Distr. GENERAL   UNCTAD/DITC/TNCD/…. 25 November 2002 Original English

 

 

 

Sink or Swim?

Helping Small Island Developing States survive further  agricultural trade liberalization

 

 

 

 

 

 

 

Note

 

This study was prepared by Luca Monge-Roffarello and Michael Swidinsky of the Trade Negotiations and Commercial Diplomacy Branch and David Vanzetti of the Trade Analysis Branch, Division on International Trade in Goods and Services, and Commodities, UNCTAD. The opinions expressed in this study are those of the authors and do not necessarily reflect the views of the UNCTAD secretariat.

 

 

 

Acknowledgements

Wojciech Stawowy provided helpful assistance in converting specific rates to ad volorem equivalents.

 

 

 

TABLE OF CONTENTS

A.  Agricultural liberalization — A two-edged sword. 3

B.  Export dependent SIDS fear preference erosion. 5

Agricultural production and trade patterns of SIDS. 5

Preferential market access for SIDS. 7

Liberalization and the erosion of preferences. 11

C. Surviving agricultural liberalization: a quantitative assessment 14

The ATPSM modelling framework. 15

Current protection levels and rents. 18

Five alternative scenarios. 19

Results. 21

Some limitations. 24

D.  Conclusions. 25

References. 27

Annex 1. Some technical details concerning ATPSM... 29

Tables…………………………………………………………………………………………31

Figures………………………………………………………………………………………..41

 

 

A.  Agricultural liberalization — A two-edged sword

Small Island Developing States (SIDS)[1] face a number of structural problems that make them less competitive in agricultural trade than many other developing countries. The United Nations, and in particular UNCTAD, has been studying the specific problems of island developing countries since the 1970s with a view to sensitizing the international community to the distinctive needs of these countries, and more recently, to their specific vulnerability (Encontre 1999)[2].  To a greater extent than in most other developing countries, and notably as a result of acute limitations in the resource base and domestic market opportunities available to SIDS, the magnitude, structure and variability of trade constitutes the most important factors affecting the socio-economic performance and development capacity of SIDS. On average, the ratio of merchandise imports to GDP is 47 per cent higher in SIDS than in other small economies while the ratio of their agricultural trade (exports and imports combined) to GDP is the highest among all countries. Whilst larger countries can count on both their domestic and international markets to foster economic growth, SIDS have to rely on their export markets as the only avenue for reaping the benefits of economies of scale and capital accumulation (Streeten, 1993).

The constraints faced by SIDS’ countries hampering their competitiveness in international markets are well documented[3].  Factors such as small size, insularity and remoteness, and problems associated with the local environment all impose a burden on SIDS in achieving efficiency in production (Briguglio 1995). Because of their small land base and population, SIDS have limited ability to exploit economies of scale in agricultural production. Land scarcity, in particular, is a binding constraint on agricultural production making SIDS highly dependent on food imports. SIDS are net agricultural importers and depend on a small number of agricultural exports to pay for their food import bill.

Similarly, small size restricts SIDS capacity to diversify exports, and the need to secure certain scale economies in production, distribution and other economic activities, together with the possibility to take advantage of some export market opportunities have, to varying degree, led SIDS to specialize in a narrow range of agricultural products, exposing the country to instabilities of world markets.

Insularity and remoteness also give rise to problems associated with transportation of agricultural imports and exports. SIDS tend to import and export fragmented cargoes of agricultural products leading to high per unit shipping cost because SIDS do not have the flexibility of road transport in handling small shipments.

Additional costs might arise in some instances with the need to provide indivisible and expensive public goods to support agricultural production, which is bound to be particularly expensive given the limited production involved.  Higher costs means loosing competitiveness and in turn frustrating diversification.

Finally, environmental degradation (as well as proneness to natural disasters) and resource depletion may have serious implications for SIDS agriculture. Due to their small size the depletion of arable land from economic development has had a disproportional effect on agricultural production for SIDS. Limited freshwater, poor water management along with population pressures and an expanding tourism industry have led to water scarcity, jeopardizing SIDS agricultural production.

Offsetting these inherent disadvantages to some extent are various preferential market access arrangement enjoyed by many SIDS. These provide duty free access into specific developed country markets. The EU market for sugar is of greatest significance in this regard.

Liberalization is a two edged sword for SIDS. Maintaining and obtaining market access is very important for trade dependent economies. On the other hand, liberalization also provides additional competition, particularly if preferential access may be eroded. While some SIDS will swim with the tide of liberalization, others will need help to adjust. Against this background, the objective of this study is two-fold: first, to examine the pattern of SIDS' agricultural trade in the world market; and second, to provide a quantitative assessment of likely impacts of continued multilateral agricultural liberalization on SIDS, using UNCTAD’s Agricultural Trade Policy Simulation Model (ATPSM). Liberalization may erode the preferential access currently provided to SIDS.

In Section I the paper looks at the main characteristics of the SIDS agricultural sector, focusing on trade flows and constraints hampering SIDS’ competitiveness in agriculture. An overview of the preferential trading arrangements available to SIDS in their main markets and the actual importance of these schemes for SIDS exports are also provided.

Section II is dedicated to a quantitative assessment, through the use of the ATPSM model, of a number of scenarios derived from "modalities" as being discussed in the ongoing WTO negotiations on agriculture. The simulations show the potential impact of liberalization on prices, exports, government revenues, quota rents and overall welfare. While SIDS as a whole may be worse off under certain assumptions, policies to improve their position are examined.

 

B.  Export dependent SIDS fear preference erosion

Agricultural production and trade patterns of SIDS

The agricultural sector remains the backbone of the economies of many SIDS. It is characterized by a combination of large-scale commercial production of cash crops and a relatively small sector that produces food crops primarily for local consumption. The most important food crops grown are starchy staples, mostly root and tuber crops. Rapid urbanization has lead to starchy staples being replaced by imported cereals (FAO, 1999a).

Annex I. and Annex II. provide trade statistics by country.  The agricultural trade balance of selected SIDS is shown in Table 1. The import-to-export ratio differs greatly between SIDS (see Annexes for countries break-down), but as a group, SIDS are net agricultural importers – for every $1 exported, SIDS import $1.10.  Atlantic Ocean SIDS have the highest import-to-export ratio, while Pacific Ocean SIDS are net agricultural exporters.

Table 2 provides the top 5 agricultural import/export products by the degree of product concentration of SIDS in agricultural trade.

SIDS import a wide variety of agricultural products, particularly cereals, meats, dairy products, animal and vegetable fats. These agricultural imports consume 20 per cent of SIDS total export earnings. For some SIDS their agricultural import bill exceeds total export revenue – for example Cape Verde 240 per cent, Comoros 197 per cent, Haiti 117 per cent and Tuvalu 109 per cent.

Table 3 compares the relative importance of agricultural trade of SIDS with that in other country groups (developed, developing, and LDCs).  As exporters, SIDS' agricultural exports are concentrated on a number of products, including raw cane sugar, coffee, cocoa and coconut.  In many SIDS, these few agricultural products are the main source of export earnings.  On average, agricultural exports (imports) by SIDS account for 24 per cent (14 per cent) of their total merchandise exports (imports), showing a considerably higher dependence of their trade on the agricultural sector than the developing country average.  In fact, this trade pattern of SIDS is remarkably similar that in least-developed countries (LDCs). In the case of Sao Tome Principe over 90 per cent of agricultural export earnings are derived from cocoa alone. 

Apart from the concentration of the type of exported products, SIDS' agricultural exports also show a concentration of the destinations, further increasing SIDS' exposure to external shocks.  As shown in Table 4, the European Union receives more than half of the total SIDS agricultural exports, and it is the most important market for African SIDS accounting for 87 per cent of their agricultural exports.  The Pacific SIDS export around 65 per cent of their agricultural products (largely from Fiji and Papua New Guinea) to the European Union notwithstanding the geographical distance.

