Trade Liberalization in a Small Open Economy: An Application of theOverlapping Generations and Multi-sector Computable General
Equilibrium Model to Australia
Ha Viet Nguyen*
November 30, 2011
Abstract
This paper investigates the effects of trade liberalization on economic performance and welfare in Australia (as a small
open economy) by an overlapping generations and multi-sector computable general equilibrium (CGE) model. In this model,
decisions of domestic agents, including households, government and producers are both intra- and inter-temporally
consistent under the key assumptions that they are endowed with perfect foresight about future prices, all markets are
perfectly competitive and production activities are characterized by the technology of constant return to scale.
While the household sector covers several generations and the production sector consists of several industries that canchange their behaviors, the government is relatively passive in the model, just performing tax collection and spending,
supposed to be predetermined. All imports into Australia are imposed on them a product specific tariff rate while goods
leaving Australia are subject to an export duty. Trade liberalization is defined as the reduction in import duty and/or
subsidizations. All conditions in the world market, such as price of goods and services and interest rate are exogenous toAustralia.
For simplicity, we assume that there is only population growth. As a result, once the economy reaches a steady state
equilibrium, all variables measured in per capita term stay unchanged. The economy moves from a steady state equilibrium
to a new one if there is a change in exogenous variables. In this research, we focus on examining the effects of trade policy
through changes in tariff and/or subsidy rates. Our model explains dynamically how the economy adjusts and incorporates
leisure in consumers’ utility, making our structure far different from existing CGE models used in international trade.
In general, a fall in import duty has a positive while a reduction in subsidy has negative impact on the Australianeconomy, for example, welfare, output, labor employment, accumulation of capital stock and trade balance. However, theseresults are uneven across industries and household generations. Findings of the papers are consistent with mainstream trade
theories and realistic facts in Australia, implying the possibility to use the model for policy analyses and prediction.
Moreover, the model can be extended in several dimensions to analyze other issues.
Key words: Australia, computable general equilibrium model, overlapping generations, liberalization, multi-sector,
subsidy, tariff, trade policy.

__________________________Ha Viet Nguyen, PhD Candidate
School of Economics, University of New South Wales
Email: ngvietha77@yahoo.com

1

Contents
1 Introduction………………………………………………………………… 3
2 Australia and trade liberalization…………………………………………

4

2.1 Trade performance……………………………………………………........................

4

2.2 Trade liberalization…………………………………………………….......................

6

3 Model specifications………………………………………………………..

8

3.1 The household sector……………………………………………................................

10

3.2 The production sector……………………………………………………....................

14

3.3 The government sector……………………………………………………..................

20

3.4 The equilibrium…………………………………………………….............................

21

4 Data…………………………………………………………………………

22

4.1 The production sector……………………………………………………....................

23

4.2 The household sector……………………………………………………..................... 25
4.3 Parameterization……………………………………………………...........................

26

5 Computation algorithm and benchmark solution………………………..

30

5.1 Equilibrium…….……………………………………………………...........................

30

5.2 Computation algorithm for steady state equilibrium………………...........................

31

5.3 The benchmark steady state solution ………………………………...........................

33

6 Policy simulations…………………………………………………………..

40

6.1 Change in the world prices …...……………………………………...........................

40

6.2 Tariff elimination..…………………………………………………...........................

45

6.3 Subsidy reduction………………………………………………….............................

51

6.4 Sensitivity analysis …………………………………………………...........................

56

7 Conclusions…………………………………………………………………

57

A Appendix……………………………………………………………………

58

A.1 Technical appendix……….…...……………………………………...........................

58

A.2 Aggregation concordance…………………………………………...........................

65

A.3 Parameters……...………………………………………………….............................

68

A.4 Data on tax, import duty and subsidy…...…………………………...........................

70

A.5 Intuitions for results caused by tariff and subsidy changes..………………………..

76

References…..………………………………………………………………… 83

2

1 Introduction
Australia has moved very quickly towards full liberalization through ambitious engagements inbilateral, regional and global trading frameworks as well as via its unilateral actions. Consequently, it
is well integrated to the world economy and is widely recognized as an open country. Market accessfor Australian exports has been expanded substantially, chances to buy cheap imports have been
improved and flows of capital, labors and other production factors into and out of Australia have been
facilitated significantly. However, as a small open economy, Australia has become more strongly
affected by changes in and shocks from the world market that are external and exogenous to its
economy and its domestic firms have had to face more severe competitive pressures. Hence, thecommercial policy needs to clarify how the economy reacts to exogenous conditions if further
liberalization is carried out. Applied economic models including computable general equilibrium(CGE) models are widely used in policy discussion in Australia.
CGE models have been developed for half of the century. (Dixon 2006) summarizes CGE models
have been used to analyze the effects on several economic variables such as welfare, environment,
employment, price, distribution after changes in policy, public consumption, taxation, technology andprice. The evolution of CGE models has been contributed continuously by theoretical and empiricalresearches on model specifications and application. Recently, the significant development of CGE
models is through large scale computing projects. Regional and even world wide data sets arecollected in order to run such models. Starting as static and simple structure models, CGE models
were limited to explaining simultaneous facts. For this reason, the extension of CGE models to cover
dynamic or inter-temporal decisions in consumption, saving or investment and to incorporate multilevel, multi-sectoral and multi-regional issues has made CGE models become a more realistic andpowerful tool in analyzing facts and forecasting the future. Similar to other areas, CGE models used
to investigate the effects of trade liberalization have played a more substantial role in research andpractical implication, thanks to their ability of incorporating different sources of data and runninglarge scale structure as well as their flexibility in employing theoretical literature. These advantages
are especially significant in the age of globalization and regionalization. Though there is splendid
CGE model based empirical research concerned with these impacts and most of them come to theconclusion that in general opening policy has positive impact, they are mainly related to the static or
atemporal effects. The most fundamental development of the world in the last decade is through the
Global Trade Analysis Project (GTAP) which is basically also a static CGE model. In the Australian
context, a large proportion of CGE models including large-scale general equilibrium models such as
ORANI, MONASH and some econometrically estimated models do not employ a dynamic structureof overlapping generations. As a result, some important trade issues related to the dynamic structureof overlapping generations still await analysis.
In line with the current evolution of CGE models, in this paper, we develop an overlapping
generations and multi-sector CGE model for Australia as a small open economy. To our knowledge,
this is the first time an overlapping generations (OLG) and multi-sector structure has been combined
to investigate the effects of trade liberalization in Australia. Basically, the household sector ispopulated by several overlapping generations while the production sector includes several industries.
Tobin’s theory on investment (Hayashi 1982) is used to explain more exactly the investment decisionof producers. Hence, we can build up a model for Australia, largely different from recently developed
CGE models in Australia and in the world as well.
The model is used to analyze how changes in commercial policy impact our national output, sector
specific output, accumulation of the capital stock, labor use, welfare and trading activities such asimports and exports. Moreover, as the model is extended to cover several production sectors andgenerations, this could help to describe the facts in more detailed at industry and age specific level.
The paper consists of seven parts. The Introduction is followed by Part 2 which describes key
points in the commercial policy and trade performance of Australia. Part 3 presents the main structureof the CGE model used for programming and analysis. Part 4 describes how the data is collected,

3

processed and calibrated. Part 5 exhibits the computation algorithm for finding equilibriums. Part 6
shows results of policy simulations. The paper closes up with policy implications and conclusion.

2 Australia and trade liberalization
2.1 Trade performance of Australia
Trade has been widely accepted to be very essential to Australia's economy and its people. Tradecan be defined to cover any activities of exchanging consumable goods/services or production factors.
Therefore, besides traditional trade in goods and services, flows of capital and labors as well as
information (such as intellectual rights, patents...) are also integral parts of modern trade. Since ourmodel is limited to trade in goods and services only, trading of production factors, (such as foreign
direct investment or portfolio investment, labor mobility...) are not mentioned in the research.
International trading activities in Australia have continued to grow strongly for the last decade,reaching over $500 billions in recent years. Although trade deficit has dominated in most of years, thetrade imbalance is very small, about 2% of total trade volume. Trade generated jobs are estimated to
exceed 2 millions.
Table 1 Australia’s Trade Performance

Source: (DFAT 2010a)
China, Japan, United States and the Republic of Korean are the biggest trading partners ofAustralia. Australia’s largest export markets are China, Japan and India (nearly half of total export
volume) while Australia’s largest import sources are China, US and Japan (one third of total import
volume).

4

Figure 1 Major goods and services export markets and import sources
Source: (DFAT 2010a)
In the last decade, trade values have increased by around 8-9% annually. The growth rate ofexports and imports are almost the same. Except for the year 2009-2010, trade deficits occurred in all
periods but were very narrow. Terms of trade have grown at the annual rate of 6% thanks to the rise inexport prices, especially those of raw materials.
Australia’s principal exports are natural resources (coal, iron ore, gold, natural gas, crude
petroleum, aluminum...), some services (education, personal travel) and some agricultural products(beef, wheat...) and major imports are personal travel/transport services, crude petroleum, motor
vehicles, refined petroleum, gold and IT equipment. Countries in the Asia – Pacific Economic Forum(APEC) share 70% of Australia’s trade volume.

Figure 2: Export and import values of Australia
Source: (DFAT 2010a)
The share of all exportable products except primary products have reduced gradually, reflecting
the fact that Australia has become more dependent on natural resources in trading with the rest of theworld. Primary products accounted for more than half of total exports. Top major export items arecoal, iron ore and concentrates, education related travel service, gold, personal travel services, crude
petroleum, natural gas, aluminium and copper ores and concentrates.

5

Figure 3: Broad composition of exports: 2004/2005 and 2009/2010
Source: (DFAT 2010a)
In contrast, primary products have a minority share in total imports. Manufactures dominate thebasket of imports. In terms of single items, personal travel services, passenger motor vehicles, crude
petroleum, refined petroleum, freight transport services are top five imports, which are followed by
medicaments, gold, telecommunication equipment and parts, computers and good vehicles.

Figure 4: Broad composition of imports: 2004/2005 and 2009/2010
Source: (DFAT 2010a)
Although there is a fall in Australia’s share in the world trading volume over the last past decades(mostly caused by substantial expansion of some emerging economies like the Republic of Korea,
Taiwan, Singapore, Hongkong and recently China, India and Brazil...), the growth rate of exports andimports of Australia are relatively higher than those of some other developed economies.
2.2 Trade liberalization
Australia has a long history of following an open trade policy although before and after the WorldWar II, Australia was regarded as a country with high rates of protection. Restrictive policy had
carried over from the 1920s and the Great Depression years to protect domestic production fromexternal competitions. During the 1950s, the main protection instrument was import licensing,strengthened by higher tariff rates than in any other later periods. Although import licensing measure
were ended in 1962, there was no clear evidence about a fall in 1960s in average level of assistance –the indicator made of quantitative restrictions and tariff rates (Lloyd 2006). The decisive move from a6

protected to an open economy did not take place until the mid of 1970s. Under the pressure of highinflation and economic downturn, the 25% unilateral tariff decrease was implemented in 1973, thatwas followed by another essential subsequent reductions in tariffs and protection, especially thosebetween the mid 1980s and the late 1990s. Consequently, they have lowered the average rate ofprotection to less than 5% (CIE 2009). Additionally, non-tariff measures such as quotas, assistanceand barriers to some services were lifted year on year. Such changes have stated clearly the movement
towards full liberalization of Australia (Leigh 2002).
According to (DFAT 2010b), Australia is now acknowledged internationally as a relatively open
economy, with a low level of protection. Australia’s trade policy aims to open new markets, reducebarriers to trade and foster market access for Australian goods and services. The Government is also
working to improve competition, innovation and productivity within Australia. Australia is committed
to fully participate in the global economy and supports an open, transparent and rules-based global
trading system. The Government is pursuing improved market access for Australian exporters inglobal markets through multilateral, regional and bilateral frameworks. At the world level, Australia isan active member in trade negotiations in the World Trade Organization (WTO). At a regional level,
the Government actively engages with the Asia-Pacific Economic Cooperation (APEC) forum and the
Association of South East Asian Nations (ASEAN). Moreover, the Australian government also
undertakes bilateral negotiations with key trading partners through comprehensive Free Trade
Agreements (FTA) in order to promote stronger trade and commercial ties between participating
countries, and open up opportunities for Australian exporters and investors to expand their business
into key markets.
In fact, Australia supports strongly goals of the Doha Round in WTO in order to improve market
access for Australia’s exports, especially agriculture, industrial goods and services across all countriesof the world. Significant initiatives to promote trade liberalization and facilitation have been proposed
and actively implemented by Australia within WTO, APEC and some other international and regional
forums. By 2010, Australia had signed six Free Trade Agreements (FTA), respectively with New
Zealand (very early, 1983), Singapore (2003), Thailand and USA (2005), Chile (2009) and mostrecently with ASEAN (2010). Additionally, Australia is undertaking numerous FTAs negotiations
with China, Japan, Malaysia, the Republic of Korea, Indonesia, the Gulf Cooperation Council (Saudi
Arabia, Qatar, Bahrain, Oman, Kuwait, United Arab Emirates), Trans-Pacific Partnership Agreement
and Pacific Agreement on Closer Economic Relations (PACER Plus). Once these agreements comeinto effect, Australia will have easy access to most major markets in the world. At the same time, they
will also create good chances for Australian customers and producers to buy good and cheap products
from the best providers. Economic benefits, job generation and especially competitiveness,
productivity gains are projected to improve significantly after such liberalizing efforts.
Active participation in bilateral and regional liberalization is considered to be a good strategy toreinforce more efficiently multilateral trading systems and improve more quickly markets access toAustralian firms and economic benefits to Australian people. Moreover, Australia has pioneered
liberalizing the economy by a series of unilateral protection decline.
Consequently, the rate of protection has dropped significantly in the last two decades, making
Australia be one of the most competitive markets in the world. According to (WTO 2007), despite thefact that tariffs have remained the substantial instruments of Australia’s trade policy, their averagerate has fallen dramatically thanks to Australia’s unilateral reductions as well as commitments underbilateral, regional or global frameworks. The overall simple average applied Most Favored Nation(MFN) tariff rate was only 3.8% in 2006. Nearly half of all tariff lines are free and nearly 40% bear
rates of below 5%. At the same time, assistances provided to encourage domestic production, thoseare in the form of tariff concessions, tax incentives, grants or concessional loans have been also
gradually removed. Details about the structure of import duty and subsidy could be found in the
Appendix on Tax Data.

7

3 Model Specifications
In this paper, we mix the pioneering models developed by (Auerbach and Kotlikoff 1987) and(Keuschnigg and Kohler 1995) to create a distinguished model for Australia. In the former model, thatthe economy is characterized by an overlapping generations household sector helps to explain moreaccurately the behavior of the consumers throughout their life time cycle. Hence, it is very useful forinvestigating consumption side related policies, for example, income tax, superannuation andconsumption tax, etc. However, since the entire production sector is represented by a single producer,
it fails to predict what would happen to alternative industries in the economy. Some distortions may
also occur because of ignoring interactions amongst industries in the economy. In proceeding works,
modelers have modified the original model in several dimensions but most of them are in thehousehold sector.
In contrast, the latter model is represented by a multi-industry production sector. Although thehousehold sector is also populated by overlapping cohorts, that they have time invariant death rate anddo not retire makes the model not much different from models with a single household. Therefore,
despite the possibility to provide industry specific analyses, it still suffers from some distortions.
Apart from that, it fails to examine generation specific changes.
For above reasons, the combination of the two models is able to correct their limitations and takes
into account their advantages. More importantly, it can help to develop an original model for Australia
that can provide more reliable and comprehensive analyses. Accordingly, Australia is regarded as asmall open economy which trades with the rest of the world (ROW). This assumption implies that
Australia does not have power to affect the world market. Consequently, prices of imported andexported goods are exogenously given to Australia. The domestic interest rate is the same as the worldinterest rate because of free capital mobility across borders. Like many other models, all markets are
perfectly competitive, all agents are price takers. And having perfect foresight, all agents correctly
anticipate all future prices, enabling them to make decision for their entire surviving life time spanand never have to revise their expectations.
The domestic economy consists of three agents: households, producers and government. The
household sector is populated by cohorts who can live for several periods but with uncertain lifespans.
Demographic features are assumed to be stationary, implying the cohort shares or age specificproportions in total population are constant over time. The growth rate of population of all age
specific cohorts is the same and constant over time. All generations are facing age specific surviving
probability to live upon next period of time. Results from the work by (Kudrna and Woodland 2011)
are employed to characterize demographic features of the household sector in our model. Retirement
is compulsory after households reach a certain age. Households make decisions on consumption andlabor supply in order to maximize their expected life time utility.
The production industries are equipped with a constant return to scale technology to combine
intermediate inputs and endowment factors, capital and labor to produce goods and services. Capitalis produced by combining goods and services while labor is supplied by household sector. Capital isperfectly mobile across countries and industries while labor is only freely mobile across productionindustries of Australia. Each product is produced by a representative firm that aims at maximizing its
present market value. Investment decision of firms is explained by the Tobin’s theory of investment(Hayashi 1982).
The government is passive in the model, just performing tax collection, transfer payments, subsidy
payment and spending, supposed to be predetermined. The government budget is assumed to be inbalance in any period of time. Taxation occurs in the form of commodity use tax, individual income
tax, value added output tax, tariffs and export tax. All imports into Australia are imposed a productand use purpose specific import duty while all exports leaving Australia are subject to a productspecific export tax. The tax revenues are used to pay for government spending, supposed proportional
to value added output and make transfers to households or subsidies to domestic producers.

8Australia and ROW are linked through trading activities and capital mobility. Trade imbalance ismirrored by a corresponding balance in the capital account or vice versa. Commercial policy inAustralia is represented by the level of tariff rates against imports and subsidy rates for domestic
production.

=

=

+

+

+

Good market
equilibrium

+

+

+

CET
CES

CES

CES

CES

CD

CD

CD

LTF

LTF

fixed ratio

CES,

MAXIMIZATION
OF FIRM VALUES+=MAXIMIZATION OF
EXPECTED LIFE
TIME UTILITY

Capital market
equilibrium=

Figure 5 Overview of the model
Labourstructure
marketequilibrium

To understand more easily the technical explanation in this paper, following use of letters andsubscripts and superscripts to denote variables should be noted. Letters , , are used to denotecalendar time. Letters , are used to denote age of cohorts. Letters , , are used to denote
production sector or product. Additionally, letter
is used to identify household relevant
variables. Letter is used to identify firm relevant variables. Letter G is used to identify government
relevant variables. Letter K is used to identify capital relevant variables. Letters I, J, S are used to
identify investment relevant variables. Letter Q is used to identify intermediate input relevant

9variables. Letter Z is used to identify production output relevant variables. Letter Y is used to identify
value added relevant variables. Letter H is used to identify home sold output relevant variables. Letter
M is used to identify import relevant variables. Letter X is used to identify export relevant variables.
For behavioral variables, capital letters are used to denote variables characterizing aggregates(economy, industry, generation or whole population level) while lower case letters are used to denotevariables characterizing individual level behaviors (household). For price variables, capital letters areused to denote prices of products while lower case letters are used to denote prices of production
factors (interest rate, wage rate, capital shadow price…).
3.1 The household sector
Following (Keuschnigg and Kohler 1995) we model the behavior of households by a multi-level(or nested) structure. The principles from (Auerbach and Kotlikoff 1987) are used to describe
decisions of cohorts at the top level but some unrealistic assumptions in the original models are
dropped. Specifically, the modeling structure for the household sector by (Kudrna and Woodland2011) that is a further developed version of (Auerbach and Kotlikoff 1987) is simplified to be used in
our model. Accordingly, in any period, there are several coexisting generations of heterogeneous
households. All households face lifespan uncertainty. At the end of each period, some fraction of eachcohort dies 1 and there appears a newly born generation. Given the survival probabilities andassumption of stationary demographics, the age structure of the population is time invariant. However,
the assumption of different income type households in (Kudrna and Woodland 2011) is ignored. Itmeans all individuals have an identical life cycle working capacity profile in our model.
Each household starts life with zero assets and once reaching the maximum age would die without
any left assets. If a household dies before the maximum age, their remaining assets would be equallyredistributed to surviving households as an accidental bequest.
Given life-time income and price indexes, the objective of the households is to maximize their
expected life-time well-being that is the discounted future utilities from consumption and leisureaccording to a time discount factor and survival probabilities. Retirement is compulsory after
households reach a certain age2. In our model, households make decision on the number of working
hours, consumption expenditure and saving for every year in their life, given the inter-temporalbudget constraint and the intra-temporal time constraint. As a result, labor supply is endogenously
determined by the households’ decision on allocating their time for relaxing and working before thecompulsory retirement age (after retirement, entire time is used for leisure). Productivity is age variant,characterized by a hump shaped profile like (Kudrna and Woodland 2011).
3.1.1 The top level
The expected life-time utility of a household who enters the economy in year is characterized bya time separable and a nested structure:
:

1
1

1

1

,

(1)

Subject to following life time budget constraint:

1

Of which all of the oldest generation die
Recently, retirement is optional. But in order to reduce computing burden, we assume that all individuals retire after the ageof 65. This simplification does not affect much computing results because the actual proportion of working population who
are older than 65 is very small (around 1%) and so ignorable.
2

10

1

,

1

,

1

1
,

,

,

0;

0;

,

( is the compulsory retirement age, and

,

,

,

1
∀

,

is total annual time endowment)

(2)

(3)

And the asset evolution over life time is given by the law of motion:
1

,

1

1

,
,

,

,
,

,

0

,

,

(4)
(5)

Where , is the instantaneous felicity which is generated by a constant elasticity of substitution
and leisure, ,,(CES) combination of the aggregate private consumption commodity, ,. Taste parameters in the expected utility function are intertemporal elasticity of substitution, intra-temporal elasticity of substitution, the subjective rateof time preference
and leisure distribution parameter.
is the unconditional survival
probability or the chance to live upon the age of , calculated as a product of conditional survival∏,
probabilities between any two continuous ages before the age of , (
0 .
1
,

,

,

The budget constraint implies that total discounted life time consumption cannot exceed total
discounted life time income. Accordingly, asset holding of households at the beginning of any year,
is determined by their asset holding in the previous year,, the world interest rate, ,,,the composite price of the aggregate private consumption commodity,, the aggregate private, the wage rate for an effective labor unit,,
consumption, , , the flat income tax rate,
total annual time endowment, , the age specific productivity, the benefit transfer from thegovernment, , , the age pension,and the accidental bequest from left assets of dying,
households, supposed given to each individual,,. While age pension is provided only to retired) andhouseholds, being calculated based on the age of recipients (age specific pension coefficient,
the average wage rate (,, other benefit transfer payment which represents all,other forms of income, welfare or allowance assistance is equally distributed to all working
population (∀). This practice reflects the fact that the largest program in the,Australian transfer system is the income support for the aged while other programs such as Disability
Support Pension, Parenting Payment, Carer Payment, Unemployed Assistance, and some allowances
are much smaller and accessible for a wide range of ages (Harmer 2008).
Given the wage rates, interest rates, price of goods, benefit transfers from the government, age
pension and tax rates (since we assume all markets are perfectly competitive and agents have perfectforesight), all households determine the level of aggregate private consumption commodity andworking time throughout their life time when they start their economic life. The first order necessary
condition gives us following relationship amongst aggregate private consumption commodity andleisure over time:11

- Euler equation characterizing consumption evolution over time:

1

,

1

(6)

,

- Relationship between commodity consumption and leisure time allocation before the retirement
age:

,

(7)

1
,

Aggregation across households
We assume that aggregate private consumption commodity is homogeneous across individuals.
is the sum of demandHence, the total demand for the aggregate private consumption commodity,
from all cohorts:(8),

Similarly, total asset holdings held by the household sector in any period,
individual
assetsofallis the sum ofgenerations:(9),

Total bequest,∑

left at the end of period is the sum of assets from dying population,, and is equally distributed to surviving households of this period:
1

1
,

1

,

1

,

(10)

,

Where
is the proportion of the generation of age . Since it is assumed that demographic
features are stationary, we have ( is the population growth rate):(11)1
3.1.2 The second level (Intra-temporal allocation)

Total expenditure for private commodity consumption is allocated for particular types ofcomposite commodities. The total aggregate private consumption commodity,
is defined by anested CES function of industry specific composite commodities, . Accordingly, components areimperfectly substitutable, being determined by their relative price and elasticity of substitution.

12

, ,…

, ,…

(12)

,

Given the amount of aggregate private consumption commodity, consumers minimize the cost to
pay for it. In this case, we have a static optimization whose solution is the unit cost foror
as adual CES (DCES) function of unit cost of industry specific composite commodities, , :, ,…

, ,...

