH4 emission of rice paddy (ton/

such as East Java Provincial Government,

year)

Central Java Provincial Government,

RPA

= Rice paddy planting area

Yogyakarta Provincial Government, West

HT

= In average total day, planting rice

Java Provincial Government and Banten

paddy within a year (rice paddy

Provincial Government; Central Statistics

harvest index in average is 220)

Agencies of East Java Province, Central

EFfield = Emission factor of rice paddy

Java Province, Yogyakarta Province, West

CH4 (1.3 kg CH4/ha/day) CO2

Java Province, and Banten Province. In

Emission of urea fertilizer can

addition, other supporting data were also

be calculated using equation

obtained from other institutions.

below (IPPC, 2006):
CO2Emission = (MUreaxEFUrea)

The Measurement of Greenhouse Gas

Where:

Emission (GRK) from Agricultural

CO2-Emission = annual CO2 emission

Sector in Java
The inventory method of greenhouse
gas emissions from the agricultural sector
is based on the inventory guidelines
published by IPCC (Intergovernmental

from Urea application (ton/year)
MUrea = total urea fertilizer being applied
(ton/year)
EFUrea = emission factor, CO2 ton per urea
application.

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and livestock manure management. In the
Based on IPCC (Tier 1) for the urea

present research, methane emissions from

emission factor is 0.20 or equivalent to C

livestock management used the formula

content of urea fertilizer based on atomic

from IPPC (2006) below (IPPC, 2006):

weight (20% of CO (NH2)2).
b. Livestock

Where:

Greenhouse gas emissions in

CH4 manure = CH4 Emission from livestock

livestock are calculated from methane

manure management (ton/

emissions (CH4) generated from livestock

year)

enteric fermentation and methane emissions

EF(T)

= CH 4 Emission factor from

from livestock manure management. The

certain types of livestock

estimation of CH4 emission level from

manure (kg CH4/animal/year)

livestock enteric fermentation uses the

N(T)

livestock being slaughtered

equation below (IPPC, 2006):
Emissions=EFTx NTx10-3
Where

= Total certain category of
(per animal)

T

= Types or categories of livestock

Emissions = CH4 Emission from enteric
EFT

fermentation (ton/year)

The Analysis of Relationship between

= CH4 Emission factor from

Environmental Degradation and

certain types of livestock (kg

Agricultural Sector GRDP per Worker

CH4/animal/year)
NT

The relationship between

= total certain types/ categories

environmental degradation and average

of livestock slaughtered

income of agricultural workers is

individually

conducted to answer whether the actors

Livestock manure does not only

in the agricultural sector in Java have

produce feces and urine, but also

allocated some of their income to improve

considerably high methane (CH4). The

the environment as an effort to manage

livestock manure potential to emit

their farming business. This analysis

methane may occur during storage and

employs The Environmental Kuznets

even processing. This methane production

Curve (EKC) model with greenhouse

process can occur and will increase if the

gas emission indicators representing

environment is in anaerobic condition. The

environmental degradation and average

methane emission is strongly affected by

agricultural sector workers representing

types of feed, the quality of poultry feed

per capita income. As stated by Kuznets,

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EKC shows that environmental degradation

best model selection was done through

(greenhouse emissions) will increase in

Chow Test, Breusch-Pagan, and Hausman.

line with increasing per capita income,
but if it has reached a certain point called

Chow Test

turning-point, there will be decline in

The testing mechanism using Chow

environmental degradation despite rising

Test is described as follows (Gujarati,

per capita income. Based on the above,

2006);

the estimation that can be used to view

Hypothesis:

the relationship between environmental

H0 : α_1 = α_2 = … = α_i (similar

degradation and per-capita income is: The

intercept, no significant

Environmental Kuznets Curve (EKC)

effects from cross section

model with greenhouse gas emission

unit)
H1 : α_i ≠ 0; i = 1,2,…,n (at least there

indicators:
GHG = C +

1

GRDP ALit +

2

GRDP

ALit2 +
Description:
GHGt

is one different intercept, a
significant effect is found in
the cross section unit).
If F_count > F_(α;[db]_1;[db]_2) or

= Total Green House Gas
Emissions (CO2 and CH4
converted to CO2) from

Probability value χ_tab

development of methane emissions resulted

or p-value is smaller than the significance

from rice cultivation activities in Java in the

level specified, H0 is rejected. That is, Fixed

period of 2001-2015.

2

Effect Model is better than Random Effect
Model.

