Chapter 5
Reducing Tariffs versus Expanding Tariff Rate Quotas
Harry de Gorter and Erika Kliauga
Tariff rate quotas (TRQs) are two-level tariffs with a limited volume of imports permitted
at the lower “in-quota” tariff, and all subsequent imports charged the (often much) higher “outof-quota” tariff (Ingco 1996, OECD 2001). In lieu of high bound tariffs resulting from
tariffication in the Uruguay Round Agreement on Agriculture (URAA), TRQs were adopted for
commodities previously subject to non-tariff protection. They were meant to guarantee minimum
levels of market access (initially 3 percent of domestic consumption and gradually expanded to 5
percent by the end of the implementation period) through “minimum access quotas, and to
safeguard current levels of access through “current access quotas” (IATRC 2001b). Hence TRQs
may have expanded imports during the URAA implementation period. A total of 1,425 TRQs
have been notified to the World Trade Organization, by 43 countries (WTO 2002a). The
implementation was envisioned to maintain or improve preferential market access for developing
countries, while often continuing to maintain a managed trade regime (Abbott 2002). Since a
substantial proportion of agricultural production in developed countries is protected by TRQs,
there is an interest in determining what the potential effects of the different ways of liberalizing
TRQs are.
When demand for imports at the low in-quota tariff is greater than the level of imports
allowed by the quota, imports must be rationed and so the method by which the rights to the
quotas are allocated also becomes important. The rights to the quota are allocated by one of
1
several methods, each with numerous conditions that affect fill rates and efficiency. Although
TRQs may have provided for more trade, a majority of the TRQs are not being filled (WTO
2002a,b,c). While market forces may be a factor, there is widespread agreement that quota
under-fill is in part attributable to the administration methods employed to implement TRQs.1
The purpose of this chapter is to evaluate the relative importance of tariff reductions
versus quota expansion in liberalizing agricultural trade. In doing so, the extent of quota underfill and the potential influence of quota administration methods on imports will be explored. The
effects of expanding TRQs or reducing tariffs in the WTO negotiations on agriculture will
depend on several key factors: which instrument is binding (the quota or the in-quota versus outof-quota tariff), whether there are imports above the quota at in-quota tariffs (“over-quota
imports”), the extent if any of quota under-fill, the levels of in-quota and out-of-quota tariffs, the
level of water in the tariffs and tariff binding overhang,2 the methods of administering the rights
to the quotas (with or without licenses), and any government responses in changing domestic
policy instruments.
The rest of this chapter is organized as follows. The next section presents data showing
the importance of TRQs in protecting domestic agricultural production and trade in developed
countries. We then explain the economics of liberalizing TRQs by identifying four basic
regimes: the first three are where the in-quota tariff, the quota and the out-of-quota tariff
respectively determine imports, while the fourth regime is where the government allows for
over-quota imports at the in-quota tariff (where no trade liberalization occurs initially with either
1
This and various other problems identified in the implementation of TRQs have been analysed by, for example,
Skully (1999, 2001b,c) Abbott and Paarlberg (1998), and de Gorter and Sheldon (2000, 2001).
2
“Water in the tariff” and “tariff binding overhang” refers to situations where a reduction in out-of-quota tariffs will
have no impact on trade initially. Water refers to situations where there are no out-of-quota imports and the
domestic price is below the out-of-quota tariff-inclusive world price. Overhang refers to the gap between bound
tariffs (to be reduced in the negotiations) and applied tariffs.
2
an out-of-quota tariff reduction or an increase in the quota). Data are presented on the value of
trade, quota under- or over-fill and tariff levels for each of these regimes. We then evaluate the
trade liberalizing effects of a 35 percent reduction in tariffs versus a 50 percent increase in quotas
to obtain a glimpse of the situation regarding TRQs and the relative importance of each initial
regime. Data are then presented along with an analysis of the administration methods and
additional regulations for the TRQs notified to the WTO. Summary data by country and
commodity are presented on tariff levels, import values and quota under-fill. We touch on some
important issues that may affect the efficacy of TRQs including minimum versus current access
quotas, changes in TRQ administration methods over time, dynamic rent seeking activities and
domestic policy responses. The chapter ends with some concluding comments and identifies
priorities for further research.
