ABARE CONFERENCE PAPER 04.6 Agricultural trade liberalisation

ABARE CONFERENCE PAPER 04.6

Agricultural trade liberalisationEffects on developing countries’

output, incomes and trade

Benjamin Buetre, Roneel Nair, Nhu Che and Troy Podbury*Australian Bureau of Agricultural and Resource Economics

7th Annual Conference on Global Economic Analysis, Trade, Poverty and the Environment,

Washington DC, 17–19 June

ABARE project 110039ISSN 1447-3666

D u ring the past decade there has been a substantial increase in trade in agri -cultural products between developing countries. Between 1990 and 1998 thevalue of agri c u l t u ral trade between developing countries grew at about 7 percent a ye a r. With this increasing importance of ‘south–south’ tra d e, the barri -e rs to such trade have become incre a s i n g ly important to the growth pro s p e c t sfor developing countries.

H oweve r, the opportunity to reduce these barri e rs may not be realised because,under the Wo rld Trade Orga n i s ation, trade is liberalised by nego t i ating thel owe ring of b o u n d t a ri ffs, wh i ch in most cases are mu ch higher than theap p l i e d t a ri ffs in developing countries. Thus the extent of libera l i s ation dep e n d son the rate by wh i ch the bound tari ffs are cut and whether such re d u c t i o n slower the applied tariffs.

In this paper, scenarios that reflect some possible outcomes in WTO negotia -tions are ex p l o red and their implications for developing countries’ output,incomes and trade are assessed. A more realistic ap p ro a ch in modeling thes c e n a rios is to take account of the binding overhang or ‘water in the tari ff ’ .The findings show that developing countries have mu ch to gain from furt h e rt rade libera l i s ation. Howeve r, nego t i ations for further agri c u l t u ral re fo rm sneed to be more ambitious if the maximum benefits are to be re a l i s e d. Moreimportantly, wider participation in the reform process and broad commoditycoverage is required to ensure that the benefits are maximised.

GPO Box 1563 • Canberra • 2601 • Australia • Fax +61 2 6 2 7 2 2001 • Tel +61 2 6 2 7 2 2000 • www. a b a r e c o n o m i c s . c o m

* The authors thank Vivek Tulpulé and Neil Andrews for their helpful comments and sugge s t i o n sand QT Tran for calibrating the demand function. Any erro rs remain the responsibility of the authors .


IntroductionA gri c u l t u re is the largest employer and a major sector in most developing countri e s .H oweve r, agri c u l t u ral incomes also tend to be lower than urban incomes in deve l o p i n gc o u n t ries, and pove rty rates are higher in ru ral areas. An implication is that incre a s e dincomes for participants in agri c u l t u re could help allev i ate pove rt y. One route to incre a s e dincomes is trade liberalisation.

A key to reducing pove rty globally is to raise the incomes of the wo rl d ’s poorest people.One way this can be ach i eved is to raise ave rage incomes in developing countri e s ,although such an increase will not guarantee a reduction in pove rt y. Th e re are manyfa c t o rs that can improve incomes in developing countries, including education, healths t a n d a rds, infra s t ru c t u re, institutional arra n gements for good gove rn a n c e, commerc eand provision of public goods and the ability of each country to exploit their compara-t ive adva n t age.

Trade barri e rs, part i c u l a rly in agri c u l t u re, are major impediments to developing countri e sbeing able to exploit their comparat ive adva n t age and increase ru ral incomes. Trade barri-e rs for agri c u l t u ral products tend to be gre ater than barri e rs for other goods. In addition, thedomestic support and ex p o rt subsidy policies of developed countries tend to further dep re s sp rices for agri c u l t u ral commodities. This not only disadva n t ages developing countries thatex p o rt agri c u l t u ral products but tends to dep ress re t u rns to fa rm e rs in all developing coun-tries.

Trade liberalisation, particularly agricultural trade liberalisation, can be expected to havea substantial impact on incomes in most developing countries. Howeve r, the actual impacton each country will differ depending on their comparat ive adva n t age, their infra s t ru c t u reand institutional arra n gements, existing trade re l ationships (including current pre fe re n t i a laccess) and differences in existing protection.

F u rther trade libera l i s ation can be pursued through a number of channels, including unilat-e ral re fo rm, bilat e ral agreements, pre fe rential access and through mu l t i l at e ral arra n ge-ments (such as in the WTO). Libera l i s ation through each of these channels can be ex p e c t e dto have very different effects.

In this pap e r, the scope to increase incomes in developing countries through trade libera l i-s ation and especially agri c u l t u ral libera l i s ation is ex p l o re d. The focus is on the impacts oft a ri ff reductions. The potential gains from reducing other fo rms of support could be large bu tthese are not assessed in this study. The impacts of a number of trade libera l i s ation scenar-ios that are like ly to rep resent an outcome under the WTO agri c u l t u ral trade nego t i at i o n sa re analysed using ABA R E ’s global trade and env i ronment model (GTEM) and an ABA R E -revised Ve rsion 5 GTAP dat ab a s e. A major innovation in this paper is an analysis of re fo rm s

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f rom bound rather than applied tari ffs. Bound tari ffs are the tari ffs that are actually nego-t i ated on in WTO processes. To make this analysis possibl e, a dat abase of the most re c e n ti n fo rm ation on applied and bound tari ffs has been constructed using the WTO dat ab a s e( W TO 2003). The study highlights the importance of successful and more ambitious tra d el i b e ra l i s ation nego t i ations. The study also highlights the importance of growth in tra d eamong developing countries — or ‘south–south’ trade — in the context of mu l t i l at e ral tra d el i b e ra l i s ation and the income growth potential of developing countri e s .

The paper is organised as fo l l ows. In the next section the importance of agri c u l t u re andagri c u l t u ral trade between developing countries, including the levels of protection in thesec o u n t ries, is ex a m i n e d. In the fo l l owing section is a discussion of the tari ff data that we reused in the analysis. This is fo l l owed by an outline of the modeling ap p ro a ch, incl u d i n gch a n ges in key model para m e t e rs, and trade libera l i s ation scenarios and a discussion ofthe results. The limitations of the present analysis are then discussed and some concl u d i n gremarks presented.

Agricultural trade among developing countriesWith a comparat ive abundance of inex p e n s ive labor in many developing countries and there l at ive ly lower tech n o l ogical re q u i rement for agri c u l t u re, many developing countries havea nat u ral comparat ive adva n t age in agri c u l t u re. Agri c u l t u re in many developing countri e sis also a significant source of ex p o rt earnings. In 1999, agri c u l t u ral ex p o rts from deve l-oping countries we re wo rth more than US$125 billion, contri buting more than 40 per centof total world agricultural trade (WTO 2001).

The role of agri c u l t u re in developing countries is even more important for a major part ofthe population. Agriculture employs a greater proportion of the population in developingc o u n t ries than in developed countries (Wo rld Bank 2003). In addition, the prevalence ofp ove rty is more pronounced in ru ral areas than in urban areas of developing countri e s(appendix A).

The major trends in agri c u l t u ral trade among developing countries are highlighted and themain policy barri e rs inhibiting developing countries from exploiting their comparat iveadvantage are identified in this section.

O v e rview of agricultural trade among developing countriesTh e re has been a steady decline in agri c u l t u re ’s share in wo rld merchandise trade over time— in 1998 agri c u l t u re accounted for 10 per cent of total merchandise trade compared with 15per cent at the beginning of the 1980s. Agri c u l t u ral trade among developing countries accountsfor a minor fraction of total wo rld trade (around 1 per cent) but contri butes more than 15 percent of total agri c u l t u ral trade in the wo rl d. In addition, ‘south–south’ trade has been the

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main area of growth in agri c u l t u ral trade — the value of‘south–south’ trade in agri c u l t u ral products expanded fro mUS$25 billion in 1990 to US$48 billion in 1999 (WTO2001). This highlights the importance of south–south tra d eto countries with a significant interest in agri c u l t u re.

The importance of south–south trade for agri c u l t u reva ries considerably across developing regions. For deve l-oping countries in Asia, ex p o rts of agri c u l t u ral pro d u c t sto developing countries are an important source of ex p o rtincomes, while for Latin America most agri c u l t u ra lexports are destined for developed markets.