(13),

Via Shephard’s Lemma, the demand for each industry specific composite commodity per unit ofaggregate private consumption commodity is derived from its unit cost function:
,

(14)
,

3.1.3 The third level (home and import allocation)
At the third level, total expenditure for each industry specific composite commodity, , isallocated between home produced, , , and imported product, , through an Armington CES
structure:
, ,

,

(15)

,

Given the amount of industry specific composite commodity, each consumer minimizes the cost to
pay for it. Similarly, in this case, we have a static optimization which leads to unit cost function for, or , as a dual CES function of price of imported and home produced product, , , , :
, ,

,

(16)

,

Via Shephard’s Lemma, the demand for home produced and imported component per unit of eachindustry specific composite product is given by:
,

,

,

,

,

,

,

,

(17)

(18)

3.1.4 Aggregation in the household sector:- Total supply of labor is given in any period of time,

(19)

,

- Household sector’s total demand for home produced product:- Household sector’s total demand for imported product:

13

,

,

- Total tax payment to the government by the household sector,,,

Where , andconsumption.

,

,

,

,

,

(20)

,

are the commodity use tax and the tariff rate imposed upon final private- Total benefit transfers received from the government as the sum of benefit transfers to all
households:(21),- Total age pensions received from the government as the sum of age pension to all households(retired persons):

,

(22)

3.2 The production sector
We assume that there are N production activities in the economy. Each production sector isrepresented by a representative firm. All of them use a constant return to scale technology and operate
in a perfectly competitive environment, implying that producers are price takers. Producers haveperfect foresight about future. Each of them produces an industry typical product that can be used forintermediate input, final consumption, capital formulation or export. In order to produce output, firms
combine factors of endowment, labor and capital that are aggregated in a value added component andintermediate inputs. The intermediate inputs are aggregates of domestically produced and imported
products. The production output of each industry is transformed into domestically usable andexportable product.
Labor is provided by the household sector while capital is provided by the capital producer.
Intermediate inputs are provided by industry specific firms or imports. The production process is alsomodeled by a multi-level structure. Accordingly, given the firms’ objective to maximize their present
value, decisions of firms are disaggregated into different stages.
Like (Keuschnigg and Kohler 1994), the capital good is identical for all sectors, produced andowned by a unique provider. In any period of time, the producer of capital good meets the investment
demand of all firms. After being installed, capital good is immobile across sectors. As a result, thereallocation of capital stock in each industry is implemented through investment adjustment. Different
from production industries, capital good provider needs to use only commodities in generating capitalgood.
We suppose that capital flow is freely mobile across industries and across country borders,
resulting in a unique interest rate as the same as the world interest rate. Labor is supposed to be freely
mobile only across domestic industries, resulting in an identical wage rate within Australia.
3.2.1 Production output
On the supply side, at the top level, production output of each industry,, is characterized by
fixed input-output coefficients with respect to intermediate inputs,,, and value added output,(Leontief type production function - LTF). This modeling choice for production output is similar to amajority of CGE models which rely on practical data condition provided by Input – Output (IO) tables.

14

On the use side, a constant elasticity of transformation function (CET) is employed to separate
production output into domestically usable product,, and exportable product,, . Unlike(Keuschnigg and Kohler 1994) and (Keuschnigg and Kohler 1995) who adopted a partial equilibrium
for export3, we follow the model by (Rutherford and Tarr 2002). Accordingly, production output isregarded as a composite commodity which can be differentiated for home and international market.
The shares of domestic and foreign sales are determined by relative difference between domestic andexport price. Home and world market sold product so are not identical. In our model, Australian firms
are assumed to sell their exported products at the world prices which are given to them. This approachhelps to simplify firms’ behavior in international market without introducing specific world demandfor Australia’s exports. In fact, it is used widely, for instance in models by (Goulder and Eichengreen1992), (Cabalu and Rodriguez 2007), (Yang 2001) and (Konan and Assche 2007).
, ,

,

, ,…,

,

, ,…,

, ;

(23)

,

Given the amount of industry specific production output, each firm maximizes the received
revenue. Similarly to the case of CES functions of the household sector, in this case, we have a static
optimization which leads to unit revenue function for , or , as a dual CET function of exported
and home sold price, , , , :
, ,

,

(24)

,

Via Shephard’s Lemma, the supply of home sold and exported product per unit of each industry
specific production output is given by:
,

,

,

,

,

,

,

,

(25)

(26)

3.2.2 Value added
3.2.2.1 Value added priceFree entry/exit and perfectly competitive market assumption implies zero profit condition for all
producers. In other words, for any production output, total revenue equals total cost. As a result, theprice of value added product, , is given by:
,

∑

,

,

Where

,

is the price or revenue unit cost of production output and

(27)

,

is the price or unit costof composite intermediate inputs produced by the th industry and used by the th industry.
and,respectively are fixed intermediate input-output and valued added-output coefficients in Leontief typeproduction output function.
3.2.2.2 Value added output

3

Keuschnigg’s and Kohler’s models propose that exported and home sold good are identical and there is a given world
demand for exported good

15

The Leontief type production function makes firm’s problems reduce to value added productproducing level. Value added product is generated by combining labor and capital in accordance witha CES function, allowing the substitution possibility between employment of labor, , and capital,
, :
, ,

,

(28)

,

The Tobin’s Q theory on investment (Hayashi 1982) is adopted to solve the dynamic decision
which isproblem of firms. The purpose of firms is to maximize their present market value,
defined as the value of all future cash flows,, discounted at the world interest rate subject to theadjustment cost and capital accumulation conditions.
Since the production function takes the Leontief type, the cash flows of firms are solely
determined by decision on value added output ( , is the value added output tax):
,

1

1

,

,

,

,

,

,

2

(29)
,

As a result, firms’ problem reduces to determine just capital stock, labor and investment in eachperiod of time:
∞
,

:

∏

(30)

1

Subject to the capital depreciation constraint or following law of motion:
1

1

,

,

,

(31)

And capital adjustment condition which takes the quadratic function form of the investment tocapital stock ratio:
,

,

,

2

(32)
,

Where , is the aggregate capital good, , is net investment, is investment adjustment costcoefficient. It implies that in order to install an additional capital stock of , , the firms have toconsume totally , units of aggregate capital good.
The key difference between our model and that of (Keuschnigg and Kohler 1994) is the evolutionof capital stock over time. Although the Tobin’s Q theory on investment (Hayashi 1982) is employed,
too, our model assumes that investment demand can be financed by different sources, rather than rely
only on firms’ retained earnings.
Firms’ decision on employed labor and capital depends on price signals. Firms recruit additionallylabor until the marginal rate of return to labor equals the market wage rate:
1

,

,

,

,

16

(33)

Similarly, capital stock and investment are selected to equalize the marginal rate of capital returnwith shadow price of capital:
1

,

,

,
,

,

2

1

1

0

(34)

,
,

1

(35)

,

Where

is the shadow price of capital andis the price of aggregate capital good.

The Tobin’s Q theorem in (Hayashi 1982) links the firm value to the shadow price of capital andthe existing capital stock:
,

(36)

,

In the steady state, we expect that the shadow price of capital is unchanged. So the firm value
grows at the same rate of capital stock. As a result, we have the total value of production firms in theeconomy,as the sum of all individual ones:

,

(37)

:

And so is total capital stock in the economy,

,

(38)

And so is total labor demand in the economy:

,

(39)

3.2.3 Investment
Since we assume that aggregate capital good is homogeneous across industries, the economy wide
demand for investment is the sum of demand from single industries. Once we know the investment
demand in each industry, , , we can calculate the required aggregate capital good, , through thecapital adjustment condition. Then, the total demand for aggregate capital good is the sum of industry
specific ones:

,

(40)

We assume that the capital good in our economy is produced by the capitalist, by combining realcommodities with a CES technology. The capital good is supposed to be identical across industries.
The role of the capitalist is like an intermediate banker linking the household sector and foreign
market with final good producers. Accordingly, the saving of consumers and net foreign asset in any
period are mobilized by this capitalist and then used to buy inputs to produce capital good to meet theinvestment demand of final good producers. The producer of capital good aims at maximizing profit
17

by determining the quantity of inputs used for producing the capital good. Free entry and exit andperfectly competitive market assumptions imply zero profit condition for producing the capital good.
3.2.3.1 The top level
At the top level, total aggregate capital good,is featured by a CES function to be
disaggregated into different industry specific composite commodities, , :
, ,…,

, ,…

(41)

,

Given the amount of aggregate capital good, profit maximization goal is obtained by minimizing,
the cost. In this case, we have a static optimization whose solution is the unit cost function for
denoted by
as a dual CES function of unit cost of industry specific composite commodities:, ,...

, ,…

,

(42)

Via Shephard’s Lemma, the demand for each industry specific composite commodity per unit ofaggregate capital good is derived from its unit cost function:(43),

3.2.3.2 The second level
At the second level, total expenditure for each industry specific composite commodity is allocatedbetween home produced and imported product, , , , through an Armington CES structure:
, ,

,

(44)

,

Given the amount of industry specific composite commodity, the capitalist minimizes the cost to
pay for it. Similarly, in this case, we have a static optimization which leads to unit cost function for, , , is a dual CES function of imported and home produced product:
, ,

,

,

(45)

Via Shephard’s Lemma, the demand for home produced and imported product per unit of eachindustry specific composite commodity is given by:
,

,

,

,

,

,

,

,

(46)

(47)

3.2.4 Intermediate input
Every intermediate input is a composite aggregate of home sold and imported product. Once wehave value added output, , , we can easily calculate the quantity of each intermediate input item,
, :

18

,

,

,

(48)

Armington assumption also is used to identify how firms allocate between home produced andimported component, depending on their relative price. The problem for each firm is to minimize thecost for required quantity of the composite intermediate input.
, ,

,

(49)

,

Given the amount of industry specific composite input, firms minimize the cost to pay for it.
Similarly, in this case, we have a static optimization which leads to unit cost function for, or,
as a dual CES function of price of imported and home produced product, , , , :
, ,

,

(50)

,

Via Shephard’s Lemma, the demand for home produced and imported product per unit of eachindustry specific composite input is given by:
,
,

,

(51)

,

(52)

,

,
,

,

3.2.5 Aggregation across production sectors- Total demand of production sector for home produced product: ∑- Total demand of production sector for imported product: ∑

,
,

,

,

:

- Total tax payment to the government contributed by production sector,

,

,

,

,

,

,

,

,

,

,

,

(53)
,

Where
, and
input consumption;
good formation; andcommodities.

,

,

,

,

,

,

1

,
,

,
,

are the commodity use tax and the tariff rate levied against intermediate, and, are the commodity use tax and the tariff rate imposed upon capital, and, are export tax rate and subsidy rate imposed upon exported,

3.3. The government sector
3.3.1 The top level

19

The government is relatively passive in the model. In order to finance its spending, benefit
transfers, age pension to retired individuals and subsidy payments to domestic production andconsumption, the government collects taxes from economic agents. To make data sets on tax, duty
and subsidy from IO tables usable, we assume that import duties are imposed on all imports whilecommodity use taxes,
are levied against any consumption regardless of home produced orimported origins. Subsidy is modeled in the form of support for the consumption of domestically
produced products. As a result, regardless of use purposes, such as intermediate inputs or final
consumptions (private consumption, capital formation or export), consuming home produced products
occurs at a lower price which is paid by the subsidy.
We suppose that government spending value,is exogenously determined, depending on theeconomy size. Therefore, we take into account the assumption that government expenditure is
proportional to total gross domestic product ( ). We also suppose that all tax and subsidy rates arealso exogenously determined.

,

(54)

,

Benefit transfer from the government to the household sector,
is endogenously determined,
enabling the government budget to be in balance in any period of time. This assumption is reasonable
in the case of Australia because the federal budget exhibits very tiny deficit in most of the last decades
and sometimes runs a surplus. At the same time, government debt is targeted to be eliminated incoming years (CA 2006).
(55)
Where:
is total age pension payment to retired households andto promote consumption of home produced products.

,

,

,

,

,

,

,

,

is total subsidy payment

,

,

1

,
,

,

(56)
,

Where: Where , ,, are the subsidy rate applied for final private consumption,, andintermediate input use and capital formation, respectively.
, is subsidy rate for exported
commodities.
Like the private consumption, the government consumption is featured by a multi-level structure.
A nested CES function is employed to model the demand of the government.
3.3.2 The second levelis featured by a CES function to
At the second level, the aggregate government consumption,
disaggregate into different industry specific composite commodities, , :
, ,…,

, ,…

,

(57)

Given the amount of aggregate consumption commodity, profit maximization goal is obtained byminimizing the cost. In this case, we have a static optimization whose solution is the unit cost foror
as a dual CES function of unit cost of industry specific composite commodities, , :, ,...

20

, ,…

,

(58)

Via Shephard’s Lemma, the demand for each industry specific composite commodity per unit ofaggregate government good is derived from its unit cost function:(59),

3.3.3 The third level
At the third level, total expenditure for each industry specific composite commodity is allocatedbetween home produced and imported product, , , , through an Armington CES structure:
, ,

,

(60)

,

Given the amount of industry specific composite commodity, the government minimizes the costto pay for it. Similarly, in this case, we have a static optimization which leads to unit cost function for, or , as a dual CES function of imported and home produced product:
, ,

,

(61)

,

Via Shephard’s Lemma, the demand for home produced and imported product per unit of eachindustry specific composite commodity is given by:
,

,

,

,

,

,

,

,

(62)

(63)

3.4 The equilibrium
3.4.1 Transactions with ROW
The Australian market and world market are linked through flows of goods and capital. Tradesurplus or deficit is mirrored by current account deficit or surplus, respectively. Capital is freely
mobile across countries, resulting in a common interest rate between Australia and the world.
Total export value of Australia to ROW:

,

(64)

,

Total import value of Australia from ROW:

,

,

,

,

,

,

,

,

(65)

Because of data limitation, we just model capital flow between Australia and ROW as the result oftrade account imbalance. Accordingly, trade deficit or surplus is mirrored by net positive or negative
foreign capital inflow respectively.

21

(66)
The accumulated net foreign capital inflow is total net foreign debt, assumed to be constrained bya transversality condition to avoid debt explosion possibility.
1

= 1
lim
→

∏

(67)

+
0

1

(68)

Walras’s law is effective, resulting in the equilibrium of all markets: good market, labor market,
capital market. In other words, in any period, there exists equilibrium in all markets (all markets arebalanced):
3.4.2 Commodity market

,

,

,

,

,

(69)

3.4.3 Labor market
Labor is assumed to be homogeneous, mobile across industries but immobile internationally.
Hence, total labor supply is determined by decisions of domestic individuals in the model:

,

(70)

3.4.4 Asset markets
In any period of time, the total assets holding of the household sector are used to finance world
debt and firm values:(71)

4 DataTo complete modeling the economy, we need values of exogenous parameters characterizing the
behavior of economic agents. It is necessary to have several sources of data for this purpose. Some ofthem can be drawn from related literature (especially parameters in the utility function), some arecalibrated to suit the practical conditions (especially parameters in production and intra-generation
allocation). The year 2005-2006 is set as the target for the benchmark steady state equilibrium.
4.1 The production sector
The most important data are Input – Output (IO) tables. According to (ABS 2000), IO tables arepart of the Australian national accounts, complementing the quarterly and annual series of national
income, expenditure and product aggregates. They provide detailed information about the supply anduse of products in the Australian economy and about the structure of inter-relationships between
Australian industries including input by industry and output by product group; use of domestic
production and imports by industry and final demand categories, and taxes, subsidies and margins on
22

supply by product. The Australian Bureau of Statistics (ABS) has completed 22 sets of IO tables forAustralia of which the most recent release is for the financial year 2006-2007.
In our model, the financial year 2005-2006 is considered to be the baseline for our artificial
economy. Therefore, the IO tables for Australia (2005-2006) are used to calibrate relevant parameters,
mostly for the production sector. 2005 – 2006 Australian IO tables are available on the website of theAustralian Bureau of Statistics (ABS). The 2005-06 IO tables are the last ones to be produced on a1993 Australian and New Zealand Industry Classification (ANZSIC93) and 1993 System of National
Accounts (SNA93) basis. The structure of the tables, with 109 product and industry groups, and theunderlying methodology used in their construction has been kept consistent with the release of 20012002 IO tables. There are 39 tables in the 2005-2006 release which contain information about theflows of output, tax, subsidies, margins,… amongst industries and categories of demands. In addition
to intermediate inputs, the original tables include final demand components: households consumption,
government consumption and gross fixed capital formation (as the sum of gross fixed capitalformation of private, public enterprises and general government), and changes in inventories andexport. Moreover, compensation of employees, gross operating surplus and mixed income or data on
income side are also available. All values are measured at producers’ or basic prices in millions ofAustralian dollars. The basic price is the amount receivable by the producer from the purchaser for aunit of a good or service, minus any tax payable (including deductible value added taxes), and plus
any subsidy receivable, as a consequence of production or sale of the unit (ABS 2000).
Industry uses
Industries

1

2

...

108

109

Final uses
Total industry
Use

Household

Government

Capitalformation

Inventories

Total final
uses

TOTAL
SUPPLY

1
2...
109
Total intermediate use
Compensation of employees
Gross operating surplus andmixed income
Net taxes on products
Net taxes on production
Competing Imports
Gross Value Added
TOTAL USE

Figure 6 The structure of the Input-Output Tables
Source: (ABS 2010a)
To match this very detailed source of data with our model’s dimension, we aggregate components
in the full IO tables to form a condensed IO table of 19 industries/products. This concordance work isexactly as the same as the one in (Keuschnigg and Kohler 1994). As a result, the following groups ofindustries are represented in our model: (i) Agriculture and Forestry; (ii) Mining and Quarry; (iii)
Food stuff; (iv) Textile and Clothing; (v) Wood and Wood processing; (vi) Paper and Paper
processing; (vii) Petroleum; (viii) Chemical excluding petroleum; (ix) Non-ferrous minerals; (x) Basic
metals; (xi) Metal processing; (xii) Energy and Water supply; (xiii) Construction; (xiv) Commerce;(xv) Hotels and Restaurant; (xvi) Transport and Communication; (xvii) Banking, Insurance and Realestate; (xviii) Public service; and (xix) Other services. The components in the first 17 groups can beeasily guessed while those in the 18th one are government administration; defense; education; healthservices and community services and those in the last group consist of motion picture, radio andtelevision services; libraries, museums and the arts; sport, gambling and recreational services;personal services and all others. The sub-industries in each sector can be found in the Appendix on
Concordance.

23

Since we do not explicitly explain how decisions on inventories are made, we distribute this final
spending item to other categories of final demand as (Keuschnigg and Kohler 1994) did. Nevertheless,inventories are also redistributed to gross fixed capital formation, besides household and government
spending and export. The redistribution shares are proportional to the original values of final demand
categories.
Separate information on use and supply of domestic production outputs and imports can be foundin Table 5 and Table 3 respectively. The composite use and supply consisting both domestic andimported components can be easily generated by adding Table 3 and Table 5 together.
In Table 5, final consumption data on water transport, air and space transport are not available.
However, we can calculate the total final uses for these two forms of transport by subtracting totalindustry uses from total Australian transport production. Then, weighted average from other forms oftransport services are used to allocate total final uses into each final consumption components. In
Table 3, final consumption data on water transport, air and space transport are also not available andwe omit them because of very small import volume in this industry. Moreover, in our condensed IO
table for imports, there appears a negative import value in the transport use by textile and clothing
industry. To correct this nonsense value of import, we transfer it to its domestic counterpart andtransport import volume used by transport industry. This way helps us to keep total use and total
supply of transport and textile and clothing industry equal respectively without affecting much thestructure of the original tables.
This aggregation and reallocation process gives us adjusted tables for use and supply of domestic
production outputs and imports. The sum of these two tables generates the composite Input – Output
Table which consists of both domestic and imported components in any categories of use and supply.
Information on product related taxes and subsidies can be obtained from Table 34, 35, 36, 37 and
38 of which Table 34 provides the net of all product related taxes and subsidies while Table 36
contains import duty and Table 38 is about subsidy. Hence, we can subtract figures in Table 36 andTable 38 from figures in Table 34 to calculate all other product related taxes except import duty, orcommodity use tax as we denote in our paper (). Actually, such type of tax may cover several subcomponents, ranging from GST, sales tax to excise tax and other fees… Based on that, we can), commodity use tax rate () and subsidy rate () for different types ofcalculate tariff rate (product in different use purposes by dividing tax revenue against their total sales values at basic prices.
Actually, the commodity tax rate, subsidy rate or duty against the intermediate use of a product are
different from industry to industry. For exports, commodity use tax is interpreted as export tax ( , )that producers have to pay to the Australian government before selling their products in foreign
markets.
Apart from product related taxes, Input – Output Tables contain information on other production
tax, which is regarded as tax against value added output production in our model. The other taxes on
production are understood as the money enterprises incur as a result of their engagement in theprocesses of production besides product related taxes. They may consist of taxes payable on the land,
fixed assets or labor employed in the production process or on certain activities or transactions. The
actual structure for this type of tax is very complicated, that may incur during the production process.
Some major items could be listed here such as taxes on payroll or workforce, recurrent taxes on land,buildings or other structures, business and professional licences, taxes on the use of fixed assets,stamp taxes, taxes on pollution and taxes on international transactions (Soriano and Thompson 2006).
For simplicity, we assume that it is proportional to value added output. Therefore, the otherproduction tax rate ( , ) for each industry can be easily derived by dividing the tax revenue by its
corresponding value added output.
The detailed description on tax data can be found in the Appendix on Tax Data.
Regarding the sources of value added output, IO Tables contain separate rows providing
information on compensation of employees, gross operating surplus and mixed income. The former
represents value of all entitlements earned by employees, covering wages and salaries and employers’
24social contributions. Contributions to pension and superannuation funds hence are also parts ofcompensation of employees. Since our model does not distinguish different sources of labor income,the figures on compensation of employees in IO Tables can be used straight away to reveal how muchtotally the representative producer in each industry has to pay for the workers and exhibit total wage
income received by the household sector. Contribution to pension or superannuation funds can be
regarded as a part of labor income that the households do not spend and put in their saving. The latterpart of value added output is defined as the surplus accruing from processes of production before
deducting interest charges, land rent or other property incomes payable on the financial assets, land orother tangible non-produced assets required to carry on the production. Therefore, this item can becalculated as gross value added minus compensation of employees, minus taxes on production and it
is interpreted as the part of value added output generated by capital employment in our model. Like
the case of labor employment, because our model does not differentiate types of capital, the figures ongross operating surplus and mixed income are used directly to specify the capital cost firms have to
pay in producing valued added output (ABS 2000).
Completing above works, we can achieve a set of data characterizing a steady state equilibrium forour economy, especially the production sector in 2005-2006, such as price indexes (price of goods,
services and factors), policy parameters (tax rates), input and output levels, value added, tradevolumes, loans to the world...
4.2 The household sector
For the household side, we assume that consumption preference is identical across generations. It
means that all generations have the same expenditure proportion of a particular type of good given
their different total expenditure. Therefore, what we focus on is to explain how the consumers allocate
their income over time. Information from IO table is used to determine how cohorts allocate intratemporally their income for different types of goods and services. Specifically, we can easily calculate
the share of each type of goods and services in final household consumption from IO tables and thenuse these shares for all generations.
Demographic features are taken from (Kudrna and Woodland 2011). Accordingly, it is assumed
that an individual starts their economic life at the age of zero (corresponding to the biological age of
15 – the first age in the labor force) and possibly live till the age of 76 (corresponding to the
biological age of 90 – the age at which the number of older persons might be ignorable). The authors
use the life tables for men from ABS to calculate conditional survival probabilities ( ) while theannual population growth rate ( is constant, equal 0.0145, taken from (Kulish, Smith et al. 2006),
which is the average annual growth rate in Australia over the last 10 years. In general, the older aperson is, the more likely he/she dies. The age specific productivity ( ) is calculated based on workby (Reilly, Milne et al. 2005). In our model, these productivities are scaled such that age specificproductivity of zero aged household is normalized to unitary. The age profile of working capacity is
hump-shaped, reaching the peak at the age of 32 (corresponding to the biological age of 47). The
retirement age ( ) is set at the age of 52 (corresponding to the biological age of 66), reflecting the factthat the number of working people who are 65 years old or older is very small and thus, ignorable(ABS 2010b).
The age specific pension coefficient ( ) is assumed to be identical across all retired individuals.
In (Kudrna and Woodland 2011), the estimates on age specific pension that are based on Household
Income, Labor Data Analysis (HILDA) display clearly that there is a small gap amongst retired
generations in terms of their pension. This result is caused by the fact that policy on age pension is not
age dependent. In fact, it is calculated based on average wage rate of male employees. In our model,
value of these coefficients is adjusted in order to match with the realistic age pension payment in thebenchmark year. While total taxation revenue at all government levels (including Commonwealth,State and local governments) is $298.156 billions (ABS 2010c), total spending value is $173.345
billions and total subsidy payment is $9.734 billions (ABS 2009). Hence, total transfer payment(including age pension payment (AP) and other benefit transfer (TR)) is $115.077 billions. Because
age pension payment is $20.6 billions (ABS 2010d), other benefit transfer is $94.519 billions.