Similarly, the United States and Canada (though to a much lesser extent than the European Union) are important markets, receiving 29per cent of the SIDS agricultural exports. The Caribbean islands sell up to 40per cent of their agricultural exports to these markets, ranging from 50per cent in the case of Jamaica to 20per cent for other smaller Caribbean Islands.

Japan captures only 3per cent of total SIDS agricultural exports, but it has become an important market for the Pacific SIDS, absorbing more than 6per cent of their exports. This figure is substantially greater than the SIDS exports to(i) Australia and New Zealand combined (despite the existence of a regional trade agreement (SPARTECA) between most Pacific SIDS and these two countries); (ii) Mexico; or (iii) the whole of the South-Eastern Asia region.

Preferential market access for SIDS

The high geographical concentration of SIDS exports in the European Union and the United States, coupled with a high level of product specialization, is probably due to the provision of non-reciprocal preferential market access to their products, stemming from historical trade relationships with these countries. 

Preferential market access, in terms of tariff advantages and/or preferential quota, are important for SIDS agricultural exporters for two reasons.  First, a preferential margin may provide substantial "quota rents" to SIDS exporters.  Second, preferential margins, where substantial, can compensate for a general lack of price competitiveness of agricultural exports from SIDS vis-à-vis low-cost exporters competing in the same markets.

This section provides an overview of preferential market access granted by the Quad countries to SIDS agricultural exports, and the values of such preferences.      

European Union

Being the largest market for the SIDS agricultural exports, the European Union grants two preferential trading arrangements that are particularly important for SIDS: (i) the EU/ACP Cotonou Partnership Agreement,[4] signed in 2000 between the European Union and 77 African, Caribbean and Pacific (ACP) States (31 of the 77 ACP countries are SIDS[5]); and (ii) the "Everything But Arms" (EBA) initiative in favour of products originating in LDCs (10 of the 49 LDCs are SIDS) under the aegis of the EU scheme of Generalized System of Preferences (GSP).

The Cotonou Partnership Agreement, which provides for an eight-year rollover of the previous trade preferences granted under Lomé (with minor improvements), grants SIDS beneficiaries with duty-free access for most of their agricultural products[6], except for a limited number of agricultural products to which only a tariff reduction is granted.  For SIDS, particularly important are the three protocols on bananas (affecting mostly the Windward Islands), sugar (Fiji, Mauritius, Barbados, Jamaica, Trinidad and Tobago) and rum (Caribbean SIDS) – those products alone account for 69per cent of SIDS total exports to the European Union.

The Cotonou Agreement creates a considerable level of preferential tariff margin not only over applied MFN rates but also over most GSP rates (excluding the EBA).  Table 5 shows that, for those products whose average MFN rates are above 20 per cent (accounting for almost a half of SIDS exports[7] - largely sugar and bananas), SIDS agricultural exports to the European Union receive preferential margins of 25 percentage points against MFN rates and 15 percentage points against GSP rates. 

The EBA provides LDCs with a duty-free treatment to all agricultural products (except bananas, rice and sugar until 2007), including very sensitive products such as beef, dairy products, fruit and vegetables (fresh as well as processed), cereals, starch, vegetable oils,  confectionary, pasta and alcoholic beverages.[8]

For those LDC-SIDS, the EBA has now made the EU GSP a more favourable scheme than the Cotonou preferences in terms of tariff treatment, product coverage and preferential tariff margins. The EBA initiative has also imparted greater stability to EBA-GSP preferences for LDCs, as the EU undertook to maintain this special preferential treatment for an unlimited period of time, exempting such treatment from the periodical reviews of the basic GSP scheme.

The United States

The US recently renewed its GSP programme (applicable until 2006), which provides duty-free access for 5000 tariff line items to over 100 beneficiary countries and territories.  The GSP programme covers agricultural and fishery products that are not otherwise duty-free or are subject to tariff quotas/ceilings. An additional 1783 lines are added to the list of eligible products for LDC recipients. 

The recently approved USA Trade and Development Act of 2000 has expanded the preferences granted to Sub-Saharan Africa under the African Growth and Opportunity Act (AGOA),[9] as well as to the Caribbean Basin under the Caribbean Basin Trade Partnership Act (CBTPA).

The AGOA beneficiary countries (including SIDS such as Cape Verde, Sao Tome' and Principe, Mauritius and Seychelles) now receive a “super GSP”,[10] i.e. a duty-free access for a wider range of products than the “normal” GSP programme.[11] 

To 24 beneficiary countries of the Caribbean Basin Initiative,[12] most of which are SIDS, the CBTPA provides trade preferences similar to those given under the AGOA.  It also provides NAFTA-equivalent tariff treatment for certain items previously excluded from duty-free treatment under the CBI program (e.g. canned tuna).  The NAFTA-parity is provided with a view to partly offsetting the negative effects in term of trade and investments diversion experienced by these countries since the entry of Mexico into NAFTA[13].

Under these preferential schemes, approximately 60 per cent of SIDS exports (which include products such as cigars, beer, alcohol and certain food preparations) enjoy preferential margins of on average 4.2 percentage points over corresponding MFN rates.  Preferential tariff margin increases – up to average 35 percentage points - as MFN tariff increases.  However, these large tariff margins apply only to a small share (6 per cent) of the total SIDS agricultural exports. It was not possible to calculate preferential margins for some 14per cent of SIDS exports to the US, largely sugar, as MFN tariffs are given in non-ad-valorem technical rates and whose ad-valorem equivalents (AVEs) could not be calculated.[14].

Canada

Canada provides two distinct preferential market access regimes that are of immediate relevance to SIDS agricultural exports: the Generalized Preferential Tariff (GPT) and the CARIBCAN or Commonwealth Caribbean Countries Tariff (CCCT).  The GPT, which is equivalent to the GSP, grants reduced tariff rates or duty-free access to 184 beneficiary countries and territories, including all SIDS.  In addition to the general GPT, LDCs receive duty-free market access to an additional 570 tariff lines. A further expansion of the preferences to LDCs is envisaged to come into effect by January 1, 2003, which will allow for duty-free and quota-free access for all but a number of "sensitive" products[15].

The CARIBCAN provides most Caribbean SIDS[16] with duty-free market access for a large number of products, including all agricultural products.  However, preferential tariff margins on those products is generally low as corresponding MFN tariffs are already low - MFN duties on more than 53 per cent of SIDS agricultural exports are already zero. As these exports consist mainly of fresh fruits and vegetables, the Caribbean exporters seem to benefit more from a geographical proximity than from the tariff preferences they receive.  Summing up, for the majority of agricultural exports (some 94per cent, including those exports already receiving MFN duty-free), SIDS receive "empty preferences", either because of zero MFN duties or because similar preferential treatment is given to other developing countries. 

Japan

Finally, trade preferences for SIDS (as for other developing countries) are made available under the Japanese GSP scheme, which was recently reviewed and extended for a new decade, until 31 March 2011.[17]  The extent of the product coverage and tariff treatment provided to beneficiary countries varies considerably among agricultural products.

Preferential GSP tariffs applicable to developing countries range from duty–free to 20 per cent reduction in MFN duties.  LDCs beneficiaries enjoy duty-free entry for all products covered under the GSP scheme plus an additional list of products.  Preferences to LDCs has been improved by increasing the number of tariff items for duty-free and quota-free access specifically available to all 49 LDC exports as long as they request them.[18]

Despite the existence of the GSP scheme, the overwhelming majority of SIDS agricultural exports enter the Japanese market on a MFN basis - 66.3per cent of SIDS exports, most importantly coffee and copra, enter Japan at zero MFN rates, while for another 31.5per cent of exports (including sugar, pumpkins and rum), preferences are simply not available.  This implies that the impact of further agricultural trade liberalization, while being rather limited on SIDS preferences, might result in new trade opportunities for all those SIDS products still affected by high MFN duties.  