Trade protection policies in developing countriesDespite the fa i l u re to re a ch agreement at the WTO Ministerial meeting in Cancun, Mex i c o ,the current WTO nego t i ations on agri c u l t u re offer an opportunity to ach i eve effe c t ive tra d el i b e ra l i s ation. As a part of wider trade nego t i ations under the Doha development ro u n d,these agri c u l t u ral nego t i ations have the potential to raise economic growth and possiblya l l ev i ate pove rt y, wh i ch is a major issue for developing countries. Th e re are many barri e rsto ach i eving effe c t ive re fo rm, but some developing countries are actually contri buting to thep ro blem. It has been observed that ‘many trade distorting protection policies are also beingp u rsued by developing countries, slowing both their own development and that of theirt rading part n e rs, including other developing countries’ (Roberts, Buetre and Jo t zo 2002).

From a developing country’s viewpoint there are a number of major concerns that couldd i s c o u rage countries from pursuing trade libera l i s ation. Th e re have been concerns about thereduced ability of food importing countries to finance imports in the face of incre a s e dmarket prices that accompany trade liberalisation. There is also a major concern that thel a ck of infra s t ru c t u re and legal and financial institutions will mean that developing coun-t ries will not be able to effe c t ive ly compete in a liberalised wo rl d. Thus, trade libera l i s at i o ncould result in we l fa re losses to local industries and reduce employment in some deve l-oping countries. Fi n a l ly, there is a concern that transaction and adjustment costs could behigh, part i c u l a rly if it means losing pre fe rential access to key developed markets. For thisreason, an assessment of the impact on diffe rent countries is re q u i re d. Given the dive rs eeconomic conditions in different countries and the unique set of policy barriers that eachc o u n t ry has to deal with, such assessments need to be based on an ap p ro a ch that can ex p l i c-itly deal with these divergences.

Economic models, such as ABARE’s global trade and environment model (GTEM), canassist with such analysis. Howeve r, to undert a ke such analysis in a compre h e n s ive wayrequires a detailed knowledge of the protection systems faced by different countries.

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‘South’ countries

In this study the concept of‘south’ countries indicates devel-oping countries, which includeLatin America and the Carib-bean, Africa including SouthAfrica, Europe less EU15 andE F TA3, the Middle East, Asialess Japan and China, andOceania less Austra lia andNew Zealand. This is consistentwith the treatment of countriesin the WTO agricultural negoti-a t i o n s .


Tariffs

Trade nego t i ations under the WTO are based on bound tari ffs. A bound tari ff is the level ac o u n t ry agrees not to exceed when establishing the actual tari ff on a specific pro d u c t .These bound tari ffs differ from product to product and from country to country. Wh i l eactual tari ffs, otherwise known as applied tari ffs, cannot exceed the bound level they can bebelow that level.

Most bound tari ffs on agri c u l t u ral products we re established under the Uru g u ay Round ofmu l t i l at e ral trade nego t i ations. The base rates we re established in diffe rent ways dep e n d-ing on the situation prevailing befo re the Uru g u ay Round. Developing countries we re abl eto offer ‘ceiling bindings’ for all prev i o u s ly unbound tari ffs, and many developing coun-t ries used this option to establish ve ry high bound tari ffs. In addition, some applied tari ffs areb e l ow bound tari ffs because countries have unilat e ra l ly reduced their protection on somep roducts. For these reasons, there can be a gap between bound and applied tari ffs in manyd eveloping countries. This distinction between bound and applied tari ffs can be crucial to anya n a ly s i s .

Evidence suggests that the level of tari ffs applied by developing countries is often fa rbelow the level of their bindings — see tables 1 and 2 on page 9. These tables also showapplied tari ffs for selected developing countries, wh i ch indicate that protection levels inL atin America are re l at ive ly low, a conclusion that would not be drawn from the boundtariff rates.

G iven these dive rgences between bound and applied tari ffs, and va ri ation of tari ffs in deve l-oping countries, it is especially important to assess the impacts of any libera l i s ation pro p o s a lon a case by case basis. In addition, if mu l t i l at e ral trade re fo rm is going to be analy s e d, itis critical to account for the differences between applied and bound tariffs.

Agricultural trade patterns of developing countriesWhile the re l at ive tari ffs implemented by diffe rent countries will have a critical infl u e n c eon the benefits that can be ach i eved from libera l i s ation, the current pat t e rn of trade is alsocritical to any trade reform analysis. As such, a substantial effort has been undertaken toassess the agri c u l t u ral trade pat t e rn of developing countries. This has included a focus onthe growing area of agricultural trade between developing countries.

Agricultural south–south trade of AsiaA gri c u l t u ral ex p o rts by Asian developing countries to developing countries accounts for 35per cent of their total agri c u l t u ral ex p o rts. In addition, during the 1990s, agri c u l t u ral ex p o rtvalues from Asia to other developing countries increased signifi c a n t ly. The gross value ofsouth–south ex p o rts from Asia increased from about US$5.5 billion in 1990 to US$8.9 billionin 1999 — a rate of growth of about 5.5 per cent a year (WTO 2001; United Nations 2003).

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The most important agricultural products exported from developing Asia are coffee, tea,cocoa and spices; cereals (including rice); fruit and vege t ables; meat; nat u ral fi b re s ;vege t able oil; and fats (WTO 2001). Among ex p o rted products coffe e, tea, cocoa andspices have had the highest rate of export growth, with the total value of exports of theseproducts exceeding US$6 billion in 1999.

Leading ex p o rt e rs in Asia are Malaysia, Thailand and India accounting for over US$6billion in 1999 or more than 17 per cent of total agricultural trade value from developingAsia.

Agricultural south–south trade of Middle EastTotal agri c u l t u ral ex p o rts from this region we re US$5.5 billion in 1999, of wh i chsouth–south trade was more than US$3 billion. Howeve r, agri c u l t u ral ex p o rts as a whole inthis region provide a share of only 2.5 per cent of total ex p o rt reve nu e( W TO 2001). It is avery small fraction compared with oil, the key source of export earnings in this area.

The total value of agri c u l t u ral imports to the Middle East from other developing countri e swas almost US$6 billion in 1999 (WTO 2001). This amount is less than 3.5 per cent oftotal imports.

Latin America’s trade with developing countriesD eveloping countries in Latin America and the Cari bbean have a comparat ive adva n t age inthe production of agri c u l t u ral commodities. Land is abundant, labor is re l at ive ly inex p e n-s ive and diffe ring cl i m atic conditions allow for the production of a va riety of commodi-ties, especially fruits and vegetables, coffee, sugar and bananas.

In 1999, Latin American and Cari bbean countries’ agri c u l t u ral ex p o rts to developing coun-tries was 34 per cent of the total agricultural exports. This is despite the value of agricul-tural exports to developing countries increasing on average by 5 per cent a year over thisp e ri o d. This growth in ex p o rts to developing countries has mainly been directed at Asiaand Africa. Also, agri c u l t u ral trade between Latin American and Cari bbean countries iss i g n i ficant, accounting for 19 per cent of all agri c u l t u ral ex p o rts from the region and 19per cent of all agri c u l t u ral imports into the region. Agri c u l t u ral imports from Africa arealso growing at the rate of 17 per cent a year on average (WTO 2001).

Africa’s trade with developing countriesA f rica has a nat u ral comparat ive adva n t age in the production of agri c u l t u ral commodities.The region has an abundance of land and low labor costs that are conducive to agri c u l-t u ral production. As the region has scarce capital and tech n o l ogy, it is heav i ly reliant onagri c u l t u re as a source of employment, income and ex p o rt reve nu e. Howeve r, it is like ly thatimpediments to agri c u l t u ral trade prevent Africa from maximising its comparat ive adva n-tage in agricultural production.