The figure provides information
related to CH4 methane emission from
rice cultivation in Java. In the period

RESULTS AND DISCUSSION

2001-2015, the emissions generated from

The Measurement of Greenhouse Gas

the rice cultivation activities in Java have

Emission (GRK) from Agricultural

increased. The growth rate of methane

Sector in Java

emissions from rice paddy is 1.10% per

Global warming is the process of

year. This condition shows that the level of

increasing the average temperature of the

methane emission in 2015 is greater than

atmosphere, the ocean, and the Earth’s land

the methane emission in 2001. The value of

caused by increasing concentrations of

methane emissions (CH4) generated from

greenhouse gases due to human activities

rice cultivation in 2001 is 1,158,627 tons,

(Suarsana and Wahyuni, 2011). The

whilst in 2013, it increases into 1,771,437

Intergovernmental Panel on Climate

tons.

Change (IPCC) has provided guidance

The level of methane emission (CH4)

to estimate Greenhouse Gas Emission

value from rice cultivation activity is in

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Figure 1. The development of the estimated value of methane emissions (CH4) from rice
field cultivation activity in Java Island in 2001-2015.
Table 1. Urea Fertilizer Application in
Each Type of Plants
Type of Plants
Crops
Paddy
Corn
Soybean
Peanuts
Green beans
Cassava
Sweet potatoes
Horticultural Crops
Vegetables (non-spesific)
Plantation Crops
Rubber
Coconut
Coffee
Tea
Cocoa
Sugarcane
Tobacco
Clove

Urea Dose
(kg/ha)

with ammonium sulphate or tablet urea
fertilizer, applying direct seeding plant
(Wihadjaka, 2015), applying intermittent
irrigation, and replacing rice varieties with

284
333
161
156
127
243
222

superior rice variety and low emission
(Kartikawati et.al., 2011).
In addition to rice cultivation
activities in the fields, urea fertilization
application onto agricultural land may

207
523
200
316
631
906
928
207
371

Source: Agricultural Census, 2013
(processed)

also lead to greenhouse gas emission,
i.e. carbon dioxide gas (CO2). The urea
fertilizer application on agricultural land
has caused the release of CO 2 trapped
during the fertilizer production.
Based on the table 1 can be seen
that in general the use of urea fertilizer by
farmers exceeds the dose recommended
by the ministry of agriculture. As a result

Java is determined by the area of rice
cultivation (this research uses the harvested
area approach). A number of mitigation
technologies in the effort of reducing the
level of methane emissions in rice paddy
can be done by applying the system without
tillage, replacing powdered urea fertilizer

a lot of actual fertilizer wasted because it is
no longer needed by the plant. In addition,
the excess N on the ground will also lead
to increased production of methane on the
ground. The use of inorganic fertilizers to
be more efficient should be based on the

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103

Figure 2. The development of the estimated value of carbon dioxide(CO2) emissions
from the use of urea fertilizer in Java Island in 2001-2015
needs of the plant. This can be seen from

apply fertilization dose, especially urea,

leaf color i by using leaf color chart.

which exceeds the dose recommended by

The figure displays information

the government. One of consequences is the

related to estimation of carbon dioxide

greater emission of carbon dioxide yielded

(CO2) emissions resulted from urea fertilizer

from urea fertilization activity.

application in Java. In the period 2001-

Based on the table 2, it is known that

2015, carbon dioxide (CO2) emission from

the CH4 emission factor value derived from

urea fertilizer application in Java Island has

the fermentation of the enteric of livestock

increased. The growth of carbon dioxide

is the most produced by the dairy cows at

emission from urea fertilizer application is

61 kg /animal/ year. While the cattle that

0.48% per year. Based on this, it can be seen

produce CH4 least seen from the emission

that value of carbon dioxide (CO2) emission

factor of pigs with emission factor value of

resulted from fertilizer application in 2015

1 kg / animal / year. This emission factor

is higher (678,940 tons) in comparison with
carbon dioxide emission at the same source
in 2001 (726,301 tons).
The value of carbon dioxide emission
(CO2) is determined by several components,

Table 2. Value of CH 4Emission Factor
from Enteric Fermentation
according to Livestock Types
(EFT)

emission is the application dose of urea

Types of
Livestock
Beef Cattle
Dairy Cattle
Buffalo
Sheep
Goat
Pig
Horse

fertilization onto crops. Average farmers

Source: IPCC, 2006

including cultivation area (this research
used the harvested area approach) for
each crop. Besides, other components
determining the level of carbon dioxide