The importance of TRQs
As many as 43 out of the nearly 150 members of the WTO employ TRQs in agriculture
and 20 percent of their agricultural tariff lines involve TRQs (Gibson et al. 2001, Wainio 2001).
Table 5.1 summarizes the value of production protected by TRQs by country and commodity for
developed countries for the commodities covered by the OECD. It shows that 51 percent of the
total is protected by tariff quotas. This number understates the true magnitude because it omits
the lightly shaded cells in Table 5.1 that refer to commodity groups that have at least some tariff
quota lines and situations that are not officially a tariff quota but act like one (e.g., sugar import
barriers in Japan).3 Milk, maize, eggs and other grains have a substantially larger proportion of
the total value of production protected by tariff quotas than their share of the total value of
3
On the other hand, the data overestimates the level of coverage in that it includes commodities that are heavily
exported (e.g., wheat for Canada).
3
production, while the opposite is true for beef and veal, rice, oilseeds and sugar. The QUAD
countries have well over half of their total production in tariff quota commodities, while Korea,
Poland and Norway have close to 90 percent.
Using the same assumptions as in Table 5.1 on OECD commodity coverage, imports
under tariff quotas represent 43 percent of total agricultural trade valued at world prices in
developed countries (Table 5.2). Hence, commodities facing tariff quotas have import values
disproportionately lower than their share of total value of agricultural production, perhaps
reflecting the higher protection tariff quotas afford. Beef, oilseeds, wheat, dairy and maize have
the highest value of trade in agriculture covered by TRQs. The share of total trade in tariff quota
commodities mimics the share of total trade, except for TRQ trade in wheat, maize, rice and
sheep meat where the shares are substantially higher (while that of other grains and pig meat are
substantially lower). The QUAD countries excluding Canada but adding Korea have by far the
largest share of the total value of tariff quota trade.
The economics of trade liberalization with TRQs4
The impact of reducing tariffs versus expanding the quota will depend critically on the
instrument that is binding initially, how soon a regime change will occur as a result of trade
liberalization, and if under-fill occurs because of the quota administration method (Skully
2001a,b). We can identify four basic regimes: the in-quota tariff is binding (because of market
conditions or by government decree); the quota is binding (resulting in some tariff equivalent
level of protection less than what would otherwise be provided by the out-of-quota tariff); the
out-of-quota tariff is binding (out-of-quota imports occur at the high out-of-quota tariff); and
4
See Moschini (1991), Boughner et al. (2000), and IATRC (2001a) for more detailed economics of TRQs.
4
finally the case where the quota is filled but by government decree imports occur beyond the
quota level and face the in-quota tariff.
Figure 5.1 depicts the in-quota tariff regime. Figure 5.1a shows the case of quota over-fill
where the government has decreed that the in-quota tariff remains operative even above the
quota, while Figure 5.1b depicts the case of under-fill. Figure 5.2 depicts the quota binding
regime (exactly 100 percent fill rate in Figure 5.2a and the case of quota under-fill in Figure
5.2b). Figure 5.3 depicts the out-of-quota tariff regimes with exact, under- and over-fill of the
quota shown in Figures 3a, 3b and 3c, respectively.5 Finally, Figure 5.4 depicts the regime where
the quota is binding but there is quota overfill at the in-quota tariff rate. Reducing the in-quota
tariff will only have an immediate impact in Regime 1, but can become ineffective in Figure 5.1b
if the government allows the quota to become binding. Expanding the quota will only have an
immediate impact in Regime 2 while a reduction in the out-of-quota tariff will have an
immediate impact in Regime 3 only. Regime 4 is a situation where a reduction in either tariff or
an expansion of the quota will have no immediate impact on trade.