Liberalization and the erosion of preferences

Further liberalization in agriculture will affect the value of preferential market access currently provided to SIDS. The impact of liberalization will depend on a number of factors. First, the impact of the erosion of preferences depends on the initial insurability provided by the preferential treatment vis-à-vis competitions with other exporters.  In terms of a geographical grouping, further MFN tariff cuts may result in a much faster erosion, if not elimination, of preferential tariff margins available to the Caribbean island countries than those to other SIDS, as the preferences received by the Caribbean SIDS on some 70 per cent of their exports are empty.  However, the impact of the preference erosion on the trade flows of the Caribbean SIDS would be on average less dramatic as they are already exposed to a certain degree of competition with other developing country exporters either on a MFN basis or within a GSP scheme of an importing country.  Conversely, the African SIDS enjoy the highest level of preferences in terms of preferential margins and product coverage, thus are subject to relatively lower level of the erosion preferences following MFN tariff cuts. They will, however, loose quota rents by the reduction of outquota tariffs. Further, should these preferences be considerably reduced as a result of the negotiations on agriculture or be legally challenged by other WTO member(s),[19] adjustment costs arising from the preference erosion to these preference-dependant countries may be significant, as they have been rather sheltered against world competition.

Second, whether preferential tariffs are "linked" or "de-linked" to MFN rates may result in different impacts upon the values of preferences after MFN tariff cut.  In the case of the ACP-EU preferences, there are still a number of products whose preferences are expressed as a percentage of MFN rate (and thus linked to MFN rates).  If the initial MFN rates are sufficiently high, further MFN cuts would reduce the nominal preferential margins of the ACP preference only marginally.  Beneficiaries of such preferences are more likely to retain tariff advantages not only over MFN tariffs but also over other preferences providing less extensive degree of market access treatment. This might be the case of various products from palm, cigars, fruits and vegetables (e.g. oranges, onion, garlic, carrots, peaches, and cabbages), although SIDS' exports of the latter items are currently limited. Where preferences to SIDS are de-linked from the corresponding MFN rates as in the case of the GSP scheme of the US, the only difference among various preferential schemes is the extent of the product coverage rather than the preferential margins provided. In this case, MFN tariff cuts will inevitably reduce SIDS preferential margins.

Third, the recent initiatives undertaken to provide better market access for LDCs and countries in the Sub-Saharan African Region have yet to fully materialize. As they are creating additional and substantial preferential margins for certain SIDS and for certain products, the negative impact in terms of preferential margins coming from further trade liberalization might be somehow mitigated.  

Finally, although wide, current preferences could be still expanded. For example in the case of the European Union, the ACP-EU preferences are quite limited for agricultural and processed products that are subject to the Common Organization of the Market (listed in the "Joint Declaration concerning agricultural products")[20] and for products that are subject to specific rules under the Common Agricultural Policy.  Many of those sensitive products (namely meat and diary products, cheese, tomatoes, mandarins and some cereals) are subject to a combined tariff which is made up with an ad-valorem component and a specific-rate component.  Preferential market access for those products normally takes the form of an elimination of the ad-valorem component and a reduced level of a specific-rate component, whose ad-valorem equivalent can go up as high as 80 per cent. 

Similarly, for certain categories of processed agricultural products of HS chapter 4 (milk and milk products), 17 (sugar and sugar confectionery), 18 (cocoa and cocoa preparations), 19 (processed foodstuffs), 20 (beverages) and 21 (miscellaneous edible preparations), the European Union maintains a system of a technical tariff which includes the so-called agricultural component: i.e. a combination of ad valorem and specific duties that may vary according to the presence in different percentages or quantities of certain ingredients such as sugar, starches or glucose and milk fat or proteins contained in the final products. However, it is largely the specific component that constitutes the bulk of the protection and not the ad valorem part.

In addition, around 15 products, mainly fruits and vegetables as well as some processed products like fruit juices, are subject to the entry price system (EPS).[21]  Neither ACP nor GSP beneficiary countries are granted special preferences for the products subject to the EPS.[22]  The Cotonou Agreement foresees to ameliorate ACP preferences[23] during the transitional period, and the European Commission has already tabled a proposal for improving the current market access conditions given to the ACP countries.[24]  

 

C. Surviving agricultural liberalization: a quantitative assessment

It is anticipated that the ongoing WTO negotiations on agriculture will result in further reductions, if not an elimination, of tariffs and trade-distorting subsidies provided to agricultural products in the world.  A recent UNCTAD study estimates that a worldwide reduction of 50 per cent in all agricultural tariffs brings about an aggregate welfare gain of $21.5 billion to the world.[25]  However, the distribution of the welfare gains is likely to be uneven among regions.  The same study suggests that welfare gains to some group of developing countries, particularly those in Sub-Saharan African and Latin America that are dependant on non-reciprocal preferential treatment, may be substantially less than gains to regions including Oceania, South East Asia and North Africa. 

Insignificant welfare gains, or indeed losses, of multilateral agricultural liberalization to SIDS may be due to (i) a rise in agricultural prices induced by liberalization, and (ii) the erosion of preferences. 

It is thought that agricultural liberalization would raise world prices of temperate agricultural products more relative to prices of tropical products, leading to an increase in food import bills for SIDS which import temperate products and export a narrow range of tropical products. At the same time, as MFN tariff cuts reduce the margin of preferences, importers are likely to take supplies from low cost countries. For example, assuming exporters of sugar to the European Union are receiving EU prices, any lowering of those prices will make other exporters, e.g. Brazil, more competitive. 

This section examines likely impacts of agricultural trade liberalization on SIDS under different liberalization "scenarios", with a view to identifying liberalization "modalities" that would at least "compensate" for possible negative impacts from liberalization, if not creating welfare gains. 

The ATPSM modelling framework

To assess the potential impacts of agricultural liberalization on SIDS, UNCTAD’s Agricultural Trade Policy Simulation Model (ATPSM) Version 1.1 is used in this study.[26] ATPSM is a partial equilibrium model that can be used to evaluate agricultural trade policy changes in the main areas covered by the URAA – market access, export subsidies and domestic support. The model distinguishes between bound and applied tariffs, as well as between inquota inquota  and outquota tariffs on products under tariff rate quotas (TRQs).  It can be used to assess the impact of policy changes on quotas rents forgone and received.  As quota rents are an important contributor to SIDS agriculture, this feature of the model is desirable in applications discussed here.

Unlike a general equilibrium model, ATPSM is confined to the agricultural sector and does not account for interactions with other sectors of the economy. As a result, capital and labour used in agricultural production cannot be reallocated across non-agricultural sectors in response to a shock. It is assumed that this limitation will have little bearing on the empirical results since SIDS have few alternative sectors for resources to shift into from agriculture.

ATPSM can simulate and evaluate the various agricultural trade policy changes that may be suggested for or in the WTO negotiations on agriculture, such as: 

-                                             MFN (bound or applied) and/or TRQ inquota inquota  tariff cuts;

-                                             Change in TRQ quantities;

-                                             Reductions in trade-distorting domestic support (e.g. market price support); 

-                                             Reductions in export subsidies; and

-                                             Different percentage changes in all the above policies applied to selected countries or country groups and commodities.

The ATPSM model produces five categories of economic estimates – (i) volume changes in production, consumption, imports and exports; (ii) trade value changes (changes in export, import and net trade revenue); (iii) welfare changes (changes in producer surplus, consumer surplus and net government revenue); (iv) price changes (at world, wholesale and farm gate levels); and (v) changes in tariff quota rents – in 161 countries including 25 of the 32 SIDS members[27] for the agricultural commodities shown in Table 7.  

