Economic Impacts of Carbon Tax in Makassar City
in Indonesia: a CGE Modeling Approach
ANY WAHYUNI
Graduate School of Environment and Life Science Engineering, Toyohashi University of Technology
YUZURU MIYATA
Graduate School of Architecture and Civil Engineering, Toyohashi University of Technology
HIROYUKI SHIBUSAWA
Graduate School of Architecture and Civil Engineering, Toyohashi University of Technology
1. Introduction
One of an instrument of greenhouse policy represents the introduction of carbon tax. The postulated
policy target in Indonesia is the Ministry of Finance Indonesia Green Paper on Climate Changecommitment of the President of the Republic of Indonesia at G-20 conference, of reducing carbon
dioxide emissions in 2020 to the equivalent of 6-24 per cent below of the 2005 levels.
The degree of abatement is measured by an estimated level of emissions in 2006 as a business-asusual (BAU). In principle, of abatement applies to all urban economic activity sources of carbon
dioxide emissions, estimates for the fossil fuels uses, which is a contributor to emissions by 68.7 percent of the total emissions in Indonesia (2010).
Energy sector of carbon dioxide emissions in Makassar city under the business as usual are estimatedat 2.57 million tonnes by 2006. Referring to the Green Paper target, it is necessary to cut emissions by
154 thousand – 616 thousand tonnes of the business as usual. In the scenario of the study is theintroduction of a carbon tax with a rate sufficient to reduce carbon dioxide emissions by 7- 8 percent
in 2006. The tax applies to all commodities as consumption within the city. This tax does not apply tothe export and distribution activity to avoid double taxation.
The study provides detailed evaluated of the impacts of the carbon tax on the production,
consumption and urban economic performance as well. It uses a Computable General Equilibrium(CGE) model,which is a quantitative method to estimates the impact of the economic and policy
shocks, particularly the economy as a whole. The model was a realistic manner to reproduces the
structure of the whole economy and therefore the nature of all existing economic transactions among
diverse economic agents (productive sectors, households, government, and external sectors). A CGE
modeling expected to have significant impacts throughout the economy.
2. Model2.1Framework of Model
This study used CGE comparative-static model which the simulation results were reported as
deviations from a base case (business as usual). It does not present changes over time, but differenceswith respect to the base case at given point in 2006. We used model of the closed-economy; that is, nointernational trade. The results are commonly reckoned as representing economic responses over a
period of about two years (McDouugall,1993). The model is consistent with price level and real
activity. The price is set an exogenously, it acts as numeraire for model.
This study assumed that industries produced products and carbon dioxide emissions by products. The
price P0 equivalent with marginal cost and after applying tax will become the equilibrium price at P1.
Output of industries are X1.
Simulations model will result in a percentage change of industry output by 100*(X1-X0)/X0, andpresented that how the policy can impact on the industry output.
2.2 Setup of the Economy
In model, supply used two production factors namely: one labor and one capital. There are twenty
eight industries representative firms, which produced twenty eight commodities in this economy. One
representative household exists who consumes all commodities to maximize its utility. The household
supplied two factors to the firms in return for income payments. The firms employ these factors in1

their production. They are demand and supply of these commodities and factors in equilibrated andperfectly competitive in 2006.
2.3 Behaviour of the Economic Agents
2.3.1 Industries
In industries, intermediate input, labour and capital are inputted to produce goods. Industries have the
Cobb-Douglas technology with respect to intermediate input and labour and capital inputs, andLeontief technology with value added inputs. Cost minimization problem can be written as follows:28

min  pi xij  (1  tp j )( wL j  rK j )( j  1,..., 28 )
i 1

(1)

with respect to xij, Lj and Kj
subject to
X j  min[

x1 j
x ij'
x 28 j1f j ( L j , K j ),,..., ' ,...,
]
a0 j
a1 j
a 28 ja ij(1 a j )f j ( L j , K j )  A1 j L j K j
aj