There are thus eight cases with these four regimes. Table 5.3 presents summary data for
each regime on the value of trade, under- or over-fill, out-of-quota imports and tariff levels and
value of tariff revenues and quota rents. The out-of-quota tariff regime has the highest value of
trade ($22.7 billion, the sum of in-quota and out-of-quota imports) with Regime 4 well behind at
$7.5 billion, Regime 1 (in-quota tariff operational) at $3.06 billion, and Regime 2 (quota
binding) at $2.07 billion. Notice that the value of under-fill in Regime 3 with out-of-quota
imports is almost four times that of Regime 2 (where the quota is binding) while under-fill is
5
Figure 5.3b shows that there can be quota under-fill and out-of-quota imports at the same time. This necessarily
implies inefficiency in the quota administration method because traders are foregoing potential quota rents that, if
available, they would gladly have taken.
5
significantly lower in the other two regimes. But net quota under-fill (under-fill minus overquota imports at the in-quota tariff) is slightly negative in Regimes 1 and 4.
Using the simple average of bound tariffs, the implied total value of tariff revenues is
$26.0 billion (in-quota plus out-of-quota tariffs) and quota rents are $16 billion. Data using tradeweighted tariffs indicate that tariff revenues are significantly lower at $19.6 billion using IDB
data (see last column of Table 5.3). Notice that the simple average bound in-quota tariff is lowest
in Regime 3, where out-of-quota imports occur, and is highest where the in-quota itself is
binding in Regime 1. Notice also that the total value of quota under-fill is 48 percent of the total
value of the quota, which has implications for how the quota is administered (see below).
Approximately 45 percent of all tariff quotas are minimum access quotas, representing a
lower share of total value of TRQ trade (41.7 percent – see the third column in Table 5.3) that
have increased from 3 to 5 percent of consumption by the end of the implementation period as
per the URAA. Note that the highest share of minimum access quota trade is in regimes that have
lower trade liberalization effects with quota expansion, namely Regimes 1b and 2b. Quotas do
not matter in Regime 1, but quota under-fill in 2b and over-fill in 4 lower the impact of quota
increases. This would be disconcerting if only minimum access quotas were to be expanded in
the negotiations, as in the URAA. The other 55 percent of the quotas are current access quotas
which were implemented to continue preferential access to developing countries (e.g., the
European Union) or to maintain historical access in cases where imports are a large proportion of
domestic consumption (e.g., wheat in Japan).
An empirical assessment of trade liberalization
The effect on the total value of TRQ imports of a 35 percent reduction in tariffs and a 50
percent expansion in import quotas is presented in Table 5.4. A 35 percent reduction in the out-
6
of-quota tariffs has a larger impact, expanding trade by $18.3 billion which is a 51.5 percent
increase in the value of total TRQ trade. Most of the increase in trade with a reduction in out-ofquota tariffs comes from changes in imports under Regime 3, but very little from Regime 2. The
relative increase in imports from Regimes 2 to 4 with a decrease in the out-of-quota tariff
depends on the level of trade initially in each regime and on the level of the in-quota and out-ofquota tariffs. The trade liberalization effects also depends critically on the amount of water in the
tariff for Regimes 2 and 4 (assumed here to be 50 percent of the gap between the out-of-quota
and in-quota tariff levels, as assumed by in Bouet, Fontagne and Jean 2005). We also assume the
elasticity of excess demand is -4.63 and world prices do not change.6 These assumptions affect
the results (the most critical assumption relating to water in the tariff), but a sense of the relative
impacts of tariff reductions versus quota expansion is nonetheless obtained.
Expanding quotas by 50 percent, on the other hand, results in a 14.5 percent increase in
the value of total TRQ imports ($5.1 billion). The increase in trade comes from Regimes 2, 3,
and 4, the latter case where the quota is not binding initially. Note that quotas up to a 105 percent
fill rate were included in Regime 4 (instead of assuming the out-of-quota tariff is automatically
binding for fill rates between 100 and 105 percent). This means over-quota imports are lower in
many instances in Regime 4, so a quota expansion has a relatively large impact.
Three key factors determine the relative amount of trade expansion with an increase in
quotas: the level of initial trade in each regime; the degree of under-fill in Regimes 2b and 3b,
and the level of over-fill in Regimes 3c and 4. If there is significant quota over-fill, then an
increase in quotas will have no effect on trade. The impact of under-fill on trade liberalization
6
This estimate of the import elasticity is the average of the elasticities used in the Linkage model for agriculture in
Chapter 12 of this volume.