25

Additionally, figures from relevant surveys such as labor and consumption expenditure surveys
conducted by ABS are used to check whether computing results of our model are practicallyreasonable.
4.3 Parameterization
Besides the raw database from national accounts, IO tables, labor and household expenditure
survey data, it is needed to have value of three types of elasticities and parameters in behaviorial
functions:(i) Elasticities of substitution between commodities or factors in CES functions and elasticities oftransformation between export and domestic sales; and share parameters in these functions;(ii) Household preferences;(iii) Investment and capital stock related parameters.
While there are external sources for the value of some of the elasticties and parameters (such aselasticity of substitution or transformation), the other ones such as preference or share parameters canbe calibrated by using dataset in the benchmark year and external sources of some elasticities andparameters.
4.3.1 External sources of parameters
First and foremost, some parameters are taken from external researches. Elasticities of substitution
between commodities or factors in CES functions are also drawn from external sources of information.
At the top levels, the aggregate for final demands (private, government or capital formation
aggregate commodity) is modeled as a CES function of industry specific products. Calibrating sharecoefficients in these functions, we need to know value of the elasticity of substitution amongst
industry specific products. In fact, due to the large differences across CGE models in defining suchaggregate final demands, there are few researches and sources of information about this type ofelasticity. At the same time, their values are much different from each other. For this reason, we
follow (Keuschnigg and Kohler 1994) in adopting a Cobb-Douglas function for these final aggregate
demand. In other words, the elasticity value equals unitary. This simplification helps us to get sharecoefficients simply as the proportion of spending on each industry specific product in total
expenditure.
Table 2 Elasticity in aggregate goods
Aggregate capital good (ρK)

Aggregate private good (ρC)

Aggregate government good (ρG)

1

1

1

Source: (Keuschnigg and Kohler 1994)
At lower levels in our nested structure, an industry specific commodity is defined as a CES
composite of domestic and imported components which are characterized by Armington elasticity.
Actually, there are a wide range of choices for this type of elasticity. In (Keuschnigg and Kohler
1994), econometric works for European communities are bases for identifying Armington elasticity intheir model. In fact, most of estimates on Armington elasticity are country specific because thedatabases for estimates are taken from particular countries (a large proportion of them are for the U.S.
economy). For this reason, using elasticity for other countries may lead to a reduction in accuracy
level of the model.
Recently, GTAP becomes an important source of elasticities because it provides a comprehensive
set of elasticities for several countries all over the world and these elasticities are tested in several
researches. According to (Dimaranan 2006), sources of elasticities in GTAP are taken from the
SALTER model and some recent econometric works such as the one by Hertel (2004). In Australia,
CGE models have been used for a long time. Some famous models have been applied not only inAustralia but also in some foreign countries such as ORANI, MONASH… Elasticities of substitution
are independently estimated in these models and are Australia specific.
26

In our model, GTAP6 and MONASH model databases are taken into account to specify
Armington elasticity of substitution between domestic and imported good. Like the case of IO table,
the original database contains product specific parameters. Therefore, we need to aggregate them tomatch with our model dimension by taking the weighted average of components. While MONASH
model provides with Armington elasticities for different commodities and different uses, elasticities in
GTAP6 are identical across categories of demand. Therefore, for commodities MONASH model has
available data, we use elasticities from MONASH model. For commodities whose Armington
elasticities are zero or not available in MONASH model, we replace them by those from GTAP6.
Table 3 Elasticity

Intermediate

CapitalGovernment

Households

Elasticity oftransformation
between export
and home sales

ρQj

ρKj

ρGj

ρCj

ρZj

Elasticity of
substitution
betweenendowment
factorsρYj

Armington elasticity of substitution between domestic
and imported products

No.

Industries

1

AgrFor

1.577

1.28

1.667

2.14330.56

0.2333

2

MinQuarr

4.635

4.415

6.933

11.75

1.26

0.73

3

Food

1.23

1.3

1.327

1.45

0.56

1.0222

4

Texcloth

2.52

1.84

2.497

3.13

1.26

1.005

5

Wood

1.92

1.67

1.753

1.67

1.26

1.26

6

Paper

1.68

2

2.26

3.1

1.26

1.26

7

Petrol

0.4

0.4

0.4

0.4

1.26

1.26

8

Chemic1.8

1.5

2.2333

3.4

1.26

1.26

9

Nonferr

0.84

0.68

0.9933

1.46

1.26

1.26

10

Metals

1.25

1.74

2.23

3.7

1.26

1.26

11

MetProc

1.777

1.99672.6233

4.0967

1.26

1.26

12

Energy

2.95

2.95

2.95

2.95

1.26

1.26

13

Constr

2.1

2.1

2.1

2.1

1.4

1.68

14

Trade

3.3

3.3

3.3

3.3

1.26

1.68

15

HotRest

4.2

4.2

4.2

4.2

1.26

1.26

16

Transp0.667

0.66670.88891.3333

1.68

1.575

17

RealEst3.84173.84173.84173.8417

1.26

1.26

18

Public

2.8

2.8

2.8

2.8

1.26

1.26

19

OthServ

1.9

1.9

1.9

1.9

1.26

1.26

Source: MONASH and GTAP6 and (DeMelo and Tarr 1992)
Besides Armington elasticities, another type of substitution elasticity is used in value addedfunctions in our model. In GTAP model, value added is generated by three endowment factors,
namely capital, labor and land. The substitution possibility amongst them is characterized by aconstant elasticity of substitution. Although value added in our model is created by only two factors,
capital and labor, elasticity from GTAP model is still usable. We draw values from GTAP model
because it covers all industries in our model.
Secondly, for export and domestic sales allocation, there is a limited number of choices. One of themain reasons is the fact that a large part of CGE models adopt other approach in allocating export anddomestic sales. The most common method is to consider exported and domestically sold goods are
identical. Therefore, for small open economies, export volume depends on the world demand for theirexport. Parameters of the world demand for export, i.e. price elasticity of the world demand areneeded for this type of model. (Keuschnigg and Kohler 1994) and MONASH model also follow thisapproach in modeling export. Some other works such as (Warr and Lapiz 1994) just estimated27

elasticity of transformation between export and home sales for some particular industries andcountries. In our model, the elasticity of transformation is drawn from (DeMelo and Tarr 1992)
because to our knowledge, only this research provides elasticity value for several industries. Although
the number of industries in (DeMelo and Tarr 1992) are less than that of our model, we still can makecalculation for all industries in our model because most of industries in (DeMelo and Tarr 1992) havethe same elasticity of transformation.
4.3.2 Calibration
Once we have enough sources of data and sets of elasticities, we can easily calibrate somebehavioral parameters in supply and demand function, specifically, share coefficients or preference
parameters.
First and foremost, some household preferences are calibrated to enforce results of our model to beconsistent with the benchmark year of 2005-2006. This practice is much different from other CGE
models which often take household preferences from external empirical studies, especially the ones
from U.S such as (Auerbach and Kotlikoff 1987), (Ballard, Shoven et al. 1985). Values of suchparameters in other researches have a wide range of variation (Auerbach and Kotlikoff 1987). In(Kudrna and Woodland 2011), all household preferences are also taken from external sources.
Actually, in order to match household sector with production sector, we have to make all markets(goods market, labor market, asset market) in balance. At the same time, we have to take into accountsome practical conditions such as government budget balance, hump shaped age profile ofconsumption and saving and labor force participation rate. Such conditions are maintained if wescarify some degree of freedoms like (Keuschnigg and Kohler 1994) did. In our case, some household
preferences are calibrated to meet these conditions. For instance, that consumption expenditure of atypical household is hump shaped with the peak at some age before retirement, asset holdings of atypical household is hump shaped with the peak at the biological age of around 60 (Kudrna andWoodland 2011), labor force participation rate is humped shaped with the peak of about 80% aroundthe biological age of around 40 are milestone to calibrate some utility preferences and demographic
features.
Table 4 Some other parameters in utility function
Intra-temporalelasticity of
substitution
Ρ

Subjective rateof timepreferenceβInter-temporalelasticity of
substitutionγ

Leisurepreference
parameterαTotal annual
timeendowment
h

3.00

0.007

1.36750.125047727

Age pension
rate

Income tax
rateπ1076200.265

Source: Authors’ calculation
Above results are reasonable. For example, inter-temporal elasticity of substitution, γ and leisurepreference parameter, α are all in the range adopted by relevant researches (Auerbach and Kotlikoff
1987). At the same time, in a recent review on application of CGE models by (Dixon 2008), it isargued that settings of key parameters should be flexibly adjusted (by sensitivity analyses) rather thanbe fixed to some external sources. Time-series econometrics estimated parameters seem to beinconsistent with specific simulation contexts.
Regarding the government budget situation, income tax rate () is calibrated so that income tax
revenue equals around two thirds of total tax revenue, according to (ABS 2008). Flat pension
coefficient ( ) is specified to meet the fact that age pension payment is the largest (ABS 2010d).
It is assumed that our economy is in a steady state equilibrium in 2005-2006. Therefore, all data
we have from this benchmark year must be consistent with the set of equations characterizing a steadystate equilibrium. With our simplification that price of all commodities at the bottom level is unitary
in the benchmark year and information on product related taxes, quantity of commodities can be28

calculated by dividing their monetary value by their tax inclusive price. Based on that, we can use
equations for a steady state to calculate their corresponding parameters.
For example, as we partly mentioned above, it is easy to calibrate the product specific shareparameters in different types of final aggregate commodity because of the assumption of CobbDouglas type function of aggregate commodities. Specifically, share coefficients are simply the
proportion of spending on each industry specific product in total expenditure.
Similarly, to calculate the value of share parameter to home and imported product in an industry
specific composite good, we can rearrange the corresponding equations to explicitly present thisparameter as a function of tax inclusive price of imported and home sold product and spending onimported and home sold product. Since we normalize prices as unitary in the steady state, information
on tax is known and all spending values can be obtained from IO tables, we can easily calculate suchshare parameters.
Regarding fixed coefficients in production output function, they can be calculated straight away bydividing value of intermediate inputs and value added by production output. Productivity coefficientin value added function can also easily obtained since we have data on compensation, gross operating
surplus and mixed income as well as value added.
Details on these parameters can be found in the Appendix on Parameters.
Finally, for investment and capital related parameters and value added related functions, despite
the fact that there are many external sources of estimates, we calibrate Australian data in order tomaintain our model consistent with practical conditions. Besides IO table, we need national accounts
which provide information on outputs, capital stock, capital formation cost and capital consumption
over time. Based on them, we can calculate ratio of capital formation cost to capital stock.
Table 5 Capital and investment related parameters
Capital formation/Capital
stock

Depreciation rate(δ)

Capital adjustment costcoefficient (σ)

Interest rate(r)

Capital shadow
price (q)

0.08

0.05

7.45150.042

8.9862

Source: (ABS 2010a) and authors’ calculation
For investment parameters, depreciation rate of capital stock can be calculated from time series
data on capital stock and capital consumption of ABS (ABS 2010a). On average over the last 10 years,
the depreciation rate of capital equals 0.05. Combining this result with annual population growth rate,
we can calculate the ratio of investment to capital (I/K), equal 0.0645 (equation (2.9)). Using timeseries data on capital formation cost, we can calculate the ratio of capital formation cost to capitalstock value, equal 0.08 on average of the last 20 years. So, it is possible to calculate the capitaladjustment cost coefficient (σ) and capital shadow price (q), using equation (2.10) and (2.13)
respectively. Then, we can calculate the world interest rate (r) by using equation (2.12). That interest
rate equal around 4% is very close to actual world interest rate in last decades (WB 2011).

5. Computation algorithm and benchmark solution
This part explains about techniques used to find steady state equilibrium solutions for our economy
and adjustment path between steady states. Results on equilibrium in the benchmark year 2005-2006
are used to test the reliability of the model.
5.1 Equilibrium
5.1.1 Steady state equilibrium

29Given tariff rates and values of exogenous variables, all endogenous variables in our model are
expected to converge to a stable value in the steady state equilibrium. From above equations for aparticular period, we can derive the set of equations for the steady state equilibrium by equalizing
values of endogenous variables across different periods of time. The set of these equations for thesteady state equilibrium is presented in the Technical Appendix.
Solving this system of equations gives us the solution for a steady state equilibrium of theeconomy, conditional on given exogenous variables. If there is a change in the trade policy, theeconomy will move from the initial steady state equilibrium to a new steady state equilibrium. By
comparing two steady state equilibriums, we can determine how the economy becomes after a policychange.
However, since we do not know how long it takes the economy to adjust from an initial to a new
equilibrium, we cannot determine exactly the welfare effect of the policy on particular living
individuals. In other words, households by the time of new equilibrium might not be households ofthe initial equilibrium time. For this reason, steady state equilibrium computation sometimes is not
significant for policy recommendation.
5.1.2 Dynamic adjustment path4
Above part helps us to find the steady state equilibrium of the economy at different trading
scenarios. Nonetheless, how and how long the economy adjusts from the initial steady state
equilibrium to the terminal steady state equilibrium is also our great concern. For simplicity, we
assume that the economy is in a steady state equilibrium at the time of the policy change. Unlike
steady state equilibrium, all agents experiencing the policy change have to revise their decision. And,of course, the markets in different time periods are related through the dynamics of the saving andinvestment decisions. The advantage of computing dynamic adjustment path over steady state
equilibrium is to clarify clearly the welfare effects on different age groups over their life time.
For household sector, we have to distinguish two groups of cohorts in this case. The first groupconsists of generations who are still alive at the time of policy change. Therefore, they change theirdecision for the rest of their life based on new price indexes as the consequence of the new policy.
The second group consists of generations who start their economic life when the new policy has been
already effective. For production sector, producers have to revise their production decisions based on
new price indexes. Consequently, we have a dynamic path of their decisions until the economy
reaches a new steady state equilibrium, described by equations in the main text.
Much more complicated than steady state equilibrium, all equations represents the equilibrium in
non-steady states. The link between inter-temporal equilibrium is through Euler equations forhousehold sector and capital motion equation for production sector. The size of this system of
equations depends on the number of periods the economy requires to adjust from an initial steadystate to a new terminal steady state.

5.2 Computation algorithm for steady state equilibrium
To find the solution for the steady state equilibrium or adjustment path, the Gauss-Seidel algorithm
is employed as (Auerbach and Kotlikoff 1987) did. In principle, it starts with guessing the initialvalues for some key endogenous variables. Together with exogenous variables, they are used to solve
for all endogenous variables, including the initially guessed key endogenous variables. If the new
solution for the initially guessed key endogenous variables is consistent with the initial guess, we can4

In comparison with finding steady state equilibrium, calculation of solutions for dynamic adjustment path requires much
more computing jobs. So, the works on dynamic adjustment path will be implemented in our next research.

30

conclude that a solution for the model has been found. Otherwise, we have to update a new guess forthese key endogenous variables, based on information from previous iterations.
For simplicity, we normalize the price of all imported goods and exported goods as numeraires inall periods, ,1.
,
Interest rate is fixed at the level of the world interest rate,. Hence, all other variables, inany period are in real value, in terms of prices of the world market. At the same time, all aggregate
variables are detrended population growth, implying that they are all in per capita terms. Since
population size in the benchmark year is normalized to unitary, such variables in other periods areterms per unit of population or equivalent to around 15 million people who are older than 15 years oldof the year 2005-2006.
The principle we adopt to find the steady state equilibrium is as follows: (1) Make a guess for thewage rate which is then used as a base to calculate all price indexes in the economy; (2) Calculate all
supplies from the view of producers by guessing labor amount used by each industry and using theprice indexes; (3) Calculate all demands from the view of consumers by using price indexes andinformation from the production sector; (4) Check the market clearing condition if demand equals
supply.

Supply quantities

Price indexes
Guess w

Yes:
Solution
Check equilibrium

Demand quantities

Guess

No: Update
guessesFigure 7 Computation algorithm

And in particular, following steps are implemented to find the steady state equilibrium:
5.2.1 Guess the wage rate,
Together with the constant interest rate (fixed at the world interest rate), it is possible to calculate
agent specific price at different levels, shadow price of capital and ratio of capital to labor (ineach industry by using price index equations, equations on marginal rate of return to production
factors:a. Guess the price of domestically produced product,b. Calculate prices at different levels: All of them can be featured as a function of price ofdomestically produced goods,
and price of imported goods,(equations 13, 16, 42, 45, 50, 57,60) or exported good,(equations 24, 27) and then shadow price of capital,(equation 35).

c. Use the equations characterizing the marginal rate of return to capital in each industry (equation
34, which can be rearranged to become a function of
in each industry,.

31) to calculate the ratio of capital stock to labord. Use the equations characterizing the marginal rate of return to labor (equation 33, which can berearranged to become a function ofrate in each industry,) and results from step (1c) to calculate the corresponding wage.

is consistent with the initiallye. Check whether the newly found wage in each industry,guessed wage rate, . If yes, move to step 2. If no, come back step (1a) to adjust the price ofdomestically produced products,.
5.2.2 Guess the level of labor employed in each industry,
Together with price indexes from step 1, it is possible to calculate supply of imported and home
sold products and demand for investment from the view of producers and demand for imported andhome sold products and supply of saving from the view of consumers, respectively. Then we cancheck the market clearing conditions if demand is as the same as supply:
a. Calculate the capital stock used by each industry,
capital to labor from step (1c),,, by using guessed labor,,

and ratio of.

(equation 28) then production output
b. Calculate the value added output for each industry,(equation 23), supply of exportable and home sold product (equation 25, 26), then demand forimported and home sold products used for investment (equations 31, 32, 35, 40, 41, 43, 44, 46, 47),
government spending (equations 54, 56, 58, 59, 61, 62) and intermediate inputs (equations 48, 49, 51,
52).
d. Calculate the demand for home sold and imported products of the household sector as thedifference between total home sold and total imported product and total demand for home sold andimported goods for investment, government spending and intermediate inputs, respectively (equations
69).
e. Calculate tax revenue and benefit transfer payment, age pension payment and subsidy payment(equations 20, 21, 22, 53, 55, 56), trade balance (equations 26, 64, 65, 66), world debt (equation 67)
and total asset holdings (equation and 71).
f. Based on information on transfer payment, age pension payment and price indexes, from the, leisureview of consumers, recalculate the demand of the household sector for home sold product,
and working decisions (equations 2, 3, 6, 7, 8, 19), and asset holdings (equations 4, 5, 9, 10).
i. Check whether the demands of the household sector from the view of the consumer (obtained
from step 2(f)) are as the same as those got from step 2(d). If yes or the number of iterations exceed
our predetermined number, we move to step 3. If no, we adjust the guessed labor level, , and comeback step 2(a).

5.2.3 Check the balance
If the total asset holdings and total labor supply of the household sector from the view of theconsumer (obtained from step 2(f)) are as the same as the ones got from step 2(e) and guessed labordemand respectively.
If yes, we find a solution for the steady state equilibrium of the economy. If no, we adjust theguessed wage rate and start step 1 again.

32

5.3. The benchmark steady state solution
Characteristics of the benchmark year 2005-2006 are used to run the model. Because model
provides results consistent with realistic conditions of this year, it is likely that the model is reliable5.
5.3.1 The production sector
Table 6: Industry specific share in production output, value added, labor and capital use and capital –labor ratio

AgrForShare in production
output value (%)
2.66

Share in total
value added (%)
3.09

Share in total
labour use (%)
1.30

Share in total
capital stock (%)
5.16

MinQuarr

5.53

7.31

2.40

13.47

6.51

Food

3.70

2.15

2.11

2.18

1.20

Texcloth

0.40

0.34

0.43

0.21

0.57

Wood

0.52

0.45

0.46

0.44

1.11

Paper

1.55

1.44

1.61

1.26

0.91

Petrol

1.27

0.36

0.13

0.64

5.63

Chemic

1.19

0.78

0.82

0.72

1.02

Nonferr

1.31

1.02

1.16

0.84

0.84

Metals

3.73

1.98

2.45

1.45

0.69

MetProc

3.92

2.65

3.44

1.72

0.58

Energy

2.32

2.49

1.35

3.93

3.38

Constr

11.16

7.036

6.05

8.45

1.62

Trade

11.45

11.24

13.85

7.64

0.64

HotRest

2.76

2.26

2.59

1.90

0.85

Transp

8.48

7.55

6.86

8.27

1.40

RealEst

23.90

28.97

22.96

35.62

1.80

Public

10.52

15.30

24.98

4.21

0.20

OthServ

3.63

3.58

5.04

1.87

0.43

All goods

28.10

24.06

17.66

32.03

1.81

All services

71.90

75.94

82.34

67.97

0.83

SUM

100%

100%

100%

100%

1.16

Industries

Capital –labor ratio
4.60

Source: (ABS 2010a) and authors’ calculation
In the benchmark year, total production output value and total value added of Australia is around$1,876 and $888 billions respectively. The largest contributions to total production output value andtotal value added are given by banking, insurance and real estate sector (23.9%-28.97%), followed bypublic service sector (10.52%-15.30%) and commerce sector (11.45%-11.24%)... Textile and clothing,petroleum, wood and wood processing and chemical sector have the smallest shares in production
output value and value added. At a larger aggregated scale, all good producing industries account for
24% while all services providing industries create 76% of total value added.
Therefore, it is not surprising that in terms of labor and capital employment, banking, insurance
and real estate, public service and commerce service are at the top while textile and clothing,petroleum, wood and wood processing and chemical sector are at the bottom. In fact, of $464.511
billions of compensation payment, $116.05, $106.66 and $64.33 billions come from public service,banking, insurance and real estate and commerce, respectively. And of $3274.35 billions of capital5

The reliability is then also supported by a sensitivity analysis

33

stock value, 35.62%, 8.45%, 8.27% and 7.65% are used by banking, insurance and real estate,
construction, transport and commerce, respectively.
In terms of factor endowment abundance, Australia as a whole is capital abundant because capital
contribution is 1.16 times bigger than labor contribution to total value added. Production of capitalintensive goods so is the advantage of Australia. The most capital intensive sectors are mining andquarry, petroleum, agriculture and forestry and energy. And the most labor intensive sectors are public
services, other services, textile and clothing and metal processing. Between goods producing andservices providing industries, the former is more capital intensive while the latter is more labor
intensive.
Table 7: Industry specific share of value added and use purposes in production output
Intermediateuse (%)

Final privateuse (%)

Governmentuse (%)

61.52

13.99

0.89

Capitalformation(%)
5.65

AgrForValue added
Contribution
(%)
54.95

MinQuarr

62.58

43.79

0.42

0.10

2.62

53.13

Food

27.49

36.54

39.72

0.04

0.43

24.20

Texcloth

39.45

27.61

37.78

0.00

7.56

27.04

Wood

40.60

87.11

2.16

0.00

1.50

9.23

Paper

44.10

73.19

20.28

0.01

1.85

4.66

Petrol

13.46

62.45

25.93

0.00

0.29

13.77

Chemic

31.13

61.42

12.73

4.70

1.46

19.69

Nonferr

36.87

89.46

4.14

0.00

2.11

4.29

Metals

25.16

55.96

1.21

0.00

4.37

38.46

MetProc

32.02

40.51

21.19

0.01

24.17

14.12

Energy

50.74

57.84

29.33

2.10

10.56

0.17

Constr

29.84

37.35

0.38

1.40

60.54

0.33

Trade

46.46

35.85

47.24

0.85

9.13

6.97

HotRest

38.87

27.53

62.85

0.01

0.00

10.27

Transp

42.17

58.55

20.01

4.21

4.92

11.71

RealEst

57.39

63.02

29.43

1.11

4.50

1.99

Public

68.84

8.01

20.07

69.26

0.34

2.33

OthServ

46.74

29.59

45.92

21.99

0.89

1.82

All goods

40.54

52.74

15.78

0.48

6.35

24.94

All services

50.01

43.08

27.39

12.46

13.02

4.03

SUM

47.34

45.80

24.12

9.10

11.15

9.91

Industries

Export (%)
18.37

Source: (ABS 2010a) and authors’ calculation
Total capital stock in the economy values $3274.35 billions or 3.68 times of national value added.
Every year, firms spend $261.95 billions on capital formation. This expenditure is transformed into an
investment flow to replace the depreciated stock of capital, equivalent to 6.45% of total capital stock.
Total value of firms in the economy is estimated at $4848.07 billions.
With respect to contribution of value added to production output, primary and services industries
are dominators. The sector with highest share of value added in production output is public service(68.84%), followed by mining and quarry (62.58%), banking, insurance and real estate (57.39%) andagriculture and forestry (54.95%). All of them use relatively less intermediate inputs in theirproduction processes and rely more heavily on the use of labor or capital. The lowest shares of value
added in production output occur in petroleum (13.77%) and food stuff industry (27.49%). Between
goods producing and services providing industries, the latter ones have a bigger share of value added34

on average which is mainly caused by their intensive use of labor. The economy-wide data indicatesthat it is quite balanced between the contribution of intermediate inputs and value added in total
domestic production output (52.66% and 47.34% respectively).
With regards to allocation between home and abroad sales, nearly 10% of total production output
is used for export in which goods producing industries far exceed services providing industries. The
most foreign market oriented sectors are mining and quarry (53.13% of output for export) and basic
metals (38.46% of output for export). Both of them are primary industries which rely heavily on theworld market in selling their products.
In terms of home use allocation, on the one hand, a majority of industries produce output mainly tomeet demands for intermediate inputs (agriculture and forestry, mining and quarry, wood and woodprocessing, paper and paper processing, petroleum, chemicals, non-ferrous minerals, basic metals,
metal processing, energy, transport and real estate). On the other hand, foodstuff, textile and clothing,trade, hotel and restaurant and other services are consumed chiefly by the household sector whilemost of production output of construction and public services are used for capital formation andgovernment consumption respectively.
5.3.2 The government sector
The actual tiny government budget deficit in Australia is interpreted into the assumption of
constant balance between tax revenue and government spending in any period in our model. At thesame time, the government consumption value is supposed to be a fixed proportion to GDP or total
value added. This proportionin the benchmark year equals 0.1953 and is applied for all otherperiods. Total government consumption value is $173.43 billions. Unlike other economic agents,
government only consumes domestically produced commodities, except chemicals.
The gap between total tax revenue and government consumption value is allocated as benefit
transfer to all households ($95.693 billions), age pension to retired cohorts ($20.588 billions) andsubsidy ($9.734 billions).
In terms of sources, of total tax revenue of $299.45 billions, commodity use tax is $89.224 billions,income tax is $182.26 billions, value added output tax is $27.97 billions and import duty is $3.24
billions. In terms of payers, producers pay $66.864 billions while households pay $232.59 billions.
5.3.3 The household sector
Table 4.3 displays how an average household allocate total consumption expenditure to alternative
types of commodity. The household sector as a whole spends $544.79 billions on goods and services
consumption of which 26.68%, 20.52% and 8.26% are spent on banking, insurance and real estate,commerce and public service, respectively.
Table 8 Commodity specific share in final private consumption (%)
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