(3)
where
pi : price of commodity I; xij: intermediate input of industry i's product in industry j; tpj: net indirect tax
rate imposed on industry j’s product (indirect tax rate - subsidy rate); w : wage rate; r : capital return
rate; Lj: labor input in industry j; Kj: capital input in industry j; Xj: output in industry j; a0j : value
added rate in industry j; aij: input coefficient; Aij,αij: technical parameters in industry j.
Conditional demands for intermediate goods, labour, and capital in the production process are as
follows:

xij  aij X j

(2)

(4)

 (1   j )r 
LD j    j w  ajw KD j   (1  a j )r 

j

a0 j X j(1 a j )Aj

(5)a0 j X j
Aj

(6)
where
LDj: conditional demand for labour in industry j; KDj: conditional capital demand in industry j; Zeroprofit condition is realized in the industries under a perfect competition.
38

profit  p j X j   pi xij  (1  tp j )[ w.LD j  r.KD j ]  0 (7)i 1

2.3.2 Households
Households in Makassar City are assumed to be homogeneous with the fixed number of households.
Thus one can consider that households share an aggregate single utility function. Households share a
CobbDouglass utility function of the current and future goods. Here the current good is defined as a
Cobb Douglass composite of current consumption goods and leisure time, while the future good isderived from saving.
To explain the household behavior, first, derivation of future good is described here. The future good
implies the future consumption which derived from household saving, however, the saving formulates
capital investment. Therefore capital good can be regarded as saving good. Investment is made byusing produced goods, and let their portions in investment be denoted by bi. Denoting the price of28

investment good by pI,

p I I   pi I i
i 1

is realized. Then the price of investment good is expressed as28

p I   bi p i. This can be regarded as the price of saving good ps.
The expected net return rate of household saving rs is written as follows:i 1

rs  (1  ty)(1  ko )(1  kr )r / ps(8)2

wherety: direct tax rate imposed on households; ko: rate of transfer of property income to the external sector
1; kr: capital depreciation rate ; δ: ratio of capital stock measured by physical commodity unit to that bycapital service unit.
It is assumed that the expected returns of saving finance the future consumption. Regarding the priceof future good as the price of the present consumption good under the myopic expectation, anddenoting the household real saving by S, the following equation holds.
Then we describe the derivation of demands for composite consumption and leisure time from thecurrent good G. The current good G is a composite of consumption and leisure time, and G is obtained
from the following optimization problem.
max G  { 1/v 2 C ( v2 1) / v2  (1   )1 / v2 F (v2 1) / v2 }v2 /( v2 1)
C,F(9)subject top  C  (1  ty )(1  lo ) w  F  (1  ty ) FI  TrHO  SH (10)where
β : share parameter; v2 : elasticity of substitution between composite consumption and leisure time; C :composite consumption; F : leisure time; p : price of composite consumption good; SH : household
nominal saving (＝PS･S ).
Solving this utility maximization problem, demand functions for composite consumption, leisuretime, and labor supply are obtained.
C [(1  ty ) FI  TrHO  SH ]p v2  (1   )[(1  ty ) FI  TrHO  SH ]F[(1  ty )(1  l o ) w] v  
2LS  E  F

(11)
(12)

(13)
  p (1v )  (1   )[(1  ty )(1  l o ) w] (1v ) (14)22whereLS : household labor supply
Substituting composite consumption (11) and leisure time (12) into (9), the price index of the present
good is derived as follows:pG  { p 1v  (1   )[(1  ty )(1  l o ) w]1v }1 /(v 1) (15)222Moreover, composite consumption good is disaggregated into produced goods through the
maximization of a Cobb-Douglas sub-sub utility function given the household income and leisure time.
28

max C   C i i
i 1

28

(  i  1)
i 1

(16)

subject to28

 p  C  (1  ty)Y  TrHO  SH
i 1

i

i

(17)
where
Ci : household consumption good produced by industry I; pi : price of good I; Y : household income( =(1-lo)w･LS+LI+(1-ko)(1-kr)r･KS+KI+TrGH+TrOH).
From this optimization problem, consumption good i is derived.