7
with a quota increase (Regimes 2b and 3b) will depend on the assumption one makes as to how
the fill rate changes (de Gorter and Boughner 1999). Here we assume the fill rate remains
constant so an increase in the quota has a proportionate increase in observed imports. But one
could consider two other plausible scenarios: the under-fill has to disappear first before trade
changes (so a quota expansion initially has no impact on trade), or the absolute level of the
under-fill is fixed such that the initial change in trade equals the change in the import quota.
Which of the three assumptions one makes in analyzing the impact of quota expansion rests
heavily on one’s view as to why there is under-fill in the first place, a topic we take up below
with our discussion of the importance of administration methods on quota under-fill.
It is possible for imports to expand in Regimes 2 to 4 if the quota expands substantially
(but less likely in Regime 3), but the in-quota tariff puts a brake on the effectiveness of the quota
increase. Hence, it is important to emphasize the benefits of a simultaneous reduction in in-quota
tariffs, even though these tariffs directly impact imports in Regime 1 only. A decision will have
to be made as to whether the negotiations will require having an increase in both current and
minimum access quotas (say 50 percent) or having minimum access quotas increase to 10
percent of consumption (current consumption or that in the base year 1986-88).7
Average in-quota tariffs are still very high, even compared to non-tariff quota tariffs, so
room for either increasing imports or increasing quota rents remains substantial. However, trade
weighted tariffs are lower: 53.5 percent compared to 59 and 115 percent for in-quota and out-ofquota simple average tariffs, respectively (Table 5.3). Using the simple average tariff may not be
so misleading though, because bound tariffs are to be negotiated and with the average cut in
7
For example, a minimum access quota of 5 percent of baseline consumption is equivalent to 8 percent of current
rice consumption in Japan today.
8
tariff formula it is possible tariff peaks will remain, imparting protection to domestic production.
Average tariffs need to be interpreted with care because production-weighted tariff equivalents
of import barriers as calculated by the OECD are not directly comparable to the average of
tariffs. This is because there are so many tariff lines and associated imports that do not directly
protect domestic production. Take the U.S. dairy case as an example – there are many different
cheeses and other dairy products imported (with over half the value of U.S. dairy imports being
non-quota and so not directly competing with domestic production) such that the average applied
tariff (however weighted or a simple average) will be far less than the level of protection of
domestically produced dairy products.
The last column of Table 5.4 gives the minimum increase in value of trade across the two
possible instruments to liberalize for each of the eight cases presented. The change in total value
of trade under the minimum is $2.8 billion, significantly less than the increase with either the
quota expansion or the out-of-quota tariff reduction scenarios. This emphasizes the importance
of not allowing countries to choose the option of reducing tariffs or expanding quotas, as has
been proposed.
The reduction of out-of-quota tariffs holds much promise in liberalizing trade as the
simulations earlier indicated. The outcome depends heavily on what level of tariff reduction
versus quota expansion one assumes, but also on the level of water in the tariffs. Table 5.5
provides some estimates of water in the tariff for selected countries and commodities. Estimates
of the tariff equivalent of the binding quota are given (taken from nominal protection coefficients
given in OECD 2003), alongside the implied tariff equivalent with our assumption of the water
to be 50 percent of the difference between the out-of-quota and in-quota tariff levels. We present
two possibilities: using the average out-of-quota tariff, or the maximum tariff line for that quota.
9
The actual and assumed water in the tariff are then compared, with the last two columns of Table
5.5 indicating the error in our assumption using the average and the maximum out-of-quota
tariffs, respectively. We overestimate the water and hence underestimate the trade liberalizing
effects of an out-of-quota tariff reduction when using average tariffs but overestimate water and
so underestimate trade liberalization effects assuming a maximum tariff protects domestic
production. Hence, substantial reductions in out-of-quota tariffs may be needed in Regimes 2 and
4 before trade liberalization occurs, especially with the high number of tariff peaks and tariff
dispersion.