1.47

0.09

6.59

1.83

0.04

1.39

1.58

1.35

0.38

0.26

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

Total

6.63

2.57

0.16

20.52

7.03

6.73

26.68

8.26

6.41

100%

Source: (ABS 2010a) and authors’ calculation
However, consumption differs from generation to generation. Overall, consumption of a typicalhousehold over her lifetime is hump shaped with the peaks around ages before and after thecompulsory retirement age. Because of the compulsory retirement assumption, the leisure time in thelast working age is essentially smaller than that of the first retirement age. Consequently, allconsumers reduce significantly commodity consumption in their first retirement ages as an effort tosmooth their felicity over time. The positive effect of full endowment time for leisure is cancelled out
by the negative effect of the decline in commodity consumption. Total consumption value of the35household sector is $544.79 billions. Asset holdings are also hump shaped with the peak at thebiological age of 58. The total asset holding value of the household sector is around $5,310 billions
which is stored in the form of firm value and loan to ROW.
Table 9 Final private consumption in industry specific home sold output (%)
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

17.06

0.89

51.77

51.79

2.38

21.27

29.24

15.85

4.33

1.97

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

Total

24.67

29.38

0.39

50.76

69.53

22.82

30.01

20.54

46.67

26.76

Source: (ABS 2010a) and authors’ calculation
70000
60000
50000
40000
30000
20000
10000
0
15‐24

25‐39

40‐54

55‐69

70‐84

85+

Model simulation

Figure 8 Age specific consumption ($)
Source: Authors’ calculation
In general, final private consumption occupies a large proportion of home sold output, 26.75% on
average. Production of final consumption oriented industries, including agriculture and forestry, food
stuff, textile and clothing, paper and paper processing, petroleum, chemicals, metal processing energy
and all services except construction rely much on domestic private demand. Hotel and restaurant
service is most while construction and mining and quarry are least dependant on final private
consumption. Industries with over half of their home sold output consumed by the household sector
are food stuff, textile and clothing, commerce, hotel and restaurant.
Consumer preferences for home sold and imported product vary significantly across types ofcommodity. On average, the entire household sector allocates 91.05% of their expenditure for home
sold product and the remaining, 8.95% for imported product. Commodities with large contribution ofimports to final private consumption are textile and clothing (nearly 70%), chemicals (nearly 60%),
non-ferrous minerals (nearly 50%) and metal processing (over 50%). Preferences for consumption ofservices are driven towards domestically provided products.
Table 10 The share of home made product in final private consumption (%)
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

95.41

93.16

84.02

31.33

100.00

85.22

78.30

42.28

53.44

65.63

36

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

Total

47.34

99.91

100.00

99.49

93.03

95.19

99.49

96.40

98.04

91.05

Source: (ABS 2010a) and authors’ calculation
In terms of leisure allocation, it reduces continuously in the first 24 years then keeps increasing
until reaching full leisure upon the biological age of 66. This is mirrored by a humped shape profile ofsupply of labor over individual lifetime. On average, the participation rate is 69.67%6. The highest
participation takes place at the age of 38, equal 79.45%.
The figures below illustrate how good our model results fit with actual observations, specifically interms of lifecycle participation rates and asset holdings.
0.900
0.800
0.700
0.600
0.500
0.400
0.300
0.200
0.100
0.000
15‐19

20‐24

25‐34

35‐44

Actual data

45‐54

55‐59

60‐64

Model simulation

Figure 9 Age specific participation rates
Source: Authors’ calculation and (Abhayaratna and Lattimore 2006)
8000007000006000005000004000003000002000001000000
15‐19 20‐24 25‐29 30‐34 35‐39 40‐44 45‐49 50‐54 55‐59 60‐64 65‐69 70‐74 75‐79 80‐84 85‐90
HILDA Wave6

Model simulation

Figure 10 Age specific asset holdings ($)
Source: Authors’ calculation and HILDA Wave 6
6This average participation rate is slightly higher than actual average because in our model, working force in the age after 65
is not included and our cohort structure is not as the same as the actual data.

37

5.3.4 Trade performance
In general, Australia is a net importer with total trade volume of $384.30 billions in the benchmark
year. The trade deficit is about $12.72 billions, or 3.3% of the total trade volume. This narrow trade
deficit represents not only in the benchmark year but also in most of the last decades. Overall, trading
performance in Australia is sustainably balanced. Trade deficit is interpreted into the result that total
ROW’s debt to Australia is around $461.76 billions. This figure does not match the actual conditionin which Australia is a net borrower from ROW. However, our model cannot capture accurately bothflow of goods and flow of capital at the same time. Therefore, we ignore the unrealistic result onAustralia’s net foreign asset, just using it to adjust trade in goods and services. To some extent, thisexperiment is less biased if we take into account the fact that a large part of capital inflows into
Australia, especially portfolio investments are not directly related to cross-border flows of goods andservices.
Table 11 Commodity specific export and import ($ billion)
Commodities AgrFor MinQuarr Food

Texcloth

Wood

Paper

PetrolChemicNonferr

MetalsExport

9.18

55.12

16.77

2.04

0.90

1.36

3.27

4.39

1.05

26.88

Import

1.06

18.23

8.98

9.60

1.53

5.67

9.71

18.20

7.37

10.64

EnergyConstr

Trade

HotRestTransp

RealEstPublicCommodities MetProc
Export

10.39

0.07

0.69

14.97

5.31

18.63

8.94

4.59

Import

84.38

0.03

0.02

0.54

3.87

6.46

8.38

1.93

OtherSer
TOTAL
v
1.24
185.791.89

198.51

Source: (ABS 2010a) and authors’ calculation
In general, Australia is a net exporter of 10 commodities and net importer of 9 commodities. Mostof net importing producers are in physical good producing industries while most of net exporting
producers are in services providing industries, clearly stating the actuality that services sector is morecompetitive than non-services sector in Australia. The leading export products are created by the
primary sectors. In other words, Australia relies on comparative advantage in services and natural
resources in liberalizing the domestic economy and integrating into the world economy.
The largest deficit occurs in metal processing industry (nearly $74 billions). The second largest
trade deficit is faced by the chemical sector, at nearly $14 billion. In terms of the import – export ratio,
the leading industries are metal processing (8.12 times); non-ferrous minerals (7.01 times); textile andclothing (4.70 times); paper and paper processing (4.17 times); chemical excluding petroleum (4.15
times). They all reflect the fact that manufacturing is not a comparative advantage of Australia. Thus,
Australia has spent a large amount on importing manufacturing goods such as transport equipment,
especially motor vehicles, electronic equipment, household appliances, production equipment andmachinery, furniture, chemical products, papers…
Table 12 Commodity specific trade deficit ($ billion)
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

8.12

36.88

7.79

-7.56

-0.63

-4.31

-6.44

-13.82

-6.32

16.24

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

TOTAL-74.00

0.043

0.67

14.43

1.44

12.18

0.56

2.66

-0.65

-12.72

Source: (ABS 2010a) and authors’ calculation

38

The biggest surplus takes place in mining and quarry industry (nearly $37 billions), followed bybasic metal industry (over $16 billions). Two other good producing industries with strong competition
power of Australia, agriculture and forestry and food stuff also perform significant trade surplus, overand nearly $8 billions respectively. In terms of export – import ratio, except some outliers ((i)
construction whose ratio is 40.38 times but not vital because of its low trade volume and limited
participating feasibility in the international trade; and (ii) commerce whose ratio is 27.93 times which
is mostly caused by its marginal contribution going along with export of manufacturing goods), theleading industries are agriculture and forestry (8.64 times), mining and quarry (3.02 times), transport(2.89 times), basic metals (2.53 times) and energy (2.49 times). This data exhibits the reliance ofAustralia on natural resources, especially coal, gas and iron and non-ferrous metal ores to promote
export activities.
Table 13 Commodity specific export – import ratio
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

8.64

3.02

1.87

0.21

0.59

0.24

0.34

0.24

0.14

2.53

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

TOTAL

0.12

2.49

40.38

27.93

1.37

2.89

1.07

2.37

0.66

0.94

Source: (ABS 2010a) and authors’ calculation
With respect to the use of imports, 57% of nearly $200 billions are utilized for production while
22% and 19% are allocated for final private consumption and capital formation respectively.
Regarding the tariff or import duty rates, the detailed description could be found in the Appendix
on Tax Data. But overall, import duty is not an important source of government budget because of
relatively low rate on average (1.63% economy wide). Totally, duty revenue is just $3.24 billions in
the baseline year. Tariffs are imposed against only imports of physical goods. Two groups of physicalgoods excluded from import duty are agriculture and forestry and mining and quarry.

6. Policy Simulations
We conduct numerical experiments for the impact of trade liberalization on important
macroeconomic variables, welfare, industry specific output, capital stock accumulation, employment,
trade performance as well as government budget situation under alternative world market conditions.
Such changes are compared with the benchmark references.
Two possible world market conditions are assumed to take place:(W1) No change in the world prices: The world market conditions are as the same as the time of
the benchmark year.
(W2) Change in the world prices: It is projected that price of some primary goods will rise
relatively to price of other goods in the long-term due to the depletion of unrecoverable natural
resources. Therefore, a circumstance in which the world price of petroleum grows by 50% and priceof some raw materials (mining and quarry) grows by 30% is adopted. This scenario is realistic, which
has been occurred recently.
Our model is used to find steady state equilibrium associated with each of the above proposed
conditions. The steady state equilibrium associated with (W1) has been described in Part 4 and iscalled the first benchmark equilibrium later on. The steady state equilibrium associated with (W2) iscalled the second benchmark equilibrium.

39

Then, following polices are simulated for both of two world market conditions:(P1) All import duties are unilaterally, immediately and permanently eliminated: As written above,
past and current negotiations with most big trading blocs will cause significant reduction in tariff rates
in near future. Therefore, it is projected that the current low tariff rates will be further reduced
substantially in coming years. A trading scenario in which all tariffs are cleared is a practicalassumption, especially after FTA negotiations with big trading partners come into full effect.
(P2) Subsidization is unilaterally, immediately and permanently reduced: In trade negotiations,discrimination between home produced goods and imported goods through subsidization programs isgradually removed. Unlike tariff barriers, countries have more flexibility in using subsidization. In
fact, countries are reluctant in removing their subsidization programs because of its substantiality inpromoting domestic production, especially for export (Lloyd 2006). Hence, it is unexpected that all
subsidies would be eliminated like the case of import duty. Instead, we adopt a realistic proposal thata flat rate decline of 50% is applied to all rates of subsidy.
The model is simulated to find the steady state equilibrium for all possible combinations between
policy choices and world market conditions. Then, comparisons between results of different scenarioswith their corresponding benchmark equilibrium are made to determine whether our economy is betteror worse off and which scenario is most desired. Based on that, optimal policy for different world
market conditions could be recommended.
In below parts, we focus on describing what would occur under alternative policies and world
price scenarios. Detailed explanation on causes and institutions of such changes could be found in the
Appendix.
6.1 Change in the world prices (W2)
6.1.1 Macro results
In general, the economy is better off when there is an increase in the world price of primary goods.
Production output, GDP, total stock of capital and real wage rate are expected to increase significantly,
around 30%. Australia would become a net exporter in the new price condition with trade surplus of$7 billions. Labor employment would rise, although with much smaller magnitude (3.7%). On
average, total equivalent variation transformed welfare of the entire household sector increases by
3.5% in comparison with that in the benchmark year. This result is theoretically and practicallyconsistent because as above analyzed, the Australian economy heavily relies on primary industries
thanks to its abundance in natural resources. An increase in price of primary products therefore
benefits much Australia as predicted by Hechscher-Ohlin theorem. What have happened actually also
support this argument.
Table 14 Change in some key aggregate macro variables under scenario W2
Indicators
Wage rate ($ mills)
Production output value ($ bills)
GDP ($ bills)
Capital stock ($ bills)
Employed labor
Trade balance ($ bills)
WelfareW1
1.00
1875532.13
887959539503.70
464511.00-12718.64
3622.14W2
1.25
1891363.34
1207056.82
670460.44481591.59
6955.993656.18

Change (%)
25.23
31.72
35.94
24.27
3.68
Deficit to Surplus
3.54

Source: Authors’ calculation
6.1.2 Production performance
Table 15 Industry specific changes in production output value, home sold output value, price of home
sold products under scenario W2
Industries

Production output value

Home sold output value

40

Price of home sold products

AgrForW1($ bills)
49970.00

W2($ bills)
57177.79

change
(%)
14.42

W1
($ bills)
41002.17

W2($ bills)
49335.75

change
(%)
20.32

W1
W2
($ mills) ($ mills)
1.00
1.23

change(%)
22.60

MinQuarr

103744.00

241691.12

132.9748690.25

73877.42

51.73

1.00

0.95

-4.80

Food

69313.00

78743.78

13.61

53185.24

65035.97

22.28

1.00

1.26

26.14

Texcloth7552.00

6340.52-16.045509.68

5165.38

-6.25

1.00

1.24

24.01

Wood

9799.00

11936.00

21.81

8894.41

11194.95

25.86

1.00

1.21

20.83

Paper

29128.00

34376.03

18.02

27769.40

33260.00

19.77

1.00

1.18

18.08

Petrol23764.00

35251.02

48.34

21072.4427656.77

31.25

1.00

1.07

6.71

Chemic22271.00

22243.77-0.1217885.35

19171.70

7.19

1.00

1.21

20.62

Nonferr

24503.00

30749.42

25.49

23452.36

29813.99

27.13

1.00

1.17

16.97

Metals
MetProc
Energy69904.00
73578.00
43518.00

74105.18
77307.24
56007.39

6.01
5.07
28.70

43020.50
63184.5443444.84

52447.73
69645.9755939.54

21.91
10.23
28.76

1.00
1.00
1.00

1.20
1.19
1.16

19.87
19.39
15.52

Constr209358.00

298002.73

42.34

208671.52

297351.80

42.50

1.00

1.18

18.41

Trade

214790.00

271752.64

26.52

199884.90

259195.73

29.67

1.00

1.21

20.93

HotRest51687.00

59402.92

14.93

46725.61

55645.19

19.09

1.00

1.22

22.08

Transp159094.11

197941.27

24.42

139518.24

182745.83

30.98

1.00

1.22

21.46

RealEst448215.01

569725.40

27.11439531.61

562298.15

27.93

1.00

1.19

19.42

Public197300.00

260689.46

32.13

192715.53

256808.19

33.26

1.00

1.22

22.14

OthServ

68044.00

87098.31

28.00

66945.4286168.52

28.71

1.00

1.20

20.30

All goods

527044.00

725929.27

37.74

397111.19

492545.16

24.03

All services

1348488.13

1744612.72

29.38

8932856.57

5072321.93-43.22

SUM

1875532.13

2470541.99

31.72

1691104.02

2192758.58

29.66

Source: Authors’ calculation
Generally, the production sector as a whole is better off after the rise in the world price of primary
products. Production value, GDP, capital use and labor employment are projected to grow by 31.7%,
35.9%, 24.3% and 3.7% respectively. If the whole production sector is disaggregated by goods andservices, both of them would experience a positive change in value added output, capital and labor
employment although the changes in the goods producing sector is much stronger than that in theservices providing sector.
The industry level disaggregated analyses would produce mixed results. In terms of GDP
expansion, all industries except textile and clothing would experience an increase in their valued
added of which as expected, mining and quarry would record the biggest rise, followed by petroleum.
Regarding the employment of labor, besides textile and clothing with largest drop in employedlabors, agriculture and forestry, food stuff, wood and wood processing, paper and paper processing,chemicals, basic metals, metal processing, hotel and restaurant and transport would also recruit fewer
labors. In contrast, as expected, mining and quarry would experience the largest expansion in labor
employment.
In terms of capital use, only textile and clothing, agriculture, food stuff, chemicals and metal
processing would record a reduction of which textile and clothing have the largest decline. Amongst
capital employment increasing industries, mining and quarry would show the highest growth, muchhigher than the closet followers, petroleum and construction.
Table 16 Industry specific changes in value added, labor and capital employment, and capital – laborratio under scenario W2
Industries

Value added

Labor use

41

Capital use

Capital – labor ratio

W1

W2

AgrForW1
W2changeW1
W2changeW1
W2change($ bills) ($ bills) (%)($ bills) ($ bills) (%)($ bills) ($ bills) (%)
27457 31134
13.39
6048
5754
-5.07
27863 26953
-3.27

4.61

4.69

change(%)
1.90

MinQuarr

64928

153565

136.52

11142

21656

92.28

72647

148145103.92

6.52

6.91

6.05

Food

19055

21676

13.75

9789

8899

-9.24

11748

11577

-1.45

1.20

1.30

8.58

Texcloth

2979

2588

-13.13

2004

1395-30.641145

861-24.80

0.57

0.62

8.43

Wood

3978

4910

23.42

2142

2101

-2.38

2379

2571

8.05

1.11

1.23

10.68

Paper

12844

15654

21.88

7457

7216

-3.50

6813

7276

6.81

0.91

1.01

10.68

Petrol

3199

4934

54.25

614

747

21.11

3457

4633

34.04

5.63

6.23

10.68

Chemic

6932

7159

3.27

3831

3146

-18.27

3893

3522

-9.54

1.02

1.12

10.68

Nonferr

9034

11825

30.90

5389

5612

3.68

4548

5219

14.76

0.84

0.93

10.68

Metals
MetProc
Energy

17591
23561
22082

20129
25867
29066

14.43
9.79
31.63

11376
15975
6272

10389
13982
6515

-9.27
-12.88
3.55

7807
9280
21211

7840
8948
24309

0.42
-3.58
14.60

0.69
0.58
3.38

0.76
0.64
3.74

10.68
10.68
10.68

Constr

62474

89951

43.98

28114

31516

11.56

45573

58207

27.72

1.62

1.86

14.49

Trade

99801

128670

28.93

64332

65213

1.13

41232

47738

15.78

0.64

0.73

14.49

HotRest

20092

23307

16.00

12030

11073

-8.12

10272

10446

1.69

0.85

0.95

10.68

Transp

67085

84112

25.38

31881

31271

-2.23

44625

49530

10.99

1.40

1.59

13.52

RealEst257235 328177

27.58

1066565741

0.66

192175 214104

11.41

1.80

1.99

10.68

Public135828 182698

34.51

116051

21424

7.12

22734

26953

18.56

0.20

0.22

10.68

OthServ

31804

41634

30.91

23408

8884

4.00

10102

11628

15.11

0.43

0.48

10.68

All goods

213640 328507

53.77

82039

1390

5.95

172792 251854

45.76

2.11

2.90

37.57

All services

674319 878549

30.29

3824722091

3.19366712 418607

14.15

0.96

1.06

10.62

SUM

887959 1207057

35.94

4645117196

3.68539504 670460

24.27

1.16

1.39

19.87

Source: Authors’ calculation
Because of above changes in capital and labor employment, capital – labor ratio is expected to risein all industries. Between goods producing and services providing sector, the capital – labor ratio of
the former would be affected more strongly. The largest change is projected to take place inconstruction and commerce services while the smallest variation is expected to happen in agriculture
and forestry industry and mining and quarry. All other industries would experience the growth incapital – labor ratio by around 10%. Australia would become more capital intensive and most capitalintensive industries would expand their production strongly while labor intensive industries(especially unskilled labor intensive industries such as textile and clothing) would contract or growslightly. This result partly goes along with Hecksher-Ohlin theorem 7 which predicts there is areduction in labor intensive industries but expansion in capital intensive industries.
Price of all home sold products except mining and quarry is expected to rise after the increase inworld prices of primary goods. These results are practical because mining, quarry and petroleum are
major inputs to all industries.
Mining and quarry industry is expected to gain most from the world price change with muchhigher growth rate of GDP and capital and labor use over those of the remaining industries. In
contrast, textile and clothing industry would suffer from a big loss with the highest contraction ofGDP, employed labor and capital stock.
6.1.3. The government sector

7

Stolper-Samuelson theorem that predicts the increase in world price of capital intensive goods would lead to a relative
expansion in production of capital intensive goods and rental rate of capital.