ATPSM is both simple and complex. Its simplicity derives from linear demand and supply curves. The complexity follows from the policy detail in the model.  For this reason it is necessary to explain in the next section how the model works.  Next we look at the initial data, particularly the distribution of rents. Then we postulate some likely liberalization scenarios, look at the results and draw some implications.

Quota rents

The Uruguay Round led to the establishment of tariff rate quotas (TRQs) - a two-tier tariff system based on import quotas. Imports below the quota level are levied at rates that are substantially lower than the corresponding out-of-quota (or outquota) MFN tariff rates.  During the Uruguay Round (UR), the quota quantities were either set as 3 per cent growing to 5 per cent of the level of domestic consumption observed during the 1986-1988 base period, or they were based on historical trade flows.  Not all countries utilize the TRQs - only 43 WTO member countries established the total of over 1370 TRQs.

The introduction of a two-tier tariff system created a new category of economic effects, the tariff quota rents. A quota rent is the difference between the outquota and inquota inquota  tariffs times the value of the quota.  This is illustrated in the figure 3.  Assuming the quota, q, is full and the domestic price reflects the higher outquota tariff, t2, exporters with quota can supply goods over the lower tariff, t1, and receive the higher domestic price. Once the quota is filled, outquota imports are taxed at the higher tariff rate and no further rents are generated. Clearly, reduction in outquota tariffs reduces the quota rent.

An important question is the distribution of the rents between exporters, processors, distributors, taxpayers and consumers, on which the effects of liberalization largely depend. Rents may be captured by the government by auctioning rights to import or export, but often they accrue to other groups depending on the means by which quotas are allocated.  There is, however, no one uniform method for the TRQ administration, thus there is no general rule on how quota rents and tariff revenues will change with trade liberalization.  In this study, it is assumed that all the quota rents in the sugar market accrue to the producers in exporting countries.  For the remaining products, the rents are assumed to be shared half and half between exporters and importers.  The rents not captured by exporters are assumed to eventually accrue to government revenue in the importing country, instead of being transferred to consumers in the importing countries. 

To estimate the actual size of a quota rent, it is necessary to have observations of global quotas, bilateral quotas, inquota and outquota tariff rates, world market prices and imports. To determine how the rents are allocated between countries requires some judgment.

 The size of the global quotas (i.e. the total level of imports at the lower tariff level) are obtained from annual notifications made to the WTO by TRQ-using countries, but these notifications do not always provide a breakdown of quotas among different exporting countries.  The model uses bilateral trade flows to estimate the distribution of global quotas among countries.[28] 

The final key assumption relates to the quota fill rate (i.e. the ratio of actual imports to the total TRQ quantity of the product concerned).  Ideally, the quota fill rate should determine the domestic price so that if the quota is unfilled, domestic prices should be determined by the inquota tariffs, and prices should be high only if the quota is filled or overfilled.  However, it is often observed that quotas are unfilled but domestic prices are nonetheless high.  This may be because administrative constraints prevent the quotas being filled.  More to the point, countries with high domestic prices are unlikely to be prepared to see them eroded by a shift in the supply of imports.  As a result the assumption here, the outquota tariffs (or possibly the applied tariffs) determine the domestic market price.  This implies that global quotas should not exceed imports, and quotas are reduced to the level of imports where the data suggests this is the necessary.  The calculation of tariff revenues and rents in the model is based on these assumptions.

The assumptions made above imply that changes in inquota  tariffs and TRQ quantities will not have price and production quantity effects, as these instruments are not binding.  They do, however, change the distribution of rents.

Data

Data on production quantity (2000) are compiled from FAO supply utilization accounts (see FAOSTAT).  Price data are from the FAO Yearbooks, using an average of 1996-98. Parameters on elasticities and feedshares are also provided by FAO.  These are based on a trawling of the literature and are not econometrically estimated specifically for the model.  Inquota  tariffs, outquota tariffs and the size of the global quotas as notified to the WTO are obtained from the Agricultural Market Access Database (AMAD)[29] and aggregated to the ATPSM commodity level using a simple average wherever trade exists. Specific tariffs are converted to ad valorem equivalents based on unit values calculated for each country at the Harmonized System (HS) six-digit level.  Data on trade-distorting domestic support and export subsidies are derived from the notifications submitted to the WTO.  Bilateral trade flow data for 1995, which were used to allocate global quotas to individual exporting countries, are provided by UNCTAD. The UNCTAD TRAINS database is a source of applied tariff information which determines whether cuts in bound rates are effective.

The main drawback to using ATPSM for this study is that it does not include information on bilateral tariffs (e.g. preferential tariff rates) and thus cannot capture trade diversion and trade creation effects from changes in preferential arrangements.  However, this is consistent with the assumptions that the quotas are filled and that changes in rents do not change production.

 

Current protection levels and rents

A good indicator of the on-going level of border protections is global tariff revenues and rents, as these are the product of the level of protection (i.e. the higher the MFN tariffs, the greater the tariff revenues and rents for a given import flow) and the trade flows. The base period data of these global indicators are shown in the first two columns in Table 8.  Across commodities, temperate goods are subject to relatively higher level of border protection in developed countries than tropical products (with the notable exception of sugar and bananas).  Developing countries, however, may levy substantial tariffs on tropical products.

Also shown in the table are the initial values of three variables important to SIDS: tariff revenues; export revenues and rent received.  It is immediately apparent that sugar is the key commodity of interest to SIDS, capturing more than 50 per cent of the total export revenues and 90 per cent of rents received. Sugar is followed in importance by vegetable oils (copra), coffee, cocoa and bananas.  The bulk of the SIDS export revenues and virtually all the quota rent received emanates from the EU and the US sugar policies.  The major supplier of the EU sugar imports (1.3 million tonnes) is Mauritius with a quota of 487,000 tonnes. The United States also imports 1.1 million tonnes of sugar under a quota from developing countries plus Australia, the only developed country exporter of cane sugar.  China has imports of 0.6 million tonnes, the bulk of it from Cuba, Thailand, India and Australia.

Multilateral trade liberalization will influence the level of these three variables – tariff revenues and rent received are most likely to be reduced, while export revenues may improve.  The next section examines the extent of such impacts and how they vary according to different trade liberalization scenarios. 

Five alternative scenarios

Taking into account the proposals and discussions made so far during the ongoing WTO negotiations on agriculture, the following five scenarios were selected for examination:

(1) "Ambitious": 

Across-the-board reductions in outquota (MFN) bound tariffs using the Swiss formula with a coefficient of 25, and total elimination of export subsidies and production-distorting domestic support.

 

(2) "Conservative – the UR approach":

A 36 per cent cut in outquota bound tariffs, 36 per cent reductions in export subsidy spending and 20 per cent cut in trade-distorting domestic support in developed countries. Two thirds of these reductions in developing countries and no reductions in least developed countries.

 

(3) "Tariff50":

A 50 per cent cut in outquota bound tariffs in all countries.

 

(4) "Preferential":

Scenario 3 plus removal of inquota  tariffs on SIDS exports under quota.

 

(5) "Compensatory":

Scenario 3 plus removal of all tariffs on all SIDS exports.

 

Scenario 1, consisting of elements that have been proposed to the WTO negotiations on agriculture by major agricultural exporters such as the United States and the Cairns Group members, will lead to substantial agricultural liberalization.  A "Swiss Formula" is designed in such a way that it eliminates tariff peaks and substantially reduces tariff escalation.[30]  A coefficient of 25 (as proposed by the United States and the Cairns Group) sets an effective tariff ceiling at 25 per cent, and achieves very deep cuts indeed - under this approach, tariff rates of 100 per cent, 200 per cent and 300 per cent are reduced to 20 per cent, 22 per cent and 23 per cent respectively. 