Finally, one has to allow for the possibility of tariff binding overhang for both in-quota
and out-of-quota tariffs, where the applied tariff is below the bound tariff (the latter is more
likely to be disciplined in the negotiations). This would make tariff reductions in Table 5.4 even
more muted, given that bound rates are assumed to be affecting trade levels in our analysis. Jean,
Laborde and Martin (2005) present estimates of the binding overhang. They find that the average
applied tariff is about half of the bound tariff in several developed countries and even less in
developing countries.
Assessment
The most effective means to liberalize trade seems to be out-of -quota tariff reductions,
the same result as that of the OECD found. However, our conclusion is heavily dependent on the
level of water assumed in the tariffs. Also, we do not know what would happen if all three
liberalizations occurred simultaneously. Reducing the in-quota tariff for those cases where the
in-quota tariff is binding and there is no in-quota tariff binding overhang has limited effects (as
shown in Table 5.4), because the in-quota tariff is binding initially for so little trade in TRQ
commodities. However, in cases where the in-quota tariff is not binding, an increase in quota
10
rents will occur, perhaps providing more political pressure to maintain the status quo by
domestic firms and reduce efficiency, depending on the quota administration method (see
below).
Reductions in out-of-quota tariffs will be more effective only if water in the tariffs can be
eliminated and where fill rates are less than 100 percent due to administration methods and
additional regulations. The interests of developing countries will depend critically on who
obtains the quota rents. Reductions in out-of-quota tariffs can reduce rents while expansion of
the quota can increase rents, even when the per unit rent falls.
Methods of quota administration and additional regulations
TRQ administration involves distributing the rights to import at the in-quota tariff.
Whoever obtains such rights can make a risk-free profit from the difference between the
domestic price and the world price inclusive of the in-quota tariff (Skully 1999; 2001b).
Therefore, governments need to ration or administer the TRQ. We summarize the definitions of
the alternative tariff quota administration methods in Table 5.6. Applied tariffs are by far the
most used method, representing 39.3 percent of the total number of TRQs (but only 14.4 percent
of the total value of TRQ trade). Licenses on demand, first come first served, and historical
importers are the next most commonly used methods in descending order of importance,
representing 27, 12 and 9 percent of total TRQs (but each having 16-18 percent of the total value
of trade). Auctions are the next most commonly used method, representing only 5.4 percent of
the total number of TRQs and less than one percent of the total value of trade. Other
administration methods are state trading enterprises, producer groups and mixed methods (a
combination of at least two administration methods), with their share of trade being much higher
than the corresponding share of TRQs.
11
First come first served is the third most widely used administration method in terms of
trade value. This has several implications, one of which is that farmers do not benefit as much
from such a trade barrier through rent appropriation by consumers or middlemen (Chau, de
Gorter and Hranaiova 2003). Furthermore, there is the likelihood of rent dissipation in rent
seeking as firms try to mitigate the negative impacts of first come first served on prices when
imports are hurried.
Approximately 36 percent of all tariff quotas are filled, with quota over-fill in the applied
tariff, state trading enterprise and mix categories. A total of 341 quotas were overfilled (at the inquota tariff) and 129 quotas exactly filled at 100 percent fill rate. There is a bi-modal distribution
of fill rates, with 339 TRQs having a fill rate of less than 20 percent (with a simple average fill
rate of only 4 percent, but the trade weighted average is significantly higher). The simple average
fill rates as reported by the WTO and cited by many academic studies give the same picture as
the trade-weighted fill rates developed in this paper. The average fill rate as reported in this
paper is 60.6 percent excluding over-quota imports, while the trade-weighted fill rate is 60.9
percent. Indeed, there is quota over-fill for the applied tariff, state trading enterprise and mix
categories, amounting to $3.1 billion. Under-fill net of over-quota imports, on the other hand, is
$13.7 billion, with license on demand, first come first serve and historical importer categories
having the largest under-fill levels. Each of these three administration types have the highest
share of trade and so are important to analyze. As we show later, these three administration types
are prone to inefficiency. Finally, the value of quota under-fill is estimated to be $16.8 billion,
approximately 48 percent of the value of the quota when filled (assuming world prices do not
12
change), thereby representing a huge amount of trade and rents foregone.8 This lost potential
value of tariff revenues and quota rents may be to a large extent dissipated (or appropriated by
other countries or groups), so further analysis of tariff quota administration methods and
additional regulations is warranted (see below).
