Modelling international developments 
GTAP simulations of TCF protection removal	
		
	Prepared for the	
		
	Productivity Commission	

		
	Centre for International Economics
Canberra & Sydney
March 2003	

The Centre for International Economics is a private economic research agency that provides professional, independent and timely analysis of international and domestic events and policies.
The CIE’s professional staff arrange, undertake and publish commissioned economic research and analysis for industry, corporations, governments, international agencies and individuals. Its focus is on international events and policies that affect us all.
The CIE is fully self-supporting and is funded by its commissioned studies, economic consultations provided and sales of publications.
The CIE is based in Canberra and has an office in Sydney.
© Centre for International Economics 2003
This work is copyright. Persons wishing to reproduce this material should contact the Centre for International Economics at one of the following addresses.
Canberra
Centre for International Economics
Ian Potter House, Cnr Marcus Clarke Street & Edinburgh Avenue
Canberra ACT
GPO Box 2203
Canberra ACT Australia 2601
Telephone	+61 2 6248 6699   Facsimile	+61 2 6247 7484
Email	cie@thecie.com.au
Website	www.thecie.com.au
Sydney
Centre for International Economics
Level 8, 50 Margaret Street
Sydney NSW
GPO Box 397
Sydney NSW Australia 1043
Telephone	+61 2 9262 6655   Facsimile	+61 2 9262 6651
Email	ciesyd@thecie.com.au
Website	www.thecie.com.au

Contents

1	Introduction	1
This report	1
Some key results	2
Key features of the modelling design	6
Treatment of TCF policies	9
Other modelling implications	12
2	Unilateral change of Australia’s TCF tariffs	13
Unilateral removal of Australia’s TCF tariffs	13
Unilateral 50% reduction in Australia’s TCF tariffs	16
3	Unilateral liberalisation of TCF trade in other countries	18
Unilateral liberalisation of TCF trade in the US	18
Unilateral removal of TCF tariffs in the EU	20
Unilateral removal of TCF tariffs in China	23
A comparison to Australia’s unilateral reform	24
4	Multilateral and global TCF liberalisation	27
Removal of TCF protections in Australia and the EU	27
Removal of TCF protection in Australia and the US	29
Removal of TCF protection in Australia and Greater China	31
Removal of TCF protection in the APEC region	33
Global TCF liberalisation	35
5	Sensitivity analysis	38
Changes in parameter groups	38
Removal of TCF protection when the US protection level is higher	41
Alternate closure	45
A	Appendix: technical simulation details	47
Model aggregation	47
Solution method	48
References	49
Boxes, charts and tables
1.1	Simulations undertaken	1
1.2	Summary effects on Australia	2
1.3	Summary welfare results Percentage change in income	6
1.4	GTAP regions and sectors used in this report	7
1.5	Export tax equivalent of import quotas	10
1.6	Comparison of the US TCF barriers (tariff equivalent)	11
1.7	Comparison of the EU clothing barriers (tariff equivalent)	11
1.8	The US imports of clothing	12
2.1	Australian tariff rates for TCF imports	13
2.2	Welfare effects of removing Australia’s TCF tariffs Changes in equivalent variation and components	14
2.3	Unilateral removal of Australia’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline	15
2.4	Welfare effects of 50 per cent reduction in Australia’s TCF tariffs Changes in equivalent variation and components	16
2.5	Unilateral removal of Australia’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline	17
3.1	Welfare effects of removing the US TCF tariffs Changes in equivalent variation and components	18
3.2	Unilateral removal of the US TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline	19
3.3	Welfare effects of removing the EU TCF tariffs Changes in equivalent variation and components	21
3.4	Removing the EU TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline	22
3.5	Welfare effects of removing China TCF tariffs Changes in equivalent variation and components	24
3.6	Removing China’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline	26
4.1	Welfare effects of removing TCF protections in Australia and the EU Changes in equivalent variation and components	27
4.2	Removing TCF tariffs in Australian and the EU: macroeconomic and sectoral results by region Per cent change from baseline	28
4.3	Welfare effects of TCF liberalisation in Australia and the US Changes in equivalent variation and components	29
4.4	Removing TCF tariffs in Australian and the US: macroeconomic and sectoral results by region Per cent change from baseline	30
4.5	Welfare effects of TCF liberalisation in Australia and China Changes in equivalent variation and components	31
4.6	Removing TCF tariffs in Australian and China: macroeconomic and sectoral results by region Per cent change from baseline	32
4.7	Welfare effects of TCF liberalisation in the APEC region Changes in equivalent variation and components	33
4.8	Removing APEC TCF protection: macroeconomic and sectoral results by region Per cent change from baseline	34
4.9	Welfare effects of global TCF liberalisation Changes in equivalent variation and components	35
4.10	Global TCF liberalisation: macroeconomic and sectoral results by region Per cent change from baseline	37
5.1	Sensitivity analysis of global liberalisation: confidence interval expressed as a percentagea	39
5.2	Sensitivity analysis of unilateral removal of TCF tariffs in Australia: confidence interval expressed as a percentagea	40
5.3	Sensitivity analysis of unilateral 50% reduction in Australia’s TCF tariffs: confidence interval expressed as a percentagea	40
5.4	Welfare effects of removing Australia’s TCF tariffs: higher US clothing protection Changes in equivalent variation and components	41
5.5	Welfare effects of removing US TCF tariffs: higher US clothing protection Changes in equivalent variation and components	42
5.6	Welfare effects of removing the EU TCF tariffs: higher US clothing protection Changes in equivalent variation and components	42
5.7	Welfare effects of removing China TCF tariffs: higher US clothing protection Changes in equivalent variation and components	43
5.8	Welfare effects of TCF liberalisation in APEC region: higher US clothing protection Changes in equivalent variation and components	43
5.9	Welfare effects of global TCF liberalisation: higher US clothing protection Changes in equivalent variation and components	44
5.10	Welfare effects of global TCF liberalisation: alternate closure Changes in equivalent variation and components	45
5.11	Global TCF liberalisation: macroeconomic and sectoral results by region: alternative closure Per cent change from baseline	46

1	Introduction

	This report
This report presents the results of a number of simulations using the GTAP model of the world economy. These simulations are designed to capture some of the potential implications of Australian, US, EU, Chinese and global liberalisation of TCF protection. This report should be used in conjunction with our previous report (CIE 2002a) examining the effect of a broad range of global liberalisation scenarios.
Table 1.1 summarises the simulations and indicates their presentation in chapters 2 to 4. Chapter 5 of the report undertakes some sensitivity analysis of the results while the appendix summarises some technical details of the simulations.
1.1	Simulations undertaken
Simulation	Reported in	
1. Unilateral removal of Australia’s TCF protection	Chapter 2	
2. Unilateral 50% reduction in Australia’s TCF protection	Chapter 2	
3. Unilateral removal of the US’s TCF protection	Chapter 3	
4. Unilateral removal of the EU’s TCF protection	Chapter 3	
5. Unilateral removal of China’s TCF protection	Chapter 3	
6. Removal of TCF protection in Australia and the EU	Chapter 4	
7. Removal of TCF protection in Australia and the US	Chapter 4	
8. Removal of TCF protection in Australia and greater China	Chapter 4	
9. Removal of TCF protection in APEC region	Chapter 4	
10. Global TCF trade liberalisation	Chapter 4	
	Some key results
	The Australian TCF sector
While the analysis in this report looks broadly at the effects of a number of TCF liberalisation scenarios, one area of particular interest is the extent to which liberalisation elsewhere in the world improves or worsens the prospects of the Australian TCF industry.
To examine this question, table 1.2 summarises key results from 5 of the simulations presented in this report. The table shows the effect on Australian GDP and real income, as well as output in three aggregate TCF sectors of: unilateral Australian liberalisation; US liberalisation, EU liberalisation; Chinese liberalisation; and global liberalisation.
1.2	Summary effects on Australia
	Australian	US	EU	Chinese	Global	
	% change	% change	% change	% change	% change	
GDP	0.10	0.00	0.00	0.01	0.10	
Real income	0.04	0.00	0.00	0.03	0.08	
Textile output	-18.3	1.7	-0.3	-1.0	-19.6	
Clothing and footwear output	-48.7	-0.2	-0.2	-0.8	-43.0	
Leather products output	-10.0	0.1	-3.4	-4.4	-22.2	
Source: GTAP simulations
	Australia liberalisation
The first results column in table 1.2 shows the effects of Australia removing its TCF tariffs from their 1997 levels (the level in the GTAP database, an average of 15.8 per cent for textiles, 27.4 per cent for clothing and 12.1 per cent for leather products — see table 2.1). The results follow the usual pattern for this type of simulation. There is a reallocation of activity away from the protected textiles sector towards other industries and an increase in total real income.
In this simulation, the output of each of the TCF industry declines. The extent of the decline in the results here is largely a function of the import substitution elasticity we have chosen for these simulations. We have chosen a relatively large value for this elasticity.
	US liberalisation
If the US alone liberalises, there is a very small effect on any of Australia’s TCF industries. While the US does have barriers against Australia’s products the barriers against other exporters, in particular China, are several times greater. Following the US liberalisation, US importers see significant relative price changes, with the Chinese product appearing relatively cheaper and hence Chinese exports to the US increasing several-fold. 
In this simulation, Australia’s clothing and footwear output declines slightly because of a loss of exports to the US market. Thus, despite a removal of US barriers against Australia, Australian exports to the US decline because of increased competition from China.
Interestingly, Australia’s exports of textiles and leather increase slightly because of increased sales to China, which now purchases more of these inputs in order to services the US market.
	EU liberalisation
There is a similar pattern of Australian results for EU liberalisation, except in this case all of Australia’s TCF industries decline. As in the case of the US, this is because EU barriers are higher against other countries (particularly in Asia) than they are against Australia, and so when the barriers are removed, the EU tends to substitute towards Asian products and away from Australian products.
	Chinese liberalisation
Removal of Chinese import protection shows another set of mechanisms at work. Following China’s liberalisation, there is an increase in Australia’s exports to China. At the same time however, China’s exports also increase. This leads Australia to import more and subsequently a decline in Australian demand for domestic TCF products.
	Global liberalisation
Global liberalisation consists of each of the above, plus liberalisation from other countries. Most of the effect on Australian TCF output is from Australia’s own liberalisation. As a result of a mix of the mechanisms described above, there are some small differences with the Australian liberalisation results, but these do not offset the decline in output from that liberalisation.
	Implications and caveats
These results suggest that the removal of the measurable trade distortions (tariffs and quotas) in countries elsewhere in the world may lead in some instances to increased TCF activity in Australia. In most cases, however, this global liberalisation will have little impact on the fortunes of the Australian industry, and in some cases it could lead to a reduction in Australian output.
The main reason for this result is that according to the protection estimates embedded in the GTAP database, restrictions against other countries are considerably greater than restrictions against Australia.
There are some important caveats to this result.
•	The GTAP model is highly aggregated, with only three broad industry groups representing all the diversity of the TCF sector. It is quite likely that this aggregations masks some important outcomes for particular niche Australia products — both in terms of the starting levels of protection, and in terms of the responses to the removal of that protection.
•	There may also be a variety of barriers to trade that do not figure in the protection estimates within the database. While these are designed to capture the key elements of policies such as the MFA, there may be other less measurable restrictions that are not covered.
•	The Australian TCF industry most likely perceives a range of restrictions to trade when they seek to export. Given the long term distortions that have been established as part of the MFA — distortions which no longer just work at the margin, but have changed the very nature of the TCF business — it is difficult to determine precisely how much things will change as the MFA is phased out. 
	Broad sources of welfare change
There are two broad sources of welfare change captured in the simulations presented here. The first is changes in allocative efficiency. Removing import tariffs and/or quotas reduces activity in the previously protected sector and increases activity in other sectors in the economy. Typically, the expanding sectors are export oriented, as import protection tends to tax exporters. This change in activity involves the reallocation of resources to uses that do not require any protection and so leads to an overall welfare gain.
The second source of welfare change is changes in a country’s terms of trade — which can change because of changes in export prices, or import prices, or both. Typically, when a country removes its own import tariff, this leads to an increase in exports. Depending on the demand conditions facing these exports, this increase in the quantity of exports may result in a decline in their price. Thus, a country removing its own tariffs may experience a terms of trade loss. On the other hand, removing import an quotas can be equivalent to reducing an export taxes in exporting countries, which may lead to terms of trade gain.
When a foreign country reduces its protection against products from the home country, then the increase in demand for the home country’s products will increase the price of those products, resulting in an improvement in the home country’s terms of trade. Thus, while removing protection at home may be associated with a terms of trade loss, protection removed overseas will result in a terms of trade gain.
	Welfare results for each simulation
Chart 1.3 summarises the welfare effects (measured as the percentage change in real income) that result from each of the simulations. In general, these effects are very small, being less than 0.1 per cent for Australia, for example, in all simulations. This is because TCF sectors account for a small share in both production and trade.
In the simulations of unilateral removal or reduction of Australia’s TCF tariffs, Australia’s gains come through improvements in domestic resource allocation which more than offset the loss of terms of trade. So does the global TCF liberalisation. On the other hand, Australia’s gains come through improvements in its terms of trade when the US or the EU unilaterally removes its TCF tariffs.  However, the unilateral removal of China’s TCF tariffs provides a special case where Australia gains through improvements in both domestic resource allocation and terms of trade with the former being larger than the latter.
An important finding from the simulations is that Australia achieves higher benefits when it unilaterally removes or reduces TCF tariffs than cases where other countries (the US, the EU and China) unilaterally remove their tariffs. This is because that Australia is a net importer of TCF products and the liberalisation in other countries does not provide any improvement in the economic strucuture which is distorted by the protection of TCF sectors. A unilateral 50 per cent reduction in Australia’s TCF tariffs brings about higher welfare gains than a unilateral removal. And the sensitivity analysis shows that the welfare gains have smaller variation as a result of changing paprameter values in the case of unilateral reduction than in the case of unilateral removal.
All the model results are sensitive to the choices of parameter values, as discussed in the chapter on sensitivity analysis.
1.3	Summary welfare results Percentage change in income
	
Data source: GTAP model simulations
	Key features of the modelling design
	The GTAP model
GTAP is a global general equilibrium model and database. Its origins lie in work originally undertaken at the (then) Industry Commission. Since the publication of the first GTAP book (Hertel et al 1997) the GTAP project (based at Purdue University) has become a global network of developers, contributors and users.
The full GTAP database covers 66 regions and 57 sectors, and the latest version of the database is calibrated around 1997 as a base year. For the simulations presented here we aggregated the database to 14 regions and 18 sectors. These are set out in table 1.4 and the mapping of these aggregates to the full GTAP database is summarised in the appendix.
We have chosen this aggregation to make simulation with the model manageable while not losing the essence of the kinds of interactions the simulations outlined above are designed to capture.