Scenario 2 is almost a replica of the liberalization approach employed during the Uruguay Round (UR).  The only difference is that, in this scenario, a linear cut of 36 per cent applies to the tariffs across all products, unlike the actual UR approach where tariffs on sensitive commodities were reduced by the minimum reduction rate of 15 per cent so long as an average cut of 36 per cent across products was achieved. 

Scenario 3 focuses purely on the impact of tariff cuts.  Reductions in MFN bound tariffs (putting aside proposals to make reductions from the applied tariffs) are likely to have the greatest impact on SIDS, through the erosion of preferences causing reductions in quota rents.  The scenario 3 is also a reasonable middle ground between the scenario 1 and 2, and will serve as a benchmark for assessment of the impact from the following scenarios 4 and 5.

 Scenarios 4 and 5 are aimed at assessing whether the SIDS could be compensated for the losses stemming from preference erosion by changes in other policy variables, such as the size of the inquota  tariffs or the TRQ quantities.  Scenario 4 will look at the likely impact of elimination of inquota  rates for SIDS' exports under TRQs.  Scenario 5 will look at a situation of elimination of all outquota (MFN) rates applicable to SIDS, which is equivalent to an expansion of TRQs only to SIDS.  As the quota rents are determined by (i) the difference between the inquota  and the outquota tariff rates and (ii) the quota quantities, changes in one of the variables (e.g. global reductions of MFN tariffs) may possibly be offset by changes in the others (e.g. SIDS-specific expansion of TRQs). 

Results

In order to interpret the outcome of the simulations, we need to take into account the following elements.  First, reductions in outquota tariff rates do not necessarily mean that the gap between domestic and world prices is reduced by 50 per cent.  In cases where applied tariffs are below the bound outquota rates, a 50 per cent cut in the outquota tariffs may result in a less than 50 per cent cut, or even no change at all,  in the applied rates.  Second, EU sugar and dairy production is assumed not to be responsive to changes in prices due to the existence of the production quotas for those products.

Prices

The impact on world prices for the first three scenarios is shown in Table 9.  The price changes are correlated with the level of distortions removed.  That is why the "ambitious" scenario shows relatively greater price rises on products that are subject to high levels of tariffs, trade-distorting domestic support and/or export subsidies (e.g. dairy products, wheat) than the other two approaches.  The model estimates similar levels of price changes for "conservative" scenario and "tariff-50" scenario.  As anticipated, the results shows that prices of tropical products (e.g. sugar, copra oils and bananas) increase less than temperate products, which implies a decline in the terms of trade facing the majority of SIDS. 

While price rises are indicative of the level of distortions, of greater interest to policy makers in SIDS are the impact of liberalization on export revenues, tariff revenues, changes in quota rents and an overall welfare impact. The welfare impact is calculated based on the changes in (i) consumer surplus, (ii) producer surplus, and (iii) government revenues.  The estimation of these data are shown for SIDS and for the world in Table 10. 

Export revenues

The comparison of estimated export revenues across different scenarios suggests that export revenues increase in proportion to the level of market access improvement.  The increase in export revenues under the "ambitious" scenario ($40.4 billion) is almost three times greater than the estimated increase under the "conservative" scenario.  

Under the "tariff-50" – or the benchmark – scenario, export revenues to SIDS rise from $2.1 billion to $2.4 billion, an increase of $166 million (or 8 per cent).  Sugar ($69 m), other tropical fruits ($ 19 million), citrus ($16 million) and bananas ($17 million) are the major beneficiaries.  Scenarios 4 and 5 do not show changes in export revenues from the benchmark, due to the assumption that changes in quota rents alone do not affect the supply decisions of the producers of exported products concerned (hence the level of export quantity remains the same).  This assumption is reasonable for small changes in quota rents.[31]   

Tariff revenues

Tariff revenues are determined by the combination of the tariff rates, import quantities and import prices.  The simulation results in Table 10 show a wide variation in the degree of changes in tariff revenue across different scenarios. Concerning tariff revenues at the global level, the "ambitious" scenario will lead to the smallest losses, largely because tariff revenues forgone are offset by reductions in domestic support and export subsidies.  The continuation of spending on these government subsidies result in substantial losses in government revenues in the "conservative" and benchmark scenarios.  

Looking at scenario 4 ("preferential") and 5 ("compensatory"), reducing inquota  or outquota tariffs on SIDS' exports involves losses in tariff revenues for importing countries equaling the gains in quota rents received by SIDS exporters.  In the "compensatory" scenario, importing government revenue losses are $187 million over and above the $4.18 billion in the benchmark scenario.  The magnitude of a global loss in tariff revenues (or an increase in quota rents for SIDS) is determined by the degree of rent capture.  It is assumed in this study that half the loss in tariff revenues (i.e. quota rents) for all products except sugar is clawed back by the importing government.  These revenue losses effectively arise from transfers between taxpayers and producers and do not involve any efficiency gains or losses.  Concerning SIDS, the benchmark scenario leads to a 13 per cent reduction of tariff revenues from the estimated initial level of $425 million to $369 million. 

Quota rents

 Global quota rents in the agricultural sector represented in the database are initially estimated to be around $9.7 billion prior to any policy change.  In total, SIDS receives $285 million in the initial database, of which $272 million is from sugar (Table 8). The rents are reduced by $166 million under the benchmark scenario, of which $160 million can be attributed to sugar. Some $16 million of this loss is offset by allocative efficiency gains (due to tariff reductions in SIDS themselves) and increased export prices (due to tariff reductions in other countries).

A comparison of the changes in SIDS' quota rents under the "preferential" scenario with the benchmark scenario suggests that eliminating inquota  rates for all SIDS' inquota  exports does not fully offset the effect of outquota tariff reductions.  The additional quota rent of $88 million over the benchmark level can be attributed to sugar ($82 million). Much of this accrues to Cuba which is the major supplier to China.  The quota gains may be overestimated as the model does not take into account preferential tariffs provided by major markets (e.g. the European Union).  The initial EU inquota  tariffs are 13 per cent on bananas and 2.3 per cent on sugar (on which the inquota  tariff revenues of the EU is calculated), but almost all SIDS inquota  exports of sugar and bananas already receive duty-free access under the EU/ACP Cotonou Partnership Agreement.  However, China imports 0.6 billion tonnes over an inquota tariff of 15 per cent. This accounts for much of the increase in quota rents under the preferential scenario.

The "compensatory" scenario, on the contrary, results in a $83 million increase in the quota rents transferred from the initial level, and $249 million increase from the benchmark result.  That is to say, removing tariffs to all SIDS exports within and out of quota (which is equivalent to increasing the size of global quotas to accommodate all of SIDS' exports) is more than sufficient to offset the $166 million losses in quota rents resulted from a 50 per cent cut in MFN tariffs in importing countries. 

Welfare

Putting together the various changes in prices, exports, tariff revenues and quota rents, the greater the degree of liberalization, the greater are the welfare gains to the world as a whole (the scenarios 4 and 5 do not change global welfare from the benchmark).  A greater global welfare increase under the "tariff-50" (benchmark) scenario than the "conservative" scenario arises from gains by developing countries as a whole, as more substantial tariff cuts by developing countries under the benchmark case increases largely due to consumer surplus increases in those countries.  However, the impact of liberalization on SIDS appears to be negative – welfare gains for SIDS are expected only under the compensatory scenario. 

