Journal of Applied Input-Output Analysis, Vol. 6, 2000

The Effect of Carbon Tax and Energy Tax on the Economy of Taiwan,
1999-2020

By

Chi-Yuan Liang*

Abstract
The purpose of this paper is to evaluate and compare the effect of a carbon tax as wellas an energy tax on the price levels, output growth, and CO2 emission by each sector andfor the economy as a whole. A dynamic generalized equilibrium model of Taiwan is
employed for this evaluation. The major findings of this paper are as follows: 1) To
achieve the same policy goal of reducing CO2 emission by 25.8%, using a one-step
approach of implementing a carbon tax will result in an increase of the GDP deflator by
4.51% and a decrease in GDP by 1.01% in 1999. In contrast, the implementation of anenergy tax will lead to an increase in the GDP deflator by 4.69 % and a decrease in GDP

by 1.04 %. The carbon tax is slightly better than the energy tax owing to its smaller impact
on price level and GDP growth under the same CO2 emission reduction goal. 2) Adopting a

progressive Ad Valorem approach, with the same CO2 emission reduction goal of 25.27%,
the implementation of an energy tax will increase the GDP deflator by 2.27% and decrease
GDP by 0.88%. Conversely, implementing a carbon tax will increase the GDP deflator by
2.39% and decrease economic growth by 0.93%. 3) Since either a carbon tax or energy tax

in a progressive Ad Valorem approach can effectively reduce carbon emission and result in
more fiscal income, while minimizing its negative impact on price level and economic
growth, employing the progressive Ad Valorem approach instead of the one-step approachis recommended.

1. Introduction
In May 1998, in responding to the new developments after the Kyoto Protocol ofDecember 11, 1997, the government of Taiwan held a Nation-wide Energy Conference.
Two important recommendations emerged from this conference: (1) the target for CO2
reduction should be 24 % to 48 % lower than the BAS (business as usual) projection
by 2020; and (2) economic incentives such as carbon tax, energy tax, and emission

trading should be considered and carefully examined. The purpose of this paper is toevaluate and to compare the effect of a carbon tax as well as an energy tax on pricelevel, output growth and CO2 emission by sector and for the economy as a whole.

Received December 2000.

* Academia Sinica, 115 Nankang, Taipei, Taiwan, Republic of China. The author would like to thankProf. D.W. Jorgenson of Harvard University for his continuous support and Prof. M. Kuroda and Prof.
H. Sakuramoto of Keio University for their valuable advice and comments.

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Journal of Applied Input-Output Analysis, Vol. 6, 2000

Policy recommendation will be drawn from the findings. This paper consists of thefollowing four sections: 1. An introduction; 2. The Theoretic Model; 3. The Simulation
Methodology and Procedure; 4. Simulation Results and Conclusion.

2. Theoretic Model—Dynamic Generalized Equilibrium Model
The dynamic generalized equilibrium model consists of the following four sub -models:(1) producer's model; (2) consumer's model; (3)DGBAS\ macroeconomic model and(4) ITRI's MARKAL-MACRO engineering energy model.
2.1 Producer's Model

The producer's model divides the economy of Taiwan into twenty-nine sectors: eightmain sectors (including agriculture, mining, manufacturing, construction, public utility,transportation and service, seventeen manufacturing sectors (excluding oil refinery);and four energy sectors (including coal mining, oil refinery, natural gas and electricity).
We assume that: (1) There exists a twice differentiable aggregate production
function relating gross output (Q) to the services of capital (K), labor (I), different
types of energy (including coal (Q, oil products (0), - namely, gasoline (G), diesel (£>),
fuel oil (F), and miscellaneous oil products (/?), natural gas (N), electricity (£), fivekinds of intermediate inputs (including agricultural material (M}), industrial material(M2), transportation service intermediate inputs (A/3), service intermediate input (A/4),
import material (M5) and technology (7). (2) The production function is of constantreturn of scale. (3) Energy inputs, intermediate inputs and oil products in the
production function are homothetically weakly separable. (4) Technology (A) is anatural logarithmic function of time (7). Finally, (5) the functional form of the
production function is of translog form.

Dual to this production function, the cost function can be written as follows:»ji,j = K,L,E,M

ori-^7Tr2 ,andi,j = K,L,E,M(2)

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

81

(3)

i,j = C,O,N,E/^ Ini
'

j

(5)

where

C :

total cost,AC :average cost (=C/0,

Pi:

price of/ inputs, and,a*, aT, a,, fifJ, >^/T, /?„., are parameters of the equations.

The last two components, i.e., £#,. lnP/and (l/2)^]/?7Tr2 in equation (3) and(4) make our model differs from that of the Hudson-Jorgenson's. They are mainly
employed to reflect the time trend of structural changes in sectoral consumptions forenergy and intermediate inputs, which are caused by intrasectoral structure changes ofsectoral value of production as well as the prevailing changes of sectoral consumption
patterns, such as the substitution between oil products and coal.

Since the Hudson-Jorgenson Model is originally designed for highly developed
countries, such as the United States, West Germany and Japan, the above modification
is essential for applying the model to an economy like Taiwan's, where economic
growth is fast and industrial structure change is drastic.

Under minimum cost conditions, equation (1), (3), (4) and (5) represent aggregate
input sub-model, energy sub-model, intermediate input sub-model and oil productsub-model respectively. The aggregate input sub-model determines the quantity
demanded for capital, labor, aggregate energy and aggregate intermediate input. Theenergy sub-model determines the quantity demanded for coal, natural gas, oil products
and electricity. The intermediate input sub-model determines the quantity demanded for
agricultural material, industrial material, transportation service intermediate input,
service intermediate input, and import material. The oil products sub-model determines
the quantity demanded for gasoline, diesel, fuel, oil and miscellaneous oil products.
Since there are a lot of unknown parameters in the above equations, we estimate
the parameters through the following reduced forms to avoid the problem of
inadequacy of degree of freedom.
Aggregate Input Sub-model

82

Journal of Applied Input-Output Analysis, Vol. 6, 2000

By Shephard's lemma, a partial differentiation of equation (1) with ]nPk, lnPL, lnPE,
and \nPM yields the following share functions:

i,j = K,L,E,M(6)

We define rate of technical change (Rt) as minus growth rate of total cost (Q,given prices of input and quantity of production (0. The minus rate of technicalchange can be written as

dlnAC

„

t

„

p t _
p 1 _
f BTT In P, + BTW In PF

In order that equation (6) and (7) satisfy the properties of neoclassical production
function theory, the following restrictions are required: (a) Total cost function is alinear homogeneous function of input prices, which indicates

i=K,L,E,M

(8)

=0'

i,j=K,L,E,M

(9)

=0,

iJ=K,L,E,M(10)

ij=K,L,E,M;

(11)

i

(b) Hessian Matrix is symmetry, which indicates

fit=fiji-(12)

In addition, given the cost function, we can define the biases of technical changewith respect to price as derivatives of the value shares with respect to time.

Alternatively, we can define the biases of technical change with respect to price asderivatives of the rate of technical change with respect to the logarithms of the price offactors. Those two definitions of biases of technical change are equivalent, namely,

Pit = fin >ij=K,L,E,M.

(13)(c) Since the price functions are increasing in each of the four input prices, the value
shares are nonnegative.

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

St>0

ij=K,L,EM.

83

(14)

(d) Concavity of the translog cost function, which implies that the matrix of second

order partial derivatives (T), which is called the matrix of constant share elasticities
by Jorgenson, is negative semidefinite so that the Hessian matrix is negative
semidefinite. This completes the specification of our aggregate input sub-model.
Energy Sub-model

Similarly, by Shephard's lemma, a partial differentiation of equation (3) with respect

to lnPc , lnPo , ln/V , and lnPe , yields the following demand equations for different
types of energy in terms of their shares:

With the only exception of equation (13), the restriction conditions of theparameters in the aggregate input sub-model are also valid in the energy sub-model.
Intermediate Input Sub-model

By Shephard's lemma, a partial differentiation of equation (4) with respect to 1ilPM7,

lnPM2 , lnPM3, ln/W and lnPM5 yields the following demand equations for various kindsof intermediate inputs in terms of cost shares:

J

(16)

The restrictions of the parameters in the above equations are similar to those inenergy sub-model.