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In 1999, Afri c a ’s major agri c u l t u ral ex p o rts we re fruits and vege t ables, coffe e, tea, cocoa,spices, sugar and tobacco. From 1990 to 1999, Afri c a ’s agri c u l t u ral ex p o rts to deve l o p i n gc o u n t ries, as a pro p o rtion of total agri c u l t u ral ex p o rts, increased on ave rage by 1.4 percent a ye a r, re a ching 33 per cent in 1999. Corre s p o n d i n g ly, Afri c a ’s agri c u l t u ral ex p o rt sto developed countries, as a proportion of total agricultural exports, decreased by 0.5 percent a year on average, and now only accounts for 66 per cent of all agricultural exports.

In addition to the increased agri c u l t u ral ex p o rts to Latin America, African agri c u l t u ra lex p o rts to developing Asia have also been increasing by 4.4 per cent a year on ave rage.At the same time, intra - A f rican agri c u l t u ral ex p o rts, as a pro p o rtion of total agri c u l t u ra lex p o rts, decreased by 0.5 per cent a year on ave rage (WTO 2001). This highlights a tre n dt owa rd African countries ex p o rting an increasing pro p o rtion of their agri c u l t u ral commodi-ties to developing countries in other regions while simu l t a n e o u s ly cutting back the pro p o r-tion exported to other African countries.

Despite large imports of agricultural products from Europe, accounting for more than 20per cent of total agricultural imports, there has been a trend toward higher levels of inter-regional trade sourced from other developing countries. From 1990 to 1999, Afri c a ’s agri-c u l t u ral imports from developing Asia, as a pro p o rtion of developing Asia’s total agri c u l-t u ral ex p o rts, increased on ave rage by 1.5 per cent a ye a r. Afri c a ’s agri c u l t u ral import sf rom Latin America, as a pro p o rtion of Latin Ameri c a ’s total agri c u l t u ral ex p o rts, incre a s e dby 3.3 per cent a year.

Tariff dataThe GTAP dat abase of the GTAP model (Hertel 1997) is a widely used dat abase fo ra n a lysing trade policy analysis with a global dimension. The dat abase provides info rm at i o non costs and sales of commodities within each economy, bilat e ral trade fl ows and leve l sof protection such as tax and subsidies including tari ffs. Howeve r, the usefulness of tari ffd ata in the GTAP dat abase is limited because the tari ff info rm ation applies to the ye a r1997. As such it does not incorp o rate progress in libera l i s ation of trade under the Uru g u ayRound Agreement. The database also does not consistently use applied or bound tariffs.

In this study, a new set of applied and bound tari ff data was constructed using two dat a-bases maintained by the WTO. The dat abases are the Integrated Ta ri ff Dat abase (IDB) andthe Consolidated Ta ri ff Schedule (CTS). These dat abases are allowed to be used by WTOmember gove rnments for analysing and advising nego t i at o rs so long as the data are notrep roduced with details below the Harmonised System 6 digit level. As an indep e n d e n tre s e a rch arm of the Au s t ralian Gove rnment, ABARE provides advice to Au s t ralian nego-t i at o rs using the GTEM model, with this info rm ation incorp o rated into the model dat a-base.

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The IDB usually contains applied tariff information and the CTS contains tariff bindingsplus info rm ation on ex p o rt subsidy and domestic support commitments including tari ffquota commitments. Members of the WTO are supposed to provide the orga n i s ation withi n fo rm ation on applied tari ffs eve ry ye a r. The WTO dat abase thus provides ve ry usefulinformation on the progress on reducing barriers to trade. As the WTO datasets are veryd e t a i l e d, running into thousands of tari ff lines for eve ry member country, GTAP ve rs i o n5 pro d u c t - s p e c i fic tari ffs are calculated using the GTAP sector c l a s s i fi c ation and the HScode concordance ava i l able at the GTAP website (www. g t ap . age c o n . p u rd u e. e d u /resources/download/582.txt). The WTO databases contains bound and applied tariffs forboth agricultural and nonagricultural products.

In total, there are 211 countri e s / regions cove red in the GTAP dat ab a s e, wh i ch are rep re-sented by 66 countries/regions. Many of the small economies are grouped into aggregateregions. For ex a m p l e, Haiti and Bahamas are part of a larger aggregation of Centra lA m e rica and the Cari bbean, while the rest of the wo rld is a mix of heterogeneous coun-t ries with both low and high incomes and with va ried economic stru c t u res. Similarly, thou-sands of product lines are also tra d e d, while the GTAP dat abase rep resents only 57 sectorsso that most of the GTAP sectors are an aggregation of tari ff specific products. ABA R Ehas calculated simple arithmetic ave rage tari ffs based on individual tari ff lines. While thisap p ro a ch is far from ideal, there is curre n t ly insufficient data to implement an ap p ro a cht h at would provide a more accurate tari ff for these groupings. Ta ri ffs on products lev i e dby aggregate regions are calculated using aggregate CIF import data of component coun-t ries. The tari ff equivalents of specific tari ffs are not yet incorp o rated in ABA R E ’s model-ing. This is an improvement that is planned for the near future.

The calculated applied and bound tari ffs used in the modeling undert a ken for this pap e ra re in appendix B and are summarised in tables 1 and 2. Many of the applied tari ffs take nf rom the WTO dat abase ap p ly for calendar year 2002 (appendix C). The ye a rs with thesecond and third most nu m e rous observations on applied tari ffs are for 2000 and 2001,while the oldest observations are for 1998. For bound tari ffs, most of the info rm ation isbased on concessions made in 1996, with the latest countries to accede into the WTOh aving the latest info rm ation — for ex a m p l e, China, wh i ch committed to tari ff bindingsin 2001. The final commitment levels have been used and will continue to ap p ly untilf u rther ch a n ges are nego t i at e d. In comparison, the GTAP ve rsion 5 dat abase contains tari ffinformation applicable for the period 1992–2000 (see table 16.A.1 of Dimaranan 2002).

An important characteristic of the data in tables 1 and 2 is the existence of large bindingoverhang or ‘water in the tari ff’, as estimated in table 3. The ‘water in the tari ff’ prov i d e sscope for a country to pre s e rve barri e rs to trade by maintaining the levels of applied tari ff sor even increase them as long as they are within the levels of current bound rates. By thism e a s u re, developing countries have scope to maintain barri e rs to trade when bound tari ff sare reduced.

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Also, the existence of binding overhang has an important implication for the way in wh i chreductions in barri e rs to trade are nego t i ated under the WTO arra n gements. The larger the‘ water in the tari ff’, the larger the cuts in bound tari ffs re q u i red to increase market access.As the tari ff info rm ation used in the model is an ave rage of the tari ff lines comprising theaggregat e, the binding overhang in the model will be larger than some tari ff lines and lessthan others. In ge n e ral, the ap p ro a ch will still provide a re a s o n able rep re s e n t ation of thet rade effect across all products. Developing countries are estimated to re q u i re a re d u c t i o n

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1 Average applied tariff s

Developed Middle Latin Rest of countriesa Asia Africa East America world

% % % % % %Agricultureand food 22 20 40 20 17 14

Manufacturedproducts 4 8 20 6 13 6

a ABARE estimates of average effective rate of protection for Japan, EU15 and the UnitedStates.Source: Compiled from WTO database.

2 Average bound tariff s


% % % % % %Agricultureand food 27 39 69 59 47 38

Manufacturedproducts 4 12 37 12 34 16

a ABARE estimates of average effective rate of protection for Japan, EU15 and the UnitedStates.Source: Compiled from WTO database.

3 Binding overhang or ‘water in the tariff’ — as percentagesof the bound tariff


% % % % % %Agriculture

and food 19 50 42 65 64 62Manufactured

products 10 32 47 54 62 62

a Based on ABARE estimates of average effective rate of protection.Source: Compiled from WTO database.


of at least 32–65 per cent in bound tari ffs befo re any increase in market access will bea ch i eve d, while developed countries need lesser libera l i s ation. The existence of this ove r-hang indicates that for meaningful trade re fo rm to occur, countries have to be ambitiousin reducing their bound tari ffs. Any nego t i ated reduction that does not re m ove the bind-ing overhang will not change access to markets and would not generate changes to agri-cultural production and trade.

Modeling trade liberalisationThe method of modeling trade libera l i s ation, the scenarios analysed and the ch a n ges onkey parameter assumptions of the model are discussed in this section.