1.4	GTAP regions and sectors used in this report
Regions	Sectors	
Australia	Crops	
NZ	Livestock	
US	Forestry & mining	
Canada	Food processing	
Mexico	Textile	
EU	Clothing	
Chinas	Leather products	
Korea	Paper products	
Other Asian APEC	Chemicals etc	
Malaysia	Ferrous metals 	
Singapore	Motor vehicles	
Thailand	Transport nec	
Japan	Other equipment	
ROW	Electrical	
	Other manufacturing	
	Utilities and construction	
	Trade & transport	
	Services	
	Trade-offs in using a global model
GTAP is a globally consistent database of production, consumption and trade. It provides an invaluable tool for analysing global interactions, particularly the effects of other countries’ trade reforms on a particular country such as Australia. 
There are, however, two important trade-offs with such a global database. First, the database will not necessarily reflect the full details of a particular sector in a particular region. For example, the export and import shares for the Australian TCF industry represented in the model may not be the same as what is observed from recent Australian data. Second, and related, the database is inevitably aggregated. For example, the three TCF sectors (textiles, clothing and leather products) include a variety of different products. 
These trade-offs mean that some care should be used in interpreting the model results. It is important to keep in mind that for the simulations presented here (most of which are concerned with the effects on Australia of the actions of other regions), it is the relativities between different simulations that are most important.
	The model closure
The main closure used in this report treats all endowments (land, labour and capital) as fixed. That is, the quantities of each of these used within a region do not vary as a result of the policy under consideration. This closure choice has both advantages and disadvantages. The advantage is that it allows the simulations to focus on the resource allocation effects of the change under consideration. The potential source of gain in this case is that resources can be used more efficiently following trade liberalisation, for example.
The disadvantage is that the simulations do not show the capital cumulation effects that might result from trade reform. That is, the simulations focus on the static rather than the dynamic effects of liberalisation. To some extent this is inevitable, as GTAP is a comparative static model. However, in the sensitivity analysis presented in chapter 5 we show the effects of an alternative closure that allows capital to vary in each region.
	Key parameter choices
We have used the standard GTAP parameters file with one exception: the trade parameters. There are two sets of these parameters:
•	those determining the substitution between domestic and imported goods in each region; and
•	those determining the substitution between imports from different sources.
For both of these sets, we have doubled the standard values. This follows common practice with the GTAP model. It is essentially based on the observation that the standard parameter set often generates unreasonably large terms of trade effects and that with the standard parameters it is difficult to replicate observed trade flows.
The values of the elasticity of substitution between imports from different sources range from 8 to 20 in the doubled-the-standard parameter set (the values for textile, clothing and leather products are, respectively, 8.8, 17.6 and 17.6). In GTAP, the export demand elasticities facing each region are implicitly determined by the import-import substitution elasticities in the countries that the region exports to. It turns out that the value of these import substitution elasticities (which are the same for all regions but differ by sector) sets an upper bound to the (absolute) value of the export demand elasticity for each commodity facing each region. Thus the upper (absolute) value of the export demand elasticities vary from 8 to 20.
In chapter 5 we present sensitivity analysis of groups of model parameters to give an indication of the importance of parameter choices for the simulations presented here.
	The welfare measure
In the simulations presented here we use equivalent variation (EV, the change in real income measured at the prices prevailing before the change in the simulation) as our welfare measure. GTAP has one single representative household per region, so EV can easily be measured. When presented in dollar terms, the change in EV refers to 1997 US dollars.
	Treatment of TCF policies
In addition to tariffs, TCF imports are often restricted by quotas. Since its inception in 1974, the Multi-Fibre Arrangement (MFA) has allowed developed countries to negotiate discriminatory quotas on imports of textiles and clothing from participating exporting countries and to unilaterally impose country specific restrictions where agreement with supplying countries could not be reached. The United States, the European Union, Canada, Norway, Japan and Switzerland are the developed country participants in the MFA, though Switzerland and Japan have not, for some time, imposed restrictions under the Arrangement. The WTO Agreement on Textiles and Clothing (ATC), which was negotiated during the Uruguay Round, requires WTO members to phase out their MFA restrictions over a ten-year period from 1 January 1995. Operating within the rules of the ATC, the US has chosen not to integrate products with the highest barriers to imports until toward the end of the transition period.
These two types of protection are present in the GTAP model and database. Import quotas in the protected developed country are treated as destination specific export taxes from the point of view of the exporting countries. This is because the MFA operates as a series of voluntary export restraints, so the quota rents accrue (at least partially) to the exporting country. 
Table 1.5 summarises the export tax equivalent (from the view of the exporter) of the protective regime of the US, the EU and Canada. 

1.5	Export tax equivalent of import quotas
	US	EU	Canada	
Exporting region	Textile	Clothing	Textile	Clothing	Textile	Clothing	
	Per cent	
Australia	0.00	0.00	0.00	0.00	0.00	0.00	
NZ	0.00	0.00	0.00	0.00	0.00	0.00	
US	0.00	0.00	0.00	0.00	0.00	0.00	
Canada	0.00	0.00	0.00	0.00	0.00	0.00	
Mexico	0.00	0.00	0.10	4.69	0.00	0.00	
EU	0.00	0.00	0.00	0.00	0.00	0.00	
Chinas	9.44	20.69	7.13	11.65	9.51	23.19	
Korea	0.00	0.00	0.00	0.00	0.00	0.00	
Other Asian APEC	2.27	1.90	1.60	0.60	2.40	1.90	
Malaysia	7.72	7.79	6.28	6.35	7.84	7.68	
Singapore	8.10	7.80	6.30	6.00	8.10	7.80	
Thailand	0.00	0.60	0.20	0.20	0.00	0.60	
Japan	8.28	13.19	6.40	7.80	8.30	13.20	
ROW	7.89	8.08	3.23	2.28	8.64	13.74	
Averagea	7.82	12.15	4.02	4.75	8.14	16.66	
a only includes quota binding exporting countries 
Source: GTAP database v.5
The GTAP database provides one source of information on the tariff and export tax equivalents of restrictions under the MFA. These equivalents are notoriously difficult to estimate, particularly because the quotas are applied at a very detailed commodity level. In order to check the values in the current GTAP database, we thought it would be useful to compare them with rates that CIE has recently estimated in some product specific projects. 
In tables 1.6 and 1.7 we compare the US and the EU’s TCF tariff rates in the GTAP Database with estimates that CIE has derived in previous projects.
These tables show that the EU clothing and the US textile barriers in the GTAP Database are similar to our earlier estimates. However, the GTAP estimates for US clothing protection are lower than our earlier estimates.

1.6	Comparison of the US TCF barriers (tariff equivalent)
	GTAP Data	CIE estimates	
	Import tariff	Export tax	Combined		
	Per cent	
Textile	11.2	7.82	19.9		
		Cotton yarn				6.9-7.5	
		Wool and wool blend yarn				6.1-7.9	
		Other fibre yarn				7.5-8.6	
		Cotton fabric				8.2-8.8	
		Wool and wool blend fabric				18.8-24.1	
		Other fibre fabric				8.4-10.7	
Clothing	13.3	12.15	27.1		
		Cotton apparel				34.9-46.2	
		Wool and wool blend apparel				3.6-33.1	
		Other fibre apparel				50.5-67.8	
Leather products	13.5	0.00	13.5	n.a.a	
a not available
Source: GTAP Database v.5; CIE (2000)
1.7	Comparison of the EU clothing barriers (tariff equivalent)
	GTAP Data	CIE estimation: import weighted	CIE estimation: product  weighted	
	Tariff	Export tax	Combined			
	Per cent	
Clothing	11.9	4.75	17.2			
		Wool				7.4	17.8	
		Cotton				12.3	17.4	
		Man-made and other				13.9	14.6	
a not available
Source: GTAP Database v.5; CIE (2002)
In order to test the importance of this difference, our sensitivity analysis reported in chapter 5 replaces the standard GTAP estimates with our alternatives. Because our estimates do not have the source specific information required by the GTAP model, we adjust the tariff equivalent rate according to the US imports of clothing from different sources (table 1.8). It can be seen from the table that most clothing imports are from Asian countries. Therefore it is assumed that the import quota for clothing from Asian countries except Japan are binding, implying that total protection level (combination of import tariff and export tax) for those countries are 46 per cent. The database is updated to reflect this assumption using GTAP’s ALTERTAX closure. 

1.8	The US imports of clothing
Sources	Import shares	
	Per cent	
Australia	0.12	
NZ	0.02	
US	0.00	
Canada	2.74	
Mexico	10.37	
EU	4.80	
Chinas	28.31	
Japan	0.32	
Korea	3.25	
Other Asian APEC	7.89	
Malaysia	1.46	
Singapore	0.49	
Thailand	3.16	
ROW	37.09	
Total	100.00	
Source: GTAP Database v.5
	Other modelling implications
The GTAP treatment of the MFA is to convert the quota into a tax equivalent. Implicitly, any quota rent goes to the government as a tax. This means that following liberalisation, the exporting country removes a tax, allowing exports to increase and, all other things constant, leading to an increase in the price received by exporters.
However, in a number of exporting countries, the quota arrangements often work differently. For example, in many (if not all) cases, the quota rents are allocated to the exporter and are not captured by the government. An implication is that following liberalisation, the exporter will lose a valuable rent. Rather than seeing an increase in price, the exporters may see a decline in their average price. This may in turn lead to a reduction in activity, rather than the increase implied by the standard GTAP treatment.
The extent to which this is an issue can only be assessed on a country by country basis. It is well known that in some developing countries, the presence of (particularly EU) export quota leads to production distortions well beyond what can be captured by an export tax. This should be kept in mind when interpreting the various results presented below.

2	Unilateral change of Australia’s TCF tariffs

In the GTAP database, average Australian tariff rates for textile, clothing and leather product imports are 15.8 per cent, 27.4 per cent and 12.1 per cent, respectively (table 2.1), and our simulations involve their removal from these levels.
2.1	Australian tariff rates for TCF imports
Sources	Textile	Clothing	Leather products	
	Per cent	
New Zealand	0.0	0.0	0.0	
US	12.6	23.8	12.6	
Canada	7.5	26.5	8.0	
Mexico	13.5	25.7	11.2	
EU	12.2	25.2	15.6	
Chinas	21.8	29.6	12.3	
Japan	14.5	25.5	4.5	
Korea	17.7	25.1	12.2	
Other Asian APEC	11.8	30.9	15.7	
Malaysia	8.4	30.2	13.4	
Singapore	10.5	29.2	9.3	
Thailand	10.5	30.3	11.7	
ROW	17.6	31.1	11.4	
Average	15.8	27.4	12.1	
Source: GTAP database v.5
Tables 2.2 and 2.3 report key results from unilateral removal of Australia’s TCF tariffs. Tables 2.4 and 2.5 report key results from a unilateral 50 per cent reduction in Australia’s TCF tariffs.
	Unilateral removal of Australia’s TCF tariffs
As table 2.2 indicates, there are three components of the welfare effects: an allocative efficiency effect (resulting from the reallocation of activity away from subsidised towards non subsidised industries); a terms of trade effect (resulting either from a change in export or import prices) and an effect related to the price of capital relative to the price of savings.
2.2	Welfare effects of removing Australia’s TCF tariffs Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	130	383	-250	-3	
NZ	-27	-16	-12	1	
US	-23	-6	-19	2	
Canada	0	0	0	0	
Mexico	2	1	2	0	
EU	41	20	23	-2	
Chinas	191	54	141	-4	
Japan	46	28	18	-1	
Korea	14	-5	19	0	
OthASAPEC	32	10	20	2	
Malaysia	3	-1	4	0	
Singapore	3	0	3	0	
Thailand	1	-3	5	0	
ROW	90	40	45	4	
Total APEC	371	443	-69	-3	
World	502	503	-1	0	
Source: GTAP simulation

Australia’s tariff removal leads to an improvement in allocative efficiency ($383 million) some of which is offset by a worsening in the terms of trade. Table 2.3 indicates that this is a result of a decline in Australia’s prices received (export prices) relative to prices paid (import prices).
Australia’s tariff removal has some flow on effects to the regions that export TCF to Australia (most significantly, China). For these countries, the positive effect is mostly due to an improvement in their terms of trade, arising from increased Australian demand for TCF.
For Australia, the sectoral results show a predictable pattern. The output of the three TCF sectors (and livestock) declines, while the output of other industries increases. The decline in livestock, although it is negligible, is caused by the decline in the output of leather products.
New Zealand has a similar sectoral impact to Australia. The clothing sector in other countries tends to benefit the most the unilateral removal of Australia’s TCF tariffs. Clothing output in other Asian APEC countries increases by 1.57 per cent, followed by China with 1.37 per cent increase and Malaysia with a 0.76 per cent rise.