Oil Products Sub-model

Similarly, by Shephard's lemma, partial differentiation of equation (5) with respect tolnPG, lnPD , lnPF, lnPR yields the oil products sub-model as follows:

Except for equation (10) the restrictions of the parameters in the above equations
are similar to those in the energy sub-model.

Liang (1987), Jorgenson and Liang (1985) and Liang (1999) contain detailed
descriptions of this theoretical model, estimation method, data compilation and the84

Journal of Applied Input-Output Analysis, Vol. 6, 2000

results of coefficients estimated. It is noted that Liang (1999) is a revised model of
Jogenson-Liang (1985) with time series data updated from 1961-1981 to 1961-1993,
and a combined macro-economic model of the Directorate General of Budget,
Accounting & Statistics, Executive Yuan and the MARKAL Engineering Model of theIndustrial Technology Research Institute.
2.2 The Consumer's Model

Following Jorgenson and Slesnick (1983), if we assume that the k* household allocates
its expenditures in accordance with the translog indirect utility function, the aggregate
expenditure shares can be written thus:

Equation (4) implies that the expenditure shares of the household sector are

determined by commodity prices (P), expenditure structure {(^Mk\nMk)lM) and thejoint distribution of household expenditure and the attributes ((^MkAk)/M). For adetailed description of the model, please refer to Liang (1990). The consumer's model
links with the producer's model through the variable of output prices by sector.
2.3 Macro-Economic Model

The macro-economic model of the Directorate General of Budget Accounting &Statistics consists of 159 equations. We retrieve the following projection data from theMacro-Economic model: (1) GDP growth rate ,(2) wage, (3) interest rate , (4) private
consumption and (5) GDP deflator.

2.4 MARKAL Engineering Energy Model

Employing linear programming, the MARKAL model combined the following
information to achieve the best energy mix: the growth of industries, the supply ofenergy, and the energy technologies. We use the aggregate energy demand projected by
the MARKAL model to control the total energy consumption with what we got fromthe producer's and consumer's models in the base projection.

3. The Simulation Methodology and Procedure
The simulation framework of the model is presented in Figure 1, and the simulation of
the effect of carbon tax and energy tax of varying types of energy on the economy, aremade in the following steps:

Figure 1

The Simulation Framework of Dynamic Generalized Equilibrium Model(Producer Model) 29 Industries
Price Equation
Oil Sub-Model

Energy Sub-Model

Share Equation
Aggregate Sub-Model

Oil Product Sub-Model

Energy Sub-Model

Int. Input Sub-Model

Aggregate Sub-Model

Int. Input Sub-Model
Oil Product Share

;z^

^;

Industrial Sectors CO2 Em

Oil Product Price

Capital Demand

Natural Gas Share
Labor Demand

Energy Price

Capital Share
Electricity Share

Natural Gas Price

Energ) Demand

Oil Product Demandi

Output Price

Coal Demand

Electricity Pricei Natural Gas Demand!
Electricity Demand

Other Oil Prices

I Agricultural Int. Input Price [Other Oil ShareInt Input Price

Energy Share->

1 Im. Input Share[|

Industrial 1Int Input Share

[|Trans. In 1 Input Sharef|

Import In I. Input Share|| Industrial Int. Input Pricc""
Capital Price|

Trans. Int. Input Price|

Sen ice Int. Input Price"

Int Input ShareTotal Output

Wage(Consumer Model)
Illustrations

CD

Private Consumption
OutputPrice

Food Demand

Clothing Pri
Clothing Share

Housing Service Price
Housing Service Share
Energy Price] Trans, Recreation and other prices \Clothing Demand
Housing Service Demand
Energy Demand

Energy Share\ Trans , Recreation and Other Share |—□Trans. Recreation; ind
Other Demand

IT."

Exogenous
Variable
Endogenous

Variable
Derived
Projection

86

Journal of Applied Input-Output Analysis, Vol. 6, 2000

(1) Inserting the projection values of exogenous variables, namely, price of capital
service (PK), wage (PL) and price of import intermediate input into the producer's
model to obtain the base projection of the sectional output growth rates and factor
costs shares over 1997-2020. The projection value of PK, PL and PM by sector
come from (i) the PK, Pl, and PM of the economy as a whole retrieved from the
DGBAS macro-economic model, and (ii) the regression result between the PK, PL
by sector and the PK, Pl of the whole economy.

(2) The coefficient of different types of energy, taking oil coefficient (O/Q) as an
example, can be calculated by the following equation:O

Pe*E Po-0

where

P

P

SE : Energy shares in total cost,
So: Oil share in energy cost,
P: Output price,
Po: Price of oil products.

Se, So, P and Po are endogenously determined in the model.

(3) Given the growth rate of sectoral output (Q), the demand for types of energy suchas oil product (O) can be obtained by multiplying the oil coefficient (O/Q) with theoutput (Q). The projected growth rate of sectoral output during 1997-2020 isderived by (i) referring to the sectoral value added growth rate provided by thisstudy, and (ii) employing the sectoral value added share endogenously determinedfrom a simulation of this model.

(4) The amount of CO2 emission of types of energy can be calculated through theemission factor between consumption of each type of energy and its corresponding
CO2 emission. The emission factor is provided by the Industrial Technology
Research Institute (ITRI), such as: coal (3.53 tonCO2/KLOE), oil products (2.89
tonCO2/KLOE, and natural gas (2.09 tonCO2/KLOE). This step completes thewhole process for base projection.

(5) Carbon tax cases as well as energy tax cases are calculated. We treat the price oftypes of energy from endogenous to exogenous ones. We vary prices of energy,
implying implementation of carbon tax as well as energy tax, and insert these into
the model to calculate their corresponding output prices, cost shares, demand fortypes of energy and CO2 emission by sectors.
(6) The results of base projection are compared with those of the carbon tax and theenergy tax cases, allowing us to evaluate the impact of different taxation on output
price, cost structure and CO2 emission.

(7) Assuming perfect competition, we measure the impact of energy price changes(due to the changes in taxation or production cost) by the following equation:

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

8\nQ
8\nQ
8\nE
8\nPE
c
—=
—x
x
£-= SF x EFF xSi9

8lnPi

dlnE

d\nPE

8\nPi

**

i

87

(20)

i = C9O,N,E.
Equation (20) implies that the impact of 1.0 percent change in energy price on

output is the product of energy share in total cost, price elasticity of demand for energy
and / type of energy share in total energy cost.

It is noted that, according to equation (20), the imposition of either a carbon tax oran energy tax will decrease the output growth, which will in turn further reduce thedemand for energy and CO2 emission. Hence, the total impact of a carbon tax as wellas an energy tax on CO2 emission reduction should also take into account its effect on
output growth.

4. Simulation Result and Conclusion
4.1 Effect of Carbon Tax on Energy Price:
The percentage of carbon tax amount based on each energy price is shown as follows:
The carbon tax rate of Holland, Finland, Denmark and Sweden, are, respectively,

US$2.24/ton CO2, US$3.93/ton CO2, US$14.88/ton CO2 and US$22.2/ton CO2.
Among all, coal has the highest tax rate, followed by fuel oil, LPG, natural gas,premium diesel oil, gasoline and electricity.
Using as an example the highest carbon tax rate (US$22.2/ton CO2), the carbon
tax rate of coal is 57.34%, fuel oil 56.16%, LPG 29.65%, natural gas 20.86%,
premium diesel oil 17.54%, premium petroleum 11.06% and electricity 8.93%, using
Taiwan's energy prices in 1998 as a basis for comparison. The effect of imposing acarbon tax on Taiwan's energy price structure is shown in Table 1. From this Table,
we can conclude the following:(i)Because types of energy are not perfectly substitutable among (e.g. coal and fueloil cannot replace car-used gasoline and diesel) and the tax rate for each type ofenergy is different, the unit caloric prices of types of energy are different in

Taiwan. The present unit caloric energy price structure is as follows (take unit

caloric price of coal as 1) coal : premium gasoline : premium diesel : fuel oil :LPG: natural gas : electricity = 1 : 4.25 : 2.68 : 0.84 : 1.58 : 1.63 : 4.29.