The ap p ro a ch used in modeling trade libera l i s ation dep a rts from the most common methodin wh i ch libera l i s ation is simu l ated by reducing applied tari ffs. ABA R E ’s ap p ro a ch re fl e c t sthe way in wh i ch tari ffs are reduced through nego t i ations under the WTO, namely byreducing bound tariffs.

Under the WTO, the reduction or elimination of barri e rs to trade is nego t i ated from ex i s t-ing bindings that WTO members have committed to. These bindings are rep resented bybound tari ffs that eve ry WTO member agreed not to ex c e e d. Th e re are large gaps betwe e napplied and bound tari ffs and the presence of these gaps will have an impact on the outcomeof any nego t i ations. For many items, large reductions in bound tari ffs will be re q u i red if anyadditional trade is to occur.

The distinction between applied and bound tari ffs and the gaps between them are an impor-tant consideration in modeling trade libera l i s ation scenarios. This distinction is not re c og-nised in the GTAP ve rsion 5 dat abase and the pro blem is ex a c e r b ated for agri c u l t u re. Inthe dat ab a s e, agri c u l t u ral tari ff data are a mixture of both bound and applied tari ffs. Ofthe 46 countries for wh i ch agri c u l t u ral tari ff data are ava i l abl e, half of the tari ffs are boundt a ri ffs while the other half use applied tari ff data (see table 16.A.2 of Dimaranan 2002).In the absence of a distinction between the two types of tari ffs, bound rates in the dat a-base are automat i c a l ly considered as applied tari ffs. As such, they serve as barri e rs thatre s t rict trade in the equilibrium dat ab a s e. Since bound tari ffs are in most cases higher thanapplied tariffs, the restrictiveness of applied tariffs is overstated.

Trade libera l i s ation scenarios using a dat abase with this kind of rep re s e n t ation of barri e rsto trade are like ly to ove re s t i m ate the impact of the policy ch a n ge. Import a n t ly, modelingt rade libera l i s ation using this ap p ro a ch is not realistic in the context of the WTO tra d enegotiations where negotiations focus on reducing bound tariffs.

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Approach to analysis

The information required to analyse trade liberalisation as discussed above requires bothapplied and bound tari ffs. The GTAP dat abase contains only applied tari ffs that are basedon calendar year 1997. Bound tariffs were compiled and more recent applied tariffs werec o l l e c t e d. Applied tari ffs are used to rep resent existing protection in the model; howeve r,when libera l i s ation is undert a ken, the applied tari ffs are only reduced when the re d u c t i o n sin bound tari ff eliminate the tari ff ove r h a n g. In these cases, the applied tari ff is re d u c e dto the level of the new tari ff binding. The libera l i s ation scenarios are then simu l ated usingthe GTEM model. A brief technical description of GTEM is in appendix D and the fulld o c u m e n t ation is ava i l able on ABA R E ’s website (www. ab a re c o n o m i c s . c o m / re s e a rch/models/GTEM/gtem.pdf).

GTEM provides a suitable fra m ewo rk for analysing trade policy ch a n ges as it takes intoaccount the interactions between sectors within countries and the linkages between coun-t ries brought about by trade and investment. For this pap e r, the data used is GTAP ve rs i o n5 dat abase (Dimaranan 2002) from the GTAP model, with modifi c ations of agri c u l t u ra lcomponents to adjust for known anomalies between costs and sales structures of agricul-t u ral sectors and info rm ation in the input–output tables (see Buetre, Rodriguez and Pa n t2003).

Typically, the policy changes arising from WTO negotiations such as reduction in boundt a ri ffs are phased in over an implementation peri o d. The ability of GTEM to provide esti-m ates of the impacts of ch a n ges to trade policies on key economic va ri ables, such as tra d efl ows, outputs, incomes and prices at regional and global levels over time, makes it a suit-able model for analysing agricultural liberalisation of tariff barriers.

The general approach to analysis using GTEM is to determine a ‘business as usual’ baseline or re fe rence case of expected values for the re l evant va ri ables under the assumption thatno policy ch a n ges occur over the period of time that is considere d. It is then assumed thatp o l i cy ch a n ges do occur, and the model is used to determine values for the re l evant va ri abl e sover the policy adjustment period. The difference between the reference case values andthose from the policy change scenario indicates the impact of the policy change.

For this analysis annual re fe rence case estimates are made for the chosen baseline peri o d,1997–2014. Such estimates are for economic va ri ables for each country and economics e c t o r, including aggregate production (gross domestic product), aggregate income (gro s sn ational product), population, capital stock, production, consumption, imports, ex p o rt sand prices. Other re l evant policy va ri ables that are important to this study, such as theapplied and bound tari ffs from WTO dat abase discussed prev i o u s ly, are introduced intothe baseline. The applied tari ffs from the WTO updates those in the dat abase when ru n n i n gthe baseline.

11


Va rious policy simu l ations are then made and the effects of the assumed policy ch a n ge sd e t e rmined through the diffe rence between the simu l ated levels and the re fe rence casevalues. For the purpose of this exe rc i s e, it is assumed that policy ch a n ges are to occur ove rthe period 2005–14. A summary of the country and commodity groups used in this studyis provided in box 1.

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Box 1: Country and commodity groups used in study

A commodity and regional cove rage that is sufficient to rep resent key agri c u l t u ral commoditiesand major pro d u c e rs and tra d e rs in the wo rld market and in va rious developed and deve l o p i n gc o u n t ries is shown in the table below. The rep re s e n t ation of 26 commodities is designed to cove r17 agri c u l t u ral sectors, most of wh i ch re c e ive some fo rms of support and are important for deve l-oping countries as well as in the WTO nego t i ations. The 18 regions identified rep resent majorp ro d u c e rs and consumers of agri c u l t u ral products. Th ey incl u d e, among others, those that havehigh support for agri c u l t u ral pro d u c t i o n .

Region and commodity representation in GTEM

Regions Commodities

Australia Primary agricultureNew Zealand Paddy riceJapan Fruits and vegetableASEAN Plant based fibresChina Other cropsRest of north Asia CattleIndia Other animal productsRest of south Asia OilseedsCanada Cane and beet sugarUnited States Processed agricultureLatin America and the Caribbean ForestryArgentina FisheriesBrazil Other mineralsEU15 + EFTA Cattle meatNon-EU Europe Other meatMiddle East DairyAfrica Other food productsRest of world Rice

SugarWoolEnergy productsManufactured productsServicesTextile, clothing and leatherElectricityIron and steel


Key parameter changes

An important modifi c ation made in this study is the set of para m e t e rs for the consumerdemand system for China. The standard GTAP parameters indicate that the income elas-ticities of demand for meat products in China are elastic and for most other agri c u l t u ra lp roducts are close to unity. These high elasticities induce mu ch larger growth in consump-tion of meat and agricultural products in China in the ‘business as usual’ baseline than isindicated by widely cited projections.

The para m e t e rs of the CDE (constant diffe rence elasticity) demand function for China aret h e re fo re revised to make growth in per person consumption consistent with publ i s h e de s t i m ates. In part i c u l a r, the income elasticities of demand are scaled down so that perp e rson consumption of agri c u l t u ral products aligns with projected growth rates in consump-

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4 Income elasticities of selected agricultural products used inthe model

GTAP ABARE FAPRI/revised IFPRI a

Oilseeds 0.87 0.35 Wheat and other coarse grains 0.41 0.11 –0.3 to 0.2Cattle meat 1.12 0.28 0.35 to 0.5Pig and poultry meat 1.12 0.43 0.2 to 0.65Dairy 0.78 0.40Vegetable oil 0.87 0.35Rice 0.41 0.11 –0.04 to 0.03 Sugar 0.87 0.27

a Rosegrant et al. (1995) on cereals and FAPRI (2004a) on meat products.