C i  i [(1  ty )Y  TrHO  SH ](i  1,  ,28 )pi(18)The price of composite consumption is calculated as follows:p p   i i 1   i 
28

i

(19)

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2.3.3 The Government
The government sector in this study consists of the national and local governmental activities in
Makassar City. Thus, the concept of the government corresponds to the definition of SAM framework.
The government obtains its income from direct and net indirect taxes of Makassar City, and current
transfers from the external sector, and then it expends the income on government consumption, current
transfers to households, and current transfers to the external sector. The difference between income
and expenditures is saved. Nominal consumption expenditures on commodities/services are assumed
to be proportional to the government revenue with constant sectorial share. These are denoted by thefollowing balance of payment.
2828

 p  CG  TrGH  TrGO  SG  ty  Y   tp (w  LD  r  KD )  TrOG
i 1

i

i

i

i 1

i

i

(20)
where
CGi: government consumption expenditures on commodity I; TrGH: current transfers to households;
TrGO: current transfers to the external sector; SG: government savings; TrOG: current transfers fromthe external sector.
2.3.4 The External Sector
The external sector gains its income from Makassar City’s imports, current transfers from thegovernment, labour income transfers and property income transfers. Then, it expands the income onexports and transfer of Makassar, current transfers to households and the government, labour(employees in Makassar City) and property income transfers. These are also expressed by thefollowing balance of payment.
2828

 p  EX  TrOH  TrOG  KI  LI  SO   p  EM  TrHO  TrGO  KIO  LIO
i 1

i

i

i 1

i

i

(21)
where
EXi: export of commodity I; EMi: import of commodity I; SO: savings of the external sector (=national current surplus); LIO: labour income transfers to the external sector (= lｏ· w ·LS ); KIO:
property income transfers to the external sector (= k0 · r · KS.
2.3.5 Balance of Investment and Savings
Household, government, the area department’s savings, and the total capital depreciation determine
the total investment.
2828

 p  I  SH  SG  SO   DR
i 1

i

i

i 1

i

(22)
where
Ii: demand for commodityi by other investments; DRi: consumption of fixed capital amount ofindustry I.
2.3.6 Prices of Commodity
From the zero profit condition of the industry commodity prices can be determined from thefollowing equation:28

p j X j   pi xij  (1  tp j )[ w  LD j  r  KD j ](23)Given a wage and a capital return rate, we can formally calculate the commodity prices as follows:P  ( I  A) 1[(1  tp j )( w.ld j  r  kd j )]
(24)
where
P: vector of commodity prices; A': transposed matrix of industries' input coefficients; [・]：column
vector whose elements are in parenthesesldj≡LDj/ Xj and kdj≡KDj/ Xj .
i 1

2.3.7 Derivation of Equilibrium
The equilibrium condition in the model can be summarized as follows:
Commodity Market4a11  a138   X 1  C1  CG1   I1   EX 1   EM 1  X1                                      a381  a3838   X 38  C38  CG38   I 38   EX 38   EM 38 
 X 38 (25)

Labour Market
28

LS   LD j

(26)
Capital Market
j 1

28

KS   KD j
j 1

(27)

3. Construction Data
The database used in this study is based on Input-Output (I-O) table of Makassar city 2006. I-O tabledatabase is consists of matrix of industry inputs, productions, and tax. All database in I-O tablecalculated in Indonesian Rupiah. Instead of I-O table, the model constructed to by Social Accounting
Matrix (SAM) table. Therefore, this study estimated of SAM table of Makassar city based on
I-O table Makassar City 2006, SAM table of Indonesia 2005, and some data related .
The impact of carbon tax determined by emissions intensity for each fuel, defined as the quality ofcarbon dioxide emitted when the fuel is burned divided by the value of the fuel. Emissions intensities
for each industry measure by the ratio of carbon dioxide emissions to output value. The industry’s
emission intensity can be expressed as the product of its fossil fuel intensity and an emission
coefficient, representing an average ration of carbon dioxide emissions to energy delivered for thefossil used in the activity.
4. Simulation Cases and Results
4.1 Simulation Cases
This article considers two representative CO２ restriction policies, which are carbon tax and CO２
emission permit trading market. Effects of these policies are compared with business as usual case.
Three cases are simulated in this study as follows:(1) Base case (business as usual)(2) Case one: introduces carbon tax to the industries by 0.01 MRupiah/tCO2(3) Case two: introduces carbon tax to the industries by 0.01 MRupiah/tCO2 which the revenues aretransferred to the household
4.2 Simulation Results
335.4218983 656.8585411
10Case I
Case II