2.3	Unilateral removal of Australia’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.10	-0.02	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	
Income	0.04	-0.05	0.00	0.00	0.00	0.00	0.02	0.00	0.00	0.01	0.00	0.00	0.00	0.00	
Investment	-0.05	-0.01	0.00	0.00	0.00	0.00	0.01	0.00	0.01	0.02	0.00	0.00	0.00	0.01	
Exports 	3.32	-0.08	0.00	0.00	0.01	0.00	0.09	0.01	0.03	0.06	0.01	0.01	0.01	0.01	
Imports	2.99	-0.12	-0.01	0.00	0.01	0.00	0.13	0.01	0.04	0.08	0.02	0.01	0.02	0.02	
GDP deflator	-0.59	-0.16	0.00	0.00	0.00	0.00	0.04	0.00	0.01	0.02	0.00	0.00	0.00	0.01	
Terms of trade	-0.34	-0.07	0.00	0.00	0.00	0.00	0.03	0.00	0.01	0.02	0.00	0.00	0.01	0.00	
Prices received	-0.34	-0.16	0.00	0.00	0.00	0.00	0.03	0.00	0.01	0.01	0.00	0.00	0.00	0.00	
Prices paid	0.00	-0.09	0.00	0.00	0.00	0.00	0.00	0.00	-0.01	0.00	0.00	0.00	0.00	0.00	
Sectoral output														
Crops	0.47	0.56	0.00	-0.01	0.00	-0.01	-0.01	-0.01	0.00	-0.01	0.00	0.00	0.00	-0.01	
Livestock	-0.03	-0.58	-0.01	-0.02	-0.01	-0.02	0.00	-0.01	-0.02	-0.01	-0.03	-0.01	-0.04	-0.01	
Forestry & mining	0.63	0.32	0.00	0.00	0.00	0.00	-0.07	-0.01	-0.02	-0.04	-0.01	-0.01	-0.01	-0.01	
Food processing	0.66	0.71	-0.01	-0.02	-0.01	-0.01	-0.05	-0.01	-0.02	-0.03	-0.03	-0.07	-0.04	-0.01	
Textile	-18.32	-9.53	-0.04	-0.13	-0.03	-0.05	0.72	0.04	0.37	0.14	-0.02	-0.32	0.01	0.11	
Clothing	-48.68	-11.60	0.03	0.04	0.02	0.06	1.37	0.03	0.09	1.57	0.76	0.46	0.48	0.38	
Leather	-10.04	-15.58	0.11	0.05	0.03	0.32	-0.03	0.02	0.09	0.97	0.65	-0.13	0.06	-0.01	
Paper products	0.13	0.19	0.00	0.00	0.00	0.00	-0.07	0.00	-0.01	-0.07	-0.02	-0.02	-0.01	-0.01	
Chemicals etc	0.64	0.14	0.00	0.00	0.00	0.00	-0.05	0.00	0.02	-0.02	0.01	0.01	0.00	0.00	
Other manufact	1.85	0.63	0.00	0.01	0.01	0.00	-0.12	-0.01	-0.05	-0.13	-0.04	-0.05	-0.03	-0.03	
Ferrous metals	1.33	0.38	0.00	0.01	0.00	0.00	-0.14	0.00	-0.03	-0.09	-0.02	-0.02	-0.03	-0.02	
Motor vehicles 	1.88	0.70	0.00	0.00	-0.01	-0.01	-0.16	-0.02	-0.07	-0.15	-0.01	0.01	-0.01	-0.02	
Transport nec	2.59	0.15	-0.01	-0.01	0.00	-0.01	-0.21	0.00	-0.08	-0.08	-0.05	0.00	-0.05	-0.04	
Electrical	1.67	0.71	0.02	0.03	0.04	0.01	-0.19	0.01	-0.03	-0.06	0.01	0.00	-0.01	-0.01	
Other equipment	1.69	0.74	0.01	0.02	0.01	0.00	-0.14	0.01	-0.02	-0.04	0.01	0.01	-0.02	-0.02	
Utilities & constr	0.02	0.01	0.00	0.00	0.00	0.00	0.01	0.00	0.01	0.02	0.00	0.00	0.00	0.00	
Trade & transport	0.18	0.16	0.00	0.00	0.00	0.00	-0.03	0.00	0.01	-0.01	0.00	0.02	0.00	0.00	
Services	0.05	0.03	0.00	0.00	0.00	0.00	-0.01	0.00	0.00	-0.03	-0.01	-0.01	-0.01	0.00	
Source: GTAP simulation

	Unilateral 50% reduction in Australia’s TCF tariffs
A unilateral 50 per cent reduction in Australia’s TCF tariffs results in smaller allocative efficiency gains and terms of trade losses than completely removing the tariffs. However, the net benefit Australia gains is higher than tariff removal (US$160 million versus US$130 million), although the total world gain is smaller (US$337 million versus US$502 million). The sectoral impacts are similar to the previous simulation, but with smaller magnitudes.
These two simulations presented here suggest that Australia can improve its welfare through unilateral tariff reform. The simulations suggest that the optimal extent of the reform depends on the balance of the allocative efficiency gain and the terms of trade loss. As will be discussed further in chapter 5, this balance depends crucially on the choice of the model’s trade parameters.
2.4	Welfare effects of 50 per cent reduction in Australia’s TCF tariffs Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	160	274	-112	-1	
NZ	-18	-8	-11	1	
US	-9	-2	-8	1	
Canada	0	0	0	0	
Mexico	1	0	1	0	
EU	26	14	13	-1	
Chinas	88	25	65	-2	
Japan	25	15	10	-1	
Korea	7	-2	10	0	
OthASAPEC	14	4	8	1	
Malaysia	1	-1	2	0	
Singapore	1	0	1	0	
Thailand	1	-1	2	0	
ROW	40	19	19	2	
Total APEC	271	305	-32	-1	
World	337	337	0	0	
Source: GTAP simulation

2.5	Unilateral removal of Australia’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.07	-0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	
Income	0.05	-0.03	0.00	0.00	0.00	0.00	0.01	0.00	0.00	0.00	0.00	0.00	0.00	0.00	
Investment	-0.02	-0.01	0.00	0.00	0.00	0.00	0.01	0.00	0.00	0.01	0.00	0.00	0.00	0.00	
Exports 	1.48	-0.11	0.00	0.00	0.00	0.00	0.04	0.00	0.01	0.03	0.01	0.00	0.01	0.01	
Imports	1.31	-0.17	0.00	0.00	0.00	0.00	0.06	0.00	0.02	0.04	0.01	0.00	0.01	0.01	
GDP deflator	-0.26	-0.11	0.00	0.00	0.00	0.00	0.02	0.00	0.01	0.01	0.00	0.00	0.00	0.00	
Terms of trade	-0.15	-0.06	0.00	0.00	0.00	0.00	0.02	0.00	0.01	0.01	0.00	0.00	0.00	0.00	
Prices received	-0.16	-0.10	0.00	0.00	0.00	0.00	0.01	0.00	0.00	0.01	0.00	0.00	0.00	0.00	
Prices paid	0.00	-0.04	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	
Sectoral output														
Crops	0.23	0.35	0.00	-0.01	0.00	-0.01	0.00	-0.01	0.00	-0.01	0.00	0.00	0.00	0.00	
Livestock	-0.06	-0.34	-0.01	-0.01	0.00	-0.01	0.00	-0.01	-0.01	-0.01	-0.01	-0.01	-0.02	0.00	
Forestry & mining	0.29	0.21	0.00	0.00	0.00	0.00	-0.03	-0.01	-0.01	-0.02	-0.01	-0.01	-0.01	0.00	
Food processing	0.31	0.45	0.00	-0.01	0.00	-0.01	-0.02	-0.01	-0.01	-0.01	-0.01	-0.04	-0.02	-0.01	
Textile	-9.86	-5.84	-0.01	-0.06	-0.01	-0.02	0.32	0.03	0.19	0.07	-0.02	-0.14	0.01	0.05	
Clothing	-24.11	-8.38	0.02	0.02	0.02	0.05	0.63	0.02	0.06	0.65	0.34	0.22	0.21	0.16	
Leather	-7.57	-10.65	0.06	0.03	0.02	0.14	0.04	0.01	0.07	0.42	0.31	-0.03	0.06	0.01	
Paper products	0.06	0.15	0.00	0.00	0.00	0.00	-0.03	0.00	0.00	-0.03	-0.01	-0.01	0.00	0.00	
Chemicals etc	0.29	0.11	0.00	0.00	0.00	0.00	-0.02	0.00	0.01	-0.01	0.01	0.01	0.00	0.00	
Other manufact	0.86	0.44	0.00	0.01	0.00	0.00	-0.06	0.00	-0.02	-0.06	-0.02	-0.02	-0.01	-0.01	
Ferrous metals	0.61	0.27	0.00	0.01	0.00	0.00	-0.07	0.00	-0.02	-0.04	-0.01	-0.01	-0.01	-0.01	
Motor vehicles 	0.88	0.47	0.00	0.00	0.00	0.00	-0.07	-0.01	-0.04	-0.06	0.00	0.01	0.00	-0.01	
Transport nec	1.20	0.20	0.00	0.00	0.00	-0.01	-0.10	0.00	-0.04	-0.03	-0.02	0.00	-0.03	-0.02	
Electrical	0.78	0.45	0.01	0.02	0.02	0.01	-0.09	0.00	-0.01	-0.02	0.01	0.00	-0.01	0.00	
Other equipment	0.79	0.50	0.00	0.01	0.01	0.00	-0.06	0.00	-0.01	-0.02	0.00	0.01	-0.01	-0.01	
Utilities & constr	0.02	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.01	0.00	0.00	0.00	0.00	
Trade & transport	0.10	0.11	0.00	0.00	0.00	0.00	-0.01	0.00	0.00	0.00	0.00	0.01	0.00	0.00	
Services	0.05	0.02	0.00	0.00	0.00	0.00	-0.01	0.00	0.00	-0.01	0.00	0.00	0.00	0.00	
Source: GTAP simulation

3	Unilateral liberalisation of TCF trade in other countries

	Unilateral liberalisation of TCF trade in the US
The unilateral liberalisation of TCF trade in the US includes the removal of the import tariffs and quotas. As discussed before, MFA quota generates rents which are treated as export tax of TCF to the US in the GTAP database. Therefore removing import quotas is equivalent to reducing the export tax of TCF to the US. Tables 3.1 and 3.2 show the effects of TCF trade liberalisation in the US. The total gain worldwide from this removal is US$10 444 million, much higher than the gain when Australia unilaterally removes its TCF tariffs presented in the previous chapter.
3.1	Welfare effects of removing the US TCF tariffs Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	25	-17	32	11	
NZ	8	-4	12	0	
US	8209	3993	4514	-298	
Canada	-48	-189	113	28	
Mexico	-650	-330	-400	80	
EU	-202	-227	21	4	
Chinas	3790	6480	-2587	-103	
Japan	-95	-15	-86	6	
Korea	60	-90	138	12	
OthASAPEC	-9	109	-183	65	
Malaysia	-31	10	-28	-13	
Singapore	-15	-10	-18	12	
Thailand	95	175	-76	-4	
ROW	-693	520	-1413	200	
Total APEC	11339	10113	1431	-204	
World	10444	10405	39	0	
Source: GTAP simulation

3.2	Unilateral removal of the US TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.00	0.00	0.10	0.00	-0.10	0.00	0.50	0.00	0.00	0.00	0.00	0.00	0.10	0.00	
Income	0.00	0.00	0.10	0.00	-0.20	0.00	0.30	0.00	0.00	0.00	0.00	0.00	0.10	0.00	
Investment	0.00	0.00	0.00	0.10	-0.60	0.00	0.40	0.00	0.10	0.20	0.00	0.00	0.30	0.10	
Exports 	0.10	0.10	4.90	0.10	1.10	0.00	4.20	0.00	0.30	0.90	0.10	-0.20	0.70	0.30	
Imports	0.10	0.10	4.60	0.20	0.60	0.00	3.70	-0.20	0.40	0.70	0.00	-0.20	0.80	0.20	
GDP deflator	0.10	0.10	-0.60	-0.10	-0.80	0.10	1.00	0.10	0.20	0.30	0.10	0.10	0.30	0.10	
Terms of trade	0.00	0.10	0.40	0.10	-0.30	0.00	-0.60	-0.10	0.10	-0.10	0.00	0.00	-0.10	-0.10	
Prices received	0.10	0.10	-0.40	-0.20	-0.60	0.10	-0.40	0.10	0.20	0.00	0.10	0.10	0.00	-0.10	
Prices paid	0.10	0.10	-0.80	-0.20	-0.30	0.10	0.20	0.10	0.10	0.10	0.10	0.10	0.10	0.00	
Sectoral output														
Crops	0.20	0.10	0.30	0.50	0.30	0.10	-0.30	0.10	0.00	-0.10	0.00	0.10	-0.20	0.00	
Livestock	0.40	0.40	0.40	0.10	0.20	0.10	0.50	0.20	-0.10	0.20	0.10	0.10	-0.40	0.00	
Forestry & mining	0.00	-0.10	0.70	0.20	1.00	0.00	-2.20	0.00	-0.20	-0.50	-0.10	-0.20	-0.90	-0.10	
Food processing	0.00	-0.10	0.30	0.20	0.20	0.10	-1.20	0.10	-0.10	-0.20	0.00	0.80	-1.00	-0.10	
Textile	1.70	1.50	-21.00	-18.80	-22.00	0.10	17.50	4.00	8.20	11.30	11.20	7.10	18.10	3.40	
Clothing	-0.20	0.40	-50.80	-15.30	-38.60	-1.10	59.10	0.90	-6.10	0.80	6.10	-10.90	24.70	-0.40	
Leather	0.10	0.30	-20.90	-16.60	-11.40	-1.10	8.20	1.50	5.70	33.80	3.40	4.00	7.20	-1.30	
Paper products	0.00	0.00	0.40	0.00	0.20	0.00	-2.30	0.00	0.10	-0.50	0.00	-0.10	-0.40	-0.10	
Chemicals etc	0.00	0.00	0.10	-0.10	-1.00	0.00	-2.10	0.10	0.50	-0.10	-0.20	0.90	-0.40	0.00	
Other manufacture	0.50	0.20	2.10	1.30	3.20	0.20	-3.90	0.20	0.00	-0.80	0.20	0.50	-1.60	0.00	
Ferrous metals	0.10	0.10	1.50	0.80	3.30	0.10	-4.90	0.10	-0.30	-0.70	0.10	0.20	-2.00	-0.10	
Motor vehicles	-0.70	-0.40	1.90	0.30	5.50	-0.40	-5.90	-1.30	-1.40	-1.90	-0.40	0.00	-0.90	-0.50	
Transport nec	-1.30	-1.10	3.00	1.10	2.00	-1.00	-7.90	-1.00	-3.00	-2.30	-2.10	-0.90	-7.60	-1.00	
Electrical	-0.10	0.00	2.70	2.40	6.50	0.20	-7.30	-0.10	-0.70	-1.00	-0.50	-0.70	-3.70	-0.10	
Other equipment	-0.30	-0.40	1.80	0.70	6.00	-0.10	-5.40	0.10	-0.70	-1.20	-0.60	-0.20	-2.90	-0.30	
Utilities & construct	0.00	0.00	0.00	0.10	-0.60	0.00	0.10	0.00	0.10	0.10	0.00	0.00	0.30	0.00	
Trade & transport	0.00	0.00	0.20	0.20	0.20	0.10	-1.20	0.00	0.20	-0.20	0.10	0.40	-0.30	0.10	
Services	0.00	0.00	0.00	0.10	0.30	0.00	-0.60	0.00	-0.10	-0.60	-0.30	-0.40	-0.80	-0.10	
Source: GTAP simulations