5 Estimated annual per person consumption growth rates forselected agricultural products

Growth using

GTAP ABARE FAPRIincome revised growth

elasticity elasticity rates a

% % %

Oilseeds 6.4 2.7 Wheat and other coarse grains 2.8 0.8 0.9 b

Cattle meat 8.6 2.3 3.7Pig and poultry meat 8.3 3.3 2.0–2.9Dairy 5.6 2.8 3.0–3.1 c

Vegetable oil 7.0 3.0 0.5–9.9 d

Rice 3.0 0.7 1.0 Sugar 6.0 2.1 1.8

a FAPRI (2004b) and Rosegrant et al. (2001). b Average of cereals. c Butter and cheese. d Sunflower oil, soybean oil, rapeseed oil and peanut oil.


tion that have been published by FAPRI (2004a) and IFPRI (Rosegrant et al. 1995, 2001).The ap p ro a ch used by Hertel (1997) to calibrate the CDE demand function is used hereto make these adjustments. The resulting elasticities used in the model along with the stan-dard GTAP elasticities are provided in table 4.

The ch a n ges in income elasticities for food and agri c u l t u ral products in China has re s u l t e din growth rates in per person consumption that are well aligned with the growth rat e sprojected by FAPRI and IFPRI, as indicated in table 5. Projections based on the originalelasticities result in large consumption growth for agricultural products. These consump-tion ch a n ges have the potential to induce large stru c t u ral ch a n ges in Chinese agri c u l t u reover time that can bias the results.

Scenarios for liberalisationFour main scenarios are explored in this paper.

■ A 15 per cent cut in bound tariff s : This rep resents a situation wh e re success in marke taccess nego t i ations is limited. The small reduction in bound tari ffs is aimed to demon-s t rate that benefits from re fo rm are neg l i gi ble in a situation wh e re bound rates are highrelative to applied tariffs.

■ 50 per cent cut in bound tariff s : This is designed to demonstrate that larger cuts to boundt a ri ffs are re q u i red to have an impact on market access when applied tari ffs are lessthan bound tariffs.

■ An additional 50 per cent comprehensive trade reform : This is undert a ken to inve s t i gat ethe impact of a wider part i c i p ation of countries in mu l t i l at e ral trade libera l i s ation. Inthis scenario, the reductions in tari ffs are based on applied tari ffs so that all of the coun-tries/regions have equal reductions in all their barriers to trade.

■ 50 per cent unilateral cut by India: This simu l ation demonstrates that for gains to bemaximised, India must liberalise its highly protected industries.

ResultsThe effects of libera l i s ation on incomes, output and tra d e, including the effects on tra d eb e t ween developing countries, are discussed in this section. An additional analysis of Indiais undertaken to understand the effects of the reductions in bound tariffs on its economy.

Larger cuts are needed to increase incomesIf nego t i ations for reduction in barri e rs to agri c u l t u ral trade are less successful, leading tosmall cuts in bound tari ffs of, say, 15 per cent, only a few countries would reduce theirapplied tari ffs because of the high binding overhang for agri c u l t u ral products. The effect onglobal incomes from this re fo rm is estimated to be an additional US$2.2 billion (table 6).

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As will be discussed lat e r, trade and production ch a n ges are also ve ry small when therea re small reductions in bound tari ffs. A notable fe at u re of the results is that even small cutswould increase the GNPs of all countries ex c ept India and Rest of south Asia. India andRest of south Asia lose because of the nat u re of trade re fo rm and the stru c t u res of theirt a ri ff settings, as will be discussed lat e r.

If negotiations are more successful so that larger cuts in bound tariffs are negotiated, theb e n e fits are signifi c a n t ly larger than in the fi rst scenario discussed ab ove. In a scenari owh e re bound agri c u l t u ral tari ffs are cut by 50 per cent, global incomes would increase byUS$12 billion re l at ive to the no trade re fo rm baseline. A third of this additional incomewould accrue to developing countries. On ave rage, these countries would ex p e rience asmaller cut in applied tari ffs than developed countries. The larger income increases from thiss c e n a rio are attained because more countries have to reduce their applied tari ffs and large rcuts are made. Howeve r, because of the large ‘water in the tari ff’, some countries haveo n ly minimal cuts in applied agri c u l t u ral tari ffs. The main countries in this cat ego ry areIndia and Rest of south Asia. These countries again ex p e rience lower incomes than in theno reform scenario.

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6 Change in GNP at 2014

Cut to bound 50 per cent agricultural tariffs cut to applied

merchandise15 per cent 50 per cent tariffs

US$m US$m US$m

Australia 67 355 873New Zealand 47 306 716Japan 452 2 129 7 522ASEAN 63 190 3 270China 60 130 2 620Rest of north Asia 166 213 3 760India –42 –177 2 457Rest of south Asia –16 –71 738Canada 93 357 1 443United States 90 770 6 210Latin America and the Carribean 146 594 2 114Argentina 48 199 825Brazil 111 391 2 048EU15 + EFTA 450 2 890 18 590Non-EU 201 993 1 379Middle East 89 858 2 470Africa 148 1 683 3 779Rest of world 44 190 160

Total 2 217 12 000 60 973

Source: GTEM simulations.


The income gains from the fi rst two scenarios pale in comparison with the scenario wh e reall countries reduce their applied tari ffs on all merchandise products. This scenario hasbeen included to indicate the re l at ive benefits that could be ach i eved from a tari ff re d u c t i o nfo rmula that ach i eves substantial gains. Cuts to applied tari ffs have been used becauseA BARE curre n t ly does not have the ability to accurat e ly model some of the more complexfo rmula ap p ro a ches that have been proposed in the WTO nego t i ations (see limitat i o n ssection). In this scenario, all countries are able to exploit their comparat ive adva n t age,leading to more efficient allocation of re s o u rces. Changes in intern ational prices alsoc o n t ri bute to the income gains. All countries gain in this scenario (table 6), with the incre a s ein incomes in developing countries estimated to be US$22 billion and the total incre a s eis US$61 billion.

Maintaining high levels of tariffs is costly – the case of IndiaIndia and Rest of South Asia (composed of Bangladesh, Sri Lanka and the remaining SouthAsian countries) lose in both the scenarios in wh i ch agri c u l t u ral bound tari ffs are re d u c e d.These two country groups maintain high levels of both applied and bound tari ffs. In add i-tion, they both have ve ry high binding overhang as indicated in appendix B. When boundt a ri ffs are libera l i s e d, most of the applied tari ffs in these countries are not reduced becauseof the ove r h a n g. The tari ffs of only a few sectors are libera l i s e d, and the most highlyprotected sectors tend to have no reduction in tariffs.

To understand further the results for India and Rest of south Asia, three scenarios thatrequire India to unilaterally liberalise were undertaken as follows:

1: 50 per cent cut in bound agricultural tariffs

2: 50 per cent cut in applied agricultural tariffs

3: 50 per cent cut in applied tariffs on all merchandise products.

The results from these simu l ations indicate that a unilat e ral reduction in the bound agri-c u l t u ral tari ffs of India would have almost no impact on its GNP (table 7). The reason is thatthe large binding overhang and the nat u re of applied and bound tari ffs in India ensure st h at levels of applied tari ffs on highly protected sectors are maintained if bound tari ff salone are re d u c e d, while protection is reduced in less highly distorted sectors such as ri c e,wh i ch has an applied tari ff of 75 per cent and low binding ove r h a n g. Cuts in bound tari ff smay just lead to a shift in resources toward more inefficient sectors and incomes fall.

A ny libera l i s ation re q u i ring the reduction of tari ffs on other sectors, including highlyp rotected ones, such as in the case of a 50 per cent reduction in applied agri c u l t u ral tari ff s ,India gains substantially. Its GNP increases by US$786 million. Gains in incomes for Indiato the tune of US$1.6 billion in GNP could be attained if the merchandise sectors cove re dfor liberalisation are expanded to include nonagricultural products.

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The same results are likely to be true for the Rest of south Asia region because India andthis region have the same structure of tariffs (appendix B).