Average in-quota tariffs are highest for applied tariffs and auctions while the average outof-quota tariffs are also high for these same methods, as well as for the state trading enterprise
method. Reducing in-quota tariffs will only have an impact on trade for cases described by
Regime 1. Even then, the benefits of some reductions in the in-quota tariff will end when it
causes a regime change to a binding quota, thereby generating quota rents. Either way, the
reduction of in-quota tariffs increases quota rents and hence political opposition to trade
liberalization. As we will show below, the increase in per unit rent can have very different
impacts on efficiency, depending on the quota administration method in place.
There are several key additional regulations that can also affect the fill rate, such as time
limits, past trading performance (applied to methods other than historical importers), license
limits per firm, seasonal quotas (quarterly or semi-annual), domestic purchase requirements, and
taxes for licenses and non-use. Table 5.7 summarizes the number of quotas, countries,
commodities and filled quotas for each regulation. These additional conditions imposed on firms
are very significant, affecting many quotas, countries and commodities. The total value of trade
affected by each regulation is very high, with time limits affecting $7.6 billion of trade. Fill rates
are particularly low for seasonal, export certificates, license fees and provision for unused
licenses. For example, less than 10 percent of the seasonal quotas are filled, while the “provision
8
This ignores the fact that in many cases, out-of-quota imports replace the quota under-fill so the actual value of
trade at observed prices attributed to quota under-fill is even lower.
13
for entry” has the second highest proportion of filled quotas. License fees have one of the highest
proportions of TRQs filled and we show below how fees can increase efficiency. Note that “useit-or-lose-it” (domestic purchase requirement has the highest. It did not change compare to The
Hague) has the highest trade-weighted fill rate, implying that firms perhaps import when it does
not pay in order to hold the valuable asset for later use, thereby adding to inefficiencies.
The next step is to match each additional regulation with the principal quota
administration method (Table 5.8). Analysis of this table reveals a high number of additional
regulations for licenses on demand, historical importers, first come first served and state trading
enterprise administration methods. The implications of additional conditions are manifold. For
example, one cannot automatically assume “applied tariffs” are represented by Regime 1 (inquota tariff binding) because one of several additional conditions associated with applied tariffs
(e.g., domestic purchase requirements) may increase the costs of importation (or act as a nontariff barrier) so rents are created. On the other hand, methods other than applied tariffs are not
necessarily precluded from Regime 1 being the outcome either, especially if there are no
additional conditions and the quota is not binding. Notice that the value of trade affected by
additional regulations for the license auction method is higher than the value of trade under
auctions, implying that no trade may occur under a basic auction system so favored by
economists. Additional regulations impose costs to the classic textbook case of efficiency with
auctions.
A note on TRQ fill rates
Fill rates do not give a complete picture as to the efficacy of a tariff quota regime. A fill
rate of less than 100 percent may not imply inefficiency if demand and supply conditions are
such that the in-quota tariff is binding. But a fill rate of 100 percent does not mean efficiency
14
either, because the lowest cost supplier may not have been used or imports could otherwise have
been even higher.
Average fill rates as reported by the WTO and academic studies can be misleading due to
aggregation problems: a subset of some commodity or country groupings may have zero fill rates
and others a 100 percent fill rate. Trade-weighted fill rates would be more indicative of import
performance (OECD 2002). Data published so far do not take into account imports above the
quota but at the in-quota tariff rate, biasing the fill rates downwards. Furthermore, some
countries only report imports up to the quota level (ignoring imports at the in-quota tariff that are
over the quota), while others simply report the number of import licenses issued which may not
be fully used.
To overcome these difficulties, we need present both the number and the value of trade
corresponding to the simple average (truncated) fill rate reported by the WTO as well as the
trade-weighted fill rates in the attached tables. Fill rates weighted by value take into account
over-quota imports at the in-quota tariff.