0.1
0.001

0.001615633

Figure 1: Change Rates in Industrial Output
The impact of government policy to the economy can be seen through to the output of industrial. The
results demonstrate that after imposing carbon dioxide emissions and all revenue of tax’s transfer tohousehold, total outputs of industry down in each case by 0.38% and 0.74, respectively.Sector of othermanufacture (335.42 %) and forestry (101.98%) had a greatest increase among the other sectors forcase 1. The increase indicated that the sectors respond positively to the government programs. In
contrast, the manufacture of cement non-metallic mineral (19.81%); and manufacture of chemical,
paper product, printing and publishing (17.71%) were negative respond shown on the decreased in thehighest outputs changes. Similarly with case 1, the other manufacture and forestry sector respondpositively to the city’s policy with larges changes, respectively: 656.86% and 125.65%. Contrarily
decreasing changes most were the manufacture of cement non-metallic mineral (19.77%); andmanufacture of chemical, paper product, printing and publishing (17.39%).

5

Applied of government policies shown that CO2 emission productions were decreased as a whole
sectors by 8.04% (case 1) and 8.25% (case 2). Households respond negatively of policies that caused
increased total of CO2 emissions became 7.78% in case 1 and 7.94% in case 2.
335.4218983 656.8585411
10
Sector 27

Sector 25

Sector 23

Sector 21

Sector 19

Sector 17

Sector 15

Sector 13

Sector 11

Sector 9

Sector 7

Sector 5

Sector 3

0.001

Sector 1

Tot…

0.1

Case I
Case II

Figure 2: Change Rates in CO2 Emissions
Changes in price of all sectors are shown in Figure 3. Prices by sectors fall down about 0.75% incase1 and 1.20% in case 2. The difference change between case 1 and case 2 does not large.
23.9770266824.27529186

0.01

Case I
Sector 1
Sector 3
Sector 5
Sector 7
Sector 9
Sector…
Sector…
Sector…
Sector…
Sector…
Sector…
Sector…
Sector…
Sector…

1

Case II

Figure 3: Commodity Price
5. Conclusions
After applying the government policies by carbon tax, in general, that simulation had negatively
impact for the economy of Makassar city. Although, the other variable responded positively to that
programs. The total GDP of city was decrease in all simulation cases. From the government
expenditure, the households consumption down in case 1 and rise in case 2 by slightly. Following thissituation, the external sector was increased saving.
As the government revenue was increased in all cases. Household income rise shown that welfare
was increase. Cost of production sectors rises following the output prices increased. Output sectors
were down that a negative an impact to the household utility in case 1.
Applied carbon tax will impacted to the environment and should increase GDP with carbon trading
permits by the government.
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General Equilibrium Modelling.Programmming and Simulations. Palgrave Macmillan, UK.
[2] Miyata, Yuzuru.,Hirobata, Yasuhiro., Shibusawa, Hiroyuki. And Nakanishi, Hitomi., 2009.
Economy-transport-environment interactive analysis: a spatial Modeling approach, Studies inRegional Science , 39 (1). (pp), 109-130.
[3] Miyata, Yuzuru., 1995. A General Equilibrium Analysis of the Waste-Economic System - A
CGE Modeling Approach, Infrastructure Planning Review, 12, 259- 270.
[4] Miyata, Yuzuru., 1997. An Intertemporal General Equilibrium Analysis of the
Waste-EconomicSystem.,Infrastructure Planning Review, 14, 421-432.
[5] Nansai, Keisuke.,Morigichi, Yuichi. andTohno, Susumu., 2002. Embodied of Energy andEmissions Intensity Data for Japan Using Input-Output Tables, National Institute forEnvironmental Studies, Japan.
[6] Oktaviani, Rina., 2011. Economic Model of General Equilibrium.Theory and Application inIndonesia. IPB Press, Bogor.

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