E ffects on trade flowsThe results on trade fl ows re flect the effects of re fo rm on incomes. The bigger the re d u c-tion in tari ffs the gre ater the volume of trade that is estimated to occur (table 8). By sector,the ch a n ge in the volume of trade is affected by the level of protection and the mag n i t u d eof reduction of applied tari ffs. Processed agri c u l t u ral products, including beve rages and

7 Gains from unilateral liberalisation — the case of India

India All countries

50 per cent cut in

bound applied applied boundagricultural agricultural merchandise agricultural

tariffs tariffs tariffs tariffs

US$m US$m US$m US$m

Gross national product 3 786 1 578 –177

Source: GTEM simulations


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8 Percentage change in exports, selected tradable products

15 per cent cut in 50 per cent cut in 50 per cent cut onagricultural bound agricultural bound applied tariffs on

tariffs tariffs merchandise products

Developed Developing Developed Developing Developed Developing

% % % % % %

Primary agriculture 0.47 0.07 1.34 1.20 2.97 9.48Fruits and vegetable –0.10 1.71 0.21 6.50 4.11 14.22Plant based fibres 0.31 –0.11 1.12 –0.28 4.48 8.88Other crops 0.38 0.29 1.82 1.39 3.33 5.08Oil seeds 0.24 0.31 0.83 1.65 0.46 8.39Processed agriculture 1.04 1.36 8.28 4.67 12.61 14.23Cattle meat 0.19 –0.04 4.00 8.37 4.86 52.52Other meat 1.07 1.03 5.07 4.96 10.47 12.00Dairy 0.63 na 3.65 na 11.82 naOther food products –0.38 3.48 –0.11 14.99 5.57 20.09Rice –0.94 1.19 –0.75 5.16 4.70 17.92Sugar 0.26 –0.10 –2.81 5.55 –5.97 28.93Wool 0.38 na 0.96 na 0.50 naManufactured products 0.04 –0.09 0.12 -0.23 1.93 8.01Textile and wearing apparel 0.10 –0.15 0.23 -0.31 4.29 13.73Iron and steel 0.04 –0.12 0.15 -0.35 2.39 8.02

na Not applicable.Source: GTEM simulations.

tobacco, dairy products, suga r, ri c e, cattle meat and other food products, are ge n e ra l lyp rotected in many developed and developing countries. Libera l i s ation of these sectorsinduces more tra d e. Howeve r, such increases in trade are hard ly realised if bound tari ff sonly are reduced at low levels of cuts.

For developing countries, gains in ex p o rts are realised in suga r, ri c e, labor intensive pro c e s s e dfood products, and pigs and poultry meat. The developed countries on the other hand incre a s eex p o rts of pri m a ry agri c u l t u re (mainly wh e at and coarse grains), dairy products, wool andp rocessed agri c u l t u re under agri c u l t u ral trade libera l i s ation. Exports of cattle meat fro md eveloping countries also increase at a high rate but this comes from a low base va l u e.

When libera l i s ation invo l ves all merchandise commodities, ch a n ges to trade fl ows aremu ch bigge r, with developing countries increasing their ex p o rts of tex t i l e, we a ring ap p a re land leather and light manufactured products.

Under the three scenarios, the effects on trade between developing countries on south–south trade are also more pronounced when larger cuts and a wider cove rage of commodi-ties and countries are involved in the liberalisation of tariffs (table 9).

South–south trade on agri c u l t u re increased in all scenarios but such increases are in allcases lower than the increase in developing countries’ ex p o rts to developed economiesindicating a much greater market access opening in developed countries than in develop-ing countries. This is implied from larger binding overhang in developing countries thatresulted in small or even no cuts in applied tariffs in developing countries.


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9 Change in the value of trade

Importer

Value of agricultural trade Value of total trade

Developed Developing Total Developed Developing TotalExporter15 per cent cut in bound tariffsDeveloped 2.1 0.7 2.8 3.1 1.6 4.7Developing 3.2 0.0 3.2 1.9 –0.4 1.5Total 5.3 0.7 6.0 5.1 1.2 6.3

50 per cent cut in bound tariffDeveloped 12.4 7.0 19.4 15.3 9.4 24.7Developing 12.8 1.1 13.9 10.1 0.2 10.2Total 25.3 8.1 33.4 25.3 9.5 34.9

50 per cent cut in applied tariffs on merchandise commoditiesDeveloped 21.7 22.3 44.0 88.5 101.8 190.3Developing 17.5 11.2 28.7 111.2 77.2 188.4Total 39.2 33.5 72.6 199.7 179.1 378.7

Source: GTEM simulations.


The simu l ation results also indicate that gre ater part i c i p ation and wider cove rage of sectorsfor libera l i s ation will provide the largest increase in trade between developing countries. Itis estimated that a 50 per cent cut to applied tari ffs on all merchandise trade would lead toan increase in trade of US$77 billion between developing countries. This expansion in tra d eis the largest among the libera l i s ation scenarios considered in the paper and is pri m a ri lyexplained by re l at ive ly larger tari ffs on nonagri c u l t u ral products in developing countri e s .

E ffects on outputThe effects on output are again influenced by the extent of the reduction in applied tari ff s .With a small binding overhang in agri c u l t u re in developed countries, this group of countri e sl i b e ralises its agri c u l t u re mu ch faster than developing countries when bound tari ffs arereduced. As a result, outputs of most agricultural sectors in developed countries contract

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1 0 Percentage change in output from

15 per cent cut in 50 per cent cut in 50 per cent cut inagricultural agricultural merchandise productsbound tariffs bound tariffs applied tariffs

Developed Developing Developed Developing Developed Developing

Primary agriculture –0.04 0.00 –0.27 0.01 –0.30 –0.74Paddy rice –0.08 0.02 t–1.09 0.10 –1.91 0.11Fruits and vegetable –0.17 0.09 –0.56 0.31 –0.24 –0.07Plant based fibres 0.07 –0.06 0.16 –0.15 1.70 1.07Other crops –0.30 0.11 –1.00 0.13 –0.87 0.09Cattle –0.04 0.01 0.03 –0.15 –0.52 –0.28Other animal products –0.06 0.04 –0.14 0.06 0.14 –0.14Oilseeds –0.05 0.07 0.03 0.09 0.18 –0.13Cane and beet sugar –0.06 0.01 –1.99 0.23 –5.53 0.92Processed agriculture –0.05 0.17 0.20 –0.36 0.76 –1.83Forestry 0.00 –0.01 –0.02 –0.02 0.42 0.13Fisheries –0.01 0.02 –0.02 0.07 0.12 –0.04Other minerals –0.01 –0.02 –0.02 –0.04 –0.15 –0.18Cattle meat 0.01 –0.01 –0.05 –0.55 –1.11 –0.25Other meat –0.10 0.02 –0.16 –0.20 0.02 –0.53Dairy –0.16 –0.03 –0.52 –0.64 0.17 –1.84Other food products –0.29 0.44 –0.98 1.52 –0.61 0.98Rice –0.10 0.04 –1.02 0.15 –1.64 0.02Sugar –0.04 0.02 –2.24 0.55 –6.51 1.34Wool 0.07 na 0.22 na 1.39 naEnergy and natural resources 0.00 –0.01 0.01 –0.01 0.10 0.20Manufactured products 0.01 –0.05 0.04 –0.12 0.02 0.23Services 0.00 0.00 0.02 0.00 0.07 –0.01Textile and wearing apparel 0.05 –0.07 0.11 –0.12 –2.00 2.09Electricity 0.00 –0.02 0.02 –0.02 0.02 0.14Iron and steel 0.03 –0.06 0.09 –0.18 0.15 –0.58

na Not applicable.Source: GTEM simulations.


while nonagri c u l t u ral sectors expand as re s o u rces are re a l l o c at e d. Agri c u l t u ral outputs ind eveloping countries ge n e ra l ly ex p a n d, with notable increase in ri c e, suga r, fruit and vege t a-bles, other crops including coffee, and other labor intensive food products (table 10).

When libera l i s ation is applied to all merchandise sectors, output increases are mu ch large rthan in the two scenarios wh e re bound tari ffs are cut. Under compre h e n s ive libera l i s at i o n ,both developed and developing countries focus more on the production of products inwh i ch they have comparat ive adva n t age. Developing countries expand their production oflabor intensive crops and industrial products such as sugar, rice, textile and clothing, andother manu fa c t u red products. On the other hand, developed countries increase their pro d u c-tion of dairy and other processed agri c u l t u re but reduce production of labor intensive pro d-ucts such as textile and clothing.