(ii)

After imposing a carbon tax, each energy price relative to coal has decreased

significantly except fuel oil. Imposing the Swedish carbon tax rate, energy price8 In Q _ E ^ dQ _ E x MPE _ E x MPE x P _ E x PE _dlnE~ QX dE ~

Q

"

QxP

" QxP ~ E

88Journal of Applied Input-Output Analysis, Vol. 6, 2000

ratio (in NT$/LOE) will be changed from the ratio of coal: premium gasoline:
premium diesel: fuel oil: LPG: natural gas: electricity = 1: 4.25: 2.68: 0.84: 1.58:
1.63: 4.29 to 1: 3.0: 2.0: 0.83: 1.26: 1.25: 2.97.
This demonstrates theadvantage of natural gas, electricity and LPG as substitutes for coal and fuel oil insome sectors.

Table 1. Comparison of Different Carbon Taxes and Energy Prices in 1998
(Unit: NTS /LOE)

Coal

Gasoline

DieselFuel

LPG

NaturalElectricity

Gas

Price in 1998
Dutch Tax Rate

(US$2.44/ton CO2)

4.51

19.15

12.07

3.77

7.14

7.34

19.37

(100.0)(100.0)(100.0)(100.0)(100.0)(100.0)(100.0)

0.261

0.214

0.214

0.214

0.214

0.154

0.174

(5.786)(1.116)(1.770)(5.667)(2.992)(2.105)(0.901)Finnish Tax Rate

0.458

0.375

0.375

0.375

0.375

(US$3.93/ton CO2)

0.271

0.306

(10.15)(1.957)(3.105)(9.942)(5.249)(3.693)(1.580)Danish Tax Rate

(US$14.88/tonC02)

1.733

1.419

1.419

1.419

1.419

1.026

1.159

(38.43)(7.410)(11.76)(37.64)(19.88)(13.98)(5.983)

Swedish Tax Rate

2.586

2.117

2.117

2.117

2.117

(US$22.2/ton CO2)

1.531

1.729

(57.34)

Q1.06)(17.54)(56.16)(29.65)(20.86)(8.926)Note:

LOE stands for liter oil equivalent.

4.2 Effect of Carbon Tax on Prices by Sector
One Step Approach

The effect of imposing a carbon tax on prices by sector is shown in Table 2. Because
information is limited, tax rates in 1999 are assumed the same as for 1998. From Table
2, we can conclude the following:(i)

Imposing the highest Swedish tax rate of US$22.2/ton CO2, the water, electricity
and gas sector will have the greatest impact on price increase (24.75%) among theseven one-digital sectors, followed by the manufacturing sector (8.79%), theconstruction sector (5.26%), the mining sector (4.5%), the transportation sector(3.57%), the agriculture sector (3.24%) and the service sector (1.87%). GDP

deflator increases 4.51%, which has a relatively large effect on the economy,
compared to the 2.0% annual GDP deflator growth rate in recent years.

(ii) At the same carbon tax rate (US$22.2/ton CO2)5 the five manufacturing sector
with the highest price increases are the following: oil refinery (28.71%);
non-metallic mineral (19.52%); textiles (8.87%); basic metal (8.67%); and clothes
and wearing apparel (8.24%).

(iii) When the tax rate increases, its effect on manufacturing price increase is notproportional. For example, when the tax rate increases from US$2.24/ton CO2 to
US$22.2/ton CO2, a ten-fold increase, the price of the manufacturing sector

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

89

increases from 1.12% to 8.79%, only a 7.8-fold increase.

(iv) When the carbon tax amount increases from US$2.24/ton CO2 to US$22.2/ton
CO2, GDP deflator increases from 0.62% to 4.51%, about a 7.3-fold increase.
Table 2. Effect of Different Carbon Taxes on Price by Sector in 1999
(Unit: %)Holland Tax

Finland Tax

Denmark Tax

Sweden Tax(US$2.44/(US$3.93/(US$14.88/(US$22.2/

ton CO2)

ton CO2)

ton CO2)

ton CO2)

Agriculture

0.43790.74732.3976

3.2372Mining0.5662

0.97103.23864.5032

Coal Mining

9.567616.831264.7782

97.6145Natural Gas

1.0553

1.84466.855810.1388

Manufacturing

1.11791.91496.34558.7921Food

0.72971.24764.06385.5444Beverage & Tobacco

0.73211.25164.07705.5632

Textiles

1.09891.88976.35998.8674

Clothes & Wearing Apparel

1.03201.77195.93198.2378

Leather & Leather Products

0.48220.82762.74823.8029Wood & Bamboo Products

0.35940.61602.04492.8263

Furniture Products

0.36420.62372.06902.8590Paper & Printing

0.8972

1.54095.16267.1785Chemical & Plastic

0.79471.36704.6242

6.4651

Rubber Products

0.67111.15103.83775.3158

Oil Refinery

3.44885.9492

20.3957

28.7066

Non-Metallic Mineral

2.56754.380014.229419.5230

Basic Metal

1.36342.28446.70208.6669

Metal Products

0.7185

1.23444.14655.7726

Machinery & Equipment

0.70931.21564.05645.6279

Elect. Mach. & Electronics

0.6762

1.15903.83195.2818Transport Equipment

0.6784

1.16343.87475.3657

Miscellaneous
Water, Electricity & Gas

1.19472.00605.83867.42362.92505.051517.4785

24.7542

Electricity

3.66486.387223.368634.2209

Construction

0.66241.13743.79295.2566

Transportation & Comm.

0.44090.75912.56503.5718Services

0.33680.5623

1.54881.8656

Industry

1.17742.01996.74649.3842

GDP Deflator

0.62471.06283.36004.5053

Progressive Ad Valorem Tax Approach

Using a progressive Ad Valorem tax approach, we assume the tax rate for 2020 is thesame as for the one step approach in 1999. Each carbon tax rate is shown in Table 1.
The effect of carbon tax on prices by sector is shown in Table 3.

90Journal of Applied Input-Output Analysis, Vol. 6, 2000

Table 3. Effect of Different Carbon Taxes on Price by Sector
by 2020 -22 Year Progressive Ad Valorem Approach(Unit: %)Sweden Tax

Denmark Tax(US$14 .88/tonCO2)
2010(US$22 21 ton CO2)
2010

2020

2020

Agriculture

0.98041.05191.34031.3238Mining1.7682

3.06642.47344.2399Coal Mining

30.0036

56.578143.6060

85.1998

Natural Gas

4.777910.9773

6.971016.2314

Manufacturing2.99074.54264.17406.2605

1.57841.84082.17592.41552.4373Food
Beverage & Tobacco

1.59071.85762.1934

Textiles

2.76293.9666

3.8686

5.4676

Clothes & Wearing Apparel2.5251

3.5521

3.52664.8784

Leather & Leather Products

1.3405

1.94771.87002.6458Wood & Bamboo Products

1.00891.41351.40501.9052

Furniture Products

1.02271.43391.42411.9320Paper & Printing

2.35853.5102

3.29474.8287

Chemical & Plastic

2.15643.22043.03144.4596

Rubber Products

1.77682.52152.47353.4183

Oil Refinery

11.1159

20.5676

15.6390

28.9475

Non-Metallic Mineral

6.639010.4438

9.210514.3994

Basic Metal

3.46165.40024.6587

6.9591

Metal Products

1.93442.83522.70593.8883

Machinery & Equipment

1.85402.65522.59193.6407

Elect. Mach. & Electronics

1.70622.27342.36703.0481

Transport Equipment

1.76282.47732.45593.3605

Miscellaneous

3.12004.89534.18786.2498Water, Electricity & Gas

8.779415.6387

12.3779

22.1362

Electricity

11.5574

20.5989

16.690930.0672

Construction

1.69712.39202.36763.2654

Transportation & Comm.

0.90590.71691.26010.8673Services

0.2825-0.3032

Industry

3.20915.01334.4872Whole Economy

1.31151.73511.7798-6.94512.3916

From this table, we can conclude the following:(i)

Imposing the 22-year progressive Ad Valorem carbon tax of US$22.2/ton CO2),
the water, electricity and gas sector (22.14%) will be affected the greatest in priceincrease among the seven one digital sectors. These are followed by the
manufacturing sector (6.26%), the mining sector (4.24%), the construction sector(3.27%), the agriculture sector (1.32%) and the transportation sector (0.87%).
(ii) At the same carbon tax rate, the five manufacturing sectors with the highest priceincrease are oil refinery (28.95%), non-metallic mineral (14.40%), basic metal(6.96%), miscellaneous (6.25%) and textiles (5.47%).