TRQs by country and commodity group
The number of tariff quotas by country and commodity group is given in Tables 5.9 and
5.10, respectively. The total value of in-quota plus out-of-quota trade is $35.4 billion while net
quota under-fill (subtracting over-quota imports) is $13.7 billion, or 39 percent of the total TRQ
trade. Countries with the highest levels of in-quota trade are Canada, China, Colombia, the EU,
Indonesia, Japan, Korea, Mexico, Switzerland, the United States and Venezuela. Notice
countries with high levels of over-quota imports (in absolute terms and even more so in relative
terms) are predominantly developing countries. Countries with high levels of out-of-quota
imports are China, the EU, Japan, Korea, Venezuela and the United States. Quota under-fill is
15
dominated by four countries: China, the EU, Poland, Venezuela and the United States. The
simple average in-quota and out-of-quota bound tariffs are also presented in Table 5.9, along
with the trade-weighted average applied tariffs (including both the in-quota and out-of-quota
tariffs that were actually applied). The simple average fill rates and trade-weighted fill rates for
each country also are presented in Table 5.9.
Corresponding data by commodity in Table 5.10 show that the value of in-quota trade
and the quota are evenly distributed within each of two categories: high and low levels of trade.
The high level group of commodities is cereals, dairy, fruit & vegetables, meat, oilseeds and
sugar. The low level of trade category includes beverages, coffee & tea, eggs, fibres, ‘other’ and
tobacco. Over-quota imports are highest for cereals and oilseeds. Out-of-quota imports are high
for cereals, sugar, fruit & vegetables and meat products. Net quota under-fill is highest for
beverages, cereals, fibres, fruit & vegetables, and oilseeds. Trade weighted fill rates are below
average for beverages, cereals, eggs, fibres, fruit & vegetables, and ‘other’. Notice that the tradeweighted fill rate is substantially higher that of the simple average for coffee & tea, dairy and
meat.
In-quota tariffs are above average for cereals, fruit & vegetables, meat, ‘other’ and
tobacco. The same commodities have a below average out-of-quota tariff except for cereals
(cereals, meat, tobacco, fruit & vegetables and ‘other’ have out-of-quota tariff above average)
which is now slightly below average. Average tariffs for quotas with several tariff lines that
differ may be misleading because of aggregation problems. A simple or trade-weighted average
does not overcome the impact of a few high tariffs protecting most of domestic production.
16
Can TRQ administration methods and regulations impact trade?
Data provided earlier showed that there are five major quota administration methods (or
combinations thereof) and a host of additional conditions that have the potential to impact not
only efficiency but also the fill rates (Monnich 2003, Skully 2001b). The most preferred method
of administrating quotas in terms of maximizing economic efficiency is either applied tariffs (the
most commonly used method but representing only 14 percent of trade) or auctions (one of the
least-used methods and representing less than 1 percent of total trade). The former is preferred
because there are no limits to imports and the latter because the most efficient supplier (trading
firm and exporting country) receives the importing licenses. All other methods and the many
additional regulations invite many possibilities for inefficiencies and potentially impacts fill
rates.
At first glance, one would expect that applied tariffs, the most commonly used
administration method, would allow for unrestricted levels of imports at the in-quota tariff. But
several applied tariff quotas have time limits, past trading performance, volume limits per firm,
domestic purchase requirements and license fees. These are the regulations that are in the
notifications (several may be unreported) and can all reduce fill rates. The significance of these
regulations, given by the number of cases for each additional regulation for the applied tariff
method, is shown in Table 5.8. License fees may be such that it does not pay to import, and that
clearly affects fill rates. The domestic purchase requirement adds costs to importation and so can
affect fill rates too.
17
The next most commonly used administration method is licenses on demand (in terms of
both the number of TRQs and value of trade). In this case licenses are allocated on a prorated
basis whereby requests for licenses are reduced proportionately if they exceed the quota.