The biggest winner of this unilateral removal of the US TCF tariffs is the US, achieving a US$8 209 million of welfare improvement due to allocation efficiency improvement and terms of trade gains. Terms of trade gains come from the lower import prices of TCF due to reduction in the export tax in exporting countries. It is followed by the greater China, (including Hong Kong and Taiwan), achieving a US$3 790 million of welfare improvement due to allocation efficiency improvement. Australia’s gain from this is moderate, being US$25 million, exclusively from terms of trade gains.
Except the rest of the world, the biggest loser is Mexico, registering a net loss of US$650 million, because of losses in both allocative efficiency and terms of trade. Trade liberalisation of TCF in the US means that the protection level in Mexico is relatively higher than before, causing losses in allocative efficiency. On the other hand, its terms of trade deteriorates due to lower TCF prices in the world market which is caused by the eliminating of import quotas to the US. The EU is the second biggest loser at US$202 million due to deteriorating allocative efficiency as the EU is relatively more protective after the liberalisation of TCF trade in the US. Malaysia loses as well because losses in quota rent due to eliminating the quota are bigger than the gains from removing import tariffs in the US.
In percentage terms, the largest income gainers are greater China (0.31 per cent), followed by the US (0.11 per cent), Thailand (0.07 per cent) and Korea (0.04 per cent). Australia and New Zealand are only marginally better (0.01 per cent). The largest losers are Mexico (-0.19 per cent), followed by Malaysia and Singapore (-0.02 per cent each).
The sectoral composition of these gains differs considerably between regions. For Australia, the textile sector gain due to better position in the world market and higher demand for textiles from other boosting countries like China. On the other hand, the clothing sector in Australia contracts because of tougher competition suggested by lower price of clothing in the world market.
	Unilateral removal of TCF tariffs in the EU
Tables 3.3 and 3.4 show the effect of the unilateral removal of the EU’s TCF tariffs. The total gain worldwide is US$6 749 million, less than the previous case.
China is the biggest winner, but the magnitude is smaller than the previous case (US$2 804 million versus US$3 790 million). It is followed by the rest of the world (US$2 384), other Asian APEC country group (US$1 313 million) and the EU (US$865 million). Again Australia benefits little from this removal, with EV being only US$25 million.
Similarly to the reasoning for the EU in the previous simulation, the biggest loser is the US which suffers from worsening allocative efficiency and terms of trade. It is followed by Japan.
The largest percentage gainers in this simulation are Other Asian APEC countries, China and Thailand and Malaysia, each of which experiences large changes in its overall trade. 
3.3	Welfare effects of removing the EU TCF tariffs Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	25	-13	40	-3	
NZ	2	-2	6	-2	
US	-737	-227	-634	124	
Canada	33	-3	67	-30	
Mexico	49	22	50	-23	
EU	865	2215	-1451	101	
Chinas	2804	2664	288	-148	
Japan	-328	-15	-114	-199	
Korea	99	-38	158	-21	
OthASAPEC	1313	770	413	130	
Malaysia	76	61	45	-30	
Singapore	-23	-7	-21	5	
Thailand	187	91	111	-14	
ROW	2384	1235	1038	112	
Total APEC	3499	3304	408	-212	
World	6749	6753	-5	0	
Source: GTAP simulation

3.4	Removing the EU TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.00	0.00	0.00	0.00	0.01	0.03	0.21	0.00	-0.01	0.25	0.06	-0.01	0.06	0.02	
Income	0.01	0.00	-0.01	0.01	0.01	0.01	0.24	-0.01	0.03	0.47	0.08	-0.03	0.14	0.05	
Investment	-0.02	-0.01	-0.06	-0.04	-0.02	-0.15	0.26	-0.07	0.03	0.74	-0.02	-0.01	0.28	0.23	
Exports 	0.05	0.01	-0.03	0.00	0.08	1.07	2.36	0.07	0.36	2.41	0.23	-0.13	0.53	0.66	
Imports	0.07	0.03	-0.15	0.00	0.09	1.01	2.49	-0.14	0.47	2.85	0.22	-0.13	0.81	0.88	
GDP deflator	0.04	0.02	-0.02	0.01	0.03	-0.51	0.79	0.01	0.18	1.05	0.17	0.05	0.37	0.13	
Terms of trade	0.06	0.03	-0.04	0.02	0.03	-0.05	0.06	-0.06	0.09	0.41	0.03	-0.01	0.15	0.09	
Prices received	0.06	0.02	0.00	0.01	0.01	-0.40	0.14	0.02	0.12	0.45	0.09	0.07	0.19	-0.01	
Prices paid	0.01	-0.01	0.04	-0.01	-0.02	-0.34	0.08	0.07	0.03	0.05	0.06	0.08	0.04	-0.10	
Sectoral output														
Crops	0.35	0.42	0.18	0.32	0.06	0.48	-0.07	0.13	0.03	-0.44	-0.01	0.03	-0.12	-0.02	
Livestock	0.18	-0.07	0.14	0.14	0.00	0.44	0.35	0.17	-0.04	0.38	-0.12	0.11	-0.35	0.06	
Forestry & mining	0.13	0.21	0.07	0.07	0.00	0.86	-1.34	0.12	-0.14	-1.72	-0.16	0.06	-0.67	-0.18	
Food processing	0.12	0.25	0.04	0.04	-0.01	0.40	-0.81	0.08	-0.09	-0.78	-0.35	0.75	-0.84	-0.21	
Textile	-0.26	-4.08	0.23	0.20	0.26	-19.47	12.85	2.91	7.65	26.60	19.08	9.43	17.33	5.27	
Clothing	-0.18	0.00	0.16	0.22	1.08	-42.22	36.10	0.42	-1.49	28.43	30.22	0.83	15.67	6.63	
Leather	-3.44	-4.09	2.46	3.04	1.24	-18.03	3.93	0.94	7.64	76.89	50.77	7.30	18.23	1.04	
Paper products	-0.02	0.09	0.00	-0.08	-0.06	0.26	-1.46	0.05	0.09	-2.51	-0.34	0.02	-0.38	-0.35	
Chemicals etc	0.01	-0.01	-0.01	-0.02	-0.03	0.35	-1.30	0.10	0.43	-0.84	-0.47	1.08	-0.37	-0.31	
Other manufacture	0.32	0.36	0.19	0.37	0.05	1.49	-2.54	0.12	-0.22	-4.15	-0.38	0.21	-1.80	-0.72	
Ferrous metals	0.05	0.11	0.00	-0.02	-0.11	1.49	-3.27	0.07	-0.47	-3.23	-0.59	0.10	-1.93	-0.83	
Motor vehicles	-0.55	-0.39	-0.36	-0.62	-0.71	1.73	-4.10	-0.87	-1.74	-6.84	-1.41	-0.40	-0.94	-1.41	
Transport nec	-0.29	0.00	0.04	-0.41	-0.15	4.06	-4.97	-0.17	-2.05	-4.83	-2.07	-0.23	-5.85	-1.00	
Electrical	0.01	0.24	0.22	0.65	0.83	2.09	-4.75	0.05	-0.72	-3.80	-0.75	-0.69	-3.33	-0.49	
Other equipment	-0.29	-0.32	-0.08	-0.10	-0.24	1.88	-3.59	-0.03	-0.88	-3.09	-1.51	-0.44	-2.87	-1.09	
Utilities & construct	-0.01	0.00	-0.03	-0.02	-0.01	-0.01	0.08	-0.06	0.07	0.66	0.11	0.00	0.28	0.07	
Trade & transport	0.01	0.02	0.02	0.05	0.00	0.32	-0.75	0.02	0.18	-0.52	-0.16	0.29	-0.41	0.03	
Services	-0.03	-0.02	-0.01	-0.04	-0.04	0.06	-0.35	-0.01	-0.10	-1.48	-0.52	-0.39	-0.75	-0.09	
Source: GTAP simulation

The sectoral impact also differs significantly across countries. But a general pattern is that those with terms of trade gains (losses) have a rise (fall) in TCF sectors. For example, textile and clothing output in greater China increases by 12.85 per cent and 36.10 per cent, respectively.  On the other hand, the EU’s outputs in these two sector declines by 19.47 per cent and 42.22 per cent, respectively. The largest percentage rising sector in Australia is crops, which increases by 0.35 per cent. The biggest falling sector is leather products, with output down by 3.44 per cent. This is due to a substitution effect. The EU imports of leather products from Australia enjoy lower tariff rates than from other countries, and the removal of tariffs means a smaller change in relative prices which substitute Australian products for products from other sources.
	Unilateral removal of TCF tariffs in China
Tables 3.5 and 3.6 show the effect of the unilateral removal of greater China’s TCF tariffs. The total gains worldwide are US$5 470 million, slightly lower than the gains when the EU unilaterally removes its TCF tariffs. It can also be seen from table 3.5 that almost all the gains are to APEC countries.
The biggest winners of this removal are China and Japan, both achieving gains of US$1 868 million, although through different channels. China gains US$3 913 million in allocative efficiency, despite losses in the terms of trade and capital prices. On the other hand, Japan gains in both allocative efficiency and terms of trade. The US, Korea and the EU also benefit from China’s unilateral removal of TCF tariffs, achieving US$907 million, US$746 million and US$483 million, respectively, through similar mechanisms to Japan.
Australia’s welfare gain from this removal is more than triple the gains in the unilateral removal of EU TCF tariffs, but still 30 per cent lower than the gains when Australia unilaterally removes its TCF tariffs.
Losers from China’s unilateral removal of TCF tariffs are other Asian countries and Mexico. These countries’ allocative efficiency deteriorates because their protection in TCF sectors is higher in relative terms after China’s removal. On top of that, their terms of trade worsens because these countries have a similar economic structure to China, ie. a higher share of TCF exports, and world price of TCFs is pulled down by China’s action.
3.5	Welfare effects of removing China TCF tariffs Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	91	54	34	3	
NZ	13	10	3	0	
US	907	378	434	94	
Canada	98	65	36	-3	
Mexico	-50	-4	-48	3	
EU	483	242	229	12	
Chinas	1868	3913	-2039	-6	
Japan	1868	831	1154	-117	
Korea	746	160	595	-10	
OthASAPEC	-138	-46	-95	3	
Malaysia	-42	-16	-24	-2	
Singapore	33	-1	30	4	
Thailand	-62	-25	-38	1	
ROW	-346	-88	-275	17	
Total APEC	5333	5319	43	-29	
World	5470	5473	-3	0	
Source: GTAP simulation
The TCF sectors are the most significantly affected sectors. Output of clothing and leather products in China increases while the output of textiles decreases, reflecting better allocation of resources. On the other hand, both Japan and Korea achieve higher output of textiles. 
All three TCF sectors in Australia decrease, with leather products being the worst hit sector (down by 4.42 per cent). On the other hand, higher output will be registered in motor vehicle and electronic equipment sectors, up by 0.34 per cent and 0.25 per cent, respectively.
	A comparison to Australia’s unilateral reform
The simulations show that Australia gains more from its unilateral removal or reduction of TCF tariffs than from other countries’ unilateral removal. This is because tariff removal usually benefits exporters, but Australia is a net importer of TCFs. Australia could have limited gains in the terms of trade because the import price is now lower due to tariff removal in other country, but it generally suffers from even more deteriorating allocative efficiency.
On the other hand, unilateral removal or reduction of Australia’s TCF tariffs can facilitate the restructuring of the economy, leading to a much higher allocative efficiency gains than losses in the terms of trade. These simulations confirm the suggestion made in the previous chapter that Australia could unilaterally reduce its TCF tariffs to improve its welfare.
It should be pointed out, however, that the welfare gains from Australia’s unilateral action are achieved in the cost of TCF sectors. When Australia unilaterally reduces its TCF tariffs to the half of the current levels, which is a more gentle reform compared to the unilateral removal, textile output decreases about 10 per cent, clothing output decreases more than 24 per cent, and leather product output is down by 7.6 per cent. Therefore, it might be in the interest of Australia to pursue bilateral or multilateral tariff reform.  We will present the results of simulating such scenarios in the next chapter.