42

Since government consumption spending shares a fixed proportion of total GDP in any period, itschange would be as the same as the change in GDP, increasing by 35.94%. Specifically, world pricechanges would cause an increase in government consumption expenditure by 35.94%. Similarly, otherbenefit transfer payment, age pension payment and subsidy payment also increase, by 19.06%,
25.23% and 41.84% respectively. Tax revenue therefore is also expected to rise by 30.00%.
Table 17 Changes in the government sector under scenario W2
Indicators
Spending ($ bills)
Other benefit Transfer ($ bills)
Age Pension ($ bills)
Subsidy ($ bills)
Tax Revenue ($ bills)

W1173434.51
95692.91
20588.00
9734.00
299449.42

W2235760.11113935.40
25782.83
13806.42
389284.76

Change (%)
35.94
19.06
25.23
41.84
30.00

Source: Authors’ calculation
6.1.4 The household sector
Table 19 Changes in the household sector under scenario W2
Indicators
Aggregate private consumption ($ bills)
Participation rate (%)
Asset holdings ($ bills)
WelfareW1
544789.70
69.67
5309833.04
3622.14W2693042.23
72.31
6708799.83
3656.18

Change (%)
27.21
3.37
26.35
3.54

Source: Authors’ calculation
Like most of the production industries, the household sector overall would gain after a positivechange in price of primary products. Total equivalent variation transformed welfare of the entire
household sector is projected to increase by 3.54%. In order to assess the welfare change, we follow(Kudrna and Woodland 2011) in adopting the basis of equivalent variations. Accordingly, thepercentage change in equivalent variation transformed welfare is measured by:
1

100

Table 20 Commodity specific changes in final private consumption under scenario W2

Commodities
AgrForConsumption of homemade products
W1
W2change($ bills)($ bills)(%)
6993.098789.76
25.69

Consumption ofimported products
W1
W2change($ bills)($ bills)(%)
336.49534.41
58.82

Consumption expenditure
W1

W2

7329.599324.17change(%)
27.21

MinQuarr

435.32592.84

36.19

31.95

1.58

-95.07467.26594.42

27.21

Food

27532.28

34410.89

24.98

5237.197269.7638.81

32769.47

41680.65

27.19

Texcloth2853.482572.19-9.86

6252.968929.5442.81

9106.45

11501.73

26.30

Wood

211.51269.07

27.21

0.00

0.00

NA

211.51269.07

27.21

Paper

5907.457074.4619.75

1024.711742.08

70.01

6932.168816.54

27.18

Petrol6161.677469.6421.23

1707.942536.9948.54

7869.61

10006.63

27.16

Chemic2835.592710.45-4.41

3871.115813.6050.18

6706.708524.05

27.10

Nonferr

1014.361246.1322.85

883.771167.33

32.09

1898.122413.46

27.15

Metals
MetProc
Energy846.03
15589.38
12763.51

880.4514205.20
16232.02

4.07
-8.88
27.18

443.0317344.32
11.42

756.3327429.11
19.27

70.72
58.14
68.78

1289.06
32933.70
12774.93

1636.7841634.31
16251.30

26.97
26.42
27.21

43

Constr

Consumption of homemade products
W1
W2change($ bills)($ bills)(%)
804.501023.43
27.21

Trade

101458.44

128706.35

26.86

520.221023.5596.76

101978.66

129729.91

27.21

HotRest32487.39

38892.33

19.72

2435.565534.14127.2234922.95

44426.46

27.21

Transp31835.9240362.38

26.78

1608.202176.0235.31

33444.13

42538.39

27.19

RealEst131902.95

167233.59

26.79

678.361426.80

110.33132581.31

168660.39

27.21

Public39591.84

49588.85

25.25

1478.812658.2879.76

41070.65

52247.13

27.21

OthServ

31243.22

39603.76

26.76

624.73935.7949.79

31867.94

40539.55

27.21

All goods

83143.6796453.09

16.01

37144.90

56200.02

51.30

120288.57

152653.10

26.91

All services

369324.26

465410.68

26.02

7345.8713754.58

87.24

376670.14479165.26

27.21

SUM

452467.93

561863.77

24.1844490.77

69954.59

57.23

496958.70

631818.36

27.14

Commodities

Consumption ofimported products
W1
W2change($ bills)($ bills)
(%)
0.00
0.00
NA

Consumption expenditure
W1

W2

804.501023.43

change(%)
27.21

Source: Authors’ calculation
Additionally, total private consumption spending, labor force participation rate and asset holdings
are expected to change positively, by 27.21%, 3.37%% and 26.35% respectively. Expenditure on
home sold products increases across commodities except textile and clothing, chemicals and metal
processing. Spending on imported products grows across commodities except mining and quarry.
The disaggregation by generation level would produce positive results. It would lead to an increase
in all age specific consumptions, participation rates and asset holdings. In terms of consumption, thegreatest variation is expected to happen to the youngest generations while the smallest change is
expected to happen to the eldest generations. Differently, in terms of participation rate, the biggest
and smallest changes are projected to occur to the eldest working and mid-career generations
respectively. Regarding asset holdings, the eldest generations would experience the largest variations
while other cohorts would see smaller changes. These results reveal the possibility that consumers
would relatively save less but consume more in the first half of their life.
6.1.5 Trade performance
In general, trade performance of Australia after the price change would show a mixed result.
Although it is projected that instead of being a net imported, Australia would become a net exporter,
different results are to happen to goods producing and services providing industry. While the former
would record an increase in export value and export-import ratio, the latter is expected to show adecrease. And both of them would import more, increasing by 32% in goods producing sector and
82% in services providing sector. Eventually, goods producing sector is expected to be a net exporter
rather than a net importer as before but services providing sector would show a big contraction in its
trade surplus by 92.8%.
Table 21 Commodity specific changes in import value, export value, export – import ratio and tradebalance under scenario W2

AgrFor

ExportImport
W1
W2
Change
W1
W2
Change($ bills) ($ bills) (%)($ bills) ($ bills) (%)
9181
8028
-12.55
1062
1499
41.12

Export-Import Ratio
Trade Balance
Change
W1
W2
ChangeW1
W2(%)($ bills) ($ bills) (%)
8.64
5.37
-37.908119
6604-19.57

MinQuarr

55116

168003204.82

18235

11096

-39.15

3.02

15.40

409.5836881

166805325.44

Food

16772

14256

-15.00

8982

11941

32.95

1.87

1.20

-35.947790

2203-70.29Texcloth

2042

1175

-42.46

9604

12768

32.94

0.21

0.09

-56.55-7562-12849

53.31

Wood

905

741

-18.08

1531

2203

43.89

0.59

0.34

-42.93

-627

-1543

133.35

Paper

1359

1116

-17.85

5672

7571

33.49

0.24

0.15

-38.35

-4313

-6582

49.66

Petrol3271

9230

182.15

9714

16488

69.73

0.34

0.56

66.60

-6443

-7290

12.65

Industries

44Chemic

ExportImport
W1
W2
Change
W1
W2
Change($ bills) ($ bills) (%)($ bills) ($ bills) (%)
4386
3072
-29.95 18202 24180
32.84

Export-Import Ratio
Trade Balance
Change
W1
W2
ChangeW1
W2(%)($ bills) ($ bills) (%)
0.24
0.13
-47.10 -13816 -21468 52.78

Nonferr

1051

935-10.97

7370

8870

20.35

0.14

0.11

-25.85-6319

Metals
MetProc
Energy

26884
10386
72

21657
7656
67

-19.44-26.29
-7.25

10641
84379
29

13751
120821
49

29.23
43.19
67.51

2.53
0.12
2.49

1.58
0.06
1.39

-37.31-48.37-44.3916243
8136-51.33-73993 -117697 52.94
43
20-57.30Constr

686

651

-5.18

17

32

89.94

40.38

20.18

-50.02

669

636

-7.59

Trade

14970

12612

-15.75

536

1056

97.05

27.93

12.00

-57.03

14434

11698

-19.94

Industries

-8187

25.56

HotRest

5307

4020

-24.263867

8690

124.731.37

0.46-66.16

1440

-4602

S to D

Transp

18634

14464

-22.38

6459

8093

25.30

2.89

1.79

-37.90

12175

6548

-47.67

RealEst

8938

7645

-14.47

8382

17917

113.761.07

0.43-59.88556-10325S to D

Public4591

3887-15.34

1934

3489

80.43

2.37

1.12

-52.842657

413-85.04

OthServ

1241

1050

-15.37

1894

2794

47.52

0.66

0.38

-42.50

-653

-1753

167.02

All goods

131424 235937

79.52

175421 231237

31.82

0.75

1.03

37.28

-439978151

D to SAll services

54368

44329

-18.47

23089

42072

82.22

2.35

1.06

-55.10

31279

2614

-92.79185791 280265

50.85

198510 273309

37.68

0.94

1.03

10.36

-1271910765

D to S

SUM

Source: Authors’ calculation
Industry level disaggregated results indicate that while all services would become less exportoriented, a mixed outcomes would happen to goods producing industries. The increase in price ofmining and quarry and petroleum would lead to a reduction in export value of all industries except
mining, quarry and petroleum. In contrast, all commodities except mining and quarry are expected toshow a rise in import value. This result is an obvious consequence of the increase in price of home
produced commodities which shifts the choice towards imported items. Consequently, all industries
except mining and quarry would have a worse trade performance, such as reduction in trade surplus,
expansion in trade deficit… It is also reflected by the fall in export – import ratio in all sectors except
mining and quarry. This result emphasizes the fact that Australia heavily depends on natural resourcesin promoting trade performance in the case of changes in world market condition. The gain of natural
resources based industries goes along with the loss of the remaining industries. Surprisingly, thesurplus of mining and quarry alone offsets the deficits of all other producers.
6.2 Tariff elimination (P1)
6.2.1 Macro results
Generally, macro performance is positive if trade liberalization is implemented entirely throughtariff elimination. The gross production output, value added (GDP), stock of capital, the number of
employed labors and trade balance are projected to improve if tariff abolition is undertaken. For
example, in any world market conditions, removal of import duty alone would cause a positive change
in production output (0.84% and 1.36% in the W1 and W2 respectively), GDP size (1.06% and 1.63%
in the W1 and W2 scenario respectively) and improvement in trade balance (contraction of trade
deficit and expansion of trade surplus in the W1 and W2 respectively). Similar results also happen to
stock of capital, volume of employed labors…The real wage rate (in terms of the imported orexported goods) is expected to increase slightly by 0.04% in the W1 scenario and 0.47% in the W2
scenario. Importantly, the equivalent variation transformed welfare of the entire household sector is
expected to increase slightly in both price scenarios, by 0.05% and 0.06% respectively.
Table 22 Changes in some key aggregate macro variables under the first trade policy P1 (%)
Indicators
Wage rate
Production output

P1-W11
0.04
0.84

45

P1-W22
0.47
1.36

1.06
2.28
0.74
-18.01(Trade deficit falls)
0.05

GDP
Capital stock
Employed labor
Trade balance
EV Welfare

1.63
2.62
0.77
54.75
(Trade surplus rises)
0.06

1: Comparison against the scenario W1 which presents no change in the world prices

2: Comparison against the scenario W2 which presents the change in the world price of primary products

Source: Authors’ calculation
If we consider the first commercial policy (P1) as an illustration of free trade between countries,
the above results go along with mainstream international trade theory that predicts an increase in both
output and welfare.
6.2.2 Production performance
In general, the production sector as a whole would gain if tariff clearance is conducted. Industries
are projected to experience bigger variation in W2 to W1. Under W1, production output, GDP, total
capital use and total volume of employed labors are expected to grow by 0.84%, 1.06%, 2.28% and0.74% respectively. Similarly, under W2, they are projected to increase, but with bigger magnitude,
by 1.36%, 1.63%, 2.62% and 0.77% respectively. If the whole production sector is disaggregated bygoods and services, the same results would occur but the variation in the goods producing sector ismuch stronger than that in the services providing sector. This result is practically consistent because
the former sector relies more on the world market, so benefits more after trade liberalization.
The industry level disaggregated analyses would produce mixed results. All industries except
textile and cloth and metal processing would experience an increase in production output while only
textile and cloth would see a reduction in value added. As expected, mining and quarry would record
the biggest rises, followed by construction. These results are reasonable because textile and cloth andmanufacturing industries are less competitive than others.
Regarding the employment of labor, besides textile and clothing with largest drop in employedlabors, food stuff and metal processing would also recruit fewer labors in W2 condition while all otherindustries would employ more labor. In contrast, mining and quarry would experience the largest
expansion in labor employment.
In terms of capital use, only textile and clothing would record a reduction. Amongst capital use
increasing industries, mining and quarry would show the highest growth, much higher than the closet
followers, basic metals.
Because of above changes in capital and labor employment, capital – labor ratio is expected to risein all industries. Between goods producing and services providing sector, the capital – labor ratio of
the former would be affected more strongly. The largest change is projected to take place inconstruction and commerce services while the smallest variation is expected to happen in agriculture
and forestry industry. All other industries would experience the growth in capital – labor ratio byaround 1%. Australia would become more capital intensive and most capital intensive industries
would expand their production strongly while labor intensive industries (especially unskilled labor
intensive industries such as textile and clothing) would contract or grow slightly. Price of all home
sold commodities is expected to fall after the abolition of import duty. These results partly go alongwith Hecksher-Ohlin theorem8 which predicts there is a reduction in labor intensive industries but
expansion in capital intensive industries.
Table 23 Industry specific changes under the first trade policy P1 (%)

8

Stolper-Samuelson theorem predicts the increase in world price of capital intensive goods would lead to a relative
expansion in production of capital intensive goods and rental rate of capital.

46

Industries

AgrFor

P1W11

P1W22

Price ofhome sold Value added
product
P1P1P1P12 P1P1-W2
W11
W11 W22 W11 W22

0.29

0.44

0.07

0.36

-0.80

-0.37

0.31

Production
outputHome soldoutputCapital –labor ratio

Labor use

Capital use

P1W11

P1W22

P1W11

P1W22

P1W11

P1W22

0.45

0.79

0.57

1.00

0.81

0.21

0.24

MinQuarr

4.78

4.56

2.66

2.04

-1.67

-1.54

4.87

4.67

5.04

4.41

5.72

5.19

0.65

0.75

Food

0.13

0.21

-0.19

0.12

-0.87

-0.33

0.42

0.48

0.37

-0.01

1.28

1.04

0.91

1.05

Texcloth

-6.91

-7.97

-7.78

-8.32

-1.50

-0.88

-6.09

-7.15

-6.13

-7.59

-5.29

-6.64

0.89

1.03

Wood

0.62

0.91

0.48

0.87

-0.64

-0.24

0.84

1.14

0.70

0.55

1.83

1.85

1.12

1.29

Paper

0.29

0.53

0.22

0.51

-0.59

-0.24

0.53

0.82

0.40

0.24

1.53

1.54

1.12

1.29

Petrol

0.98

1.51

0.78

1.01

-0.75

-0.99

0.97

1.94

0.74

1.25

1.87

2.56

1.12

1.29

Chemic

0.88

0.74

0.55

0.65

-0.73

-0.30

1.13

1.04

1.00

0.45

2.13

1.75

1.12

1.29

Nonferr

0.54

0.99

0.47

0.97

-0.71

-0.36

0.92

1.42

0.80

0.84

1.92

2.15

1.12

1.29

Metals
MetProc
Energy

1.57
-0.27

1.24
-0.37

0.21
-0.55

0.61
-0.47

-1.53
-0.89

-0.94
-0.45

2.27
0.27

2.05
0.20

2.15
0.17

1.48
-0.35

3.29
1.29

2.79
0.94

1.12
1.12

1.29
1.29

0.50

0.95

0.49

0.95

-0.73

-0.41

0.63

1.10

0.43

0.44

1.56

1.74

1.12

1.29

Constr

1.33

1.97

1.33

1.97

-0.68

-0.33

1.57

2.21

1.20

1.33

2.71

3.09

1.50

1.73

Trade

0.41

0.79

0.33

0.78

-0.52

-0.15

0.65

1.07

0.42

0.36

1.92

2.10

1.50

1.73

HotRest

0.33

0.54

0.17

0.50

-0.69

-0.27

0.65

0.87

0.53

0.29

1.65

1.59

1.12

1.29

Transp

0.75

1.07

0.54

1.02

-0.63

-0.25

0.89

1.25

0.59

0.47

2.00

2.09

1.40

1.62

RealEst

0.55

0.98

0.53

0.97

-0.50

-0.15

0.58

1.01

0.41

0.38

1.54

1.68

1.12

1.29

1.52

0.92

1.01

2.05

2.31

1.12

1.29

Public

0.81

1.32

0.80

1.32

-0.26

0.15

0.99

OthServ

0.37

0.79

0.36

0.79

-0.43

-0.05

0.62

1.07

0.53

0.53

1.66

1.83

1.12

1.29

All goods

1.23

1.85

0.31

0.57

1.89

2.60

1.16

1.27

3.25

3.63

2.06

2.34

All services

0.69

1.16

-14.49 -33.52

0.80

1.27

0.65

0.66

1.82

2.02

1.16

1.34

SUM

0.84

1.36

0.57

1.06

1.63

0.74

0.77

2.28

2.62

1.53

1.84

1.02

1

: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Once again, mining and quarry industry is expected to gain most from tariff clearance with muchhigher growth rate of production output, GDP and capital and labor use over those of the remaining
industries. In contrast, textile and clothing industry would suffer from a big loss with the highest
contraction of production output, GDP, employed labor and capital stock.

6.2.3 The government sector
Since government consumption spending shares a fixed proportion of total GDP in any period, itschange would be as the same as the change in GDP. Specifically, tariff elimination would cause anincrease in government consumption expenditure by 1.06% in W1 and 1.63% in W2. However,
because of the disappearance of tariff revenue, total tax revenue drops by 0.54% and 0.17% in the
scenario W1 and W2 respectively.
Payment for age pension is expected to rise by 0.04% and 0.47% respectively in W1 and W2
scenario. If tariff elimination is implemented alone, it is expected that the government would have tospend more on subsidy payment (1.42% more in W1 and 1.86% more in W2). It could be interpreted
as further assistance from the government to promote the competition of domestic producers in a morechallenging environment.

47

Table 24 Changes in the government sector under the first trade policy P1 (%)
Indicators
Spending
Other Benefit Transfer
Age Pension
SubsidyTax Revenue

P1-W11
1.06
-3.76
0.04
1.42
-0.54

P1-W22
1.63
-4.28
0.47
1.86
-0.17

1

: Comparison against the scenario W1 which presents no change in the world prices

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Consequently, payment for other benefit transfer would change in an opposite direction. It isprojected to decrease due to tariff elimination, by around 4% as a result of reduction in tax revenue
and increase in other spendings of the government.
6.2.4 The household sector
Table 25 Changes in the household sector under the first trade policy P1 (%)
Indicators
Real aggregate private consumption
Participation rate
Asset holdings
EV Welfare

P1-W11
0.57
0.76
-0.27
0.05

P1-W22
0.60
0.79
0.08
0.06

1

: Comparison against the scenario W1 which presents no change in the world prices

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Similar to the production sector, the household sector overall would get better off if the tariffelimination is simulated. Specifically, equivalent variation transformed welfare of the household
sector is projected to increase slightly in all price conditions, by 0.05% in the W1 scenario and 0.06%
in the W2 scenario. Like above, we follow (Kudrna and Woodland 2011) in adopting the basis ofequivalent variations. This result is consistent with other researches on tariff liberalization in Australia
though they do not incorporate leisure in the utility function. Recent researches such as the ones by(Siriwardana 2006a; Siriwardana 2006b) show that welfare of Australia improves after free trade
agreement with US, Singapore or Thailand comes into effect. In their model, utility is totally driven
by good consumption. As a result, after output expansion, consumption increases and leads to a rise in
welfare. In our model, the increase in output and then commodity consumption are associated with an
expansion in working time which implies a fall in leisure time. The abolition of import duty would
lead to an increase in real private consumption by around 0.6% and participation rate by around 0.8%.
The leisure time contraction has a negative impact on utility but is fully offset by the positive effect ofcommodity consumption rise. Consequently, although it would also lead to an improvement inwelfare, its magnitude is smaller than that of other researches. To our knowledge, until now only
Keuschnigg and Kohler (Keuschnigg and Kohler 1994; Keuschnigg and Kohler 1995) have examinedthe effect of tariff liberalization by using multi-sector OLG CGE models that incorporate leisure in
consumers’ utility. Hence, we have a limited number of relevant models for the purpose of testing our
computing results.
Asset holdings of the household sector are expected to change very slightly. In contrast,
participation rate in the labor force would rise by around 0.8% in both price conditions.
Table 26 Commodity specific changes in private consumption under the first trade policy P1 (%)

48

Commodities

Consumption of home madeproducts
P1-W11

P1-W22

Consumption of imported
products
P1-W11

P1-W22

Consumption expenditure
P1-W11

P1-W22

AgrFor

-0.17

0.15

-1.09

-0.27

-0.22

0.12

MinQuarr

0.93

0.16

-15.78-15.20

-0.22

0.12

Food

-0.23

0.07

0.89

1.43

-0.05

0.31

Texcloth-9.85-11.57

12.66

12.00

5.61

6.73

Wood

-0.22

0.12

NA

NA

-0.22

0.12

Paper

-0.18

0.03

0.03

0.98

-0.15

0.22

Petrol

-0.31

-0.03

0.14

0.57

-0.22

0.12

Chemic

-0.40

-0.80

0.79

1.43

0.29

0.72

Nonferr

-0.65

-0.41

3.05

3.47

1.07

1.46

Metals
MetProc
Energy

-0.25
-3.21
-0.21

-0.68
-4.47
0.13

1.45
5.15
-1.62

2.65
5.19
-0.67

0.33
1.19
-0.22

0.86
1.90
0.12

Constr

-0.22

0.12

NA

NA

-0.22

0.12

Trade

-0.21

0.13

-1.39

-0.21

-0.22

0.12

HotRest

-0.06

0.23

-2.26

-0.63

-0.22

0.12

Transp

-0.20

0.13

-0.41

0.05

-0.21

0.12

RealEst

-0.21

0.13

-1.63

-0.30

-0.22

0.12

Public

-0.20

0.11

-0.66

0.38

-0.22

0.12

OthServ

-0.21

0.13

-0.59

0.08

-0.22

0.12

All goods

-1.12

-0.94

4.82

4.94

0.71

1.22

All services

-0.19

0.13

-1.27

-0.21

-0.22

0.12

SUM

-0.36

-0.05

3.81

3.92

0.01

0.39

1

: Comparison against the scenario W1 which presents no change in the world price2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
The disaggregation by generation level would produce mixed results. Tariff elimination would
lead to an increase in all age specific consumptions and participation rates but a mixed movement inage specific asset holdings. In terms of consumption, the growth rate keeps decreasing as consumers
become older, implying a relative decline in saving of young generations. Differently, the growth rateof participation rate is largest before the retirement age and smallest in mid-career ages. The
magnitude of the policy’s effect on consumption and participation rate is almost the same across twoworld market conditions. Regarding asset holdings, this liberalization policy is expected to cause adrop in all age specific asset holdings except those of eldest cohorts in the scenario W2. And thegreatest variation happens to eldest generations while the smallest change occurs to mid-career ages.
The policy is more significant under the W1 condition. Such changes show that households generally
work more, consume more but save less during their working ages.
6.2.5 Trade performance
Like the case of change in world price, trade performance of Australia after tariff abolition would
show a mixed result. Generally, Australia would improve its trade balance, reducing trade deficit by
18% in W1 condition and increasing trade surplus in W2 condition by 54.75%. Similar variation is
projected to occur to both goods producing and services providing industry. The former would record
an increase in export value, import value and export – import ratio. As a result, goods producing
industry is expected to reduce trade deficit in W1 scenario and expand trade surplus in W2 scenario.
The latter is expected to show a rise in export value and export – import ratio but a fall in import value49

in W1 condition. In W2 condition, all of these indicators of services providing sector would grow.
Eventually, services providing industry would lift its trade surplus in both conditions.
Table 27 Commodity specific changes in export value, import value, export – import ratio and tradebalance under the first trade policy P1 (%)
Industries

Export1

Import2

1

Export-Import Ratio2

12

Trade Balance

P1-W1

P1-W2

P1-W1

P1-W2

P1-W1

P1-W2

P1-W11

P1-W22

AgrFor

1.33

0.93

-0.52

0.06

1.86

0.87

1.57

1.13

MinQuarr

6.64

5.67

-2.49

-3.29

9.37

9.27

11.16

6.31

Food

1.17

0.64

1.23

1.70

-0.06

-1.04

1.10

-4.83

Texcloth

-4.56

-6.46

9.12

9.25

-12.54-14.38

12.82

10.84

Wood

1.94

1.43

3.45

4.14

-1.46

-2.61

5.63

5.52

Paper

1.57

1.06

1.36

1.83

0.21

-0.75

1.29

1.96

Petrol

2.51

3.32

1.63

2.06

0.87

1.24

1.18

0.45

Chemic

2.23

1.34

1.14

1.66

1.08

-0.32

0.79

1.71

Nonferr

2.10

1.79

2.65

3.04

-0.53

-1.21

2.74

3.18

Metals
MetProc
Energy

3.76
1.48
2.17

2.78
0.56
1.89

2.05
3.16
-1.14

2.70
3.79
-0.12

1.67
-1.64
3.34

0.07
-3.11
2.02

4.88
3.40
4.38

2.91
4.00
7.18

Constr

2.99

2.78

0.97

2.19

2.00

0.58

3.04

2.81

Trade

1.51

1.11

-1.36

-0.17

2.92

1.29

1.62

1.23

HotRest

1.76

1.11

-1.95

-0.27

3.78

1.39

11.71

-1.46

Transp

2.25

1.70

0.50

0.85

1.74

0.84

3.18

2.77

RealEst

1.68

1.32

-0.65

0.86

2.35

0.46

36.85

0.51

Public

1.38

0.99

-0.41

0.66

1.80

0.33

2.69

3.90

OthServ

1.34

0.91

-0.02

0.68

1.36

0.23

-2.61

0.54

All goods

4.03

4.52

2.34

3.12

1.65

1.36

-2.70

73.43

All services

1.82

1.35

-0.49

0.57

2.32

0.77

3.53

15.85

SUM

3.38

4.01

2.01

2.72

1.34

1.26

-18.0154.75

1: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Industry level disaggregated results indicate that uneven outcomes would happen to specificindustries. The import duty elimination would lead to a rise in export value of all industries except
textile and clothing. The largest and smallest variation would take place in mining and quarry andfood stuff industry respectively. 11 out of 19 industries would import more in both world pricescenarios are food stuff, textile and clothing, wood and wood processing, paper and paper processing,petroleum, chemicals, non-ferrous minerals, basic metals, metal processing, construction and transport.
The largest and smallest change are expected to textile and clothing and transport respectively.
Industries that would experience the drop in import value in both W1 and W2 are agriculture andforestry, mining and quarry, energy, trade and hotel and restaurant. Industries that would face a mixed
outcome (import value decrease in W1 but increase in W2) are real estate, public and other services.
Consequently, export – import ratio in all services and agriculture and forestry, mining and quarry,
petroleum, basic metals and energy would rise. This ratio of textile and clothing, wood and woodprocessing, non-ferrous minerals and metal processing would decline while that of food stuff, paper
and paper processing and chemicals is expected to rise in W1 but fall in W2.