(iii) When carbon tax increases, its impact on prices will not proportionally increase inEffect of Carbon Tax and Energy Tax on the Economy of Taiwan

91

the manufacturing sector. For example, when the tax rate increases 50%,
manufacturing sector price increases only 38%, i.e. from 4.54% to 6.26% by
2020.

(iv) When carbon tax rate increases 50%, the GDP deflator in 2020 will increase 38%,
i.e. from 1.74% to 2.39%.

(v)

Comparing Table 2 and 3, we found that the progressive Ad Valorem tax
approach can effectively reduce the negative effect on the price level. For instance,at the same Swedish carbon tax rate of US$22.2/ton CO2, using one step
approach will increase the GDP deflator by 4.51%, while using a 22-year

progressive approach will increase the GDP deflator by 2.39%, about half of thatobtained by using the one step approach.
4.3 Effect of Carbon Tax on Output Growth

One Step Approach

The effect of a carbon tax on output growth is shown in Table 4 (Dutch tax rate),
Table 5 (Finnish tax rate), Table 6 (Danish tax rate) and Table 7 (Swedish tax rate).
From the above tables, we conclude the following:(i)

The effect of a carbon tax on output growth is through price increases in types ofenergy. Among them, the effect of an increase in oil price is the greatest. For

example, in the case where the Swedish carbon tax of US$22.2/ton CO2 is
imposed on oil, output will decrease by 0.63%, followed by coal at (-0.21%),

electricity at (-0.12%) and natural gas at (-0.05%). The total effect of imposing acarbon tax on output growth is -1.01 percentage point.
(ii) Among seven one-digital sectors, imposing a carbon tax has the largest effect on
the output growth of water, electricity and gas sector. For example, when the

carbon tax is US$22.2/ton CO2, the output of water, electricity and gas will
decrease by 11.29%, followed by decreases in these sectors: mining (-4.20%);transportation(-2.0%);

manufacturing(-1.57%);

agriculture(-1.17%);

construction (-0.72%); and service (-0.22%).

(iii) The largest effect on output growth of imposing the same tax rate in the
manufacturing sectors would be on oil refinery (-8.77%), miscellaneous (-6.91%),
non-metallic mineral (-3.32%), basic metal (-2.21%) and chemical and plastic(-1.86%).

(iv) As the tax rate increases, the negative effect of a carbon tax on output growth will

increase proportionally. When the carbon tax rate increases from US$2.24/ton
CO2 (Dutch tax rate) to US$22.2/ton CO2 (Swedish tax rate), the reduction of
GDP growth rate will decrease from 0.103 percentage point to 1.01 percentage
point.

92

Journal of Applied Input-Output Analysis, Vol. 6, 2000

Table 4. Effect of Carbon Taxes (US$22.2/ton CO2) on Output Growthin 1999 (One Step Approach)(1)

Tax Effect

(2)

(3)

Tax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity(4)
Total EffectAgriculture

0.0000-0.1109

0.0000-0.0071-0.1180

Mining-0.1029-0.2971-0.0185-0.0209-0.4394-0.0864

Coal Mining-0.0142-0.02790.0000-0.0443

Natural Gas

0.0000-0.0616-0.1170-0.0161-0.1947

Manufacturing-0.0427-0.0831-0.0096-0.0205-0.1559

Food-0.0010-0.0225-0.0004-0.0110-0.0348

Beverage & Tobacco-0.0014-0.0506-0.0005-0.0096-0.0621-0.0720

Textiles-0.0002-0.0407-0.0002-0.0310

Clothes & Wearing Apparel-0.0009-0.02500.0000-0.0100-0.0359

Leather & Leather Products-0.0003-0.02190.0000-0.0131-0.0353

Wood & Bamboo Products

0.0000-0.0304-0.0001-0.0202-0.0507

Furniture Products

0.0000-0.0301-0.0001-0.0200-0.0502

Paper & Printing-0.0045-0.0547-0.0005-0.0430-0.1027

Chemical & Plastic-0.0102-0.1495-0.0024-0.0294-0.1914

Rubber Products-0.0003-0.04700.0000-0.0183-0.0656

Oil Refinery-0.0143-0.8590-0.0112-0.0020-0.8865

Non-Metallic Mineral-0.1210-0.1631-0.0199-0.0295-0.3335

Basic Metal-0.3831-0.2079-0.0093-0.1081-0.7085-0.0530

Metal Products-0.0055-0.0302-0.0004-0.0168

Machinery & Equipment-0.0042-0.0295-0.0003-0.0112-0.0452

Elect. Mach. & Electronics-0.0004-0.0112-0.0007-0.0092-0.0216

Transport Equipment-0.0006-0.0167-0.0008-0.0066-0.0247

Miscellaneous-0.0007-0.0631-0.0003-0.0369-0.1010-0.4035-0.6209-0.0895-0.1101-1.2241

Water, Electricity & Gas
Electricity-0.3420-0.4314-0.0488-0.0902-0.9124Construction-0.0243-0.04530.0000-0.0020-0.0716

Transportation & Comm.

-0.0003-0.19410.0000-0.0080-0.2024

Services

0.0000-0.0156-0.0001-0.0066-0.0223

Industry-0.5734-1.0464-0.1176-0.1536-1.8909

Whole Economy-0.0218-0.0641-0.0047-0.0126-0.1032

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

93

Table 5. Effect of Carbon Taxes (US$3.93/ ton CO2) on Output Growthin 1999 (One Step Approach)(Unit: %)

(1)

(2)

(3)

(4)

Tax EffectTax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity

Total EffectAgriculture

0.0000-0.19440.0000-0.0125-0.2069

Mining-0.1804-0.5181-0.0324-0.0370-0.7679

Coal Mining-0.0250-0.04890.0000-0.0777-0.1516Natural Gas

0.0000-0.1078-0.2054-0.0282-0.3414

Manufacturing-0.0750-0.1462-0.0169-0.0359-0.2739

Food-0.0017-0.0394-0.0007-0.0194-0.0611

Beverage & Tobacco-0.0025-0.0888-0.0009-0.0168-0.1090

Textiles-0.0003-0.0717-0.0003-0.0543-0.1265

Clothes & Wearing Apparel-0.0016-0.04380.0000-0.0175-0.0630

Leather & Leather Products-0.0006-0.03890.0000-0.0228-0.0623

Wood & Bamboo Products

0.0000-0.0534-0.0002-0.0355-0.0891

Furniture Products

0.0000-0.0529-0.0002-0.0351-0.0881

Paper & Printing-0.0079-0.0959-0.0008-0.0755-0.1801

Chemical & Plastic-0.0168-0.2630-0.0037-0.0518-0.3352

Rubber Products-0.0004-0.08240.0000-0.0321-0.1150

Oil Refinery-0.0251-1.5065-0.0199-0.0034-1.5549-0.5854

Non-Metallic Mineral-0.2122-0.2859-0.0358-0.0515

Basic Metal-0.6116-0.3440-0.0153-0.1785-1.1494

Metal Products-0.0096-0.0530-0.0008-0.0295-0.0929

Machinery & Equipment-0.0074-0.0517-0.0005-0.0196-0.0793

Elect. Mach. & Electronics-0.0007-0.0197-0.0013-0.0161-0.0378

Transport Equipment-0.0010-0.0293-0.0014-0.0115-0.0432

Miscellaneous-0.0090-0.7642-0.0037-0.4462-1.2231-2.1367

Water, Electricity & Gas-0.7055-1.0824-0.1565-0.1923

Electricity-0.6021-0.7524-0.0858-0.1583-1.5985

Construction-0.0426-0.07960.0000-0.0035-0.1257

Transportation & Comm.