3.6	Removing China’s TCF tariffs: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.01	0.02	0.00	0.01	0.00	0.00	0.30	0.02	0.04	-0.01	-0.02	0.00	-0.02	0.00	
Income	0.03	0.02	0.01	0.02	-0.01	0.01	0.16	0.05	0.19	-0.05	-0.04	0.05	-0.04	-0.01	
Investment	0.00	-0.01	-0.01	0.00	-0.07	-0.01	0.27	0.01	0.14	-0.10	-0.01	0.03	-0.08	-0.08	
Exports 	0.17	0.08	0.17	0.11	0.14	-0.01	6.48	0.80	0.86	-0.08	0.03	0.05	-0.01	0.00	
Imports	0.20	0.09	0.18	0.13	0.08	-0.01	6.53	1.15	1.25	-0.18	0.02	0.08	-0.08	-0.08	
GDP deflator	-0.01	-0.04	-0.03	-0.03	-0.10	-0.05	-0.33	0.13	0.45	-0.13	-0.06	0.01	-0.08	-0.09	
Terms of trade	0.05	0.02	0.05	0.01	-0.05	0.01	-0.45	0.24	0.36	-0.08	-0.03	0.02	-0.05	-0.02	
Prices received	-0.02	-0.04	-0.03	-0.03	-0.08	-0.05	-0.56	0.11	0.31	-0.11	-0.03	0.01	-0.07	-0.08	
Prices paid	-0.07	-0.06	-0.08	-0.04	-0.03	-0.06	-0.11	-0.13	-0.06	-0.03	0.00	-0.02	-0.01	-0.06	
Sectoral output														
Crops	-0.04	-0.03	-0.02	-0.03	0.01	-0.06	-0.18	-0.11	-0.12	0.04	0.01	-0.07	0.03	0.01	
Livestock	0.02	0.08	0.11	0.07	0.02	0.01	0.06	0.07	0.05	0.00	0.08	0.06	0.10	-0.04	
Forestry & mining	-0.04	0.02	-0.02	-0.02	0.06	0.00	-0.12	-0.25	-0.80	0.15	0.02	-0.16	0.06	0.07	
Food processing	0.01	0.01	0.01	0.02	0.01	-0.01	0.02	-0.05	-0.09	0.09	0.09	0.19	0.16	0.06	
Textile	-1.00	-1.97	-1.67	-2.23	-2.05	-2.29	-3.90	14.82	19.18	-3.31	-7.01	-6.86	-2.67	-1.62	
Clothing	-0.76	-5.69	-3.49	-4.81	-4.87	-5.14	11.61	6.22	0.09	-4.77	-7.67	-3.53	-3.75	-3.72	
Leather	-4.42	-1.80	-1.56	-4.08	-1.63	-3.54	3.63	-2.27	29.83	-2.98	-0.85	-5.01	-3.75	-1.91	
Paper products	-0.01	0.06	0.01	0.02	0.02	-0.02	0.03	0.03	-0.24	0.30	0.13	-0.06	0.02	0.06	
Chemicals etc	-0.02	0.07	-0.04	0.00	-0.12	-0.05	-0.01	-0.03	0.44	0.11	0.06	-0.15	0.07	0.04	
Other manufacture	-0.17	0.06	-0.03	-0.08	0.23	0.00	0.33	-0.32	-1.45	0.38	0.04	-0.29	0.12	0.18	
Ferrous metals	0.12	0.18	0.11	0.20	0.37	0.14	-0.27	-0.35	-1.66	0.49	0.34	0.11	0.53	0.29	
Motor vehicles	0.34	0.53	0.21	0.47	0.91	0.33	-0.17	-1.02	-2.50	1.23	0.40	0.23	0.21	0.42	
Transport nec	0.11	0.08	0.30	0.35	0.26	0.63	-0.78	-1.10	-4.76	0.32	0.45	-0.02	1.06	0.81	
Electrical	0.25	0.35	0.34	0.51	0.98	0.40	-0.84	-0.38	-2.16	0.56	0.39	0.17	0.91	0.38	
Other equipment	0.11	0.24	0.12	0.21	0.73	0.23	-0.36	-0.58	-1.94	0.35	0.54	0.21	0.54	0.34	
Utilities & construct	-0.01	0.00	0.00	0.00	-0.07	0.00	0.17	-0.02	0.21	-0.09	-0.07	-0.01	-0.07	-0.03	
Trade & transport	0.03	0.07	0.03	0.05	0.03	0.10	-0.23	0.00	-0.08	0.07	0.17	0.29	0.08	0.12	
Services	0.01	0.02	0.00	0.01	0.03	0.01	-0.17	0.00	-0.14	0.11	0.02	-0.10	0.06	0.04	
Source: GTAP simulation

4	Multilateral and global TCF liberalisation

In this chapter we present simulations involving TCF liberalisation in more than one country. The simulations are presented in the order of broadness. First, TCF liberalisation in Australia and each one of the EU, the US and China is discussed. This is followed by simulation of TCF liberalisation in APEC countries. Finally global TCF liberalisation is discussed.
	Removal of TCF protections in Australia and the EU
Tables 4.1 and 4.2 show the effects of removing TCF protection in Australia and the EU. Australia, the EU and the world as a whole have higher welfare than the cases where Australia or the EU unilaterally removes their protection.
4.1	Welfare effects of removing TCF protections in Australia and the EU Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	153	373	-215	-6	
NZ	-26	-18	-7	-1	
US	-757	-232	-650	125	
Canada	33	-4	67	-30	
Mexico	51	23	52	-23	
EU	906	2239	-1432	99	
Chinas	2993	2717	428	-152	
Japan	-281	13	-95	-200	
Korea	114	-42	177	-21	
OthASAPEC	1343	779	433	132	
Malaysia	79	60	49	-30	
Singapore	-20	-6	-19	5	
Thailand	189	88	116	-14	
ROW	2487	1281	1090	117	
Total APEC	3871	3750	336	-215	
World	7264	7270	-6	0	
Source: GTAP simulation

4.2	Removing TCF tariffs in Australian and the EU: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.09	-0.03	0.00	0.00	0.01	0.03	0.21	0.00	-0.01	0.25	0.06	-0.01	0.06	0.03	
Income	0.04	-0.04	-0.01	0.01	0.01	0.01	0.26	-0.01	0.03	0.48	0.08	-0.03	0.14	0.06	
Investment	-0.08	-0.02	-0.07	-0.04	-0.02	-0.15	0.27	-0.07	0.04	0.76	-0.02	-0.01	0.29	0.23	
Exports 	3.34	-0.07	-0.03	0.01	0.08	1.08	2.45	0.08	0.39	2.46	0.24	-0.12	0.54	0.67	
Imports	3.02	-0.10	-0.15	0.00	0.10	1.01	2.61	-0.14	0.51	2.93	0.25	-0.12	0.84	0.91	
GDP deflator	-0.56	-0.15	-0.02	0.01	0.03	-0.50	0.83	0.01	0.19	1.07	0.18	0.05	0.38	0.14	
Terms of trade	-0.29	-0.04	-0.05	0.02	0.03	-0.05	0.09	-0.05	0.11	0.42	0.03	-0.01	0.16	0.10	
Prices received	-0.28	-0.14	0.00	0.01	0.01	-0.39	0.17	0.02	0.13	0.47	0.09	0.07	0.19	-0.01	
Prices paid	0.01	-0.10	0.04	-0.01	-0.02	-0.34	0.08	0.07	0.02	0.04	0.06	0.08	0.04	-0.10	
Sectoral output														
Crops	0.82	0.99	0.18	0.31	0.05	0.47	-0.07	0.12	0.03	-0.45	-0.01	0.04	-0.12	-0.03	
Livestock	0.15	-0.65	0.12	0.12	-0.01	0.42	0.35	0.16	-0.06	0.37	-0.15	0.10	-0.39	0.05	
Forestry & mining	0.77	0.54	0.07	0.07	0.00	0.85	-1.40	0.11	-0.17	-1.76	-0.18	0.05	-0.68	-0.19	
Food processing	0.79	0.97	0.04	0.02	-0.01	0.39	-0.86	0.07	-0.11	-0.81	-0.38	0.68	-0.89	-0.22	
Textile	-18.63	-13.68	0.20	0.07	0.24	-19.50	13.50	2.94	8.02	26.71	19.13	9.10	17.37	5.38	
Clothing	-49.49	-11.92	0.19	0.26	1.11	-42.11	37.34	0.45	-1.39	29.90	31.18	1.35	16.17	7.06	
Leather	-15.28	-20.27	2.56	3.08	1.27	-17.60	3.86	0.94	7.69	77.64	51.69	7.18	18.27	1.04	
Paper products	0.11	0.28	0.00	-0.07	-0.06	0.25	-1.52	0.05	0.08	-2.57	-0.36	0.00	-0.38	-0.35	
Chemicals etc	0.65	0.14	-0.02	-0.02	-0.03	0.35	-1.34	0.10	0.45	-0.85	-0.47	1.09	-0.38	-0.31	
Other manufacture	2.20	1.00	0.19	0.38	0.06	1.48	-2.66	0.11	-0.27	-4.27	-0.43	0.16	-1.83	-0.75	
Ferrous metals	1.40	0.49	0.00	-0.01	-0.10	1.49	-3.39	0.06	-0.50	-3.31	-0.62	0.07	-1.96	-0.85	
Motor vehicles	1.33	0.32	-0.36	-0.62	-0.71	1.72	-4.24	-0.90	-1.81	-6.97	-1.42	-0.38	-0.95	-1.43	
Transport nec	2.32	0.16	0.04	-0.42	-0.15	4.04	-5.15	-0.17	-2.13	-4.90	-2.12	-0.23	-5.90	-1.04	
Electrical	1.70	0.95	0.24	0.68	0.87	2.10	-4.92	0.06	-0.74	-3.85	-0.74	-0.68	-3.35	-0.50	
Other equipment	1.42	0.43	-0.08	-0.08	-0.23	1.88	-3.72	-0.03	-0.90	-3.13	-1.51	-0.43	-2.89	-1.12	
Utilities & construct	0.02	0.00	-0.03	-0.02	-0.01	-0.02	0.08	-0.06	0.07	0.67	0.11	0.00	0.28	0.07	
Trade & transport	0.20	0.18	0.02	0.05	0.00	0.33	-0.77	0.02	0.18	-0.53	-0.16	0.31	-0.41	0.03	
Services	0.03	0.01	-0.01	-0.04	-0.04	0.06	-0.36	-0.01	-0.10	-1.50	-0.53	-0.40	-0.76	-0.10	
Source: GTAP simulation

Australia achieves significant gains compare to the previous two unilateral removal simulations. Relative to its own unilateral removal, Australia’s allocative efficiency gains are similar, but the term of trade losses are much smaller.
	Removal of TCF protection in Australia and the US
Tables 4.3 and 4.4 present the effects of removing TCF protection in Australia and the US. This is also a better policy for Australia and the world as a whole than unilaterally removing TCF protection in Australia or the US. It leads to a slightly smaller gain in terms of trade for the US than the case where the US unilaterally liberalises its TCF trade.
4.3	Welfare effects of TCF liberalisation in Australia and the US Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	152	371	-227	8	
NZ	-20	-20	-1	1	
US	8176	3990	4484	-297	
Canada	-48	-189	113	28	
Mexico	-648	-329	-399	80	
EU	-159	-206	45	2	
Chinas	3991	6535	-2437	-107	
Japan	-49	14	-68	5	
Korea	75	-94	157	12	
OthASAPEC	27	120	-161	68	
Malaysia	-28	9	-23	-13	
Singapore	-12	-10	-15	12	
Thailand	97	172	-70	-4	
ROW	-589	566	-1360	205	
Total APEC	11715	10569	1353	-207	
World	10967	10929	38	0	
Source: GTAP simulation