50

This result emphasizes again natural resources based industries benefit most while labor intensive
manufacturing industries loss much if tariff elimination is undertaken. These results go along with
Heckscher-Ohlin theorem that predicts that a capital abundant country would specialize in and export
capital intensive goods. Actually, most capital intensive commodities would become more exportoriented after the tariff elimination is conducted.
6.3 Subsidy reduction (P2)
6.3.1 Macro results
In general, a reduction in subsidy rate would cause a negative macro performance of the Australianeconomy. The production output, GDP, stock of capital, the number of employed labors and tradebalance are all projected to fall if subsidization decline is undertaken. For example, in any world
market conditions, reduction of subsidy rate would lead to a negative change in production output (by2.5% and 3% in W1 and W2 respectively), GDP size (by 2.93% and 3.55% in the W1 and W2
scenario respectively), stock of capital by around 3%, use of labor by around 1% and worsening oftrade balance (expansion of trade deficit in the W1 and contraction of trade surplus in the W2). The
real wage rate (in terms of the imported or exported goods) is expected to decrease.
Table 28 Changes in some key aggregate macro variables under the second trade policy P2 (%)
Indicators
Wage rate
Production output
GDP
Capital stock
Employed labor
Trade balance
EV Welfare

P2-W11
-1.49
-2.50
-2.93
-3.07
-1.15
23.05
(Trade deficit rises)-0.06

P2-W22
-1.97
-3.04
-3.55
-3.48
-1.18
-74.99(Trade surplus falls)
-0.01

1

: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
6.3.2 Production performance
In general, the production sector as a whole would lose if reduction in subsidization is
implemented. Like the case of import duty elimination, production industries are projected toexperience bigger variation in W2 to W1. Under W1, production output, GDP, total capital use andtotal volume of employed labors are expected to drop by 2.5%, 2.93%, 3.07% and 1.15% respectively.
Similarly, under W2, they are projected to fall, with bigger magnitude, by 3.04%, 3.55%, 3.48% and1.18% respectively. If the entire production sector is disaggregated by goods and services, the same
results would occur but the variation in the goods producing sector is much stronger than that in theservices providing sector.
Unlike the case of tariff elimination, the industry level disaggregated analyses are quite similar
across particular industries. In terms of GDP expansion, all industries would experience a decline intheir valued added of which mining and quarry would record the biggest fall, followed by petroleum
and basic metals. The smallest change is to happen to textile and clothing industry. Similarly, in termsof capital use, all production sectors would record a reduction. Amongst them, mining and quarry
would show the highest drop, followed also by petroleum and basic metals. The least variation is
expected to take place in textile and clothing, too.
Table 29 Industry specific changes under the second trade policy P2 (%)

51

Production
outputHome soldoutputHome soldprice change

Value addedchangeLabor usechange

AgrFor

P2W11
-1.04

P2W22
-1.29

P2P2W11 W22-0.97 -1.33

P2W11
0.24

P2W22
-0.20

P2W11
-1.76

P2W22
-2.01

P2W11
-1.01

P2P2W22 W11-0.87 -1.30

P2W22
-1.20

Capital –labor ratiochangeP2- P2W11 W22-0.30 -0.33

MinQuarr

-5.32

-5.49

-3.58

-3.69

1.54

1.21

-6.43

-6.61

-5.27

-5.03

-6.15

-6.01

-0.92 -1.04

Food

-1.03

-1.20

-1.17

-1.44

-0.40

-0.86

-1.62

-1.80

-0.12

0.19

-1.41

-1.27

-1.29 -1.45

Texcloth

-0.18

-0.13

-0.66

-0.62

-0.79

-1.15

-0.73

-0.76

0.78

1.24

-0.50

-0.20

-1.27 -1.43

Wood

-2.77

-3.20

-2.88

-3.33

-0.55

-0.93

-3.19

-3.65

-1.58

-1.54

-3.14

-3.30

-1.59 -1.79

Paper

-1.78

-2.05

-1.84

-2.12

-0.63

-0.99

-2.16

-2.49

-0.55

-0.38

-2.13

-2.16

-1.59 -1.79

Petrol

-4.46

-6.04

-3.84

-4.72

0.56

0.89

-5.18

-7.08

-3.48

-4.92

-5.01

-6.62

-1.59 -1.79

Chemic

-1.58

-1.76

-1.84

-2.06

-0.59

-0.94

-2.06

-2.31

-0.43

-0.19

-2.01

-1.97

-1.59 -1.79

Nonferr

-2.60

-3.15

-2.64

-3.21

-0.39

-0.77

-3.23

-3.82

-1.64

-1.74

-3.20

-3.49

-1.59 -1.79

Metals
MetProc
Energy

-2.77
-3.21
-2.20

-2.88
-3.36
-2.71

-2.59
-3.25
-2.20

-3.10
-3.48
-2.71

0.20
-0.53
-0.17

-0.35
-0.93
-0.54

-3.93
-3.80
-2.62

-4.09
-4.01
-3.12

-2.37
-2.25
-0.91

-2.04
-1.97
-0.91

-3.92
-3.80
-2.48

-3.79
-3.72
-2.68

-1.59 -1.79-1.59 -1.79-1.59 -1.79

Industries

Capital use
changeConstr

-3.19

-3.90

-3.19

-3.91

-0.36

-0.73

-3.63

-4.35

-1.71

-1.90

-3.79

-4.23

-2.11 -2.37

Trade

-1.86

-2.30

-1.96

-2.41

-0.64

-1.03

-2.35

-2.82

-0.60

-0.55

-2.69

-2.91

-2.11 -2.37

HotRest

-1.19

-1.23

-1.34

-1.38

-0.67

-1.06

-1.60

-1.66

0.02

0.47

-1.56

-1.33

-1.59 -1.79

Transp

-3.30

-3.41

-2.30

-2.89

0.34

-0.22

-4.09

-4.21

-2.28

-1.87

-4.21

-4.05

-1.98 -2.23

RealEst

-2.06

-2.46

-2.09

-2.49

-0.67

-1.05

-2.18

-2.59

-0.51

-0.42

-2.09

-2.20

-1.59 -1.79

Public

-2.48

-3.04

-2.53

-3.09

-1.04

-1.48

-2.79

-3.38

-1.28

-1.39

-2.84

-3.15

-1.59 -1.79

OthServ

-1.92

-2.35

-1.94

-2.37

-0.75

-1.15

-2.37

-2.83

-0.81

-0.79

-2.38

-2.56

-1.59 -1.79

All goods

-2.82

-3.55

-2.38

-2.77

-3.82

-4.71

-1.87

-2.11

-3.94

-4.55

-2.11 -2.49

All services-2.37-2.83 -29.06 -67.42

-2.65

-3.11

-1.00

-0.97

-2.67

-2.83

-1.69 -1.87

SUM

-2.50

-3.04

-2.93

-3.55

-1.15

-1.18

-3.07

-3.48

-1.95 -2.32

-2.32

-2.81

1

: Comparison against the scenario W1 which presents no change in the world prices

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Regarding the employment of labor, except textile and clothing with growth in employed labors,
all other production industries would recruit fewer labors in both of the world market conditions.
Amongst them, the highest movement would be experienced by mining and quarry and petroleum.
Because of above changes in capital and labor employment, capital – labor ratio is expected to
decline in all industries. Between goods producing and services providing sector, the capital – laborratio of the former would be affected more strongly. The largest change is projected to take place inconstruction and commerce services while the smallest variation is expected to happen in agriculture
and forestry industry. All other industries would experience the growth in capital – labor ratio byaround 1-2%. Australia would become less capital intensive and most capital intensive industries
would reduce their production strongly while labor intensive industries (especially unskilled labor
intensive industries such as textile and clothing) would contract slightly. Price of all home produced
commodities except mining and quarry and petroleum is expected to fall after the reduction in subsidy
rate.
Unlike the case of import duty elimination, mining and quarry industry is expected to lose mostafter subsidization reduction with much higher dropping rate of GDP and capital and labor use overthose of the remaining industries. In contrast, textile and clothing industry would suffer from asmallest loss with the tiniest contraction of GDP, employed labor and capital stock.

52

6.3.3 The government sector
Table 30 Changes in the government sector under the second trade policy P2 (%)
P2-W11
-2.93
4.34
-1.49
-53.07-2.14

Indicators
Spending
Other benefit Transfer
Age Pension
SubsidyTax Revenue

P2-W22
-3.55
5.32
-1.97
-53.52-2.62

1: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Since government consumption spending shares a fixed proportion of total GDP in any period, itschange would be as the same as the change in GDP. Specifically, subsidization reduction would cause
a decline in government consumption expenditure by around 3%. Because of the negative change inproduction performance, tax revenue is projected to drop by 2.14% and 2.62% in W1 and W2
respectively. It is projected to increase due to the fall in subsidy rates, by around 4-5%. Payment forage pension is expected to drop by 1-2%. If subsidization reduction is undertaken, it is unsurprisedthat the government would decrease significantly subsidy payment, by around 53% in both world
price scenarios. Consequently, payment for other benefit transfer would change in an opposite
direction in comparison with other components.
6.3.4 The household sector
Table 31 Changes in the household sector under the second trade policy P2 (%)
P2-W11
-0.84
-1.18
-1.01
-0.06

Indicators
Real aggregate private consumption
Participation rate
Asset holdings
EV Welfare

P2-W22
-0.81
-1.23
-1.35
-0.01

1

: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Like the production sector, the household sector overall would get worse off if subsidization
reduction is simulated. Specifically, equivalent variation transformed welfare of the household sector
is projected to decrease slightly in all price conditions, by 0.06% and 0.01% in W1 and W2
respectively. Like above, we follow (Kudrna and Woodland 2011) in adopting the basis of equivalentvariations. In our model, the decline in output and then real private commodity consumption areassociated with a contraction in working time which implies a rise in leisure time. Specifically, real
private consumption and participation rate in the labor force would decline by about 0.8%. The leisuretime increase has a positive impact on utility but cannot exceed the negative effect of commodity
consumption fall. Consequently, it would lead to a tiny decrease in welfare. Asset holdings of thehousehold sector are also expected to decline in all price scenarios, by around 1%.
Table 32 Commodity specific changes in private consumption under the first trade policy P2 (%)
Commodities
AgrForConsumption of home madeproducts

Consumption of imported
products

Consumption expenditure

P2-W11

P2-W22

P2-W11

P2-W22

P2-W11

P2-W22

-1.12

-1.40

-0.84

-1.62

-1.10

-1.42

53

Commodities

Consumption of home madeproducts

Consumption of imported
products

Consumption expenditure

P2-W11

P2-W22

P2-W11

P2-W22

P2-W11

P2-W22

MinQuarr

-2.29

-1.45

15.12

12.21

-1.10

-1.41

Food

-1.07

-1.35

-1.25

-1.73

-1.10

-1.41

Texcloth

0.08

0.52

-1.60

-1.93

-1.07

-1.38

Wood

-1.10

-1.41

NA

NA

-1.10

-1.41

Paper

-0.91

-1.01

-2.22

-3.05

-1.10

-1.41

Petrol

-1.56

-1.79

-1.64

-2.08

-1.58

-1.87

Chemic

-0.29

0.13

-1.69

-2.13

-1.10

-1.41

Nonferr

-1.02

-1.24

-1.20

-1.59

-1.10

-1.41

Metals
MetProc
Energy

-1.29
-2.95
-1.67

-0.98
-2.64
-1.98

-0.75
-0.39
-0.32

-1.91
-1.31
-1.36

-1.10
-1.60
-1.67

-1.41
-1.76
-1.98

Constr

-1.10

-1.41

NA

NA

-1.10

-1.41

Trade

-1.09

-1.40

-2.55

-3.71

-1.10

-1.41

HotRest

-0.96

-1.00

-3.06

-4.33

-1.10

-1.41

Transp

-3.67

-3.97

-0.18

-0.68

-3.50

-3.80

RealEst

-1.09

-1.39

-2.97

-4.30

-1.10

-1.41

Public

-1.04

-1.28

-2.89

-3.89

-1.10

-1.41

OthServ

-1.29

-1.59

-1.58

-2.24

-1.29

-1.60

All goods

-1.49

-1.56

-0.97

-1.65

-1.33

-1.60

All services

-1.31

-1.59

-2.23

-3.48

-1.33

-1.64

SUM

-1.35

-1.58

-1.18

-2.01

-1.33

-1.63

1

: Comparison against the scenario W1 which presents no change in the world prices

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
The disaggregation by generation level would produce mixed results. Subsidization reduction
would lead to a fall in all age specific consumptions and participation rates but a mixed movement inage specific asset holdings. In terms of consumption, the contraction rate keeps decreasing as
consumers become older, implying a relative decrease in saving of young generations. The
contraction rate of participation rate is largest in eldest working ages and smallest in mid-career ages.
The magnitude of the policy’s effect on consumption and participation rate is almost the same across
two world market conditions. Regarding asset holdings, this liberalization policy is expected to causea drop in all age specific asset holdings except those of some eldest cohorts in the scenario W1. And
the greatest variation happens to eldest cohorts while the smallest fall occurs to youngest ages. The
policy is more significant under the W2 condition. Such changes show that households generally work
less, consume less and save less throughout their working lifetime.
6.3.5 Trade performance
Different from the case of change in world price and import duty elimination, trade performance ofAustralia after subsidy reduction changes in an opposite way. Generally, this policy would worsen
Australian trade balance, increasing trade deficit by 23.05% in W1 condition and decreasing trade
surplus by 74.99% in W2 condition. Export value, import value and export-import ratio would all
drop in both of the world market price scenarios.
Table 33 Commodity specific changes in export value, import value, export – import ratio and tradebalance under the second trade policy P2 (%)

54

Industries

Export1

P2-W1

Import
2

1

P2-W2

P2-W1

Export-Import Ratio
2

P2-W2

1

P2-W1

2

P2-W2

Trade Balance
P2-W11

P2-W22

AgrFor

-1.35

-1.02

-0.74

-1.39

-0.61

0.37

-1.43

-0.94

MinQuarr

-6.85

-6.28

0.28

-0.70

-7.11

-5.63

-10.38

-6.68

Food

-0.55

-0.10

-1.27

-1.68

0.73

1.61

0.28

8.09

Texcloth

1.13

2.01

-1.71

-2.02

2.89

4.12

-2.47

-2.43

Wood

-1.67

-1.26

-3.31

-4.03

1.70

2.89

-5.67

-5.43

Paper

-0.43

0.10

-2.18

-2.75

1.79

2.93

-2.74

-3.24

Petrol

-7.47

-9.01

-0.32

-0.58

-7.18

-8.48

3.32

10.14

Chemic

-0.51

0.06

-2.41

-2.93

1.95

3.08

-3.02

-3.37

Nonferr

-1.77

-1.49

-2.34

-2.72

0.58

1.26

-2.43

-2.86

Metals
MetProc
Energy

-3.04
-2.58
-2.67

-2.33
-1.92
-2.35

-2.39
-2.43
-0.61

-3.06
-3.11
-1.75

-0.67
-0.16
-2.07

0.75
1.23
-0.61

-3.47
-2.40
-4.04

-1.07
-3.19
-3.93

Constr

-2.35

-2.21

-3.89

-5.28

1.60

3.25

-2.31

-2.05

Trade

-0.52

-0.10

-2.59

-3.77

2.13

3.81

-0.44

0.23

HotRest

0.17

1.03

-3.55

-4.80

3.86

6.13

10.16

-9.82

Transp

-7.79

-6.98

-1.08

-1.43

-6.79

-5.62

-11.36-14.02

RealEst

-0.59

-0.14

-4.31

-5.77

3.89

5.97

55.52

-9.95

Public

-0.19

0.22

-3.26

-4.30

3.16

4.73

2.03

39.91

OthServ

-0.50

-0.03

-1.95

-2.63

1.48

2.67

-4.71

-4.20

All goods

-4.08

-5.14

-1.91

-2.63

-2.21

-2.58

4.57

-128.74

All services

-2.95

-2.25

-2.96

-4.35

0.00

2.20

-2.95

36.95

SUM

-3.75

-4.68

-2.03

-2.90

-1.75

-1.84

23.05

-74.991: Comparison against the scenario W1 which presents no change

2: Comparison against the scenario W2 which presents only the change in the world price of primary products

Source: Authors’ calculation
Similar variation is projected to occur to both goods producing and services providing industry.
The former would record a decrease in export value, import value and export – import ratio by 4.08%,
1.91% and 2.63% respectively in W1 and 5.14%, 2.63% and 2.58% respectively in W2. As a result,goods producing industry is expected to enlarge trade deficit by 4.57% in W1 scenario and contract
trade surplus by 128.74% in W2 scenario. The latter is expected to show a fall in export value (by2.95%), import value (by 2.96%) and export – import ratio (by 0.00%) in W1 condition. In W2
condition, while export and import value would decline by 2.25% and 4.35% respectively, export –import ratio grows by 2.2%. Eventually, services providing industry would reduce its trade surplus by
2.95% in W1 but increase its trade surplus by 36.95% in W2 condition.
Industry level disaggregated results indicate that uneven outcomes would happen to specificindustries. The subsidization reduction would lead to a fall in export value of all industries except
textile and clothing and hotel and restaurant in W2 condition. The largest variation would take placein mining and quarry, petroleum and transport while the smallest change would happen to public
services. It is not a surprise if we know that highest subsidy rate is given to petroleum and transport.
All industries except mining and quarry would import less in both world price scenarios. The
largest and smallest changes are expected to occur to real estate and petroleum respectively.
Consequently, export – import ratio in food stuff, textile and clothing, wood and wood processing,paper and paper processing, chemicals, non-ferrous minerals, construction, commerce, hotel andrestaurant, real estate, public services and other services would rise. This ratio of mining and quarry,
petroleum, energy and transport would decline while that of agriculture and forestry, basic metals and55metal processing is expected to fall in W1 but rise in W2. This result emphasizes again natural
resources based industries are more vulnerable while labor intensive manufacturing industries are lessaffected if subsidization reduction is undertaken.
6.4 Sensitivity analysis
In order to test the reliability of the model, it is needed investigate whether computed results are
sensitive to specification of some parameters from external sources. Like any other nested structured
CGE models, we focus on Armington elasticities of substitution between home produced andimported commodities, elasticities of transformation between home sales and export and elasticities ofsubstitution between factors of productions in value added function. Higher and lower values for such
elasticities are used to examine how much the economy differs from the benchmark case after a new
scenario is simulated. Particularly, new values of elasticities are assumed to be 29% lower and 25%
higher than the original values. The former shows the possibility in which the economy is lesssensitive to external conditions while the latter indicates the possibility in which the economy is more
vulnerable to world scenarios. Based on that, we can also calculate the remaining parameters tocharacterize the benchmark year of 2005-2006. Next, without losing the generality, we simulate thechange in the world price of primary products, mining and quarry and petroleum (W2) andelimination of all tariffs (P1-W1) for the economy. How the economy varies in the new sets ofparameters is compared against the results in part 1. Actually, the movement direction of variables in
the new specifications of parameters are as the same as the benchmark case. Moreover, the variation
magnitudes are relatively close across contexts. Therefore, we can conclude that the model is reliable
and could be used for further analyses. Particular changes of some key variables in different settingsof parameters are shown in the below table.
Table 34 Changes of some key variables under scenario W2 and P1-W1 in different specifications ofelasticities1
Variables
Asset holdings
Capital stock
Labor use
Participation rate
Wage rate
Equivalent variationtransformed welfare
Production output
GDP
Trade balance

Original
26.3
24.27
3.68
3.68
25.23

W2 (%)
Low
25.31
15.52
2.67
2.75
23.95

High
27.44
33.45
4.67
4.8
26.62

Original
-0.27
2.28
0.74
0.76
0.04

P1-W1 (%)
Low
-0.31
1.76
0.65
0.67
0.01

High
-0.26
2.72
0.81
0.83
0.06

3.54

3.55

3.49

0.05

0.08

0.03

31.72
35.94
Deficit tosurplus

26.78

37.10
42.38
Deficit tosurplus

0.84
1.06

0.55
0.75

1.09
1.31

-18.01-12.82%-22.5829.88
Deficit tosurplus1: Comparisons against the benchmark year

Source: Authors’ calculation

7. Conclusion
If further trade liberalization is implemented through tariff elimination, Australia would be betteroff overall. Not only macro economic indicators, industry specific performance and welfare are also
expected to improve significantly in any world market conditions. Textile and clothing and somelabor intensive industries would suffer from the greatest loss while natural resources based industries

56

would benefit most. In contrast, if subsidy reduction is undertaken, Australia would be negatively
affected both at macro and disaggregated industry and generation level.
Therefore, the optimal liberalization policy for Australia in coming years is to remove tariffbarriers and maintain current subsidization measures. If possible, Australia should swap subsidization
reduction by further decline of import duty in negotiations with its trading partners.
In addition to trade policy, the model could be used to examine effects of other policies, forexample, income tax, consumption tax, social security programs as well as investigate impacts ofsome external conditions such as exchange rate and world interest rate…
Despite some positive aspects, there are some limitations to the employment of the model. For
example, liberalization of trade in services is investigated only through subsidization policy and flows
of capital, especially FDI are not explicitly described. Imperfect competition, economies of scales andproductivity change have not been included. Trade liberalization is analyzed only via unilateral
actions of Australia. The overlapping generation structure is utilized to investigate only the allocation
between commodity consumption and relax time. The age specific preferences of commodity
consumption are still omitted, making analyses on product and industry specific changes less reliable.
This shortage can be handled by collecting more data on age specific features.
For these reasons, the model can be further improved in several dimensions. And if so, theprediction and implication power of the model will be enhanced significantly.

57

A. Appendix
A.1 Technical Appendix
A.1.1 Basic Functions
A.1.1.1 Leontief function (LTF):
,…,
Where

,…,

,…,

,…,

is the Leontief fixed coefficient associated with quantity variable

Dual Leontief function (DLTF):
,…,
Where

,…,

is the price variable associated with quantity variable, ∈A.1.1.2 Constant elasticity of substitution (CES) function

,…,

,…,

Where:: the share coefficient associated with variable, ∈: the elasticity of substitution amongst variables,

0

,∑

1

Dual constant elasticity of substitution (DCES) function

,…,

Where

,…,

is the price variable associated with quantity variable, ∈A.1.1.3 Constant elasticity of transformation (CET) function

,…,

,…,

Where:: the share coefficient associated with variable, ∈: the elasticity of substitution amongst variables,

0

58

,∑

1

, ∈

Dual constant elasticity of transformation (DCET) function

,…,

Where

,…,
, ∈

is the price variable associated with quantity variable

A.1.2 Solutions for the household sector
Following (Auerbach and Kotlikoff 1987), we can solve for decisions of the household sector once
all exogenous variables are known.
1

:

1

,

1

1

,

,

,

Subject to following life time budget constraint:
1

,

1

,

1

1

,

,

,

1

The first order conditions give us Euler equations characterizing the evolution of consumption(equation (6) in the main text):
,

1

,

1
,

,

More specifically,

1

,

1

,

,

,

,

,

59

1

1

1

1

,

,

,

1
1

,

,

1

,

The intra-allocation between consumption and leisure time before retirement:,

1,

So, we have:

,

,

1

Substitute it back to (6) we have:
1
,

1

,

1

,

,

Where:
1,

1

A.1.3. Inclusion of tax, duty and subsidy in aggregate price indexes
In our model, like quantity variables, prices also have a nested structure. Therefore, price index ofany aggregate commodity can be expressed as a function of grass-root prices or price of home soldproduct, imported or exported single products as well as commodity use tax, import duty and subsidy.
For nested CES structure:
The intermediate level or price of industry specific composite good (? represents C, K, Q or G):
?
,

?,

?

1

?

?

?
,

1

?,

?

1

The top level or price of aggregate good: (? represents C, K or G):

60

?

?

?
,

?

?
?

?

?

?
,

For CET structure:

,

,

1

,

1

Therefore, above the grass-root level, all price indexes are inclusive of taxes, duties and subsidies.
A.1.4. Equations for steady state equilibrium
A.1.4.1 Household sector

,

,

,

1
1

,

,

,

(S1)

1

,

(S2)

,

1

(S3)

,

(S4)

,

,

1

1

,

1

,

,

(S5)

,

(S6)

,

1

1

1

,

1

,

,

(S7)

,

(S8)

∑

(S9)

,

61

,

1
,

,

1

,

1

,
,

1

,

(S10)

1

,

,
,

1

,

,

,

,

,

1

1

,

1

,

(S11)

,

1

,

,

,

,

1

1

,

,

,

(S12)

(S13)

,

(S14)

,

(S15)

,

(S16)

A.1.4.2 Production sector

1

,

S(17)

,

,

(S18)

,

,

,

,

1

,

(S19)

,

1

1

,

,

,

1
,

,
,

1

,

,

,

,

1

,

,

(S20)

1

1
∑

,

,

62

(S21)

(S22)

,

,

,

2
,

1

1

,

1

(S25)

1

,

,

(S26)

,

1

,

(S24)

,

,

,

(S23)

,

,

,

2

,

(S27)

1

(S28)

,

(S29)

,

,

,

,

(S30)

,

(S31)

,

(S32)

(S33)

∑

,

,

(S34)

,

,
,

1

,

,

,

1

,

,

(S35)

1

,

1

,

1

,

1

,

,

1
1

,

,

,

,

1

1

,

,

,

,

,

1

,

63

1

(S36)

,

(S37)

,
,

1

,

,

,

,

1

,

(S38)

,

1

1

,

,

,
,

1
1

,

,

,

,

1

1

,

1

1

,

(S40)

,

,

(S41)

,

,

(S42)

,

,

,

(S39)
1

,

1

,

,

,

1

,

,

,

,

,

,

,

,

,

,

(S43)

,

1

A.1.4.3 Government sector
(S44)
,

,

,

,

,

,

1

,

,

,

,

(S45)

(S46)

,

0

,

,

1

(S47)
(S48)

∑

,

64

(S49)

,

,
,

,

,

,

,

,

,

,

,

,

,

,

1

(S51)

,

1

,

,

(S50)

,

1

,

1
,

,

,

(S52)

,

A.1.4.4 Equilibrium

,

,

(S53)

,

(S54)

=
,

,

,

,

,

(S55)

,

,

,

,

,

(S56)
(S57)
(S58)

,

,

,

(S59)

1

(S60)
A.2. Aggregation concordance
Table A1 Industries/Commodities in the model
Ref. No.
1

Name of 19 industries/commodities

BriefsAgriculture and Forestry

AgrFor2

Mining and Quarry

MinQuarr

3

Food stuff

4

Textile and Clothing

Texcloth5

Wood and Wood processing

Wood

Food

6

Paper and Paper processing

Paper

7

Petroleum

Petrol8

Chemicals excluding Petroleum

Chemic9Non-ferrous minerals

Nonferr

10

Basic metals

Metals11

Metal processing

MetProc

65

Ref. No.