Emission Factor CH4
(kg/animal/year)
47
61
55
5
5
1
18

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Table 3. Estimates of Methane Emissions (CH4) from Livestock Enteric Fermentation (ton)
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
In average
Growth (%)

Beef Cattle Dairy Cattle
201.868
21.134
203.036
22.062
205.238
21.426
207.507
21.296
207.703
21.732
221.231
22.255
228.864
23.318
270.331
28.411
281.451
29.149
313.457
35.999
326.738
36.799
302.653
27.429
318.973
30.193
330.387
31.175
254.630
26.204
3,65
2,98

Buffalo
31.901
31.491
32.691
25.627
25.489
25.360
25.244
24.969
25.187
19.958
19.814
16.397
17.155
16.949
24.760
-4,68

Goat
34.861
34.615
37.133
37.204
38.106
39.472
41.999
45.017
47.185
48.452
50.962
53.013
54.046
55.179
43.460
3,38

Sheep
35.195
35.899
37.638
38.155
41.319
43.791
48.019
47.288
48.343
54.924
62.659
69.147
75.271
79.920
50.128
6,22

Pig
174
182
224
233
215
191
200
186
194
215
231
250
223
218
207
1,86

Horse
974
968
1.003
829
890
898
855
696
717
773
821
759
718
695
839
-2,47

Source: Secondary Data Analysis, 2017
value is then multiplied by the existing

largest one is methane emissions (CH4)

livestock population in Java Island, so that

from beef cattle is 254,630 tons per year;

will be obtained CH4 emission value from

while the smallest emission comes from

the fermentation of enteric cattle in each

pigs, by 207 tons per year .

livestock each year.

Overall, the level of methane (CH4)

Based on the table 3, it can be seen

emission from enteric fermentation of

that methane (CH 4) in 2002 is mostly

beef cattle in Java has increased by 3.65%

produced by enteric fermentation of

per year. This value is in line with the

beef cattle, i.e. 201,868 tons, whilst the

increasing beef cattle population from 2002

livestock producing the least amount of

to 2015. As for pigs, the positive growth

methane (CH4) from enteric fermentation

happening is 1.86% per year. Buffalo and

is 174 tons. Such condition remains

horse in Java experience the growth of

unchanged by 2015. That is, methane

negative methane (CH4) emission per year.

emission from enteric fermentation of

It is parallel with the declining buffalo

beef cattle still dominates the livestock

and horse population in Java. It happens

methane emission contribution in terms of

because of the difficulties in providing

enteric fermentation in Java, whereas pigs

suitable land for buffaloes and horses in

contributes to smallest methane emission

Java, in addition to their more complicated

in Java in terms of livestock’s enteric

raising methods - in comparison with beef

fermentation. If viewed from the average

cattle or sheep’s, making the breeders have

number per year for each livestock, the

less interest in raising buffalos and horses.

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Table 4. CH 4 Factor Value of Manure
according to Types of Livestock
(EFT)
Types of Livestock
Beef Cattle
Dairy Cattle
Buffalo
Sheep
Goat
Pig
Horse
Local chicken
Broiler Chicken
Laying hens
Ducks
Muscovy Ducks

CH4 Emission Factor
(kg/animal/year)
1.00
31.00
2.00
0.20
0.22
7.00
2.19
0.02
0.02
0.02
0.02
0.02

Source: IPCC, 2006

105

by the population of livestock and poultry
which will be obtained CH4 emission value
resulting from cattle and poultry manure.
The highest methane (CH4) emission
from livestock manure in 2002 produced by
dairy cattle of 10.740 tons; whilst livestock
producing the lowest livestock manure
emission is horses by 118tons. Such
condition is relatively unchanged until
2015, where dairy cows still contribute to
the largest methane (CH4) emission. And
horse manure is still the lowest contributor
of methane emission from livestock

Based on the table 4 can be seen that

manure. If viewed from the average

the value of CH4 emission factor generated

emission of methane produced, dairy cows

from the highest livestock manure produced

produce an average methane emission of

by the dairy cattle that is equal to 31.00 kg/

13,136 tons per year, while horses produce

animal/year while CH4 emission value of

average methane emission of 102 per year.

the lowest emission factor produced from

When viewed from the value of each

poultry group of 0.02 kg/animal/year. The

livestock emission factor, dairy cow is

value of emission factor is then multiplied

indeed the highest methane (CH4) emitter

Table 5. Estimates of Methane Emissions (CH4) from Livestock Manure (ton)
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
In average
Growth (%)