-0.0006-0.3404

0.0000-0.0141-0.3551

Services-0.0001-0.0274-0.0003-0.0115-0.0392

Industry-0.1152-0.2070-0.0245-0.0426-0.3893

Whole Economy-0.0382-0.1125-0.0083-0.0220-0.1810

94

Journal of Applied Input-Output Analysis, Vol. 6, 2000

Table 6. Effect of Carbon Taxes (US$14.88/ton CO2) on Output Growthin 1999 (One Step Approach)(Unit %)

(1)

(2)

(3)

(4)

Tax EffectTax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity

Total EffectAgriculture

0.0000-0.73430.0000-0.0478-0.7821

Mining-0.6792-1.8970-0.1223-0.1478-2.8462

Coal Mining-0.0945-0.18520.0000-0.2944-0.5741Natural Gas

0.0000-0.4011-0.7802-0.1063-1.2875

Manufacturing-0.2838-0.5620-0.0649-0.1342-1.0450

Food-0.0064-0.1491-0.0026-0.0733-0.2313

Beverage & Tobacco-0.0095-0.3360-0.0035-0.0635-0.4126

Textiles-0.0010-0.2753-0.0010-0.2050-0.4824

Clothes & Wearing Apparel-0.0062-0.16680.0000-0.0659-0.2389

Leather & Leather Products-0.0022-0.15930.0000-0.0839-0.2454

Wood & Bamboo Products

0.0000-0.2030-0.0006-0.1347-0.3383

Furniture Products

0.0000-0.2008-0.0006-0.1333-0.3347

Paper & Printing-0.0298-0.3632-0.0030-0.2858-0.6818

Chemical & Plastic-0.0393-1.0117-0.0034-0.2021-1.2565

Rubber Products-0.0017-0.31180.0000-0.1217-0.4353

Oil Refinery-0.0952-5.6910-0.0822-0.0121-5.8805

Non-Metallic Mineral-0.8036-1.0786-0.1520-0.1884-2.2226

Basic Metal-1.1832-0.8208-0.0347-0.4230-2.4618

Metal Products-0.0364-0.2006-0.0029-0.1119-0.3518

Machinery & Equipment-0.0282-0.1966-0.0023-0.0746-0.3017

Elect. Mach. & Electronics-0.0028-0.0746-0.0049-0.0609-0.1432

Transport Equipment-0.0037-0.1106-0.0054-0.0433-0.1630

Miscellaneous-0.0341-2.8933-0.0141-1.6896-4.6311-0.7083-7.8424

Water, Electricity & Gas-2.6119-3.9446-0.5777

Electricity-2.3219-2.7552-0.3286-0.6026-6.0083

Construction-0.1624-0.3033

0.0000-0.0134-0.4791

Transportation & Comm.

-0.0022-1.28810.0000-0.0534-1.3436

Services-0.0003-0.1044-0.0010-0.0440-0.1496

Industry-0.4323-0.7795-0.0926-0.1588-1.4632

Whole Economy-0.1434-0.4248-0.0312-0.0827-0.6821

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

95

Table 1. Effect of Carbon Taxes (US$22.2/ton CO2) on Output Growthin 1999 (One Step Approach)(Unit %)

(2)

(3)

(4)

Tax EffectTax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity(1)

Total EffectAgriculture

0.0000-1.09400.0000-0.0716-1.1656

Mining-1.0098-2.7788-0.1820-0.2263-4.1970

Coal Mining-0.1411-0.27630.0000-0.4392-0.8565

Natural Gas

0.0000-0.5924-1.1663-0.1580-1.9167

Manufacturing-0.4234-0.8457-0.0977-0.1987-1.5655

Food-0.0095-0.2225-0.0038-0.1093-0.3451

Beverage & Tobacco-0.0141-0.5013-0.0053-0.0948-0.6155

Textiles-0.0015-0.4140-0.0015-0.3054-0.7224

Clothes & Wearing Apparel-0.0092-0.2495

0.0000-0.0979-0.3567

Leather & Leather Products-0.0032-0.2472

0.0000-0.1231-0.3735

Wood & Bamboo Products

0.0000-0.3033-0.0009-0.2013-0.5055

Furniture Products

0.0000-0.3001-0.0009-0.1991-0.5001

Paper & Printing-0.0445-0.5418-0.0045-0.4264-1.0171

Chemical & Plastic-0.0382-1.51810.0000-0.3056-1.8619

Rubber Products-0.0025-0.46520.0000-0.1816-0.6493

Oil Refinery-0.1420-8.4800-0.1285-0.0173-8.7677

Non-Metallic Mineral-1.1989-1.6064-0.2394-0.2761-3.3208

Basic Metal-0.9934-0.7805-0.0321-0.4008-2.2068

Metal Products-0.0543-0.2993-0.0043-0.1669-0.5248

Machinery & Equipment-0.0422-0.2940-0.0036-0.1114-0.4511

Elect. Mach. & Electronics-0.0042-0.1112-0.0073-0.0908-0.2135

Transport Equipment-0.0055-0.1646-0.0080-0.0644-0.2425

Miscellaneous-0.0509-4.3167-0.0210-2.5207-6.9093-3.7753-5.6607-0.8336-1.0215-11.2911-8.9279

Water, Electricity & Gas
Electricity-3.4969-4.0366-0.4926-0.9017

Construction-0.2432-0.45420.0000-0.0200-0.7173

Transportation & Comm.

-0.0032-1.9208

0.0000-0.0795-2.0036-0.2240

Services-0.0004-0.1562-0.0015-0.0659

Industry-0.6368-1.1530-0.1370-0.2334-2.1602

Whole Economy-0.2112-0.6306-0.0462-0.1224-1.0104

96

Journal of Applied Input-Output Analysis, Vol. 6, 2000

Progressive Ad Valorem Tax Approach

Using a progressive Ad Valorem approach, the tax rate in 2020 would be the same as
if one step approach were used in 1999. The effect of carbon tax on output growth isshown in Table 8 (carbon tax: US$14.88/ton CO2in 1999) and Table 9 (carbon tax:
US$22.2/tonCO2inl999).
Table 8. Effect of Carbon Taxes (US$14.88/ton CO2) on Output Growthin 2020 (22-year Progressive Ad Valorem Tax Approach)(Unit %)

(1)

(2)

(3)

(4)

Tax EffectTax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity

Total EffectAgriculture

0.0000-0.77310.0000-0.1024-0.8755

Mining-0.5799-1.7124-0.1035-0.1119-2.5077

Coal Mining-0.0684-0.13390.0000-0.2129-0.4152

Natural Gas

0.0000-0.7921-1.3940-0.2160-2.4021

Manufacturing-0.2283-0.4554-0.0586-0.1047-0.8471

Food-0.0088-0.0778-0.0066-0.1211-0.2144

Beverage & Tobacco-0.0125-0.2946-0.0082-0.1060-0.4213

Textiles-0.0015-0.2615-0.0015-0.3236-0.5881

Clothes & Wearing Apparel-0.0113-0.23800.0000-0.1309-0.3802

Leather & Leather Products-0.0053-0.0608-0.0002-0.2546-0.3209

Wood & Bamboo Products-0.0008-0.3906-0.0011-0.2591-0.6515

Furniture Products-0.0007-0.3786-0.0011-0.2511-0.6315

Paper & Printing-0.0270-0.2012-0.0027-0.2791-0.5101

Chemical & Plastic

0.0000-0.7500

0.0000-0.1545-0.9045

Rubber Products-0.00480.00000.0000-0.2101-0.2149

Oil Refinery-0.0770-4.6377-0.0196-0.0248-4.7592

Non-Metallic Mineral-0.6249-0.8005-0.0720-0.1724-1.6698

Basic Metal-4.4148-1.0459-0.0917-0.9509-6.5034

Metal Products-0.0427-0.1437-0.0028-0.1167-0.3059

Machinery & Equipment-0.0382-0.2663-0.0018-0.1016-0.4079

Elect. Mach. & Electronics-0.0060-0.1048-0.0009-0.1299-0.2416

Transport Equipment-0.0005-0.0085-0.0006-0.0054-0.0150

Miscellaneous
Water, Electricity & Gas

-

-

-

-

-

-4.2560

0.0000-0.6317-1.0873-5.9750

Electricity-3.41680.0000-0.3659-0.8637-4.6464

Construction-0.2590-0.39690.0000-0.0351-0.6910

Transportation & Comm.