Name of 19 industries/commodities

Briefs12

Energy and Water supply

Energy13Construction

Constr14

Commerce

Trade

15

Hotels and Restaurants

HotRest16

Transport and Communication

Transp17

Banking, Insurance and Real Estate

RealEst18

Public service

Public19

Other services

OthServ

Table A2 Industries/Commodities in the IO Tables

0101

Industries/Commodities
in the IO Table
Sheep

0102

1

2701

Grains

1

2702

0103

Beef cattle

1

2703

Industries/Commodities
in the IO Table
Iron and steel
Basic non-ferrous metaland products
Structural metal products

0104

Dairy cattle

1

2704

Sheet metal products

10

0105

Pigs

1

2705

10

0106

Poultry

1

2801

0107

1

2802

11

1

2803

Railway equipment

11

0300

Other agriculture
Services to agriculture;hunting and trapping
Forestry and logging

Fabricated metal products
Motor vehicles and parts;
other transport equipment
Ships and boats

1

2804

11

0400

Commercial fishing

1

2805

11

1101

Coal

2

2806

AircraftPhotographic and scientificequipment
Electronic equipment1201

Oil and gas

2

2807

Household appliances

11

1301

Iron ores

2

2808

11

1302

Non-ferrous metal ores

2

2809

1400

Other mining

2

2810

1500

Services to mining

2

2901

Other electrical equipment
Agricultural, mining andconstruction
machinery,liftingandmaterial
handling equipment
Other
machineryandequipment
Prefabricated buildings

2101

Meat and meat products

3

2902

Furniture

11

2102

Dairy products
Fruit
and
vegetable
products
Oils and fats
Flour mill products andcereal foods

3

2903

Other manufacturing

11

3

3601

Electricity supply

12

3

3602

12

3

3701

IO Code

0200

2103
2104

IO CodeConcordanceConcordance
10
10
10

11

11

11
11
11

2106

Bakery products

3

4101

2107

Confectionery

3

4102

Gas supply
Water supply; sewerageand drainage services
Residentialbuilding
construction
Other construction

2108

Other food productsSoft drinks, cordials andsyrups34201

Construction trade services

13

3

4501

Wholesale trade

14
14

2105

2109
2110

Beer and malt

3

4502

Wholesalerepairs2113

Wine, spirits and tobacco
products

34503

Other wholesale repairs

66

mechanical

12
13
13

14

2202

Industries/Commodities
in the IO Table
Textile fibres, yarns andwoven fabrics
Textile products

4

5102

Retail mechanical repairs

14

2203

Knitting mill products

4

5103

14

2204

Clothing

4

5701

2205

Footwear
Leatherandleather
products
Sawmill products

4

6101

4

6201

5

6301

Other retail repairs
Accommodation, cafes andrestaurants
Road transport
Rail, pipeline and othertransport
Water transport

Other wood products
Pulp,
paper
and
paperboard
Paper containers andproducts
Printing and services toprinting
Publishing;recorded
media and publishing
Petroleumandcoal
products

5

6401

6

6601

6

7101

Communication services

16

6

7301

Banking

17

6

7302

Non-bank finance

17

7

7401

Insurance

17

2502

Basic chemicals

8

7501

2503

PaintsMedicinalandpharmaceutical products,
pesticides

8

7701

Servicestofinance,investment and insurance
Ownership of dwellings

8

7702

Other property services

IO Code
2201

2206
2301
2302
2303
2304
2401
2402
2501

2504

IO CodeConcordance
45101

Industries/Commodities
in the IO Table
Retail trade

Air and space transport
Servicestotransport;
storage

Concordance
14

15
16
16
16
16
16

17
17
17

2505

Soap and other detergents

8

7801

2506

Cosmetics andpreparations

8

7802

2507

Other chemical products

8

7803

2508

Rubber products

9

8101

2509

Plastic products

9

8201

Scientificresearch,technical and computer
services
Legal,
accounting,marketing and business
management services
Other business services
Government
administration
Defence

2601

Glass and glass products

9

8401

Education

18

2602

Ceramic products
Cement,lime
andconcrete slurry
Plaster and other concrete
products
Othernon-metallic
mineral products

9

8601

Health services

18

9

8701

Community services

18

9

9101

9

9201

2603
2604
2605

toiletry9501

Motion picture, radio andtelevision services
Libraries, museums andthe arts
Sport,
gambling
andrecreational services
Personal services

9601

Other services

9301

67

17
17
17
18
18

19
19
19
19
19

A.3. Parameters
Table A3 Fixed coefficients in Leontief production output function and Productivity coefficient invalue added function
θQHjk

Ref. No.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

Y

A

No.

BriefsAF

MQ Food TC Wood Paper Petrol Chem Nonfe Metals MetP Ener Con TradeHoRe Tran Real PublicOther VA

TFP

1AgrFor

0.37 0.00 0.56 0.14 0.23

0.02

0.00

0.02

0.01

0.00

0.00 0.00 0.00 0.02 0.06 0.00 0.00 0.00 0.04

1.65

1.07

2

MinQua0.00 0.14 0.01 0.00 0.00

0.01

0.78

0.02

0.15

0.34

0.00 1.02 0.02 0.06 0.01 0.00 0.00 0.01 0.01

1.25

1.14

3

Food

0.07 0.00 0.23 0.10 0.00

0.00

0.00

0.04

0.00

0.00

0.00 0.01 0.01 0.06 0.30 0.00 0.01 0.01 0.07

0.70

1.79

4

Texcloth 0.00 0.00 0.00 0.22 0.00

0.01

0.00

0.00

0.01

0.00

0.01 0.01 0.01 0.00 0.01 0.00 0.00 0.01 0.02

0.87

1.75

5

Wood

0.00 0.00 0.00 0.00 0.24

0.01

0.00

0.00

0.01

0.00

0.04 0.01 0.15 0.00 0.00 0.00 0.00 0.01 0.01

1.27

1.77

6

Paper

0.00 0.00 0.04 0.03 0.02

0.33

0.00

0.03

0.03

0.00

0.01 0.02 0.04 0.05 0.03 0.02 0.03 0.06 0.08

1.80

1.79

7

Petrol0.04 0.03 0.00 0.00 0.01

0.01

0.06

0.03

0.04

0.01

0.01 0.18 0.06 0.02 0.01 0.07 0.01 0.01 0.02

0.33

1.37

8

Chemic0.07 0.01 0.01 0.02 0.05

0.08

0.04

0.27

0.24

0.01

0.03 0.13 0.08 0.01 0.01 0.00 0.01 0.02 0.05

0.75

1.80

9

Nonferr0.01 0.00 0.04 0.01 0.02

0.05

0.00

0.05

0.31

0.01

0.04 0.09 0.46 0.01 0.01 0.01 0.00 0.01 0.02

1.55

1.79

10

Metals0.01 0.02 0.02 0.01 0.05

0.02

0.00

0.03

0.06

0.25

0.22 0.11 0.41 0.01 0.01 0.02 0.01 0.02 0.03

0.51

1.76

11

MetProc 0.02 0.02 0.01 0.02 0.03

0.02

0.01

0.01

0.03

0.01

0.23 0.20 0.20 0.08 0.02 0.08 0.02 0.10 0.09

0.86

1.75

12

Energy0.03 0.02 0.02 0.02 0.04

0.05

0.01

0.03

0.14

0.04

0.03 1.60 0.04 0.03 0.07 0.04 0.04 0.05 0.06

8.70

1.53

13

Constr

0.02 0.05 0.01 0.01 0.03

0.01

0.06

0.01

0.02

0.01

0.01 0.92 2.81 0.05 0.06 0.07 0.06 0.08 0.02

3.27

1.73

14

Trade

0.15 0.05 0.15 0.15 0.16

0.16

0.05

0.15

0.16

0.06

0.22 0.43 0.35 0.17 0.21 0.20 0.09 0.11 0.22

1.61

1.80

15

HotRest0.01 0.00 0.03 0.01 0.01

0.03

0.02

0.02

0.02

0.01

0.01 0.05 0.00 0.02 0.00 0.02 0.04 0.02 0.05

1.13

1.78

16

Transp0.11 0.06 0.17 0.10 0.24

0.25

0.04

0.15

0.29

0.09

0.09 0.39 0.34 0.29 0.11 0.24 0.16 0.19 0.34

1.13

1.78

17

RealEst0.09 0.09 0.08 0.08 0.19

0.34

0.09

0.17

0.25

0.09

0.19 0.93 1.03 0.40 0.22 0.26 1.02 0.30 0.60

3.28

1.74

18

Public0.00 0.00 0.01 0.01 0.01

0.03

0.01

0.02

0.01

0.00

0.01 0.06 0.04 0.01 0.01 0.03 0.04 0.09 0.04

3.74

1.48

19

OthServ

0.00 0.00 0.01 0.00 0.01

0.02

0.00

0.01

0.01

0.00

0.01 0.05 0.04 0.02 0.10 0.01 0.06 0.05 0.29

2.64

1.69

Source: Calibrated
Table A4 Share parameters in top aggregate goods

No.

Industries

Share parameters incapital good

Share parameters inprivate good

Share parameters ingovernment goodθCj0.0137

θGj
0.0026

1

AgrForθKj
0.0108

2

MinQuarr

0.01050.00140.00063

Food

0.00110.08240.0002

4

Texcloth0.00270.02240.00005

Wood

0.00060.00040.0000

6
7
8
9

Paper
PetrolChemicNonferr

0.00350.00030.00120.00280.01490.02470.01490.00450.00000.00000.02230.000010

Metals

0.01270.00270.000011

MetProc

0.21800.06910.0000

12
13
14
15

EnergyConstr
Trade
HotRest0.01750.50350.07480.00000.02540.00150.19120.07560.00530.01690.01050.000068

Share parameters incapital good

Share parameters inprivate good

Share parameters ingovernment goodθCj0.01370.06310.2496
0.0762

θGj
0.0026
0.03870.02880.78790.06650.0863

No.

Industries

1
16
17
18

AgrForTransp
RealEstPublicθKj
0.01080.02990.10500.002619

OthServ

0.0024

Source: Calibrated
Table A5 Share parameters of home made products in composite commodities and capital stock invalue added
Capital goodPrivate good

Government good

Value added

Production
outputRef. No.

Briefs

θKHj

θCHj

θGHj

θYj

θZj

1
2

AgrFor
MinQuarr

1.00000.74750.8046
0.55531.00001.00000.99800.90530.0661
0.52493

Food

1.00000.75661.00000.46700.11704

Texcloth0.70740.41771.00000.29570.3127

5

Wood

1.00001.00001.00000.44340.1401

6

Paper

0.5862

0.63651.00000.40560.0836

7

Petrol1.00000.96071.00000.74290.21708

Chemic1.00000.47500.39080.42610.24689Nonferr0.80240.51681.00000.39050.0784

10

Metals

0.79790.53971.00000.35220.4078

11

MetProc

0.39990.48161.00000.32270.1925

12Energy1.00000.91431.00000.65850.006113

Constr1.00001.00001.00000.49420.016614

Trade

1.00000.83171.00000.36000.113815

HotRest1.00000.64951.00000.39270.159916

Transp1.00000.89921.00000.47580.2231

17

RealEst0.72630.79771.00000.5391

0.044718

Public1.00000.76391.00000.16740.0491

19

OthServ

0.97640.88651.00000.27340.0455

Source: Calibrated
Table A6 Share parameter of home made products in intermediate inputs
θQHjk

Ref. No.

1

2

3

4

5

6

7

8

9

10

11

12

13

No.

Briefs

AF

MQ

Food

TC

1

AgrFor0.96

0.94

0.921 0.95

0.996

0.97

0.00

0.772 0.743 0.922 0.845 0.848 0.607 0.919 0.881 0.893 0.81

0.91

0.819

2

MinQua0.62

0.72

0.657 0.67

0.608 0.646

0.48

0.671

0.563 0.576 0.72 0.662 0.495 0.643 0.653 0.659

0.66

0.611

3

Food

0.93

0.87

0.796 0.99

0.941 0.876 0.972 0.788 0.954 0.951 0.908 0.875 0.863 0.848 0.814 0.849 0.822

0.81

0.848

4

Texcloth

0.46

0.51

0.451 0.42

0.461 0.384 0.478

0.43

0.455

5

Wood

0.58

0.63

0.589 0.51

0.704 0.733 0.618 0.582 0.594 0.616 0.669 0.741 0.744 0.654 0.704 0.717 0.75

0.71

0.661

6

Paper

0.77

0.6

0.815 0.86

0.43

0.79

0.839

14

15

16

17

18

19

Wood Paper Petrol Chem Nonfe Metals MetP Ener Con Trade HoRe Tran Real Public Other

0.43

0.65

0.395 0.448 0.466 0.416 0.518 0.508 0.365 0.438 0.454

0.464 0.742 0.779 0.707 0.704 0.808 0.791 0.777 0.798 0.807 0.847 0.86269Petrol

0.74

0.7

0.947 0.96

0.865 0.953 0.616

0.91

0.972 0.896 0.982 0.87 0.683 0.878 0.941 0.854

0.9

0.87

0.903

8

Chemic0.55

0.55

0.627 0.55

0.502 0.457 0.463

0.52

0.478 0.513 0.554 0.389 0.578 0.527 0.622 0.594 0.541

9

Nonferr

0.78

0.73

0.813 0.77

0.782 0.671 0.702 0.776 0.876

10Metals

0.78

0.7

0.832 0.66

0.71

11

MetProc

0.49

0.45

0.679 0.74

0.761 0.634

12Energy0.9

0.93

0.922 0.91

13Constr

0.96

0.95

1.00

14

Trade

0.95

0.92

15

HotRest0.61

16

Transp17

RealEst

18
19

7

0.51

0.478

0.666 0.722 0.902 0.711 0.736 0.574 0.728

0.57

0.613

0.736 0.965 0.711 0.693 0.783 0.719 0.621 0.774 0.722 0.548 0.784 0.71

0.58

0.579

0.508 0.536 0.553 0.444 0.472 0.573 0.48 0.529 0.551 0.444

0.47

0.41

0.927 0.924 0.924

0.92

0.941 0.929 0.924 0.927 0.916 0.935 0.925 0.919 0.907

0.93

0.919

0.968 0.983 0.944

1.00

0.985

1.00

0.97 0.982

0.98

0.982

0.954 0.95

0.931 0.925 0.968 0.954

0.93

0.945 0.956 0.931 0.946 0.925 0.957 0.925 0.901

0.95

0.939

0.64

0.671 0.69

0.641 0.609 0.557 0.633 0.659

0.64

0.671 0.626 0.661

0.62

0.633

1.00

0.99

0.998 1.00

0.998

0.99 0.981 0.998 0.995 0.993 0.991 0.961

0.97

0.985

0.68

0.7

0.695 0.69

0.709 0.708 0.694 0.705 0.692 0.725 0.713 0.715 0.727 0.723 0.729

0.72 0.728

0.72

0.715

Public0.71

0.8

0.759 0.73

0.753

0.812 0.765

0.79

0.739

OthServ

0.93

0.92

0.974 0.94

0.981 0.947 0.992 0.948 0.963 0.962 0.973 0.891 0.913 0.955 0.959 0.941 0.74

0.91

0.805

1.00

1.00

0.79

0.88

0.79

0.985 0.996 0.998 0.996

0.76

0.758 0.762 0.779

1.00 0.992 1.00 0.976 0.94

0.643 0.638 0.607 0.6

0.76 0.748 0.859 0.801 0.75

Source: Calibrated
A.4. Data on taxes, import duty and subsidy
Australian taxes and subsidies consist of several types and have a complicated structure. The
calculation methods are also a complexity. Because of limited data condition on taxes and in order tomake computation jobs possible, we simplify tax and subsidy policy to be used in our model.
Accordingly, based on available relevant data from Input – Output Tables, only product provision or
use related taxes (), subsidy rate (), value added output production taxes (), personal
income tax () and of course, import duty () are taken into account.
A.4.1. All product related taxes except import duty
Information on product provision or use related taxes and subsidies can be obtained from Table 34,
35, 36, 37 and 38 of which Table 36 contains import duty while Table 34 provides the net of all
product supply or use related taxes and subsidies and Table 38 is about subsidy.
Table 34 reveals the net taxes, which is taxes less subsidies, associated with the provision ofdomestic and imported products to intermediate usage and final use categories. Major contributors aregoods and services (GST) taxes, sales tax, excises and levies (most importantly excices and levies on
crude oil and LPG) and taxes on international trade (export related taxes and import duties). For GST
taxes, the rate of 10% is applied on the supply of most goods and services to final private
consumption.
Table 36 exhibits separately the duty, mostly imports duty associated with the provision ofdomestic and imported products to intermediate usage and final use categories. Table 38 provides dataon subsidy to consumption of each commodity and use purpose.
Hence, we can subtract figures in Table 36 and Table 38 from figures in Table 34 to calculate all).
other product related taxes except import duty, or commodity use tax as we denote in our paper (), subsidy rate () and commodity use tax rate ()
Based on that, we can calculate tariff rate (for different types of product in different use purposes by dividing tax revenue or subsidy value
against their total sales values at basic prices. Actually, the commodity use tax rate, subsidy rate or
duty against the intermediate use of a product is different from industry to industry. For exports,
commodity use tax is interpreted as export tax ( , ) that producers have to pay for the Australian
government before selling their products in foreign markets.
In our model, product related taxes or commodity use tax rate, subsidy rate and import duty go
directly to the bottom level of our CES or CET price structure, being added to the basic price of goods

70and services. As a result, any price indexes above the bottom level are inclusive of product related
taxes and subsidy. For example, the top aggregate private consumption price ( ) are the net pricepaid by households before consumption.
In general, the commodity tax rate for the entire economy is 4.15% but it is different across use
purposes. This tax rate is 2.05%, 9.85% and 5.81% against intermediate use, final private
consumption (very close to flat GST rate of 10%) and capital formation respectively. The highest
commodity tax rate at 47.16% is faced by petroleum industry, mostly caused by high excise tax
against petroleum products, then followed by food and stuff industry (18.28% - which is chiefly
caused by high excises against consumption of alcohol drinks and tobacco), textile and clothing(14.43%), hotel and restaurant (11.94%) and finally, the lowest commodity tax rate at 0.24% is given
to public services industry which are mainly contributed by government conducted activities ofservices.
In consumption as intermediate inputs, petroleum and food and food stuff face highest rate andother service, 41%, 5.6% and 2.6% respectively while all of the remaining products are subject tovery tiny rates, all below 1%.
In final private consumption, very high product related tax rate against petroleum, mining andquarry, food, textile and clothing are also caused by very high excise or mining tax against some of
their components such as fuel, alcohol drinks, tobacco…
In capital formation, real estate and paper have highest rate, 33.1% and 13.7%.
Table A7 Commodity use tax rates
No.

Briefs1

AgrForIndustry
Supply0.0056

2

MinQuarr

30.0185

Capitalformation
0.00340.00320.64240.00000.00110.00620.0046Food

0.05640.36690.00000.04000.25740.18284Texcloth

0.00030.26780.05160.00000.20920.1443

5

Wood

0.00300.06370.00240.00000.01090.00396Paper

0.00110.16700.13720.00000.13940.0372

7

Petrol

0.4096

0.72600.00000.26620.60480.4716

8

Chemic0.00050.20030.00000.00000.08790.03359

Nonferr

0.00140.26140.01000.00000.13740.017010
11
12

Metals
MetProc
Energy0.00200.00030.00260.11910.13790.09490.00060.03960.00000.00000.00750.00220.00490.0692
0.06600.0031
0.04300.029313

Constr

0.00210.00000.04070.00000.03940.025514

Trade0.00190.02130.00000.00440.01620.0111

15

HotRest0.00120.17950.00000.06970.16580.119416

Transp0.00070.07920.00000.00800.04150.0174

17

RealEst0.02540.02570.33120.02930.06290.0391

18

Public0.00010.01130.01860.00150.00260.002419

OthServ

0.02550.14040.04700.13380.09580.0743

Industry

0.02050.09850.05810.0146

0.05990.0415

HH Cons

ExportFinal use

TOTAL

0.02380.01830.0105

Source: (ABS 2009) and authors’ calculation
For export tax, six industries do not have to pay tax (textile and clothing, wood and woodprocessing, chemicals, nonferrous mineral, metals and construction) and all nine remaining industries
have to pay an industry specific export tax rate. The highest export tax rate at 26.62% is faced by71petroleum industry, followed by other services (13.38%) and hotel and restaurant (6.97%). The
economy wide export tax rate is very small, at 1.46%.
Above tax rates are interpreted into total product related tax revenue except duties of $86 billions
in the benchmark year of which $20, $49.46, $14 and $27 billions come from intermediate use, final
private consumption, capital formation and export, respectively. In terms of commodities, the biggest
contributors are food and stuff ($12.7 billions), real estate ($10.5 billions).

A.4.2 Subsidy
In our model, subsidy is also a part of trade policy. Trade liberalization requires gradual abolitionof subsidization programs to support domestic producers. This practice implies there is nodiscrimination between local and foreign firms, assuring fair competition in the market. There aremany forms of subsidization, such as tariff concessions, tax incentives, grants, concessional loans orexport assistance (WTO 2007). Because we don’t have enough data, a single aggregate subsidy is
proposed to include all forms of subsidization. According to (ABS 2000), product specific subsidies
are regarded as negative taxes and so, if buyers buy some products which attract a subsidy, theamount of subsidy is deducted from taxes on products paid by them. In IO tables, subsidies are shown
to be associated with the supply of domestic and imported products to intermediate or final usage.
Since the amount of subsidies associated with supply of imported products is very small andnegligible, it is reasonable to assume that subsidies associated only with supply of home produced
products. This simplification is consistent with the goal of Australia’s subsidization policy to support
domestic production (WTO 2007). In our model, subsidy rate is calculated by dividing the amount ofsubsidies by their corresponding sales values at basic prices.
Table A8 Subsidy rate
No.

Briefs

1
2

AgrFor
MinQuarrIndustry
Supply0.00040.00000.00000.0000Capitalformation
0.00000.00003

Food

0.00000.00000.00000.00000.00000.00004

Texcloth

0.00000.00000.00000.00000.00000.00005

Wood

0.00000.00000.00000.00000.00000.00006Paper

0.00000.00000.00000.00000.00000.00007

Petrol0.27680.02110.00000.05070.02990.1841

8

Chemic0.00000.00000.00000.00000.00000.00009

Nonferr

0.00000.00000.00000.00000.00000.000010
11
12

Metals
MetProc
Energy0.00000.00000.01160.00000.02320.01250.00000.02360.00000.00000.00820.01360.00000.01980.00870.00000.01180.010413

Constr0.00000.00000.00000.00000.00000.000014

Trade

0.00000.00000.00000.00000.00000.000015

HotRest0.00000.00000.00000.00000.00000.000016

Transp0.01040.05370.00000.0561

0.04260.0237

17

RealEst0.00000.00000.00000.00000.00000.000018
19

PublicOthServ

0.00000.00550.00000.00440.00000.00360.00000.00420.00000.00300.00000.0038Industry

0.00640.00550.00200.00720.00420.0052

HH Cons(Source: (ABS 2009) and authors’ calculation)

72

ExportFinal use

TOTAL

0.00000.00000.00000.00000.00030.0000

The production of six commodities (agriculture and forestry, petroleum, metal processing, energy,transport and other services) receives subsidy from the Government. The subsidy rate for the wholeeconmy is 0.52% in which the highest rate is for consumption of petroleum (18.41%) and transport(2.4%). The largest subsidy is given to consumption of petroleum ($4.4 billions) and transport ($3.8
billions) in the total subsidy payment of $9.7 billions. In terms of use purpose, most of subsidy isprovided to intermediate input use ($5.5 billions). $2.5 and $1.3 billions are for final private
consumption and export promotion respectively.