Table 11 provides a breakdown of welfare impacts of each of the five scenarios across different groups of countries.  It is apparent from the table that gains from agricultural liberalization to SIDS are more limited compared to other groups of countries listed.  Under the "ambitious" scenario, for instance, only SIDS are expected to make welfare losses while all other groups gain.  Under the "conservative" scenario, in which export subsidy reductions are relatively important, LDCs will also experience a welfare loss due to a combination of higher import prices and the absence of efficiency gains from liberalization (LDCs are exempted from making reduction commitments), though they will make welfare gain of $800 million in other scenarios.  Welfare gains to a group of developing country agricultural-importers appear to be modest – they experience gains only in the case of the "ambitious" scenario, whereas in other scenarios import price rises and losses in tariff revenues lead to welfare losses.  Extending compensation to the SIDS, (scenario 5) tends to make non-SIDS slightly worse off.  The major costs is borne by the developed countries which provide the compensation through extended preferential access, predominantly the European Union and the United States.

A breakdown of the welfare impact under the benchmark scenario - for individual SIDS by commodity - is presented in Table 12.  The largest welfare loss is anticipated to Mauritius, Jamaica and Fiji.  The major losses by commodity occur in sugar (due to loss of quota rents) and wheat, dairy products and meat (due to increases in food import prices). 

The importance of quota rents to the welfare figures highlights the assumption about their distribution. In an alternative simulation, where all rents are assumed to accrue to importers, SIDS welfare under the benchmark scenario rises by $16 million rather than falling by $166 million.

Some limitations

The major limitation in this analysis is the lack of knowledge of the distribution of quota rents. This is unfortunate, as these have a large bearing on the overall results for SIDS.  Another limitation is that this model is likely to overestimate the amount of quota rents accruing to the world in general, due to the assumption that quotas are effectively filled and that outquota or applied tariffs rather than inquota  tariffs drive domestic prices. Rents accruing to SIDS in particular may be further overestimated as the model does not take into account various reciprocal or non-reciprocal preferential tariffs most SIDS receive in major markets for their agricultural exports.  A final consideration is the assumption that producers don't respond to changes in rents, which further implies no trade diversion. These are reasonable for small policy changes but less so for elimination of tariffs. Preference erosion is expected to benefit low-cost producers from liberalization of markets in which they were excluded from preferential market access (e.g. Brazilian sugar in the EU market).

D.  Conclusions

In spite of these limitations, several implications can be drawn from the results.

First, preferences provide significant benefits to some SIDS members and trade liberalization will lead to some erosion of these preferences. This will have a significant impact in some cases, particularly for those SIDS currently enjoying quota rents. Sugar and banana producers are likely to be the sectors most affected. Yet, the magnitude of the overall impact depends on the chosen scenarios, being the highest in the "Ambitious" scenario and the lowest in the "Conservative " scenario.  

Second, the results of the simulations suggest that there is scope for these countries to be compensated, if was considered desirable, in two distinctive ways.

 One possibility would be to provide inquota duty-free treatment for all those SIDS exports already benefiting from quotas. Although the gains are insufficient to compensate entirely for the rents losses stemming from the benchmark simulation (Tariff 50), they are nonetheless positive for SIDS. There might be, however, individual SIDS currently not capturing quota rents that may be inclined to favor liberalization as estimates indicate that if quota rents are ignored there are positive net benefits from improved market access and efficiency gains from domestic reform. Similarly, low cost SIDS producers may find themselves shut out of markets by the import quota system and may be favoured by the erosion of preferences.

Another avenue bringing significant benefits to (certain) SIDS would be to expand import duty-free quotas to cover all SIDS exports. According to the model estimates, this would entirely compensate for losses in the rents. Given the high degree of specialization by SIDS on a limited number of products, additional preferential quotas appear therefore to guard beneficiaries against the erosion of preferential tariff margins and quota rents. However, this assumes that beneficiary countries are capable of filling the additional quotas.

Tellingly, this particular scenario, that has been selected as a possible modality to compensate SIDS, would have no or very limited effects on the welfare gains of developing countries.   

Finally, compensation, if any, might be sought both within the WTO framework and bilaterally. In fact, given the high geographical concentration of SIDS exports in few markets, there may yet be scope for improving the effectiveness of non-reciprocal preferential market access via expansion of product coverage, expansion of quantitative limits on preferential market access or lowering preferential tariff rates, with a view to offsetting the impacts of MFN tariff cuts.

References

Briguglio, Lino. 1995. "Small Island Developing States and Their Economic Vulnerabilities". World Development. Vol. 23, No.9. pg. 1615-1632.

Cernat, L., Laird, S. and Turrini, A. Back to Basics: Market Access Issues in the Doha Agenda, UNCTAD, 2002.

Commonwealth Secretariat. Small States: Economic Review and Basic Statistics. Annual Series

Downes, A.S (1988) “On the statistical measurement of smallness: a principal component measure of size”, Social and Economic Studies 37(3), 75-96.

Encontre, Pierre. 1999 "The vulnerability and resilience of small island developing States in the context of globalization". Natural Resources Forum, 23 (1999), pp. 261-270.

FAO. 1999a. "Sustainable Production, Intensification and Diversification of Agriculture, Forestry and Fisheries in Small Island Developing States". Special Ministerial Conference on Agriculture in Small Island Developing States. Rome.

FAO. 1999b. "Trade Issues Facing Small Island Developing States". Special Ministerial Conference on Agriculture in Small Island Developing States. Rome.

Houck, James. 1992. "Elements of Agricultural Trade Policies". Waveland Press, Inc.

IMF, 2002. IMF Primary Commodity Prices. Actual Market Prices for Non-Fuel Commodities and Petroleum, 1997 – current. http://www.imf.org/external/np/res/commod/index.asp.

Lockhart, D. G.,  Drakakis-Smith, D., and Schembri, J. (1993) "The Development Process in Small Island States". Routledge, London.

OECD. 2001. "The Uruguay Round Agreement on Agriculture: An evaluation of its implementation in OECD countries". Paris.

Streeten, Paul. 1993. "The Special Problems of Small Countries. World Development". Vol. 21, No.2. pg.197-202.

Tangermann, Stefan. 2001. "The Future of Preferential Trade Arrangements for Developing Countries and the Current Round of WTO Negotiations on Agriculture". FAO Geneva Round Table on Selected Agricultural Trade Policy Issues. Discussion paper no.3.

UNCTAD (1997) "The Vulnerability of Small Island Development States in the Context of Globalisation: Common Issues an Remedies". Background Paper for Expert Group Meeting on Vulnerability Indexes for SIDS, New York December  1997.

UNCTAD. 2002. "Handbook on the UNCTAD Agricultural Trade Policy Simulation Model (ATPSM)". Version 1.1.

Wainio, John. et al. 2001. "Options for Reducing Agricultural Tariffs. in Agricultural Policy Reform in the WTO: The Road Ahead. USDA-ERS". Agricultural Economic Report Number 802.

Yamazaki, Fumiko. 1996. "Potential erosion of trade preferences in agricultural products". Food Policy. Vol. 21, No. 4/5. pg. 409-417.

Annex 1. Some technical details concerning ATPSM

Annex 1. Some technical details concerning ATPSM

The Agricultural Trade Policy Simulation Model (ATPSM) is a comparative static, determomistic, linear, partial equilibrium, global model with 36 commodities and 162 countries or regions. Technical specifications of the model are provided in this section.

Price determination

One principal characteristic of the model is that domestic prices are all function of the world market prices and the border protection or special domestic support measures. Thus, no data is provided about the domestic prices and no transaction costs (such as wholesale and retail margins) are taken into account. All protection measures are expressed in tariff equivalents.

A second characteristic is two way trade. In the ATPSM database a country is often an importer and exporter of the one (aggregated) good. To accommodate this feature of trade data, composite tariffs for determining the domestic consumption and production price are estimated. The technique chosen to derive the composed tariffs is to divide the volumes into three groups, imports, exports and production supplied to the domestic market (S_d).