-0.0026-1.53430.0000-0.0708-1.6077

Services-0.0004-0.1047-0.0023-0.0607-0.1681Industry-0.5087-0.4367-0.0910-0.1628-1.1993

Whole Economy-0.1687-0.3293-0.0314-0.0963-0.6258

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

97

Table 9. Effect of Carbon Taxes (US$22.2/ton CO2) on Output Growthin 2020 (22-year Progressive Ad Valorem Tax Approach)

(1)

(2)

(3)

(4)

Tax EffectTax EffectTax EffectTax Effecton Coalon Oilon Natural

on

Gas

Electricity

Total EffectAgriculture

0.0000-1.1509

0.0000-0.1532

Mining-1.3041-0.8609-2.5073-0.1538-0.1715-3.6935-0.6194

Coal Mining-0.1020-0.1998

0.0000-0.3176Natural Gas

0.0000-1.1702-2.0837-0.3211

Manufacturing-3.5749-0.3407-0.6845-0.0880-0.1552-1.2684-0.3199

Food-0.0132-0.1161-0.0099-0.1807

Beverage & Tobacco-0.0186-0.4396-0.0123-0.1581

Textiles-0.6286-0.0022-0.3952-0.0023-0.4819-0.8816

Clothes & Wearing Apparel-0.0168-0.3572

0.0000-0.1947

Leather & Leather Products-0.5687-0.0079-0.0906-0.0003-0.3791-0.4778

Wood & Bamboo Products-0.0011-0.5829-0.0017-0.3866

Furniture Products-0.9724-0.0011-0.5650-0.0016-0.3747

Paper & Printing-0.9425-0.0403-0.3002-0.0041-0.4164

Chemical & Plastic-0.76100.0000-1.1184

0.0000-0.2306-1.3490-0.3207

Rubber Products-0.00730.00000.0000-0.3134

Oil Refinery-0.1149-6.9190-0.0308-0.0364

Non-Metallic Mineral-7.1011-0.9323-1.1932-0.1160-0.2537-2.4951-8.7559

Basic Metal-5.7314-1.5394-0.1276-1.3575

Metal Products-0.0637-0.2144-0.0042-0.1741

Machinery & Equipment-0.4563-0.0570-0.3973-0.0029-0.1514-0.6085

Elect. Mach. & Electronics-0.0089-0.1561-0.0013-0.1935

Transport Equipment-0.3599-0.0006-0.0116-0.0008-0.0073-0.0203-8.7833

Miscellaneous
Water, Electricity & Gas

-

-

—

-6.2605

0.0000-0.9265

Electricity-1.5963-5.10690.0000-0.5446

Construction-1.2849-6.9364-0.3870-0.59300.0000-0.0525-1.0324

Transportation & Comm.

-0.0039-2.28900.0000Services-0.1056-2.3985-0.0006-0.1562-0.0035-0.0906-0.2508

Industry-0.7530-0.6551-0.1351

Whole Economy-0.2404-1.7836-0.2498-0.4924-0.0467-0.1428-0.9316

From these tables, we can conclude the following:(i)

The effect of a carbon tax on output growth is channeled through price increases
in four types of energy. Among them, the effect resulting from an oil priceincrease is the greatest. When the Swedish carbon tax of US$22.2/ton CO2 is
imposed on oil, the GDP growth rate will decrease by 0.49 percentage points in
2020. A coal price increase would cause a decrease in GDP growth rate of 0.25%,
while electricity and natural gas price increases would produce figure of -0.14%
and -0.05% respectively. The total effect of imposing the Swedish carbon tax of98

Journal of Applied Input-Output Analysis, Vol. 6, 2000
US$22.2/ton CO2 on GDP growth is -0.93 percentage.

(ii)

Imposing a carbon tax has the largest effect on the output growth of the water,electricity and gas sector among the seven one-digital sectors. For example, when

the Swedish carbon tax rate is US$22.2/ton CO2, the output growth of water,electricity and gas will decrease 8.78 percentage points by 2020. Tax on thefollowing

sectorstransportation

would produce these output decrease:(-2.40%);agriculture(-1.30%);mining(-3.69%);manufacturing(-1.27%);

construction (-1.03%); and service (-0.25%).
(iii) If the same carbon tax rate is imposed on the top five manufacturing sectors

would experience the following output decreases: basic metal (-8.76%); oilrefinery (-7.10%); non-metallic mineral (-2.50%); chemical and plastic (-1.35%);
and wood and bamboo products (-0.97%).

4.4 Effect of Carbon Tax on Energy Demand and CO2 Emission
One Step Approach

The effect of a carbon tax on energy demand and CO2 emission is shown in Table 10.
From this table, we can conclude the following:(i)

If a Dutch carbon tax (US$2.24/ton CO2) is imposed in the one step approach,CO2 emission decreases 3.95% in 1999. Demand for coal decreases most, at-7.67%, followed by electricity (-2.82%), oil (-2.52%) and natural gas (-0.486%).

(ii)

Imposing a carbon tax by using the one step approach has the largest effect onenergy demand and CO2 emission in the mining sector. For example, when the
Dutch carbon tax is US$2.24/ton CO2, the CO2 emission of the construction

sector decreases 6.02%, followed by mining (-5.94%), water, electricity and gas(-4.79%), manufacturing (-4.34%), transportation (-3.14%), agriculture (-3.08%)
and service (-3.02%).

(iii) If the same tax rate is imposed, the top five manufacturing sectors with the largest
effect on CO2 emission are basic metal (-15.28%), non-metallic mineral (-3.94%),
chemical and plastic (-3.50%), metal products (-3.41%) and machinery andequipment (-3.32%).
Progressive Ad Valorem Tax Approach

The effects of imposing a 22-year progressive Ad Valorem carbon tax on energy

demand and CO2 emission are shown in Tables 11 and 12. From Table 12, weconclude the following:(i)

Imposing a progressive Ad Valorem Swedish carbon tax rate of US$22.2/ton CO2
will bring about a decrease in CO2 of 25.71% by 2020. Energy demand for coaldecreases most, at a rate of -42.24%, followed by electricity (-21.34%), oilEffect of Carbon Tax and Energy Tax on the Economy of Taiwan

99(-20.13%) and natural gas (-6.56%). The tax effect on reducing CO2 emission andenergy demand is remarkable.

(ii)

Imposing a carbon tax has the largest effect on energy demand and CO2 emission
reduction in the construction sector. For example, when the Swedish carbon tax is

US$22.2/ton CO2, the CO2 emission of the construction sector decreases 35.97%
in 2020, followed by these sectors: mining (-35.67%), water, electricity and gas(-33.89%), manufacturing (-27.53%), service (-24.49%), transportation (-24.3%)

and agriculture (-23.02%).
(iii) With a 22-year progressive Ad Valorem tax approach, when the tax rate increases

from US$14.88/ton CO2 to US$22.2/ton CO2, a 50% increase, the CO2 emission
reduction rate will increase from -19.43 percentage point to -25.71 percentage
points, a 32% increase.
Table 10. Effect of Carbon Taxes (US$2.24/ton CO2) on Energy Demand and CO2
Emission in 1999
(Unit: %)

(1)

Coal

(2)

(3)

(4)

Oil

(5)

Nature Gas

Electricity

CO2Agriculture

0.000-2.9620.000-2.954-3.078Mining-8.337-3.601-0.564-1.556-5.938

Coal Mining--

Natural Gas

0.000-2.716

Manufacturing-7.712-8.066Beverage & Tobacco

Textiles

Food

-

-

-

0.078

-2.648-1.8700.465-2.779-4.335-2.628-0.322-2.831-2.952-8.064-2.626-0.320-2.829-2.940-7.729-1.9100.043-2.550-2.444-1.680

Clothes & Wearing Apparel-7.876-2.2060.000-2.718-2.703

Leather & Leather Products-8.378-0.762142.747-3.730-2.812

Wood & Bamboo Products

0.000-2.908-0.608-3.111-3.095

Furniture Products

0.000-2.912-0.613-3.115-3.098Paper & Printing-7.913-2.465-0.157-2.670-2.953Chemical & Plastic-15.407-2.178-14.261-2.015-3.504

Rubber Products-8.120-2.6970.000-2.883-2.891

Oil Refinery-5.584-0.0534.657-1.829-1.100Non-Metallic Mineral-6.389-0.9455.008-1.925-3.942

Basic Metal-18.210-9.009-8.058-9.368-15.282

Metal Products-8.076-2.639-0.333-2.842-3.439Machinery & Equipment-7.978-2.5352.787-2.771-3.317

Elect. Mach. & Electronics-8.092-2.656-0.350-2.858-2.910Transport Equipment-8.197-2.767-0.464-2.970-3.032

Miscellaneous
Water, Electricity & Gas

-

-

-

-

-

-6.486-1.3701.353-1.307-4.788

Electricity-4.938-0.606

2.928

0.132

-3.391

Construction-7.967-2.5230.000-2.726-6.024

Transportation & Comm.