LimitationsIn this study, substantial additional info rm ation has been incorp o rat e d, part i c u l a rly in thea rea of bound and applied tari ffs, w h i ch will dra m at i c a l ly improve the ability to useA BA R E ’s model GTEM to more re a l i s t i c a l ly analyse mu l t i l at e ral libera l i s ation scenar-ios. Yet further re finements could be undert a ken that could improve the operation of themodel when undertaking liberalisation scenarios.

At present, GTEM does not have a rep re s e n t ation of tari ff-quotas or specific tari ffs. Th e s epolicy measures are heavily used by a limited number of countries, which strongly influ-ences the results of trade libera l i s ation, including for the United States, the Euro p e a nUnion, Japan and China. Pre s e n t ly, there is no info rm ation on applied tari ffs for Chinaafter their accession to the WTO.

In this analysis of the effects of agri c u l t u ral trade libera l i s ation, other trade distorting agri-c u l t u ral policies such as domestic support and ex p o rt subsidy are ignore d. Previous ex p e-rience has indicated that analysing these policies in combination provides a more accu-rate reflection of the impact of liberalisation — because of the integrated nature of thesepolicies in providing support for domestic industries.

In the current WTO nego t i ations, most proposals for market access re fo rm invo l ve ap p ly-ing diffe rential cuts to diffe rent tari ff lines. To accurat e ly rep resent such ch a n ges re q u i re sthe specific cut to be made to bound tari ffs at a disaggregated level (pre fe rably the indi-vidual tari ff line) and to compare the impact of such a reduction to each applied tari ff. Th eresulting applied tari ffs should then be aggregated up to the GTAP commodities andregions. As ABARE currently does not have the ability to apply differential cuts to indi-vidual tariffs, the scenarios examined in this paper have involved uniform cuts.

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ConclusionA gri c u l t u ral ex p o rts between developing countries has been growing in recent times, andis one of the few areas of agri c u l t u ral trade that is ex p e riencing growth. This trade can beexpanded further if the barriers to agricultural trade are substantially reduced.

If sizable reductions in bound agri c u l t u ral tari ffs are ach i eve d, most developing countri e sa re estimated to ex p e rience increased incomes. The ex c eptions are India and the southAsia group. The economic stru c t u re and protection data in these groupings are similar,i n cluding ve ry high bound tari ffs and a large tari ff ove r h a n g, especially for agri c u l t u re. Inalternative scenarios, incomes in India are estimated to increase when unilateral liberali-s ation in agri c u l t u re or all merchandise sectors is undert a ken and when all countries re d u c eall applied tari ffs by 50 per cent. This indicates that India will gain if it unilat e ra l ly liber-alises or if it is part of a substantial global reduction in applied tariffs. Conversely, Indiaex p e riences contractions in incomes when libera l i s ation occurs that does not result in themost highly protected sectors in India being reformed.

M o re ge n e ra l ly, this study indicates that growth in tra d e, activity levels and incomesi n c reases as more sectors and more countries part i c i p ate in re fo rm. In addition, the widerthe re fo rm and the larger the reduction in tari ffs, the more countries benefit and the higherincome gains are attained from liberalisation.

The study demonstrated that cutting bound tari ffs alone does not guarantee an increase inm a rket access. Larger reductions in bound tari ffs are re q u i red to initiate ch a n ges in tra d e.The benefits that can be realised from a partial cut from bound tari ffs are small compare dwith the same magnitude of libera l i s ation of applied tari ffs, especially in cases wh e re thereare large binding overhangs.

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22

Appendix A

1 1 Prevalence of rural poverty in developing countries

Rural population Total population Reportingin poverty in poverty year

% %

Djibouti 87 45 1996

Zambia 83 73 1998

Bolivia 82 63 1999

Madagascar 77 71 1999

Mozambique 71 69 1997

Kyrgyz Republic 70 64 1999

Nicaragua 69 48 1998

Chad 67 64 1996

Malawi 67 65 1998

Panama 65 37 1997

Peru 65 49 1997

Mauritania 61 46 2000

Burkina Faso 51 45 1998

Philippines 51 37 1997

Zimbabwe 48 35 1996

Yemen, Rep. 45 42 1998

Ethiopia 45 44 2000

Nepal 44 42 1996

Papua New Guinea 41 38 1996

Lao PDR 41 39 1998

Cambodia 40 36 1997

Kazakhstan 39 35 1996

Bangladesh 37 34 2000

Pakistan 36 33 1999

Mongolia 33 36 1995

Algeria 30 23 1995

India 30 29 2000

Morocco 27 19 1999

Sri Lanka 27 25 1996

Moldova 27 23 1997

Jamaica 25 19 2000

Egypt, Arab Rep. 23 23 1996

Estonia 15 9 1995

Tunisia 14 8 1995

China 5 5 1998

Source: World Bank (2003).


Appendix B

23


24


25


Appendix C

26

1 3 Countries/regions with bound and applied tariff inform a t i o n

Data year

Code Name Member country Code Applied Bound a

1 AUS Australia Australia AUS 1999 20042 NZL New Zealand New Zealand NZL 1999 20043 CHN China China CHN 2004/20104 HKG Hong Kong Hong Kong HKG 2001 20045 JPN Japan Japan JPN 2000 2004/20096 KOR Korea, Republic of Korea, Republic of KOR 2000 2004/20097 TWN Taiwan Taiwan TWN 2001 2004/20118 IDN Indonesia Indonesia IDN 2002 2004/20059 MYS Malaysia Malaysia MYS 2001 2004/200510 PHL Philippines Philippines PHL 2000 2004/200511 SGP Singapore Singapore SGP 200012 THA Thailand Thailand THA 1998 2004/200514 BGD Bangladesh Bangladesh BGD 1999 200415 IND India India IND 2000 2004/200516 LKA Sri Lanka Sri Lanka LKA 1998 200417 XSA Rest of South Asia Maldives MDV 2002 200417 XSA Pakistan PAK 2001 200418 CAN Canada Canada CAN 2000 200419 USA United States of America United States of America USA 1999 200420 MEX Mexico Mexico MEX 2000 200421 XCM Central America and Antigua & Barbuda ATG 2004

the Caribbean21 XCM Bahamas BHS 200221 XCM Barbados BRB 2001 200421 XCM Belize BLZ 200421 XCM Costa Rica CRI 2000 2004/200521 XCM Cuba CUB 2000 200421 XCM Dominica DMA 2000 200421 XCM Dominican Republic DOM 2000 200421 XCM El Salvador SLV 2000 2004/200521 XCM Grenada GRD 200421 XCM Guatemala GTM 1998 200421 XCM Haiti HTI 200421 XCM Honduras HND 2000 200421 XCM Jamaica JAM 1999 200421 XCM Nicaragua NIC 2000 200421 XCM Panama PAN 2002 2004/201121 XCM Saint Kitts and Nevis KNA 200421 XCM Saint Lucia LCA 2002 200421 XCM Saint Vincent and

the Grenadines CVT 200421 XCM Trinidad and Tobago TTO 200422 COL Colombia Colombia COL 2000 200423 PER Peru Peru PER 1998 2004

continued


1 3 Countries/regions with bound and applied tariff information c o n t i n u e d

Data year


24 VEN Venezuela Venezuela VEN 2000 200425 XAP Rest of Andean Pact Bolivia BOL 1999 200425 XAP Ecuador ECU 2000 200426 ARG Argentina Argentina ARG 2000 200427 BRA Brazil Brazil BRA 2000 200428 CHL Chile Chile CHL 1999 200429 URY Uruguay Uruguay URY 2000 200430 XSM Rest of South America Guyana GUY 2002 200430 XSM Paraguay PRY 2001 200430 XSM Suriname SUR 200431 AUT Austria Austria AUT 1998 200432 BEL Belgium Belgium BEL 1998 200433 DNK Denmark Denmark DNK 1998 200434 FIN Finland Finland FIN 1998 200435 FRA France France FRA 1998 200436 DEU Germany Germany DEU 1998 200437 GBR United Kingdom United Kingdom GBR 1998 200438 GRC Greece Greece GRC 1998 200439 IRL Ireland Ireland IRL 1998 200440 ITA Italy Italy ITA 1998 200441 LUX Luxembourg Luxembourg LUX 1998 200442 NLD Netherlands Netherlands NLD 1998 200443 PRT Portugal Portugal PRT 1998 200444 ESP Spain Spain ESP 1998 200445 SWE Sweden Sweden SWE 1998 200446 CHE Switzerland Switzerland CHE 1999 200447 XEF Rest of EFTA Iceland ISL 2000 200447 XEF Norway NOR 1999 200448 HUN Hungary Hungary HUN 1999 200449 POL Poland Poland POL 2002 200450 XCE Rest of central European Bulgaria BGR 2001 2004/2005