First, a domestic market tariff (t_d) is computed as the weighted average of two trade taxes, the export subsidy rate (t_x) and import tariff (t_m), where the weights are export (X) and imports (M):

t_d = (X t_x + M t_m)/(M + X);

Then, a consumption (domestic market) tariff is computed as the weighted average of the import tariff (t_m) and the domestic market tariff (t_d), where the weights are imports (M) and domestic supply (S_d):

t_c = (M t_m + S_d t_d) / D;

Similarly, a supply (domestic market) tariff is computed as the weighted average of the import tariff (t_m) and the domestic market tariff (t_d), where the weights are exports (X) and domestic supply (S_d) plus the domestic support tariff (t_p):

t_s = (X t_x + S_d t_d) / S + t_p;

These calculations are applied both to the baseline and the final tariffs.

 

 

Model equations

 

The equation system for all countries esentially has four equations, specifying domestic consumption, production, exports and imports:

 

where D, S, X, and M denote demand, supply, exports and imports respectively,

^ denotes relative changes and  absolute changes,

P_w denotes world price, t_c denotes the domestic consumption tariff and t_s denotes the domestic production tariff,  denotes supply elasticity and  denotes demand elasticity, and i and j are commodities indexes and r is a country index.

 

By transforming , , and  and  to vectors with dimensions of 5832 (162 * 36) by 1, the equation system above can be simplified and solved by matrix inversion. Further details are available in UNCTAD (2002)[32].

 

Tables

 

Table 3.                        Importance of Agricultural Trade (year 2000)

Country Groups	Agricultural exports in total exports	Agricultural imports in total imports	Imports/ Exports Ratio in Agriculture	Ratio of agricultural exports to GDP (1999)*	Ratio of agricultural imports to GDP (1999)*
	%	%		%	%
Developed	6.8	6.5	1.1	1.1	2.9
Developing  (exc. LDCs)	7.2	6.7	0.98	2.7	7.0
LDCs	31.4	16.4	1.1	3.7	7.4
SIDS[33]	24.0	14.0	2.5	7.4	14.7

Note: trade information from UN COMTRADE, GDP data are taken from the World Bank's World Development Indicators; *Data on GDP only available for selected countries.

 

 

 

 

 

 

 

Table 4.                       Concentration of SIDS agricultural trade (%) (year 2000)

	All SIDS	African SIDS	Caribbean SIDS	Pacific SIDS
European Union	52.1	87.1	41.6	65.0
United States	27.1	5.2	37.6	8.2
Canada	1.6	0.8	2.3	0.1
Japan	3.1	1.8	2.4	5.8
Australia/New Zealand	0.7	0.1	0.3	2.1
Mexico	0.5	0.1	0.8	0.0
Southern-East Asia	2.6	2.0	0.3	9.4
Others	12.0	2.8	14.4	9.4
Regions in total SIDS exports (%)	100	10.90	65.37	23.73

 

 

 

European Union

(year 2000)	% in total SIDS exports	MFN Rate	GSP Rate	LDC Rate	ACP Rate	Pref. Margin 1   (MFN - GSP)	Pref. Margin 2 (MFN -ACP)	Pref. Margin 3   (=GSP- ACP)
MFN = 0%	14%	0	0	0	0	0	0	0
0% < MFN =< 10%	35%	6	3.8	0	0.2	2.6	6.1	3.5
10% < MFN =< 20%	2%	14.8	10	0	1.1	4.7	13.7	9
MFN > 20%	48%	39.9	19.2	0	10.3	10.4	25.1	14.7

 

 

 

 

Table 9.                        Preferential trading arrangements for SIDS in the QUAD

African SIDS

EU ACP: Cape Verde, Sao Tome' & Principe, Comoros, Seychelles, Mauritius GSP: as ACP +Maldives GSP-EBA Cape Verde, Sao Tome' & Principe, Comoros +Maldives	Canada GSP: Cape Verde, Sao Tome' & Principe, Comoros, Seychelles, Mauritius +Maldives GSP-LDC: Cape Verde, Sao Tome' & Principe, Comoros, +Maldives
USA GSP: Cape Verde, Sao Tome' & Principe, Comoros, Seychelles, Mauritius GSP-LDC: Cape Verde, Sao Tome' & Principe, Comoros GSP-AGOA: Cape Verde, Sao Tome' & Principe, Mauritius and Seychelles	Japan GSP: Cape Verde, Sao Tome' & Principe, Comoros (*), Seychelles, Mauritius +Maldives GSP-LDC: Cape Verde, Sao Tome' & Principe +Maldives

 

Caribbean SIDS

EU ACP: Bahamas, Dominican Republic, Antigua and Barbuda, Barbados, Dominica, Grenada, Haiti, Jamaica, St. Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago GSP: as ACP + Cuba GSP-EBA: Haití	Canada GSP: Antigua and Barbuda, Bahamas, Barbados, Cuba, Dominica, Grenada, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, St. Vincent & the Grenadines, Trinidad and Tobago GSP-LDC: Haiti CARIBCAN:, Antigua and Barbuda, Bahamas, Barbados, Dominica, Grenada, Jamaica, St. Kitts-Nevis, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago
USA GSP: Bahamas, Dominican Republic, Antigua and Barbuda, Barbados, Dominica, Grenada, Haiti, Jamaica, St. Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago GSP-LDC: Haiti CBI/ CBTPA: same as GSP	Japan GSP: Antigua and Barbuda, Barbados, Dominica, Grenada, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Trinidad and Tobago GSP-LDC: Haití

Pacific SIDS

EU ACP: Fiji, Kiribati, Marshall Islands, Federated States of Micronesia, Nauru, Palau, Papua New Guinea, Solomon Islands, Tonga, Tuvalu, Vanuatu, Samoa. GSP: as ACP GSP-EBA : Kiribati, Solomon Islands, Tuvalu, Vanuatu, Samoa	Canada GSP: Fiji, Kiribati, Marshall Islands, Nauru, Papua New Guinea, Solomon Islands, Tonga, Tuvalu, Vanuatu, Samoa. GSP-LDC Kiribati, Solomon Islands, Tuvalu, Vanuatu, Samoa
USA GSP: Fiji, Kiribati, Palau, Papua New Guinea, Solomon Islands, Tonga, Tuvalu, Vanuatu GSP-LDC: Kiribati, Solomon Islands, Tuvalu, Vanuatu, Samoa	Japan GSP: Fiji, Kiribati, Marshall Islands, Federated States of Micronesia, Nauru, Palau, Papua New Guinea, Solomon Islands, Tonga, Tuvalu, Vanuatu, Samoa. GSP-LDC: Kiribati, Solomon Islands, Tuvalu, Vanuatu, Samoa

 

Table 10.                   Commodity Coverage in ATPSM

01100 Bovine meat 01210 Sheep meat 01220 Pig meat 01230 Poultry 02212 Milk, fresh 02222 Milk, conc. 02300 Butter  02400 Cheese 04100 Wheat 04400 Maize  04530 Sorghum 04300 Barley 04200 Rice 06100 Sugar 22100 Oil seeds 42000 Vegetable oils 05420 Pulses 05480 Roots & tubers

05440 Tomatoes     05700 Non-tropical Fruits 05710 Citrus fruits 05730 Bananas 05790 Other tropical fruits 07110 Coffee green bags 07120 Coffee roasted 07131 Coffee extracts 07210 Cocoa beans 07240 Cocoa butter 07220 Cocoa powder 07300 Chocolate 07410 Tea 12100 Tobacco leaves 12210 Cigars 12220 Cigarettes 12230 Other tobacco - mfr. 26300 Cotton linters