-8.337-2.9150.000-3.129-3.143Services-8.245-2.818-0.516-3.020-3.019Industry-7.671-1.8660.498-2.747-6.067Whole Economy-7.672-2.5200.486-2.822-3.948

100

Journal of Applied Input-Output Analysis, Vol. 6, 2000

Table 11. Effect of Carbon Taxes (US$14.88/ton CO2) on Energy Demand and CO2
Emission by 2020(22 Year Progressive Ad Valorem Tax Approach)(Unit: %)

(1)

Coal
Agriculture
MiningCoal Mining

0.0000-34.932
-

(2)

(3)

(4)

(5)

Oil

Nature Gas

Electricity

CO2-16.5960.0000-15.674-17.061-18.487-7.994-7.333-27.164-

Natural Gas-100.000-6.853

Manufacturing-33.233-11.581Food-34.958

Beverage & Tobacco-34.948

TextilesClothes & Wearing Apparel
Leather & Leather Products
Wood & Bamboo Products

Furniture Products

-

-

-

-0.183-8.934-7.646-4.306-14.771-20.914-15.532-8.233-15.554-16.433-15.518-8.218-15.540-16.647-33.601-10.734-6.317-14.166-14.109-34.023-12.801

0.0000-14.768-15.113-35.144-15.774

28.771-15.804-16.357-15.789-8.512-15.815-16.468-15.779-8.501-15.805-16.437-27.302-27.389

Paper & Printing-33.892-14.148-6.728-14.170-15.618

Chemical & Plastic-100.000-14.560

0.0000-13.904-15.6020.00000.0000-15.012-15.420-3.769-5.416

Rubber Products

Oil Refinery-29.368-23.468

0.141

8.642

Non-Metallic Mineral-29.464-8.63327.859-11.751-20.426

Basic Metal-50.991-11.540-18.726-19.555-48.786-14.707-7.337-14.730-17.843-17.524

Metal Products-34.323

Machinery & Equipment-34.394-14.79917.013-14.956

Elect. Mach. & Electronics-34.806-15.335-8.018-15.357-16.037

Transport Equipment-45.293-28.954-22.814-28.972-29.473

Miscellaneous

Water, Electricity & Gas

-

-

-

-

-

-28.455-7.4900.342-7.721-25.039

Electricity-22.548-0.2588.399-0.801-17.690

Construction-34.331-14.7170.0000-14.739-27.698

Transportation & Comm.

-35.690-16.466

0.0000-16.679-18.128

Services-36.688-17.779-10.674-17.800-17.993

Industry-32.893-11.510-4.089-14.464-21.290

Whole Economy-32.904-15.210

4.292-15.610-19.431Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

101

Table 12. Effect of Carbon Taxes (US$22.2/ton CO2) on Energy Demand and CO2
Emission by 2020 (22 Year Progressive Ad Valorem Tax Approach)(Unit: %)

(1)

(2)

Coal

Agriculture
MiningCoal Mining

(3)

Oil

(4)

Nature Gas

Electricity

(5)
CO2

0.000

-21.975

0.000-21.389-23.018-44.639-24.348-11.523-10.690-35.67---_Natural Gas-100.000-9.679Manufacturing

0.004-11.868-42.624-15.332

Food-6.564-20.215-27.532-44.700-20.576

Beverage & Tobacco-11.887-21.260-22.271-44.688-20.559

Textiles-11.868-21.243-22.399-43.052-14.222

Clothes & Wearing Apparel-9.261-19.401-19.298-43.554-16.943

Leather & Leather Products

0.000-20.185-20.411-44.901-20.865

37.239-21.557-22.273-10.431

Wood & Bamboo Products-36.994-20.853

Furniture Products-12.194-21.539-22.3-37.084-20.840-12.180-21.526-22.257-21.185

Paper & Printing-43.397-18.705

Chemical & Plastic-9.810-19.404-100.000-19.196

Rubber Products

0.000-19.182-20.908-38.475

0.000

0.000

-20.515-21.079

Oil Refinery-30.798

0.137

Non-Metallic Mineral

16.860-6.172-29.541-38.229-11.592

36.445-16.385-27.898

Basic Metal-63.411-17.194

Metal Products-26.604-27.571-62.162-43.905-19.434-10.619-20.127-23.827-23.459

Machinery & Equipment-44.015-19.591

Elect. Mach. & Electronics

21.346-20.456-44.543-20.350

Transport Equipment-11.636-21.035-21.791-57.712-39.265-32.620-39.788-40.174

Miscellaneous
Water, Electricity & Gas
Electricity

-

—

—

-37.011-10.054-0.523-11.072-33.89-29.2480.465

11.367-1.080-28.195-35.913

Construction-43.927-19.466

0.000

Transportation & Comm.

-20.159-45.554

Services-21.7820.000-22.699-24.3-46.832

Industry-23.638-15.284-24.296-24.488-42.224

Whole Economy-15.242-6.281-19.816-28.081-42.238-20.132-6.558-21.344-25.707

102

Journal of Applied Input-Output Analysis, Vol. 6, 2000

4.5 Comparison of Carbon Tax and Energy Tax
Effect on relative energy price

After carbon and energy taxes are levied, all energy prices are lower than that of coal.
Imposing only a carbon tax will result in even lower energy prices relative to coal pricethan imposing an energy tax.

Comparison of the effect of carbon and energy taxes on the economy and CO2
emission

It is difficult to use the same tax rate to compare the effects of carbon tax and energy
tax because different types of energy have different tax rates. Therefore, the method of
trial and error is used to estimate the same reduction rate of CO2 emission for carbon
tax and energy tax respectively. Then, the corresponding negative impacts on GDP
deflator and economic growth are compared corresponding to two different kinds oftax.

Based on primary energy demand and CO2 emission, the energy tax is calculated
as NT$2.19/LOE, corresponding with the Swedish carbon tax amount, US$22.2/ton
CO2.
Assuming an ad valorem tax is imposed, by 2020, carbon tax and energy tax rates
are the same as for 1999. Taking coal as an example, the carbon tax rate and theenergy tax rate are 57.34% and 44.35%, respectively, in 1999 and 2020. The rates ofenergy tax and carbon tax are shown in Table 1 and Table 13, respectively.
Table 13. Comparison of Different Energy Taxes and Energy Prices in 1998
(Unit: NTS /LOE)

Price in 1998

Coal

Gasoline

Diesel

Fuel

LPG

4.51

19.15

12.07

3.77

7.14

NaturalGas

7.34(100.00) (100.00) (100.00) (100.00) (100.00) (100.00)
Converted From Dutch

Carbon Tax Amount1(NTS0.16/LOE)
Converted From Finnish

Carbon Tax Amount1(NTS0.28/LOE)
Converted From Danish

Carbon Tax Amount1(NTS 1.05/LOE)
Converted From Swedish

Carbon Tax Amount1(NT$1.56/LOE)

Electricity
19.37(100.00)

0.157

0.157

0.157

0.157

0.157

0.157

0.157

(3.488)(0.821)(1.303)(4.172)(2.203)(2.143)(0.812)

0.276

0.276

0.276

0.276

0.276

0.276

0.276

(6.119)(1.441)(2.286)(7.320)(3.865)(3.760)(1.425)

1.045

1.045

1.045

1.045

1.045

1.045

(23.168)(5.456)(8.657)(27.716) (14.634) (14.235)

1.045(5.394)

1.56

1.56

1.56

1.56

1.56

1.56

1.56

(34.565)(8.140)(12.915)(41.350)(21.833)(21.238)(8.048)

Note: The conversion factor from carbon tax rate to energy tax rate is based on Taiwan energy usage and CO2 emission in
1998. LOE stands for liter oil equivalent.

Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

103

Table 14. Comparison of the Impact of Carbon Tax & Energy Tax on Price, CO2
Emission and Output Growth by Sector in 1999 (One Step Approach)(Unit: %)Output-price

CO2-Reduction

OutputCarbonEnergyCarbonEnergyCarbonEnergy

Tax

Tax

Tax

Tax

Tax

Tax

US$ 22.2

NT

US$ 22.2

NT

US$ 22.2NT/ton-CO2:2.19/LOE/ton-CO2:2.19/LOE/ton-CO2:2.19/LOE

Agriculture

3.237

3.407

-1.166-1.224-21.855-22.999

Mining

4.503

4.702

-4.197-4.335-37.617-36.634

Coal Mining

97.61584.420-0.857-0.959Natural Gas

10.13913.639-1.917-2.479-12.003-11.977

Manufacturing

-

-

8.792

9.164

-1.566-1.609-27.931-27.602

Food

5.544

5.846

-0.345-0.381-21.198-22.677

Beverage & Tobacco

5.563

5.867

-0.616-0.657-20.743-21.803

Textiles

8.867

9.490

-0.722-0.812-18.265-20.132

Clothes & Wearing Apparel

8.238

8.791

-0.357-0.387-19.346-20.762

Leather & Leather Products

3.803

4.032

-0.374-0.409-20.455-22.474

Wood & Bamboo Products

2.826

3.015

-0.505-0.569-22.344-24.177

Furniture Products

2.859

3.051

-0.500-0.563-22.369-24.202

Paper & Printing

7.179

7.553

-1.017-1.142-21.371-23.023

Chemical & Plastic

6.465

6.986

-1.862-1.987-23.249-24.202

Rubber Products

5.316

5.647

-0.649-0.711-20.818-22.370

Oil Refinery

28.70729.793-8.768-9.084-10.179-10.181

Non-Metallic Mineral

19.52319.416-3.321-3.345-27.023-25.640

Basic Metal

8.667

9.059

-2.207-2.354-83.013-82.149

Metal Products

5.773

6.201

-0.525-0.572-23.567-24.559

Machinery & Equipment

5.628

6.000

-0.451-0.484-22.709-23.680

Elect. Mach. & Electronics

5.282

5.607

-0.214-0.243-21.264-23.121Transport Equipment

5.366

5.721

-0.242-0.267-21.522-22.972

Miscellaneous

7.424

7.676

-6.909-7.71424.75425.942-11.291-11.328-35.733-34.501

Water, Electricity & Gas--

Electricity

34.22138.585-8.928-8.850-23.208-18.885

Construction

5.257

5.574

-0.717-0.700-36.230-34.099

Transportation & Comm.

3.572

3.780

-2.004-2.086-21.939-22.719

Services

1.866

1.921

-0.224-0.247-22.747-24.853

Industry

9.384

9.802

-2.160-2.198-28.546-28.168

Whole Economy

4.505

4.694

-1.010-1.043-25.802-25.802

Note\ LOE stands for liter oil equivalent.

104

Journal of Applied Input-Output Analysis, Vol. 6, 2000

Table 15. Comparison of the Effect of Carbon Tax & Energy Tax on Price, CO2
Emission and Output Growth by 2020 (22 year Progressive Ad Valorem Approach)(Unit: %)Output-priceOutput

CO2-Reduction

CarbonEnergyCarbonEnergyCarbonEnergy

Tax

Tax

Tax

Tax

Tax

Tax

US$ 22.2

NT

US$ 22.2

NT

US$ 22.2NT/ton-CO2:2.19/LOE/ton-CO2:2.19/LOE/ton-CO2:2.19/LOE

Agriculture

1.324

1.245

-1.304-1.269-23.018-22.368

Mining

4.240

4.023

-3.694-3.474-35.67-31.720

Coal Mining

85.20067.320-0.619-0.635Natural Gas

16.23120.017-3.575-4.204-10.431-8.986-24.903

Manufacturing

-

-

6.261

5.942

-1.268-1.197-27.532

Food

2.416

2.294

-0.320-0.342-22.271-22.077

Beverage & Tobacco

2.437

2.315

-0.629-0.629-22.399-21.729

Textiles

5.468

5.313

-0.882-0.929-19.298-19.592

Clothes & Wearing Apparel

4.878

4.722

-0.569-0.573-20.411-20.133

Leather & Leather Products

2.646

2.538

-0.478-0.530-22.273-22.403

Wood & Bamboo Products

1.905

1.846

-0.972-1.001-22.3-22.067

Furniture Products

1.932

1.871

-0.942-0.970-22.257-22.025

Paper & Printing

4.829

4.607

-0.761-0.802-21.185-21.001

Chemical & Plastic

4.460

4.395

-1.349-1.322-20.908-20.234

Rubber Products

3.418

3.286

-0.321-0.369-21.079-21.280

Oil Refinery

28.94827.315-7.101-6.704-29.541-7.440Non-Metallic Mineral

14.39912.992-2.495-2.282-27.898-23.753-54.154

Basic Metal

6.959

6.531

-8.756-7.873-62.162

Metal Products

3.888

3.800

-0.456-0.459-23.827-22.681

Machinery & Equipment

3.641

3.533

-0.609-0.597-23.459-22.298

Elect. Mach. & Electronics

3.048

2.919

-0.360-0.380-21.791-21.699

Transport Equipment

3.360

3.244

-0.020-0.020-40.174-40.356

Miscellaneous
Water, Electricity & Gas

6.250

5.849

-6.030-6.15122.13621.173-8.783-7.902---33.89-28.894-17.285

Electricity

30.06731.083-6.936-6.162-28.195

Construction

3.265

3.130

-1.032-0.920-35.913-31.115

Transportation & Comm.

0.867

0.811

-2.398-2.288-24.3-22.992-51.696

Services-0.251-0.257-24.488

Industry

6.945

6.607

-1.784-1.651-28.081-25.289

Whole Economy

2.392

2.274

-0.932-0.883-25.707-25.707

Note: LOE stands for liter oil equivalent.

--Effect of Carbon Tax and Energy Tax on the Economy of Taiwan

105

The conclusions are as follows:(1)

The One Step Approach: To achieve the same goal of reducing CO2 emission by
25.8%, the implementation of a carbon tax will result in an increase in the GDP
deflator by 4.51% and a decrease in GDP by 1.01%. In contrast, theimplementation of an energy tax will lead to an increase in the GDP deflator by
4.69 % and a decrease in GDP by 1.04 %. Consequently, the carbon tax isslightly better than the energy tax, owing to its smaller impact on price level and
GDP growth under the same CO2 emission reduction goal (Table 14).

(2)

The progressive Ad Valorem Approach: Adopting a progressive ad valorem
approach (tax rate increases progressively year by year for 22 years), with thesame reduction goal of 25.27% in total CO2 emission, by 2020, the carbon tax on

coal, for example, is 57.34 %, while the energy tax rate is 44.35 %. Implementing
an energy tax will increase the GDP deflator by 2.274% and decrease GDP by

0.883%. Conversely, implementing a carbon tax will increase the GDP deflator by
2.392% and decrease economic growth by 0.932%. The negative effects of theenergy tax are smaller than for a carbon tax, making it better than the carbon tax

when using a progressive ad valorem approach (refer to Table 15). The result of

the progressive approach on carbon tax and energy tax differs from that of the one
step approach could be attributed to the BAU (business as usual) assumption in
our base projection.
(3)

Since either a carbon or energy tax in a progressive ad valorem approach caneffectively reduce carbon emission while minimizing its negative impact on pricelevel and economic growth, the progressive ad valorem approach is strongly
recommended.

References[1] Hudson, E.A. and Jorgenson, D. W. (1974), "U.S. Energy and Economic Growth,
1975-2000," The BellJournal ofEconomics, No. 2.

[2] Jorgenson, D.W. and Slesnick, D. T. (1983), "Individual and Social Cost-of-Living
Indexes," in D.W. Diewert and C. Montmarquette eds., Price Level Measurement,
Ottawa, Statistics Canada.
[3] Jorgenson, D.W. and Liang, C. Y. (1985), "A Study on Energy-Economic Model of

Taiwan," Project Report submitted to Energy Committee, Ministry of Economic Affairs.
[4] Liang, C. Y. (1987), "A Study on Energy-Economic Model of Taiwan," Studies ofModern Economy Series, No. 7, Institute of Economics, Academia Sinica.
[5] Liang, C. Y. (1990), "Impact of Energy Pricing Policies on Consumption Pattern andHousehold Economic Welfare in Taiwan," Discussion Paper No.9007, Institute of
Economics, Academia Sinica.
[6] Liang, C. Y. (1999), "Impact of Carbon Policy on CO2 and Economic Development of
Taiwan 1997-2010," paper Submitted to Environment Protection Administration.