Associates50 XCE Czech Republic CZE 1998 200450 XCE Romania ROM 1999 200450 XCE Slovakia SVK 2001 200450 XCE Slovenia SVN 2002 200451 XSU Former Soviet Union Armenia ARM 2004/200751 XSU Belarus BLR 200151 XSU Estonia BST 2000 2004/200551 XSU Georgia GEO 2004/200651 XSU Kyrgyzstan KGZ 2001 2004/200551 XSU Latvia LVA 1999 2004/200851 XSU Lithuania LTU 2002 2004/200951 XSU Moldova, Republic of MDA 2004/200551 XSU Russian Federation RUS 200152 TUR Turkey Turkey TUR 2000 200453 XME Rest of Middle East Bahrain BHR 200453 XME Israel ISR 1998 2004/2005

continued

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Data year


53 XME Jordan JOR 2001 2004/201053 XME Kuwait KWT 200453 XME Oman OMN 2001 2004/200953 XME Qatar QAT 2004/200953 XME United Arab Emirates ARE 2004/200954 MAR Morocco Morocco MAR 2002 200455 XNF Rest of North Africa Egypt EGY 200455 XNF Tunisia TUN 2004/200556 BWA Botswana Botswana BWA 2002 2004/200757 XSC Rest of South African Lesotho LSO 2004

Customs Union57 XSC Namibia NAM 2002 2004/200757 XSC South Africa ZAF 2002 2004/200757 XSC Swaziland SWZ 2002 2004/200758 MWI Malawi Malawi MWI 2000 200459 MOZ Mozambique Mozambique MOZ 200460 TZA Tanzania, United, United Republic of TZA 2004

Republic of Tanzania61 ZMB Zambia Zambia ZMB 2001 200462 ZWE Zimbabwe Zimbabwe ZWE 2001 200463 XSF Other Southern Africa Angola AGO 200463 XSF Mauritius MUS 2001 2004/200564 UGA Uganda Uganda UGA 2001 200465 XSS Rest of Sub-Saharan

Africa Benin BEN 200465 XSS Burkina Faso BFA 200465 XSS Burundi BDI 200465 XSS Cameroon CMR 2001 200465 XSS Central African Republic CAF 200465 XSS Chad TCD 200465 XSS Congo COG 200465 XSS Cote d'Ivoire CIV 200465 XSS Djibouti DJI 1999 200465 XSS Gabon GAB 2000 200465 XSS Gambia GMB 200465 XSS Ghana GHA 200465 XSS Guinea GIN 1998 200465 XSS Guinea-Bissau GNB 200465 XSS Kenya KEN 2001 200465 XSS Madagascar MDG 2000 200465 XSS Mali MLI 1999 200465 XSS Mauritania MRT 2001 200465 XSS Niger NER 2002 200465 XSS Nigeria NGA 200465 XSS Rwanda RWA 2002 200465 XSS Senegal SEN 2002 2004/200565 XSS Sierra Leone SLE 200465 XSS Togo TGO 2002 2004

continued

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Data year


66 XRW Rest of World Albania ALB 2001 2004/200966 XRW Brunei BRN 2000 200466 XRW Croatia HRV 2002 2004/200766 XRW Cyprus CYP 2000 200466 XRW Fiji FJI 200466 XRW Macau MAC 2000 200466 XRW Malta MLT 2000 200466 XRW Mongolia MNG 2002 2004/200566 XRW Myanmar MMR 2002 200466 XRW Papua New Guinea PNG 1999 2004/200866 XRW Solomon Islands SLB 1998 2004

a Some countries are implementing reductions in bound tariffs beyond 2004.Source: As compiled from WTO database

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Appendix DA brief technical description of GTEM

GTEM is a dy n a m i c, mu l t i region, mu l t i s e c t o r, computable ge n e ral equilibrium model of thewo rld economy. ABARE has developed the model to specifi c a l ly add ress policy issueswith global dimensions. ABARE has developed GTEM from its MEGABARE model andthe static GTAP model, with a number of enhancements carried out to broaden ABA R E ’smodeling cap a c i t y. GTEM simu l ates the impact of policy ch a n ges or specific events on alarge number of economic variables of a particular national/regional economy, includinggross domestic product, consumption, production, tra d e, investment and greenhouse ga semissions.

The key structural features of GTEM are:

■ A computable ge n e ral equilibrium fra m ewo rk with a sound theoretical fo u n d ation basedon microeconomic principles and accounting for economic transactions occurring inthe global economy — the theoretical stru c t u re of the model is based on the optimis-ing behavior of individual agents (for ex a m p l e, fi rms and households), as rep resented bythe equation systems, the data and parameters.

■ A dynamic analytical fra m ewo rk ch a ra c t e rised by capital and debt accumu l ation ande n d ogenous population growth, wh i ch enables the model to account for tra n s a c t i o n sbetween sectors and trade flows between regions over time — as a dynamic model, itaccounts for the impacts of ch a n ges in labor fo rce and investment on a regi o n ’s pro d u c-tion capabilities.

■ R ep re s e n t ation of up to 68 regional economies (corresponding to individual countries orc o u n t ry groups) that are linked through trade and investment fl ows, allowing for detailedanalysis of the direct as well as flow-on impacts of policy and exogenous changes fori n d ividual economies — the model tra cks intra - i n d u s t ry trade fl ows as well as bilat e ra ltrade flows, allowing for detailed trade policy analysis.

■ A high level of sectoral disaggregation (defining up to 62 broad sectors), wh i chminimises likely biases that may arise from an undue aggregation scheme.

■ A demographic module that determines the evolution of a regi o n ’s population (andhence the labor supply) as a function of fe rt i l i t y, migration and mora l i t y, all distin-guished by age group and/or gender.

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ReferencesB u e t re, B., Rodriguez, G. and Pant, H. 2003, Data issues in ge n e ral equilibrium model-

i n g, Paper presented at the 47th Au s t ralian Agri c u l t u ral and Resource Economics SocietyConference, Western Australia, 11–14 February.

D i m a ranan, B. 2002, ‘Construction of the protection data base’, in Dimaranan, B. andM c D o u gall, R. (eds) 2002, Global Tra d e, Assistance, and Production: The GTAP 5 Dat aBase, Center for Global Trade Analysis, Purdue University, Indiana.

FAPRI (Food and Agri c u l t u ral Po l i cy Research Institute) 2004a, FAPRI Search abl eElasticity Dat ab a s e, Iowa State Unive rs i t y, Ames (www. fap ri . i a s t at e. e d u / t o o l s / e l a s t icity.aspx).

—— 2004b, FAPRI Search able Outlook Dat ab a s e, Iowa State Unive rs i t y, Ames(www.fapri.iastate.edu/tools/outlook.aspx).

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—— and Tsigas, M. 1997, ‘Stru c t u re of GTAP’ in Hertel, T. (ed.), Global Trade Analy -sis: Modeling and Applications, Cambridge University Press, Massachusetts.

R o b e rts, I., Buetre, B. and Jo t zo, F, 2002, A gri c u l t u ral Trade Refo rm in the WTO SpecialTreatment for Developing Countries, ABARE Report, Canberra.

R o s egrant, M., Agcaoili-Sombilla, M. and Pe rez, N. 1995, Global Food Projections to2020: Implications for Investment, 2020 Vi s i o n, Discussion Paper no. 5, Intern at i o n a lFood Policy Research Institute, Washington, DC.

——, Pa i s n e r, M., Meijer, S. and Wi t c ove r, J. 2001, Global Food Projections to 2020:E m e rging Trends and Altern at ive Future s, Intern ational Food Po l i cy Research Institute,Washington DC.

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ABARE CONFERENCE PAPER 04.6 Agricultural trade liberalisation

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