4.4	Removing TCF tariffs in Australian and the US: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.09	-0.03	0.05	-0.03	-0.08	0.00	0.51	0.00	-0.02	0.04	0.01	-0.01	0.11	0.01	
Income	0.04	-0.03	0.11	-0.01	-0.19	0.00	0.34	0.00	0.02	0.01	-0.03	-0.02	0.07	-0.01	
Investment	-0.05	-0.01	-0.01	0.07	-0.58	-0.03	0.42	-0.05	0.08	0.17	-0.04	0.04	0.30	0.06	
Exports 	3.35	-0.03	4.91	0.06	1.11	-0.02	4.27	0.01	0.32	0.93	0.07	-0.22	0.74	0.34	
Imports	3.04	-0.03	4.63	0.16	0.64	-0.04	3.85	-0.18	0.47	0.83	0.02	-0.21	0.83	0.27	
GDP deflator	-0.48	-0.05	-0.56	-0.13	-0.79	0.05	1.05	0.07	0.23	0.30	0.11	0.14	0.34	0.09	
Terms of trade	-0.31	-0.01	0.38	0.06	-0.32	0.00	-0.56	-0.05	0.09	-0.12	-0.04	0.00	-0.10	-0.11	
Prices received	-0.21	-0.04	-0.43	-0.15	-0.62	0.05	-0.39	0.07	0.16	0.01	0.08	0.13	0.00	-0.07	
Prices paid	0.09	-0.03	-0.80	-0.21	-0.30	0.06	0.17	0.12	0.06	0.13	0.12	0.14	0.10	0.04	
Sectoral output														
Crops	0.64	0.67	0.31	0.52	0.27	0.09	-0.26	0.04	0.02	-0.13	0.03	0.06	-0.17	0.03	
Livestock	0.40	-0.14	0.34	0.12	0.20	0.12	0.53	0.19	-0.08	0.17	0.03	0.10	-0.46	0.04	
Forestry & mining	0.60	0.27	0.69	0.18	0.97	-0.04	-2.27	0.01	-0.23	-0.55	-0.12	-0.17	-0.89	-0.13	
Food processing	0.70	0.65	0.33	0.14	0.18	0.05	-1.25	0.07	-0.11	-0.25	-0.06	0.72	-1.04	-0.08	
Textile	-16.52	-8.10	-21.00	-18.90	-21.96	0.00	18.12	4.00	8.61	11.48	11.24	6.75	18.14	3.56	
Clothing	-49.90	-11.65	-50.77	-15.23	-38.54	-1.08	60.28	0.93	-5.98	2.50	6.96	-10.40	25.24	0.07	
Leather	-10.96	-16.20	-20.76	-16.62	-11.42	-0.80	8.20	1.47	5.77	34.78	4.07	3.87	7.24	-1.36	
Paper products	0.12	0.19	0.36	-0.02	0.20	-0.03	-2.38	0.04	0.05	-0.53	-0.01	-0.09	-0.38	-0.11	
Chemicals etc	0.65	0.11	0.07	-0.11	-0.98	-0.04	-2.15	0.08	0.54	-0.11	-0.24	0.92	-0.45	-0.04	
Other manufacture	2.35	0.89	2.14	1.36	3.22	0.20	-3.99	0.16	-0.05	-0.94	0.12	0.40	-1.68	-0.06	
Ferrous metals	1.41	0.46	1.53	0.77	3.29	0.07	-5.01	0.10	-0.32	-0.75	0.05	0.20	-2.05	-0.16	
Motor vehicles	1.18	0.28	1.86	0.27	5.54	-0.45	-6.02	-1.33	-1.49	-2.08	-0.43	0.03	-0.94	-0.49	
Transport nec	1.22	-0.88	3.04	1.13	2.03	-1.04	-8.08	-0.96	-3.11	-2.34	-2.16	-0.89	-7.65	-1.00	
Electrical	1.54	0.77	2.70	2.43	6.58	0.17	-7.47	-0.04	-0.72	-1.07	-0.47	-0.74	-3.69	-0.12	
Other equipment	1.44	0.33	1.76	0.71	6.00	-0.08	-5.48	0.06	-0.77	-1.23	-0.62	-0.19	-2.91	-0.36	
Utilities & construct	0.04	0.02	0.02	0.08	-0.63	-0.01	0.13	-0.03	0.11	0.16	0.04	0.04	0.31	0.03	
Trade & transport	0.20	0.17	0.23	0.17	0.23	0.14	-1.19	0.03	0.23	-0.17	0.07	0.46	-0.34	0.09	
Services	0.03	0.00	0.04	0.09	0.32	-0.03	-0.58	-0.01	-0.10	-0.59	-0.30	-0.39	-0.81	-0.08	
Source: GTAP simulation

	Removal of TCF protection in Australia and Greater China
Tables 4.5 and 4.6 presents the effect of removing TCF protection in Australia and greater China region (including Hong Kong and Taiwan). To both Australia and China, this is a better policy in terms of welfare improvement than unilateral removal of either country’s TCF tariffs.
To the world as a whole, this is also a better policy. Total welfare gains increase from US$502 million and US$5 470 million, respectively, to US$5 915 million. But it has different impacts on other countries. Generally speaking, Asian countries are better off than with China’s unilateral removal, but worse off than Australia’s unilateral removal. On the other hand, the EU and North American countries tend to be better off than Australia’s unilateral removal, but worse off than China’s unilateral removal.
4.5	Welfare effects of TCF liberalisation in Australia and China Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	223	407	-184	0	
NZ	-12	-5	-8	1	
US	882	371	414	97	
Canada	97	64	36	-3	
Mexico	-48	-4	-47	3	
EU	523	260	253	11	
Chinas	2027	3950	-1914	-9	
Japan	1912	858	1173	-118	
Korea	761	156	616	-10	
OthASAPEC	-112	-38	-79	5	
Malaysia	-39	-17	-20	-2	
Singapore	36	-1	32	4	
Thailand	-61	-28	-34	1	
ROW	-275	-56	-241	21	
Total APEC	5667	5714	-14	-32	
World	5915	5918	-3	0	
Source: GTAP simulation

4.6	Removing TCF tariffs in Australian and China: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.10	-0.01	0.00	0.01	0.00	0.00	0.31	0.02	0.03	-0.01	-0.02	0.00	-0.02	0.00	
Income	0.06	-0.02	0.01	0.02	-0.01	0.01	0.17	0.05	0.19	-0.04	-0.04	0.05	-0.04	-0.01	
Investment	-0.04	-0.01	-0.01	0.00	-0.07	-0.01	0.28	0.00	0.15	-0.09	-0.01	0.04	-0.07	-0.08	
Exports 	3.53	0.01	0.17	0.11	0.15	0.00	6.61	0.81	0.89	-0.03	0.04	0.06	0.00	0.02	
Imports	3.29	-0.01	0.18	0.13	0.08	0.00	6.70	1.16	1.29	-0.12	0.04	0.09	-0.06	-0.06	
GDP deflator	-0.59	-0.18	-0.03	-0.03	-0.09	-0.05	-0.29	0.13	0.47	-0.11	-0.06	0.02	-0.08	-0.09	
Terms of trade	-0.25	-0.04	0.05	0.01	-0.04	0.01	-0.42	0.24	0.38	-0.07	-0.03	0.03	-0.05	-0.02	
Prices received	-0.35	-0.19	-0.03	-0.03	-0.07	-0.05	-0.53	0.11	0.31	-0.10	-0.03	0.01	-0.06	-0.08	
Prices paid	-0.10	-0.15	-0.07	-0.04	-0.03	-0.06	-0.11	-0.13	-0.06	-0.04	0.00	-0.02	-0.01	-0.06	
Sectoral output														
Crops	0.40	0.48	-0.03	-0.04	0.00	-0.06	-0.19	-0.12	-0.12	0.02	0.00	-0.07	0.03	0.00	
Livestock	-0.01	-0.48	0.09	0.04	0.01	-0.01	0.06	0.05	0.03	-0.01	0.05	0.05	0.06	-0.04	
Forestry & mining	0.56	0.31	-0.02	-0.02	0.06	-0.01	-0.19	-0.26	-0.83	0.12	0.01	-0.17	0.05	0.06	
Food processing	0.64	0.65	0.00	0.00	0.01	-0.02	-0.03	-0.06	-0.11	0.06	0.06	0.12	0.12	0.05	
Textile	-18.49	-10.92	-1.71	-2.35	-2.07	-2.35	-3.20	14.94	19.64	-3.25	-7.08	-7.18	-2.71	-1.53	
Clothing	-45.60	-15.31	-3.46	-4.76	-4.84	-5.09	13.08	6.23	0.13	-3.54	-7.04	-3.16	-3.39	-3.43	
Leather	-14.57	-16.31	-1.44	-4.03	-1.60	-3.24	3.61	-2.24	29.95	-2.01	-0.21	-5.11	-3.68	-1.91	
Paper products	0.11	0.22	0.01	0.02	0.02	-0.02	-0.04	0.03	-0.25	0.24	0.12	-0.08	0.02	0.06	
Chemicals etc	0.60	0.19	-0.04	0.00	-0.12	-0.05	-0.06	-0.02	0.46	0.09	0.07	-0.14	0.07	0.04	
Other manufacture	1.59	0.61	-0.03	-0.07	0.24	0.00	0.21	-0.33	-1.50	0.28	0.00	-0.33	0.10	0.16	
Ferrous metals	1.40	0.51	0.11	0.21	0.38	0.15	-0.41	-0.35	-1.70	0.41	0.32	0.09	0.51	0.28	
Motor vehicles	2.14	1.16	0.21	0.47	0.90	0.32	-0.33	-1.05	-2.58	1.11	0.39	0.24	0.20	0.40	
Transport nec	2.60	0.17	0.29	0.34	0.25	0.62	-0.99	-1.11	-4.86	0.25	0.41	-0.02	1.03	0.78	
Electrical	1.84	0.99	0.36	0.54	1.02	0.41	-1.04	-0.37	-2.20	0.52	0.41	0.18	0.91	0.38	
Other equipment	1.73	0.91	0.13	0.22	0.74	0.23	-0.50	-0.57	-1.97	0.32	0.55	0.23	0.53	0.33	
Utilities & construct	0.02	0.01	0.00	0.00	-0.07	0.00	0.18	-0.02	0.21	-0.08	-0.06	-0.01	-0.08	-0.03	
Trade & transport	0.20	0.21	0.03	0.06	0.03	0.11	-0.26	0.00	-0.07	0.07	0.17	0.31	0.08	0.12	
Services	0.05	0.04	0.00	0.01	0.03	0.01	-0.18	0.00	-0.14	0.09	0.01	-0.11	0.05	0.03	
Source: GTAP simulation

	Removal of TCF protection in the APEC region
Tables 4.7 and 4.8 present the effects of expanding TCF trade liberalisation to whole APEC region. Every country except Mexico, Malaysia and the rest of the world benefits from this liberalisation. Consequently, the world welfare gain reaches US$24 443million.
The US appears to be the largest winner in this simulation with an EV increase of US$10 684 million, for the same reason discussed in the unilateral removal of the US TCF protection. China is the second largest winner with and EV increase of US$5 330 million, more than double the value at previous simulation where Australia and China remove their TCF tariffs. Compared to China, Australia’s further gain is moderate, but still 18 per cent higher than the previous simulation. For Japan, its welfare gain increases slightly from US$1 912 million to US$1 937 million because tariff removal leads to terms of trade losses. This effect is more serious in Mexico where the terms of trade loss is higher than the allocative efficiency gains.
4.7	Welfare effects of TCF liberalisation in the APEC region Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	263	396	-141	8	
NZ	26	55	-30	1	
US	10684	4211	6675	-202	
Canada	1771	977	753	42	
Mexico	-335	329	-770	106	
EU	2707	1387	1443	-123	
Chinas	5330	10295	-4782	-184	
Japan	1937	2002	-4	-62	
Korea	1444	372	1095	-23	
OthASAPEC	1074	1290	-456	240	
Malaysia	-23	171	-156	-39	
Singapore	164	-2	144	21	
Thailand	247	585	-334	-4	
ROW	-845	2300	-3364	220	
Total APEC	22581	20683	1995	-97	
World	24443	24369	74	0	
Source: GTAP simulation

4.8	Removing APEC TCF protection: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.10	0.08	0.05	0.15	0.08	0.02	0.80	0.05	0.08	0.42	0.16	0.00	0.37	0.05	
Income	0.08	0.04	0.15	0.31	-0.10	0.04	0.46	0.05	0.37	0.38	-0.02	0.24	0.18	-0.02	
Investment	-0.13	0.02	-0.07	0.13	-0.99	-0.10	0.82	-0.12	0.40	1.21	0.05	0.18	-0.01	-0.02	
Exports 	3.56	2.43	5.28	1.99	4.64	0.10	13.49	4.09	3.59	8.39	2.00	-0.23	4.98	2.23	
Imports	3.27	2.47	5.09	2.61	4.04	0.08	13.26	4.66	4.50	7.87	2.09	-0.09	4.84	1.85	
GDP deflator	-0.51	-0.47	-0.63	-0.66	-1.47	0.02	1.00	-0.13	1.04	1.16	-0.10	0.37	-0.60	-0.20	
Terms of trade	-0.19	-0.17	0.60	0.36	-0.64	0.05	-1.03	-0.04	0.66	-0.37	-0.19	0.12	-0.46	-0.28	
Prices received	-0.23	-0.29	-0.50	-0.40	-0.99	0.01	-1.01	-0.05	0.63	-0.30	-0.06	0.22	-0.43	-0.34	
Prices paid	-0.04	-0.11	-1.09	-0.75	-0.35	-0.04	0.02	-0.01	-0.03	0.07	0.13	0.10	0.03	-0.05	
Sectoral output														
Crops	0.67	1.15	0.32	0.96	0.44	-0.02	-0.46	0.10	-0.21	-0.80	-0.03	-0.19	0.04	-0.06	
Livestock	0.52	-0.11	0.47	0.59	0.33	0.13	0.61	0.34	-0.27	0.64	0.06	0.24	0.03	0.01	
Forestry & mining	0.72	0.91	0.74	0.81	1.53	-0.04	-2.95	0.21	-1.72	-2.89	-0.41	-0.67	-0.11	0.05	
Food processing	0.77	1.71	0.36	0.71	0.27	0.02	-1.77	0.08	-0.42	-1.33	-0.23	0.86	-0.20	0.12	
Textile	-20.34	-18.73	-24.00	-39.17	-30.44	1.11	22.79	17.61	55.47	31.33	25.91	22.05	6.80	-6.63	
Clothing	-49.39	-56.38	-58.67	-80.62	-62.74	-8.92	85.69	-10.84	-3.64	56.91	15.83	-4.19	-0.84	5.36	
Leather	-22.44	-4.65	-20.50	-54.68	-34.29	-4.37	9.49	-42.66	31.37	138.26	770.13	52.13	-2.54	-3.09	
Paper products	0.14	0.71	0.37	0.60	0.48	-0.07	-2.97	0.00	-0.48	-3.96	-0.29	-0.45	0.05	0.07	
Chemicals etc	0.67	0.54	0.03	0.53	-1.35	-0.16	-2.61	0.31	1.87	-1.33	-0.55	1.38	0.34	0.00	
Other manufacture	2.27	1.94	2.23	3.13	5.06	0.07	-4.81	0.25	-2.81	-5.95	-0.69	-0.62	-0.01	0.43	
Ferrous metals	1.61	1.36	1.67	2.53	5.22	0.07	-6.70	0.45	-3.84	-5.00	-0.05	-0.18	0.07	0.28	
Motor vehicles	1.19	1.13	1.85	2.48	9.48	-0.56	-8.08	-1.06	-6.50	-10.67	-1.04	-1.01	-0.39	0.13	
Transport nec	1.20	-0.05	3.57	3.89	3.40	-0.81	-10.77	-0.23	-12.55	-8.10	-3.98	-2.05	-3.15	-0.07	
Electrical	1.79	2.01	3.26	4.23	10.20	0.49	-10.37	0.47	-5.39	-6.21	-1.13	-1.14	-0.55	0.45	
Other equipment	1.45	1.38	1.94	2.21	9.48	-0.07	-7.41	0.55	-4.97	-5.20	-1.90	-1.22	-0.80	0.06	
Utilities & construct	-0.02	0.09	-0.01	0.25	-1.05	-0.06	0.36	-0.07	0.60	1.04	0.20	0.19	0.07	-0.03	
Trade & transport	0.25	0.46	0.30	0.46	0.42	0.35	-1.70	0.07	0.00	-0.94	0.07	0.86	0.12	0.30	
Services	0.05	0.07	0.06	0.34	0.61	0.00	-1.00	-0.01	-0.40	-2.59	-0.79	-0.83	-0.27	-0.06	
Source: GTAP simulation