Beef Cattle Dairy Cattle
4,295
10,740
4,319
11,212
4,366
10,889
4,415
10,822
4,419
11,044
4,707
11,310
4,869
11,850
5,751
14,438
5,988
14,813
6,669
18,294
6,951
18,701
6,439
13,939
6,786
15,344
7,029
15,843
5,417
13,316
3.65
2.97

Source: Secondary Data Analysis, 2017

Buffalo
1,160
1,145
1,188
931
926
922
917
907
915
725
720
596
623
616
900
-4.68

Goat
1,533
1,523
1,633
1,636
1,676
1,736
1,847
1,980
2,076
2,131
2,242
2,332
2,378
2,427
1,912
3.37

Sheep
1,407
1,435
1,505
1,526
1,652
1,751
1,920
1,891
1,933
2,196
2,506
2,765
3,010
3,196
2,005
6.21

Pig
1,224
1,277
1,570
1,637
1,511
1,343
1,402
1,307
1,359
1,507
1,621
1,755
1,562
1,529
1,452
1.86

Horse
118
117
122
100
108
109
104
84
87
94
99
92
87
84
102
-2.46

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Table 6. Estimates of Methane Emissions (CH4) from Poultry Manure (ton)
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
In Average
Growth (%)

Local Chicken
2.301
2.348
2.384
2.357
2.278
2.300
2.381
2.023
2.039
2.180
2.275
2.271
2.339
2.362
2.266
0,65

Laying hens
753
817
1.128
1.028
1.229
1.394
1.323
1.128
1.181
1.517
1.616
1.716
1.660
1.761
1.265
6,52

Broiler chicken
3.003
3.072
8.404
3.192
3.280
3.532
3.736
4.484
5.017
5.435
5.811
6.605
9.282
10.123
5.142
11,71

Ducks
237
257
272
275
274
305
341
409
424
440
426
413
431
450
346
4,67

Source: Secondary Data Analysis, 2017
of livestock manure, by 31/kg/animal/

livestock with negative methane emission

year. It is one of the reasons why dairy

growth, namely buffalo (-4.68% per

cattle contribute the highest methane

year) and horses (-2.46% per year). Such

emissions coming from manure. In terms

condition is in line with the population of

of the population, beef cattle are more

these two which tend to decline each year.

widely bred in Java than the dairy cattle.

Based on the table 6, the methane

Nevertheless, the emission factor from beef

emission (CH4) yielded by poultry manure

cattle manure is lower, making the methane

in 2002, mostly comes from broiler chicken

emission (CH4) from beef cattle manure

which is equal to 3.003 tons. In contrast, the

become lower than that of dairy cattle.

poultry producing the least manure methane

The methane emission produced

(CH4) level includes ducks, by 237 tons.

by each livestock in Java is growing.

Such condition does not change from year

This value is in accordance with the

to year until 2015, where broiler chicken still

increasing number of livestock population

have the highest methane emission (CH4)

in Java, in the period 2002-2015. The

contribution from poultry manure, by 10.123

methane emission from livestock manure

tons. If viewed from the average value of

experiencing positive growth is beef cattle

total methane (CH4) emission from poultry

(3.65% per year), dairy cows (2.97%

manure, broiler chicken have average

per year), goats (3.37% per year), sheep

methane emission of 5,142 tons per year,

(6.21% Per year), and pigs (1.86% per

whereas ducks have an average methane

year). Nevertheless, there are two types of

emission of 346 tons per year.

Agro Ekonomi Vol. 28/No. 1, Juni 2017
In general, methane emission (CH4)
from poultry manure has increased from
2001 to 2015. Furthermore, each type of

worker is used. The model is:
GHGt=C+ 1GRDP ALt+ 2(GRDP ALt)2+
In the function above, GHGt is the

poultry has grown each year: local chicken
by 0.65% per year, laying hens by 6.52 per
year, broiler chicken by 11.71% per year,
and ducks by 4.67% per year, respectively.

107

level of greenhouse gas emission from
agricultural activity, GRDP AL is GRDP
per agricultural worker, and ε is a stochastic
disruption. The regression model selection

The Analysis of Relationship between
Environmental Degradation (Greenhouse
Gas Emission) and Agricultural GRDP

in the panel data is at stage for determining
the best estimation method among common
effect, fixed effect and random effect.
Based on the table 7, p-value on chi-

per Agricultural Labor
In this research, the analysis of
relationship between greenhouse gas
emission from the agricultural sector and the
GRDP per agricultural worker in Java uses

square’s cross section is 0.0000 0 and 2