A.4.3. Import duty
Open trade policy has been followed by Australia for a long time, being targeted at opening newmarkets, reducing barriers and improving market access for Australian goods and services. At thesame time, domestic market is also liberalized gradually for foreign goods and services. In fact, theAustralian government has engaged in several trade liberalization negotiations (eg., in the World
Trade Organization (WTO), Asia-Pacific Economic Cooperation (APEC) forum and the Associationof South East Asian Nations (ASEAN) and some bilateral Free Trade Agreements...). As a result,
Australia is globally recognized as a deeply open economy with low level of trade protection (ABS2010c).
In fact, there are two main types of trade barriers against imports of goods and services, tariff andnon-tariff barriers. While the former can be easily quantified and is mostly used against import ofgoods, it is very hard to do the same job with the latter which cover a wide range of measures against
import of both goods and services. In modern international trading context, non-tariff measures aremajor trade barriers employed by countries. Both tariff and non-tariff barriers may vary amongst
different sources and types of imports. For these reasons, numerical economic models including CGE
models often use tariff barriers rather than non-tariff ones in measuring trade openness degree
although a comprehensive and accurate indicator must cover both. In some models, tariff equivalentmeasures can be calculated for non-tariff barriers. Nonetheless, this calculation requires a lot of works
and its accuracy is still controversial.
Table A9 Tariff rate
No.

BriefsIndustry
SupplyPrivateconsumption

Capitalformation

Final use

TOTAL

1

AgrFor0.00000.00000.00000.00000.00002

MinQuarr

0.00000.00000.00000.00000.00003

Food

0.01800.01420.00000.01420.01584Texcloth0.05440.10770.03800.10660.08895

Wood

0.01950.00000.00000.00000.0196

6Paper

0.01170.00550.00000.00430.01007

Petrol0.00040.00000.00000.00000.00038

Chemic0.00730.01040.00000.00600.00689Nonferr

0.0276

0.03490.02260.03270.0284

10

Metals

0.01940.01780.02060.01890.0194

MetProc

0.01320.03110.01830.02240.0191

Industry use

0.01200.03700.01830.02660.0185

11(Source: (ABS 2009) and authors’ calculation)
Indeed, Australia has a complicated structure of protection barriers that can take several different
forms such as tariff, quota, subsidy, import/export licensing, anti-dumping measures, and technicalregulations, etc... Of course, it is impossible to quantify and incorporate all forms of protection into asingle model. Moreover, the intra-industry structure of CGE requires a lot of data dimensions for any
type of barrier that is practically infeasible. Therefore, we concentrate only on tariff barriers and73

ignore all other types of protection in our model. Import duty data can be taken from relevant IO
tables. Similar to other countries, import duties in Australia are levied against tradable goods only
(agricultural, primary and manufacturing commodities). Although services sector and some nontradable good producing industries (ie., energy) also perform import and export activity, their nature ismuch different from that of producing sector. And because protection measures against import ofservices and non-tradable goods are all non-tariff, trade restriction against them is not analyzed by ourmodel.
In our paper, the trade policy is partly reflected through the tariff rate for different use purposes
and products (besides subsidization). In general, Australia is a largely liberalized economy with low
tariff rates on average. If we use import weighted average method, the average tariff rate of Australiais 1.85% in the benchmark year 2005-2006. However, import duty is uneven across commodities anduse purposes.
In 2005-2006 (the year considered to be the benchmark for our economy), the average tariff rate
against imports used for intermediate input, investment and private consumption is 1.20%, 1.83% and3.70%. However, trade barriers are applied against only 9 out of 11 tradable commodities: food stuff,
textile and clothing, wood and wood processing, paper and paper processing, petroleum, chemicals
excluding petroleum, non-ferrous minerals, basic metals, metal processing. The industry with highest
protection is textile and clothing, followed by non-ferrous minerals and basic metals.
In our model, import duty is used to measure liberalization level. This practice is reasonable since
tariffs have been still considered to be essential trade barriers in Australia (WTO 2007). Table 34
contains information on import duty revenue while Table 3 provides information on import values for
all groups of products and purposes of use. Dividing numbers in the former table by theircorresponding numbers in the latter table gives us import duty rate or tariff rate () against different
types of product in different use purposes. Obviously, import duty varies across different types of
product. Moreover, it is interesting that for a specific type of product, import duty can change between
use purposes because we do not process the data at tariff line level. Commodities in our model areaggregate of sub-items whose structure may change across use purposes. Moreover, it is partly causedby the fact that import duty may change from trading partner to trading partner (some get morefavorable treatments than the others when sell their products in Australia) and product to product. In
addition, for a specific product, different use purpose may lead to a change in sources of import. For
example, the use of imported food stuff for agricultural production is in favor of goods from country
A while for mining and quarry production, it is in favor of goods from country B. That import duty
against imported food stuff is different between those from country A and B makes the tariff rate
against food stuff is different from their use in agriculture to mining and quarry. At the same time, allgoods and services in our model are aggregated from several single components. Structure of anaggregated good can be different from use purpose to use purpose which is explained carefully in Part
III. Data.
In our model, we do not distinguish sources of import or all trading partners of Australia aretreated as a whole as the rest of the world. In general, import duty in Australia is very low, just 1.85%
on average in 2005-2006. Nevertheless, imports used as intermediate input faced lower duty (1.20%)
than when they are used for capital formation (1.83%) or final private consumption (3.70%). Onlynine out of eleven tradable commodities in our model are imposed import duty. Agricultural, forestry,mining and quarry products are exempted from tariff barriers. The highest protection is given to
textile and clothing industry with the average tariff rate of 8.89%, followed by non-ferrous minerals(2.84%), wood and wood processing (1.96%), basic metals (1.94%), metal processing (1.91%), food
stuff (1.58%), paper and paper processing (1.00%), chemicals excluding petroleum (0.68%) andfinally petroleum (0.03%).
Above tax rates are interpreted into total duty revenue of $3.24 billions in the benchmark year ofwhich $1.18, $1.37 and $0.69 billions come from intermediate use, final private consumption andcapital formation, respectively. Amongst industries, the largest contributions are given by the importsof metal processing ($1.61 billions) and textile and clothing ($0.85 billions).

74

Low import duties in most sectors have reflected clearly open trade strategy of Australia. Current
negotiations and some other plans are about to clear all tariff rates expectedly in coming time. It isargued that because of already low duty, there is a little room for the trade policy to have large impact
on the economy. This argument is reasonable if we consider tariff rate reduction as the main target oftrade liberalization and the little actual changes in trading performance of Australia in the last few
years.
A.4.4 Other production tax
Table A10 Other production tax rate
AgrFor

MinQuarr

Food

Texcloth

Wood

Paper

PetrolChemicNonferr

Metals

3.58%

0.82%

3.43%

4.57%

2.31%

3.06%

1.59%

3.56%

3.44%

2.80%

MetProc

EnergyConstr

Trade

HotRestTransp

RealEstPublicOtherServ

TOTAL

3.32%

1.18%

1.53%

5.25%

2.65%

3.71%

3.77%

2.29%

3.12%

3.15%

(Source: (ABS 2009) and authors’ calculation)
Apart from above product related taxes or subsidy, Input – Output Tables contain information onother production tax, which is regarded as tax against value added output production in our model.
The other taxes on production are understood as the money enterprises incur as a result of their
engagement in the processes of production besides product related taxes. They may consist of taxes
payable on the land, fixed assets or labor employed in the production process or on certain activities
or transactions. The actual structure for this type of tax is very complicated, that may incur during the
production process. Some major items could be listed here such as taxes on payroll or workforce,recurrent taxes on land, buildings or other structures, business and professional licences, taxes on theuse of fixed assets, stamp taxes, taxes on pollution and taxes on international transactions (Soriano
and Thompson 2006). For simplicity, we assume that it is proportional to value added output.
Therefore, the value added tax rate ( , ) for each industry can be easily derived by dividing revenueof tax on production by value added output, covering all kinds of tax that firms have to pay in theirproduction processes. On average, this tax rate is 3.15% for the whole economy. Similar to productrelated tax, value added production tax rate varies across industries of which the highest rate of 5.25%
is faced by trade industry and the lowest rate of 0.82% is given to mining and quarry industry.
Above tax rates are interpreted into total other production tax or value added output tax revenue of$28 billions in the benchmark year of which the largest contributions come from banking, insurance
and real estate ($9.71 billions), commerce ($5.24 billions) and transport ($2.49 billions).
A.4.5 Income tax
In addition to revenue from product and production related taxes, the government budget issignificantly contributed by income tax revenue. Actually, income tax has a very complicatedstructure. In our model, it is simplified as a flat rate against all sources of income of the household
sector including wage income and investment income. This flat income tax rate is calculated to get thetargeted share of income tax revenue in total tax revenue. Actually, income tax revenue contributes
nearly two thirds of total tax revenue or equivalent to $182.3 billions in the benchmark year. Twomain types of income tax used in Australia are personal income tax and corporate profit tax. In
general, the latter one is set at the rate of 30%. Because of zero profit condition assumption in ourmodel, corporate profit tax is not analyzed directly. In contrast, we assume that all sources of income
are taxed at personal level. This simplification is still practically reasonable if we take into account thefact that corporate profits are basically owned by and eventually would be distributed to individuals(ie, in the forms of dividend) and this source of income is included in gross operating surplus andmixed income in Input - Output tables. Therefore, income tax in our model can be interpreted as a
combination of both personal income and corporate profit tax and the rate is selected to reflect thepractical condition that income tax revenue share around two thirds of total tax revenue. The income
tax rate is calculated to be 26.5% across the entire economy.

75

A.5 Intuitions for results caused by tariff and subsidy changes
A.5.1 Intuitions for results caused by tariff changes
Generally, a reduction in tariff upon import of a particular product has several impacts which occur
in different levels. It is assumed that tariff reduction is imposed on imported product .
↓→ 1

↓→

Ei

↑,

↓,

↓→

↑

E i’
Bi’
Bi

Figure A.5.1 Substitution between home made and imported product that is imposed lower dutyFirst, at the bottom levels, local price index of imported product that is imposed lower duty falls,
creating chances for local buyers to purchase more imported quantity given their previous income.
Since imported and home made component in the same type of commodity are related through an
Armington structure, they are good substitutes for each other. In our model, that the Armington
elasticities in all categories of demand are greater than unitary implies the substitution between homemade and imported product is elastic. Therefore, within the commodity whose imported component is
imposed lower tariff, the demand for imported product rises but the demand for home made productdrops as the consequence of substitution effect9. As a result, composite price index of the commodity
whose imported component is imposed lower tariff decreases, too, regardless of their use purposes or
categories of demand10. Next, because alternative composite commodities are combined through a
CES structure, the demand for the commodity whose imported component is imposed lower tariff
expands relatively in comparison with the demand for the remaining commodities as the consequenceof substitution effect.
Second, in production, industrialists substitute imported products with lower duty for their homemade counterparts in intermediate inputs and capital formation. So both of the cost of intermediate
inputs and value added reduce. The LTF structure employed in production implies there is a reduction
in total production cost. Consequently, it is expected to cause an expansion in production capacity ofall producers. Therefore, local industries which do not have to face further competition from imported
products are projected to increase their production capacity. Because industry specific production
9

The income effect is available but it is totally offset by the substitution effect as the consequence of elastic substitution
between home made and imported product. For this reason, the income effect is ignored here.
10
Consist of final private consumption, government consumption, capital formation and intermediate input

76

outputs in our model are separated into home sold and exported product through a CET structure, it isobvious that both quantity of home sold and exported product rise. The increase in quantity ofexported product is larger than that of home sold product because the world price of exported
products is given meanwhile the demand for home sold products is downward sloping. A part fromthe change in quantity, the price of home sold product of these industries reduces. Eventually, the top
price index of aggregate commodities in all categories of demand reduces, too.

Ej

Ej

E j’

E j’

Figure A.5.2 Change in the industry whose competing import is not imposed lower duty
Whereas the industry whose direct competing import is imposed lower duty would experience
different results. Although this industry also expands its production capacity like the others, thatbuyers in all categories of demand substitute imported product for its home sold product creates alarge drop in its domestic demand. Since the drop in domestic demand far exceeds the rise in supply,
this industry would face a big fall in its home sold price and quantity. And despite the increase inexported quantity like other industries, this industry still experience a reduction in production output
as well as value added. It is reasonable also because in most industries, the share of domestic sales intotal production output is much larger than that of export11.
Generally, because the total increase in output of expanding industries exceeds the reduction in
output of the contracting industry, a tariff cut is projected to lead to a net positive change in output of
the whole economy.
Because of the reduction in price index of all industry specific home sold products, the price index
at composite commodity level and top aggregate level in all categories of demand further decreases,
so deepening production capacity expansion above. Moreover, it can create some substitution effectbetween imported and home made products in all categories of demands. But in this round, theincome effect is significant as the consequence of output expansion. Therefore, the demand foralternative home made and imported products depends on specific characteristics of buyers. In ourmodel, value added and intermediate inputs are combined through a LTF technology to generateindustry specific production output. Since price index of value added and intermediate inputs all fall,
it is certain that price index of industry specific production outputs reduces, too, of which the largest
drop obviously occurs to industries whose competing import has to pay lower duty.
11

The industry with largest share of export is mining and quarry (around 50%).

77

Ei

E i’

Figure A.5.3 Change in industries whose competing import is imposed lower duty
Table A.5.1 Elasticity of industry specific GDP to alternative tariffs in 2010 – 20111
Tariff upon1

AgrFor MiQuar

Food

Texclot

Wood

Paper

Petro

Chemi

Nonfer

Metal

MetProAgrFor0.1396-0.0008

1.03740.7686

0.0465-0.2139-0.0010-0.3304-0.8264-0.7000-4.5696

MinQuarr-0.05240.0217-2.5373-6.7924-1.0764-0.9789-0.0045-2.7588-2.8467-2.1661 -34.8060

Food-0.0301-0.0015

2.23920.3055-0.2086-0.2785-0.0009-0.3281-1.0593-0.8528

Texcloth-0.0349-0.0054-1.0183 51.8910 -0.4566-0.5190-0.0010-1.3099-1.4504-1.5986 -10.9807

Wood-0.0114-0.0013-0.5951-1.7096 10.2194 -0.5445-0.0018-1.2003-1.8007-1.9723-5.6236-9.5613Paper-0.0047-0.0001-0.0069-0.1569-0.2384

2.2006-0.0011-0.4971-1.1202-0.9125-6.4944

Petrol-0.00130.0020-0.2550-0.8177-0.2454-0.2507-0.0027-0.5661-0.9243-0.8015-7.7328

Chemic-0.0223-0.0044-0.8747-2.0028-0.3852-0.5534-0.00198.8098-1.7473-1.9943 -12.4172

Nonferr-0.0112-0.0013-0.3061-1.2150-0.4448-0.3763-0.0018-0.9773

4.5409-1.6461 -10.9366

Metals-0.0281-0.0129-1.3569-3.9287-0.8209-0.6871-0.0026-1.8582-2.4458

3.0723 -17.9212

MetProc-0.0146-0.0055-0.7296-2.2593-0.8466-0.4743-0.0016-1.3588-2.2468-3.3791

4.9349Energy-0.00110.0009-0.0774-0.2740-0.2036-0.1886-0.0012-0.4143-0.7944-0.6085-5.6984

Constr

-0.00640.0020-0.4120-1.2519-0.4978-0.4065-0.0020-0.9942-1.7829-1.6583 -12.0471

Trade-0.0005

0.00050.00720.0874-0.2405-0.2441-0.0011-0.3429-0.9658-0.8569-6.4829

HotRest-0.0122-0.0007-0.8465-0.0654-0.1946-0.2086-0.0008-0.2948-0.8482-0.7701-5.2570

Transp-0.00410.0002-0.1362-0.4978-0.2290-0.2533-0.0015-0.4521-1.0750-0.9271-7.7437

RealEst-0.00100.0010-0.0243-0.0998-0.2023-0.1755-0.0010-0.3244-0.8249-0.7023-5.4291

Public-0.00240.0012-0.1476-0.5323-0.2944-0.3125-0.0014-0.5743-1.2210-1.0771-8.5865

OthServ-0.00340.00080.03880.0132-0.2337-0.2117-0.0010-0.3660-0.9429-0.8650-6.0299

Total GDP

-0.00350.0018-0.2554-0.7067-0.2884-0.2822-0.0015-0.6054-1.1773-1.0040-8.9548

All the numbers in the table are 1000 times smaller

Source: Authors’ calculation
However, the change in commodity specific imports is much more complicated. After a tariff
reduction, it is certain that import of product that is imposed lower tariff expands rapidly but the
movement direction of other imports varies across remaining products. It is worth noting that thedemand for composite commodities whose competing import is not imposed lower duty rises andprice of home made products reduces in all categories of demand. Obviously, the demand for home78

made products increases. However, that the demand for their corresponding imported products rises ordrops depend on the magnitude of the income effect and the substitution effect. Consequently, it isundetermined about the change in import volume in alternative categories of demand. Moreover, incomparison with output, import volume is less sensitive to the change in import duties. This finding
can be illustrated clearly by the results on elasticity of commodity specific imports to tariff change.
Accordingly, a reduction in tariff imposed on a particular product might have different effects onimports of other products. Except reduction in tariff imposed on mining and quarry and petroleum has
a negative and positive impact on imports of all remaining products respectively, tariff reform upon
imports of all other products would show a mixed results.
Table A.5.2 Elasticity of commodity specific import to alternative tariffs in 2010 – 20112
Tariff upon

AgrFor MiQuar

Food

Texclot

Wood

Paper

Petro

Chemi

Nonfer

Metal

MetProAgrFor-6.3600

0.00311.40421.70470.0008-0.01780.00000.7389-0.26120.04971.4379MinQuarr

0.0300-0.0726

1.31613.22330.28690.26070.00071.06230.52593.955516.1998

Food

0.02600.0025 -27.8512 1.3807-0.04080.0777-0.00030.3336-0.1037-0.0253-0.2304

Texcloth0.01060.00190.4803 -58.9652 -0.0816

0.0350-0.0005

0.1433-0.3211-0.2241-1.4001

Wood-0.0009

0.0014-0.1386-0.3907 -54.3765 0.1691-0.0014-0.1118-1.1895-0.8010-3.8762Paper

0.00040.00160.18420.4894-0.0154 -12.9081 -0.0009

0.2065-0.3807-0.5533-4.8237

Petrol-0.0056

0.0020-0.5845-1.7407-0.3566-0.3463-0.7354-1.2409-1.1625 -12.7658-0.0123

Chemic0.01460.00170.13130.1156-0.1148-0.0099-0.0010 -11.4995 -0.0704-0.5980-5.6828

Nonferr-0.00650.0014-0.1955-0.7096-0.2994-0.1527-0.00120.0810 -23.3816 -1.0656-7.0764

Metals-0.00160.0072-0.0909-0.3260-0.2372-0.2012-0.0010-0.3534-1.0187 -23.0115 -1.2069

MetProc

0.00220.00420.01530.0019-0.1011-0.1763-0.0013-0.2776-0.7103-0.1546 -34.8046

Energy0.02130.00780.93742.34340.11110.11890.00000.85480.2644

1.1647

6.1920Constr

-0.00160.0112-0.4579-0.81850.0145-0.2199-0.0017-0.2845-0.3327

0.3355-9.7063Trade

0.02880.0076

1.60853.54120.11040.4023-0.00020.74760.13110.7051

6.3856

HotRest0.06490.01064.45714.48210.11040.4803-0.0004

1.0706

0.37971.06706.9715

Transp-0.0006

0.00100.0037-0.0988-0.1693-0.1336-0.0006-0.2383-0.6322-0.5514-4.9065

RealEst0.01980.00840.94952.2084-0.03430.0756-0.00130.3631-0.5192

0.22282.3040Public0.01690.00511.00042.6332-0.1052

0.1166-0.00090.3396-0.5042-0.0766-1.1607

OthServ

0.01480.00330.53991.3783-0.11810.0251-0.00070.0947-0.5085-0.2011-2.7708-0.4903-0.4362-0.0014-1.0566-1.3255-1.1029 -14.9218

Total-0.0253 -0.0032 -0.9647 -2.4483
Import2
All the numbers in the table are 1000 times smaller

Source: Authors’ calculation
In comparison with output and import volume, the influences of tariff cut on utility are much lesssignificant, that is caused by the role of leisure in utility and income earning.
On the one hand, leisure can be treated as a kind of non-traded commodity whose price isestimated by the wage rate or the income amount consumers have to give up in order to obtain a unitof leisure. In our model, commodity consumption and leisure are related also through a CES structure
which implies the substitutability between them. As above analysed, a tariff reduction leads to adecrease in price index of aggregate private consumption commodity. Consequently, as usual,consumers substitute consumption of commodity for leisure.

79

On the other hand, different from the case of two normal commodities whose substitution effectdominates income effect, the substitution of commodity consumption for leisure has a strong income
effect that is caused by the direct link between leisure and working time. The substitution ofcommodity consumption for leisure implies an increase in supply of labour.

E2

E
E’

E1

E’’
u'

E
u

u''

Figure A.5.4 Substitution between commodity consumption and leisure and change in the labour
marketTable A.5.3 Vectors of elasticity of welfare to tariff rates//

19961997

19971998

19981999

19992000

20032004

20042005

20052006

20092010

20102011

20142015

20152016

AgrFor

0.18E

0.18E

0.18E

0.17E

0.16E

0.15E

0.15E

0.15E

0.14E

0.14E

0.14E

MinQuarr-0.09E-0.09E-0.09E-0.10E-0.09E-0.09E-0.09E-0.09E-0.09E-0.09E-0.09E

Food

2.98E

2.95E

2.90E

2.76E

2.56E

2.44E

2.32E

2.20E

2.08E

2.04E

2.00E

Texcloth-60.95E -45.80E -31.87E-8.75E-10.23E

1.02E

9.61E

14.88E

16.61E

15.52E

13.22E

Wood-7.87E

-7.88E

-7.65E-7.12E

-7.28E

-7.08E

-6.77E

-6.59E

-6.42E

-6.59E

-6.42E

Paper

4.59E

4.57E

4.52E

4.47E

3.72E

3.69E

3.61E

3.60E

3.60E

3.59E

3.59E

Petrol-0.08E-0.08E-0.08E-0.06E-0.04E-0.04E-0.03E-0.03E-0.03E-0.03E-0.03E

1.75E

1.73E

1.79E

0.61E

0.80E

1.85E

1.82E

1.79E

1.77E

1.75E

Chemic1.78E

Nonferr-20.32E -20.20E -20.08E -19.53E -19.66E -18.80E -17.08E -16.83E -16.73E -16.73E -16.73E

Metals-28.88E -28.94E -29.00E -28.80E -27.41E -26.25E -22.77E -22.22E -21.67E -21.68E -21.70E

MetProc-565.11E -530.01E -492.46E -409.24E -410.97E -364.92E -319.00E -274.64E -231.15E -231.32E -231.49E

E=10-6

Source: Authors’ calculation
At the same time, because of the reduction in the price index of the capital good, in order togenerate value added which is a CES combination of capital and labour, producers would substitutecapital for labour, implying a decrease in demand for labour. The computation results reveal thissituation very clearly that given a reduction in any tariff, all industries in Australia would become
more capital intensive. It is the main reason why there is a drop in value added price of all industries.
In addition to the substitution effect, because of the drop in production costs, firms expand their80

production, implying an increase in demand for labour. The net effect on demand for labour depends
on the difference between the substitution effect and the production expansion effect. As a result, it
may lead a rise or fall in wage rate and quantity of employed labour as well. If the substitution effectdominates the production expansion effect, the demand for labour shifts downward, leading a fall inwage rate. Therefore, the income of the household sector decreases, making the positive effect of the
reduction in price of commodities on utility less significant. Oppositely, if the production expansion
effect exceeds the substitution effect, there would be an increase in employed labour. As a result, it
can be concluded that utility is less elastic to tariff change in comparison with output and import
volume.
In addition to direct changes to producers and consumers, it is expected that there is a negative
impact on the government budget because of the disappearance of import duty revenue. Because of
the output expansion and real wage increase, the government would spend more, pay more for subsidy
and age pension. As a result, there is a big fall in other benefit transfer to the consumers thatnegatively influence the utility of households. However, it is still offset by the positive consumption
expansion effect.
A.5.2 Intuitions for results caused by subsidy changes
In our model, subsidy is used to encourage domestic production, including those for exports.
Accordingly, buyers of home made products are provided with price assistance. Subsidy could be
regarded as a negative consumption tax. If products are exported, producers get additional payment totheir selling price from the government. Similarly to the case of tariff reduction, a fall in subsidy for aparticular home made product is expected to cause changes at several levels. We can reemploy theinstitutions used above to explain the causes of the effects of subsidy reduction. Once again, it isassumed that the subsidy toward the consumption and export of product is halved.
↓→ 1

↑→

↓,

↑,

↓

tsi
E i’

Ei

tsi’

Ei

E i’

Figure A.5.5 Change in the industry whose product is given lower subsidy
In principle, a decline in subsidy makes all of the variables in the economy except price indiceschange in the opposite direction with the case of tariff reduction.
81

In the first stage, there is a relative fall in demands for the product with lower subsidy incomparison with other products. After the decline in demands, there is a reduction in the price index
of the home made product with lowered subsidy but an increase in its corresponding net purchasing
price. Because of higher production cost, all producers contract their production capacity, implying a
reduction in all supplies. As a result, all other industries would experience a fall in output.
In the proceedings stages, arguments similar to the above part can be utilized to explain why there
would be a fall in welfare, labour force participation rate and other variables.

82

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