	Global TCF liberalisation
Tables 4.9 and 4.10 presents the effects of global TCF trade liberalisation. The world welfare gain increase by about 40 per cent compared to the APEC liberalisation simulation. All regions except Mexico gain under this simulation. But Mexico’s welfare loss decreases due to the EU joining the liberalisation process.
The US and greater China are still the largest winners with EV rising by 5 per cent and 60 per cent, respectively, from the APEC liberalisation. Australia also achieves a 12 per cent further increase in welfare.
4.9	Welfare effects of global TCF liberalisation Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	295	390	-101	7	
NZ	24	53	-28	-1	
US	11190	4337	6694	159	
Canada	1683	971	711	1	
Mexico	-303	373	-750	74	
EU	4983	3461	1566	-43	
Chinas	8527	12781	-3908	-345	
Japan	1980	2106	203	-330	
Korea	1765	350	1463	-48	
OthASAPEC	2393	2042	-70	421	
Malaysia	19	229	-135	-75	
Singapore	163	-6	140	29	
Thailand	500	684	-164	-20	
ROW	897	6258	-5533	172	
Total APEC	28237	24312	4054	-129	
World	34117	34030	87	0	
Source: GTAP simulation

The only loser of the global TCF liberalisation is Mexico, which suffers a terms of trade loss of US$750 million which more than offsets the allocative efficiency gain. This is due to two effects. First, its TCF exports in this simulation have much lower prices than those in any other unilateral or bilateral liberalisation simulations simply because of a broader extent of liberalisation which is compounded by the strong competition from Chinese and other Asian countries’ TCF exports. This may partly explain why Mexico was one of the last few countries who finalised the WTO accession agreement with China. Second, because every country liberalises TCF protection, some resources are shifted from TCF production to other products, leading to higher export supply and lower price of other products, which hurts Mexico further.

4.10	Global TCF liberalisation: macroeconomic and sectoral results by region Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	0.10	0.08	0.05	0.15	0.10	0.04	0.99	0.05	0.08	0.66	0.22	-0.01	0.43	0.13	
Income	0.08	0.04	0.16	0.30	-0.09	0.07	0.73	0.05	0.45	0.86	0.02	0.24	0.36	0.02	
Investment	-0.14	0.00	-0.10	0.06	-1.03	-0.19	1.14	-0.15	0.51	2.20	0.08	0.23	0.36	-0.05	
Exports 	3.72	2.36	6.03	1.99	4.77	1.25	17.05	4.23	4.21	12.32	2.73	-0.30	5.85	6.49	
Imports	3.48	2.39	5.73	2.54	4.16	1.28	17.16	4.73	5.40	12.26	2.89	-0.14	6.14	5.68	
GDP deflator	-0.45	-0.48	-0.52	-0.65	-1.46	-0.50	1.97	-0.07	1.38	2.47	0.07	0.46	-0.15	-0.63	
Terms of trade	-0.13	-0.17	0.63	0.32	-0.65	0.07	-0.83	-0.04	0.88	0.02	-0.19	0.12	-0.23	-0.46	
Prices received	-0.16	-0.29	-0.43	-0.38	-0.97	-0.41	-0.72	0.01	0.86	0.14	0.01	0.32	-0.17	-0.73	
Prices paid	-0.03	-0.12	-1.05	-0.70	-0.33	-0.48	0.11	0.05	-0.02	0.12	0.21	0.19	0.06	-0.27	
Sectoral output														
Crops	0.85	1.47	0.37	1.10	0.46	0.25	-0.67	0.17	-0.23	-1.42	-0.08	-0.28	-0.12	0.09	
Livestock	0.78	-0.11	0.57	0.83	0.35	0.45	1.44	0.53	-0.32	1.16	-0.10	0.40	-0.39	-0.06	
Forestry & mining	0.72	1.07	0.53	0.78	1.47	0.65	-4.54	0.17	-2.22	-5.22	-0.77	-0.92	-1.03	0.31	
Food processing	0.84	1.88	0.30	0.76	0.28	0.29	-2.35	0.14	-0.56	-2.32	-0.82	1.42	-1.18	0.15	
Textile	-19.56	-22.91	-20.88	-38.04	-30.15	-17.74	32.96	24.41	66.69	54.74	47.69	31.57	23.26	-3.33	
Clothing	-43.02	-56.50	-39.97	-79.32	-62.91	-46.93	121.79	-8.75	0.06	96.89	50.71	-0.53	17.79	-5.80	
Leather	-22.16	-17.57	-7.47	-51.95	-31.78	-22.12	29.03	-41.11	43.97	241.59	1091.38	90.24	28.63	-21.15	
Paper products	0.13	0.90	0.26	0.63	0.45	0.10	-4.53	0.06	-0.46	-6.98	-0.71	-0.47	-0.39	0.11	
Chemicals etc	0.65	0.60	-0.09	0.58	-1.41	0.09	-4.12	0.40	2.31	-2.52	-1.02	2.76	-0.15	0.09	
Other manufacture	2.33	2.35	1.77	3.39	5.11	1.27	-7.58	0.24	-3.49	-10.76	-1.37	-0.83	-2.41	1.02	
Ferrous metals	1.59	1.54	1.24	2.54	5.10	1.34	-10.09	0.39	-4.84	-8.95	-0.77	-0.35	-2.37	0.73	
Motor vehicles	0.63	1.06	1.07	2.00	9.09	1.09	-12.30	-2.14	-8.79	-18.08	-2.58	-1.60	-1.40	0.37	
Transport nec	0.95	0.29	2.74	3.56	3.38	3.44	-15.30	-0.90	-15.85	-13.40	-6.15	-2.35	-9.62	1.61	
Electrical	1.88	2.54	2.95	4.86	11.27	2.74	-15.10	0.50	-6.63	-10.69	-1.88	-1.84	-4.32	1.37	
Other equipment	1.11	1.31	1.38	2.21	9.46	1.71	-11.07	0.38	-6.33	-8.80	-3.54	-1.72	-4.12	0.56	
Utilities & construct	-0.02	0.08	-0.04	0.20	-1.07	-0.07	0.46	-0.12	0.73	1.88	0.35	0.23	0.35	0.00	
Trade & transport	0.24	0.50	0.26	0.50	0.40	0.71	-2.50	0.09	0.20	-1.58	-0.11	1.20	-0.36	0.58	
Services	0.00	0.05	0.02	0.28	0.56	0.05	-1.38	-0.03	-0.55	-4.39	-1.49	-1.39	-1.17	-0.01	
Source: GTAP simulation

5	Sensitivity analysis

	Changes in parameter groups
There are three key parameter groups in the GTAP model:
•	trade parameters which include the elasticity of substitution between domestic and imported goods in aggregate, and the elasticity of substitution between imported goods from different sources;
•	supply parameters including the elasticity of substitution between primary factors, the elasticity of substitution between intermediate inputs (in composite) and value added and the elasticity of transformation between endowment commodities; and
•	demand parameters which include the substitution and income parameters.
We undertake sensitivity analysis for each of these parameter groups using the sensitivity facilities built into the GEMPACK implementation of GTAP. This essentially involves simulating a variation in the parameters according to some distribution, and then observing the mean and standard deviation of the corresponding results. A 50 per cent variation in a set of parameters will result in a particular standard deviation for the model results. This standard deviation provides information about the sensitivity of the model results to the parameter group.
For the sensitivity analysis here we conduct our variations around simulations of the global liberalisation and Australia’s unilateral actions (unilateral removal or 50 per cent reduction in Australia’s TCF tariffs). We have assumed a 50 per cent variation in each of the parameter groups and this variation is assumed to have a triangular distribution.
Results are presented in tables 5.1 to 5.3. To summarise what would otherwise be a large number of results, we have reported the sensitivity to changes in EV, and the allocative and terms of trade components of EV only. Further, we have converted the standard deviation to a 95 per cent confidence interval and expressed this confidence interval as a single percentage of the mean value. Thus, for example, a value of 50 per cent implies that the 95 per cent confidence interval involves a 50 per cent variation above or below the mean. A value of greater than 100 per cent implies that the confidence interval includes a change in sign of the base value. 
Several points are evident from these results.
•	EV results are extremely sensitive to the choice of trade parameters, as are its allocative efficiency and terms of trade components.
•	All country results are very sensitive to the trade parameters, but Mexico and New Zealand are the most sensitive in the global liberalisation simulation.  The overall EV results vary by 154 per cent and 130 per cent, respectively, as a result of the 50 per cent variation in the trade parameters. This means that its welfare gain is not unlikely to be negative. It may look erroneous as the allocative and terms of trade components vary by less than 100 per cent. But it is correct because the mean of allocative efficiency gains and terms of trade losses are of large and similar magnitude and have opposite sign and thus the total EV effects are small in mean and high in variance.
5.1	Sensitivity analysis of global liberalisation: confidence interval expressed as a percentagea
Region	Trade parameters	Supply parameters	Demand parameters	
	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	
Australia	66	40	38	0	0	2	4	0	9	
NZ	130	44	31	8	1	5	7	0	6	
US	47	38	49	0	0	0	0	2	1	
Canada	38	33	49	0	0	1	0	1	1	
Mexico	154	94	15	6	5	1	1	1	0	
EU	74	51	131	0	1	1	0	1	2	
Chinas	17	46	110	1	0	0	4	2	2	
Japan	89	52	415	0	0	3	3	2	9	
Korea	10	41	3	2	7	0	4	8	3	
Other Asian APEC	25	48	626	0	2	23	2	2	3	
Malaysia	30	55	84	37	1	4	29	2	2	
Singapore	17	49	18	1	10	1	1	7	2	
Thailand	27	54	153	1	0	2	3	2	1	
ROW	75	36	27	3	0	0	13	2	0	
a Analysis is for simulation of global liberalisation of TCF trade. Results refer to the effect of a 50 per cent variation in the underlying parameter group. Parameters within the group are assumed to move together according to a triangular distribution.
Source: GTAP model simulations

5.2	Sensitivity analysis of unilateral removal of TCF tariffs in Australia: confidence interval expressed as a percentagea
Region	Trade parameters	Supply parameters	Demand parameters	
	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	
Australia	140	39	11	2	0	1	7	0	3	
NZ	0	34	45	1	1	2	0	1	2	
US	8	22	18	6	4	5	4	6	3	
Canada	195	10	93	57	6	33	5	12	11	
Mexico	8	26	21	0	14	5	1	4	3	
EU	3	11	15	6	7	6	0	2	2	
Chinas	2	28	13	1	2	0	3	4	3	
Japan	4	13	29	9	4	15	5	6	2	
Korea	41	38	22	3	2	3	5	3	3	
Other Asian APEC	5	32	8	2	3	3	3	5	3	
Malaysia	31	62	1	9	3	6	6	5	2	
Singapore	13	81	10	3	5	3	1	1	1	
Thailand	177	51	18	5	1	1	19	2	4	
ROW	8	26	7	4	3	5	4	4	3	
a Analysis is for simulation of unilateral removal of TCF tariffs in Australia. Results refer to the effect of a 50 per cent variation in the underlying parameter group. Parameters within the group are assumed to move together according to a triangular distribution.
Source: GTAP model simulations

5.3	Sensitivity analysis of unilateral 50% reduction in Australia’s TCF tariffs: confidence interval expressed as a percentagea
Region	Trade parameters	Supply parameters	Demand parameters	
	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	EV	Allocative component	Terms of trade component	
Australia	73	40	6	1	0	1	1	0	2	
NZ	1	29	23	1	1	1	0	1	1	
US	1	27	9	8	5	7	2	6	1	
Canada	59	11	845	22	20	690	13	22	227	
Mexico	4	29	8	0	12	5	0	4	1	
EU	11	28	8	5	4	5	1	2	1	
Chinas	5	34	7	1	2	0	2	3	2	
Japan	9	26	18	7	3	13	3	4	0	
Korea	30	46	14	3	2	3	4	6	2	
Other Asian APEC	9	35	3	2	3	4	2	4	2	
Malaysia	22	56	3	10	4	6	5	5	2	
Singapore	7	11	6	3	3	2	0	2	0	
Thailand	123	48	11	6	1	1	14	3	3	
ROW	14	31	2	4	3	5	2	3	2	
a Analysis is for simulation of global liberalisation of TCF trade. Results refer to the effect of a 50 per cent variation in the underlying parameter group. Parameters within the group are assumed to move together according to a triangular distribution.
Source: GTAP model simulations