Table 11.                   Global distortions: Revenues and Rents by Commodity

	World		SIDS
	Tariff revenue	Rent forgone	Tariff revenue	Export revenue	Rent received
	$m	$m	$m	$m	$m
Bovine meat	3859	105	7	4	0.00
Sheep meat	241	589	24	0	0.00
Pig meat	615	66	6	0	0.00
Poultry	2183	165	37	3	0.00
Milk, fresh	87	2	0	1	0.00
Milk, conc.	1093	419	36	2	0.23
Butter	534	169	10	0	0.00
Cheese	1057	360	16	6	0.62
Wheat	1882	2315	27	14	0.64
Rice	705	955	85	3	0.22
Barley	439	583	0	0	0.00
Maize	2652	2120	10	0	0.00
Sorghum	74	17	0	0	0.00
Pulses	338	1	8	1	0.00
Tomatoes	184	35	0	0	0.00
Roots & tubers	103	0	5	7	0.00
Apples	1119	15	8	0	0.00
Citrus fruits	537	15	1	23	0.05
Bananas	639	390	1	91	11.36
Other tropical fruits	251	0	0	18	0.00
Sugar	1850	789	35	1110	271.82
Coffee green	576	3	1	183	0.00
Coffee roasted	20	0	0	11	0.00
Coffee extracts	7	0	0	0	0.00
Cocoa beans	61	0	0	118	0.00
Cocoa powder	44	0	0	4	0.00
Cocoa butter	48	0	0	10	0.00
Chocolate	1314	108	9	7	0.11
Tea	357	0	1	15	0.00
Tobacco leaves	2173	20	1	75	0.04
Cigars	3684	0	14	41	0.00
Cigarettes	27	0	0	51	0.00
Other mfr tobacco	666	0	1	0	0.00
Oilseeds	2634	188	8	34	0.10
Cotton linters	288	29	0	0	0.00
Vegetable oils	2894	1	41	273	0.00
Total	35235	9457	394	2106	285.19

Source : ATPSM database.

Table 12.                 Impacts on world commodity prices of alternative scenarios

		Ambitious		Conservative		Tariff-50
			%		%	%
Bovine meat			8		3	3
Sheep meat			10		4	7
Pig meat			4		2	2
Poultry			7		2	4
Milk, fresh			10		4	7
Milk, conc.			18		6	6
Butter			25		10	8
Cheese			16		7	7
Wheat			13		5	2
Rice			3		1	1
Barley			3		1	1
Maize			4		1	2
Sorghum			1		0	0
Pulses			4		1	1
Tomatoes			3		2	2
Roots & tubers			3		1	3
Apples			4		2	3
Citrus fruits			2		1	1
Bananas			2		1	1
Other tropical fruits			3		1	2
Sugar			10		3	4
Coffee green			1		0	1
Coffee roasted			0		0	0
Coffee extracts			0		0	1
Cocoa beans			0		0	0
Cocoa powder			1		1	1
Cocoa butter			1		1	1
Chocolate			6		3	5
Tea			4		1	2
Tobacco leaves			4		1	3
Cigars			6		2	4
Cigarettes			2		1	2
Other mfr tobacco			14		5	8
Oilseeds			2		1	2
Cotton linters			2		1	1
Vegetable oils			4		1	2

Source : ATPSM simulations.

Table 13.                    Impact of Alternative Scenarios on Key Variables

 

	Ambitious	Conservative	Tariff-50	Preferential	Compensatory
	$m	$m	$m	$m	$m
Export revenues
SIDS	328	123	166	166	166
World	40381	13747	21386	21386	21386
Gov. revenue
SIDS	-96	1	-47	-47	-49
World	-1455	4891	-4176	-4191	-4363
Quota rents
SIDS	-254	-124	-166	-78	83
World	-4638	-1225	-1926	-1911	-1740
Welfare
SIDS	-271	-145	-150	-62	97
World	24981	10737	12944	12944	12944

Source : ATPSM simulations.

 

 

Table 14.                   Impact on welfare of five scenarios

			Ambitious		Conservative		Tariff 50		Preferential		Compen-satory
		$m		$m		$m		$m		$m
SIDS		-271		-145		-150		-62		97
Developed ag importers1		6971		2706		3801		3801		3768
Developed ag. exporters2		2779		1427		1321		1333		1314
European Union		10806		6286		3917		3925		3873
Developing ag. Importers3		531		-139		-99		-88		-102
Developing ag. Exporters4		643		136		362		323		317
All developed		19958		11083		9442		9463		9354
All developing5		4175		-89		2647		2622		2736
Least developed countries		849		-194		855		860		854
World		24981		10737		12944		12944		12944

1. Japan, Korea, Norway, Switzerland.

2. Australia, Canada, New Zealand, United States.

3. India, Kenya, Pakistan, Sri Lanka, Zimbabwe.

4. Argentina, Brazil, Indonesia, Malaysia, Philippines, Thailand, South Africa.

5. Excludes least developed countries.

Source : ATPSM simulations.

 

 

Table 15.                    Welfare impacts by commodity group in individual SIDS from 50 per cent tariff reduction ($m)

	Meat	Dairy	Cereals	Vegetables	Fruit	Sugar	Beverages	Tobacco & cotton	Oilseeds	Total
Bahamas	-1.0	-0.7	-0.1	0.0	0.0	-0.1	0.0	0.5	0.0	-1.4
Barbados	-0.8	-0.8	-0.2	-0.1	-0.1	-3.6	-0.1	-0.2	-0.1	-6.0
Cape Verde	-0.1	-0.4	-0.3	0.0	-0.1	-0.1	0.0	0.0	-0.1	-1.1
Comoros	-0.2	0.0	-0.1	0.0	0.0	0.0	0.0	0.0	0.0	-0.4
Cuba	-3.8	-7.0	-6.6	-0.7	0.2	20.2	0.0	1.3	-1.0	2.5
Dominica	-0.2	-0.1	0.0	0.0	-0.4	0.0	0.0	0.0	0.0	-0.8
Dominican Rep.	20.8	-2.6	-4.6	0.1	-0.7	-2.3	0.1	1.9	-1.6	11.3
Fiji	-0.9	-0.6	0.0	0.3	0.2	-20.5	0.0	0.3	0.3	-20.9
Grenada	-0.4	-0.3	-0.1	0.0	0.0	-0.1	0.0	-0.1	0.0	-1.0
Haiti	1.3	-1.0	2.3	1.1	1.9	-0.9	0.1	0.0	-0.5	4.2
Jamaica	-4.0	-2.5	-1.6	-0.3	-0.7	-12.2	-0.1	0.0	-0.6	-21.9
Maldives	-0.2	-0.3	-0.1	0.0	-0.1	-0.1	0.0	-0.2	0.0	-1.1
Mauritius	1.7	-2.3	-1.1	-0.1	-0.3	-28.1	-0.3	-0.4	-0.4	-31.2
Papua New Guinea	-4.0	-0.4	-1.1	0.6	0.5	0.8	1.4	-0.2	4.2	1.8
Sao Tome	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	-0.1
Seychelles	-0.1	-0.2	0.0	0.0	0.0	0.0	0.0	0.1	0.0	-0.2
Solomon Islands	0.1	0.0	-0.2	0.9	0.0	0.0	0.0	-0.1	0.4	1.0
St. Lucia	-0.5	-0.3	-0.1	0.0	-1.3	-0.1	0.0	-0.1	0.0	-2.5
St. Vincent	-0.3	-0.1	-0.2	0.0	-0.6	-0.1	0.0	0.0	0.0	-1.4
Trinidad Tobago	-1.3	-3.2	-0.8	-0.2	-0.2	-0.2	-0.2	0.7	-0.6	-6.0
Vanuatu	0.1	0.0	-0.1	0.0	0.0	0.0	0.0	-0.1	0.1	0.0
Total	6.2	-23.0	-14.9	1.6	-1.7	-47.5	0.8	3.3	0.1	-75.2

 Source : ATPSM simulations.

 

Table 16.                   (Figure 1)

 

 

 

 

Table 17.                   (Figure 2)

 

 

 

ED

Figure 3: Quota rents with a binding out-of-quota tariff