•	For Australia, the overall EV results vary by 66 per cent as a result of the 50 per cent variation in the trade parameters in simulations of global liberalisation. The results are more sensitive to trade parameter values when Australia acts unilaterally, especially in the case of unilateral removal where the total welfare gain could be turned into net loss. Australia’s terms of trade losses are higher when it acts unilaterally than in the case of global liberalisation, resulting to higher variation in the total welfare results. This may justify a conservative reform policy when we are not clear about the parameter values.
•	The supply and demand parameters generally have a very small effect on the EV results. 
	Removal of TCF protection when the US protection level is higher
As discussed in chapter 1, considering non-tariff barriers leads to much higher tax-equivalent rates on the clothing imports in the US. In this section we present simulations of TCF protection removal when the US clothing protection rates are 46 per cent for imports from Asian countries except Japan, ceteris paribus.
5.4	Welfare effects of removing Australia’s TCF tariffs: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	130	383	-249	-3	
NZ	-27	-16	-12	1	
US	-24	-6	-19	2	
Canada	0	0	0	0	
Mexico	2	1	2	0	
EU	41	20	23	-2	
Chinas	184	46	141	-4	
Japan	46	28	18	-1	
Korea	15	-4	19	0	
OthASAPEC	31	9	20	2	
Malaysia	3	-1	4	0	
Singapore	3	0	3	0	
Thailand	2	-3	5	0	
ROW	89	39	45	4	
Total APEC	364	436	-69	-3	
World	494	495	-1	0	
Source: GTAP simulation
The simulations proceed as follows. First, using ALTERTAX facility, the export tax rate of clothing from Asian countries except Japan to US are changed so that the combined tariff rate and tax rate equal to 46 per cent, and consequently, the database is adjusted. Then, various TCF liberalisation schemes are simulated against the new database. Results are reported in tables 5.4 to 5.9.
5.5	Welfare effects of removing US TCF tariffs: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	21	-28	31	18	
NZ	6	-7	15	-2	
US	22854	5805	16937	112	
Canada	1260	607	657	-4	
Mexico	-643	-371	-321	49	
EU	3758	1754	2144	-140	
Chinas	5964	19321	-13118	-240	
Japan	-38	159	73	-270	
Korea	-62	-193	125	6	
OthASAPEC	-478	330	-944	135	
Malaysia	-138	12	-108	-42	
Singapore	-48	-28	-48	27	
Thailand	-180	269	-440	-9	
ROW	-3910	457	-4731	364	
Total APEC	28517	25876	2860	-220	
World	28364	28087	273	4	
Source: GTAP simulation
5.6	Welfare effects of removing the EU TCF tariffs: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	24	-13	40	-3	
NZ	2	-2	6	-2	
US	-735	-229	-626	121	
Canada	31	-4	65	-29	
Mexico	43	16	49	-22	
EU	704	2190	-1591	104	
Chinas	2662	2506	303	-148	
Japan	-321	-13	-112	-196	
Korea	105	-38	164	-21	
OthASAPEC	1269	723	416	130	
Malaysia	76	61	45	-30	
Singapore	-23	-6	-21	5	
Thailand	183	84	113	-14	
ROW	2509	1259	1144	105	
Total APEC	3316	3084	441	-210	
World	6528	6533	-5	0	
Source: GTAP simulation

5.7	Welfare effects of removing China TCF tariffs: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	92	54	35	3	
NZ	13	10	3	0	
US	924	384	445	94	
Canada	98	65	36	-3	
Mexico	-51	-5	-49	3	
EU	485	243	230	12	
Chinas	2674	4721	-2042	-6	
Japan	1860	824	1152	-117	
Korea	713	133	590	-10	
OthASAPEC	-174	-81	-96	3	
Malaysia	-49	-23	-23	-2	
Singapore	31	-2	29	4	
Thailand	-80	-43	-37	1	
ROW	-617	-358	-276	17	
Total APEC	6052	6038	43	-29	
World	5920	5922	-3	0	
Source: GTAP simulation
5.8	Welfare effects of TCF liberalisation in APEC region: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	263	395	-146	14	
NZ	21	53	-31	-1	
US	28414	6461	21519	434	
Canada	1632	949	692	-10	
Mexico	-336	321	-722	64	
EU	3869	1895	2270	-296	
Chinas	6376	21390	-14727	-287	
Japan	2343	2086	576	-319	
Korea	1460	285	1205	-30	
OthASAPEC	628	1488	-1150	290	
Malaysia	-141	157	-237	-61	
Singapore	150	-16	131	35	
Thailand	85	622	-528	-9	
ROW	-2951	5429	-8560	180	
Total APEC	40894	34192	6582	120	
World	41813	41517	292	4	
Source: GTAP simulation
5.9	Welfare effects of global TCF liberalisation: higher US clothing protection Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	
	US$ million	US$ million	US$ million	US$ million	
Australia	294	391	-106	9	
NZ	24	53	-26	-3	
US	28023	6403	21189	431	
Canada	1654	957	725	-28	
Mexico	-313	334	-698	51	
EU	309	2333	-1806	-218	
Chinas	8051	22347	-13925	-371	
Japan	2044	2084	414	-454	
Korea	1599	300	1350	-51	
OthASAPEC	2135	2228	-495	401	
Malaysia	-42	222	-185	-80	
Singapore	167	-13	146	35	
Thailand	271	698	-408	-18	
ROW	1790	7353	-5861	298	
Total APEC	43907	36003	7981	-77	
World	46005	45688	314	3	
Source: GTAP simulation
Several points are evident from these results.
•	As the US protection is now higher in the baseline, any policies involving the US liberalisation of TCF trade result in higher global welfare gains. For example, the US unilateral removal of TCF tariffs leads to a global welfare improvement of US$28 364 million, while the welfare gain was US$10 444 million when the lower US clothing protection presented in chapter 3. 
•	Similarly, APEC and global liberalisation of TCF trade result in welfare gains of US$41 813 million and US$46 005 million, respectively, compared with the previous gains of US$24 443 million and US$34 117 million, respectively. 
•	However, these increased welfare gains are not evenly allocated to country regions. It seems that some gains are transferred from Asian countries to the US. This is understandable because the quota rents which was accumulated to exporting countries now disappear after removing import quotas.
•	Despite the magnitudes of welfare changes, the qualitative results derived from the simulations presented in the previous three chapters still hold.
	Alternate closure
In tables 5.10 and 5.11 we present the results of global liberalisation of TCF trade using an alternate model closure. This closure (initially suggested by Francois et al 1996) assumes a fixed savings rate in each region, but allows the capital stock to vary according to investment allocated to each region.
As table 5.10 indicates, there is now an additional component to the change in EV: the endowment effect, which is the contribution to increased income of the additional capital put in place in each region. The endowment effect may either add or subtract from the overall welfare results.
Australia will experience capital outflows under this closure, leading to significant endowment losses which almost offset all the allocative efficiency gains. Together with terms of trade losses, Australia has net welfare losses in this situation. 
China is the largest winner with additional endowment effect of US$5 826 million. 
5.10	Welfare effects of global TCF liberalisation: alternate closure Changes in equivalent variation and components
	Total	Allocative efficiency	Terms of trade	Price of capital	Endowment effect	
	US$ million	US$ million	US$ million	US$ million	US$ million	
Australia	-199	330	-65	8	-472	
NZ	-19	47	-25	-1	-40	
US	4451	4357	6809	182	-6897	
Canada	1445	929	708	2	-196	
Mexico	-4083	-245	-600	65	-3304	
EU	-4047	2295	1934	-44	-8232	
Chinas	15124	13975	-4338	-338	5826	
Japan	-1012	1453	330	-320	-2475	
Korea	2554	458	1390	-45	752	
OthASAPEC	6829	2339	-352	369	4473	
Malaysia	-8	220	-125	-74	-29	
Singapore	230	1	143	29	58	
Thailand	1454	794	-225	-17	902	
ROW	-3283	5703	-5489	186	-3683	
Total APEC	26767	24658	3651	-140	-1402	
World	19437	32657	95	1	-13317	
Source: GTAP simulation

5.11	Global TCF liberalisation: macroeconomic and sectoral results by region: alternative closure Per cent change from baseline
	Australia	NZ	US	Canada	Mexico	EU	Chinas	Japan	Korea	Other ASAPEC	Malaysia	Singapore	Thailand	ROW	
Macroeconomic results														
GDP	-0.10	0.00	-0.10	0.10	-1.10	-0.10	1.70	-0.10	0.30	2.60	0.20	0.10	1.20	0.00	
Income	-0.10	0.00	0.10	0.30	-1.20	-0.10	1.30	0.00	0.60	2.40	0.00	0.30	1.10	-0.10	
Investment	-0.40	-0.20	-0.30	-0.10	-1.90	-0.40	1.80	-0.30	0.60	4.00	-0.10	0.20	1.00	-0.30	
Exports 	3.60	2.30	5.90	2.00	3.10	1.10	18.00	4.10	4.70	15.20	2.70	-0.20	6.70	6.40	
Imports	3.40	2.30	5.60	2.50	3.10	1.20	17.70	4.70	5.60	14.20	2.80	0.00	6.80	5.50	
GDP deflator	-0.40	-0.50	-0.50	-0.70	-1.30	-0.50	1.90	-0.10	1.30	2.10	0.10	0.40	-0.20	-0.60	
Terms of trade	-0.08	-0.15	0.64	0.32	-0.52	0.08	-0.92	-0.01	0.83	-0.23	-0.18	0.13	-0.32	-0.46	
Prices received	-0.13	-0.28	-0.43	-0.39	-0.86	-0.41	-0.83	0.01	0.80	-0.13	0.00	0.29	-0.27	-0.74	
Prices paid	-0.05	-0.13	-1.07	-0.71	-0.34	-0.49	0.08	0.03	-0.03	0.10	0.18	0.17	0.04	-0.28	
Sectoral output														
Capital goods	-0.40	-0.22	-0.31	-0.13	-1.88	-0.37	1.81	-0.29	0.64	4.00	-0.07	0.25	0.99	-0.26	
Crops	1.05	1.61	0.39	1.20	0.51	0.23	-0.47	0.18	-0.19	-1.39	-0.05	-0.24	-0.11	0.09	
Livestock	0.80	-0.05	0.51	0.84	-0.11	0.39	1.77	0.51	-0.22	2.05	-0.09	0.43	-0.31	-0.11	
Forestry & mining	0.58	0.97	0.41	0.73	0.67	0.50	-4.04	0.06	-1.98	-3.82	-0.76	-0.84	-0.45	0.24	
Food processing	0.72	1.90	0.23	0.77	-0.37	0.20	-2.04	0.09	-0.45	-1.43	-0.86	1.67	-1.01	0.12	
Textile	-19.91	-23.18	-21.04	-38.13	-31.15	-18.01	33.92	24.29	67.33	59.75	47.50	31.23	24.09	-3.67	
Clothing	-43.38	-56.71	-40.16	-79.41	-63.77	-47.25	122.82	-9.04	0.11	105.37	49.79	-0.67	18.61	-6.50	
Leather	-22.56	-18.11	-7.81	-52.19	-33.21	-22.74	28.58	-41.28	44.10	254.01	1090.75	89.94	29.72	-21.55	
Paper products	-0.07	0.83	0.14	0.61	-1.11	-0.06	-3.73	-0.05	-0.15	-4.22	-0.76	-0.35	0.48	0.00	
Chemicals etc	0.48	0.51	-0.21	0.56	-2.74	-0.07	-3.27	0.29	2.75	-0.24	-1.09	3.22	0.68	-0.03	
Other manufactues	1.95	2.10	1.63	3.31	3.10	1.05	-6.64	0.09	-3.14	-7.58	-1.44	-0.70	-1.43	0.86	
Ferrous metals	1.32	1.34	1.11	2.49	3.38	1.16	-9.15	0.25	-4.42	-5.89	-0.83	-0.19	-1.18	0.59	
Motor vehicles	0.19	0.91	1.02	2.12	6.45	0.94	-11.01	-2.31	-8.44	-14.25	-2.62	-1.51	-0.40	0.26	
Transport nec	0.65	0.04	2.64	3.40	1.58	3.32	-14.23	-1.13	-15.59	-10.61	-6.25	-2.26	-8.08	1.41	
Electrical	1.42	2.26	2.72	4.61	9.74	2.49	-13.99	0.28	-6.35	-8.81	-1.95	-1.75	-2.98	1.17	
Other equipment	0.82	1.04	1.22	2.17	7.32	1.57	-10.03	0.24	-5.88	-6.79	-3.54	-1.56	-2.81	0.37	
Utilities & construct	-0.27	-0.07	-0.19	0.07	-1.99	-0.24	1.15	-0.25	0.90	3.79	0.23	0.26	1.03	-0.17	
Trade & transport	0.05	0.39	0.16	0.47	-1.03	0.54	-1.71	0.00	0.49	0.72	-0.17	1.29	0.40	0.46	
Services	-0.17	-0.04	-0.09	0.22	-0.64	-0.12	-0.63	-0.15	-0.30	-1.96	-1.49	-1.28	-0.51	-0.11	
Source: GTAP simulation

A	Appendix: technical simulation details

	Model aggregation
Tables A.1 and A.2 summarise the sectoral and regional aggregation used in this report.
A.1	Sectoral aggregation

A.2	Regional aggregation
	
	Solution method
For all simulations we used GEMPACK’s automatic accuracy facility. The base set up is a 2, 4, 6 step Gragg with 2 subintervals. Automatic accuracy was set to achieve 80 percent of results with accuracy of 4 figures (using both data and solution as criteria). The minimum subinterval size was set at 10^n-3.

References
Centre for International Economics, 2002, Extending the MFA Model, Canberra.
Centre for International Economics, 2002a, Modelling International Developments: Effects of PMV and Other Tariff Changes, Canberra.
Centre for International Economics and the Trade Partnership, 2000, Barriers to Wool Fibre Products Trade, Canberra and Washington, D.C.
Francois, J., McDonald, B. and Nordstrom, H. 1996, Liberalisation and Capital Accumulation in the GTAP Model, GTAP Technical Paper No. 7, Global Trade Analysis Project, Purdue.
Hertel, Thomas (editor) 1997 Global Trade Analysis: Modelling and Applications, Cambridge University Press, New York and Melbourne.