Inefficiency is incurred because licenses are allocated to high-cost firms away from low cost
firms (Hranaiova, de Gorter and Falk 2003). The higher the firm’s costs, the closer the allocated
quantity to its desired allocation and the higher the probability that it will receive its desired
allocation. Quota expansion causes high-cost firms to decrease their bids, and so reduces
inefficiency. The entry of a new firm causes all incumbent firms to increase bids or bid the
quota. How that affects efficiency depends on whether high-cost or low-cost firms enter. The
number of firms bidding for the quota never decreases. Not penalizing firms for the non-use of
licenses will almost guarantee quota under-fill, which also increases with the heterogeneity of
cost structures across firms. In-quota tariff reductions causes per unit rent to increase and so
provides incentives for high-cost firms not to exit (or to enter), causing inefficiency to increase.9
When a limit on the licenses received by each firm is imposed, inefficiency increases because the
limit will be more binding on low-cost firms.
First come first served is the next most commonly used method, resulting in a race to the
border with imports not occurring in the optimal time of year, resulting in waiting in line
inefficiencies (Chau, de Gorter and Hranaiova 2002). Time limits are very common with this
method (see Table 5.8). Countries with a geographic advantage will benefit, and uncertainty as to
whether the quota will be filled upon arrival at the border is increased. More-perishable
commodities will reduce rents, to the disadvantage of importing firms, exporting countries and
9
This has the opposite effect of introducing a license fee.
18
producers in the importing region. The degree of “rent appropriation” (rather than “rent
dissipation”) depends critically on, inter alia, the ratio of the import quota volume to free trade
levels. Given that first come first served represents 16.8 percent of the total value of TRQ
commodities traded, the scope for rent appropriation is very large indeed. It reduces the
effectiveness of quotas in protecting domestic producers in the importing country, but aids
domestic consumers. Furthermore, some of the rents may be dissipated in rent seeking where
firms try to get around the consequences of hurried-up imports and reduced domestic prices in
the interim. They may do so by changing the timing of domestic production, or storing the
product. Although these latter practices increase profits for the firms involved, they increase
social costs compared to a situation where property rights to the import licenses are clearly
defined.
License allocation on the basis of historical imports is the next most commonly used
method of quota administration. The effects of this trade liberalization on efficiency are opposite
to that of licenses on demand. For example, a decrease in the in-quota tariff will increase
inefficiency in the case of licenses on demand, but with historical shares, efficiency increases
unless high-cost firms have a disproportionate share of the quota licenses. Meanwhile, an
increase in the quota, holding per unit rents constant, will increase efficiency with licenses on
demand because high-cost firms are at their desired level of licenses anyway because additional
imports are allocated to lower-cost firms only. The decline in per unit rent resulting from the
quota increase will reinforce this increase in efficiency effect with high-cost firms exiting. With
historical shares, on the other hand, an increase in the quota will unambiguously reduce
efficiency (and hence potentially fill rates), except in the unlikely event that the historical share
to each firm corresponds exactly to optimal shares with an auction. This example emphasizes the
19
potential importance of quota administration methods on trade patterns and how tradeliberalizing effects can have opposite effects, depending on the method in use.
State trading enterprises (STEs) can also have significant impacts on efficiency and fill
rates, because it is immune to some degree from market forces and so may not provide the
incentive to fill the quota. If the STE represents producers’ interests, it may choose to limit the
quota to lower-valued imports within the category or to pay exporters lower prices for the good
in question, as compared to a situation of competition among private traders. STEs also have
been alleged to price discriminate and deliberately allocate export quotas to higher-cost exporters
for political reasons. If the quota rents are blended with revenues from domestic production,
domestic production expands beyond efficient levels for a given domestic price determined by
the import quota.
The impact of the STE on efficiency and fill rates depends on its objective function
(maximize producer profits, stabilize prices, etc.) and the degree of control it has over imports
and the domestic market. Part of the import quotas with STEs is now typically given to private
traders, and the control of domestic market prices and production varies by country and over
time. The outcome also depends on whether the STE feels obligated to fill the quota or take the
option to destroy the product. The effect of the STE also depends on what the initial regime of
the tariff quota would be under perfect competition (quota binding versus in-quota tariff versus
out-of-quota tariff) while the effects of trade liberalization in terms of tariff reductions and quota
expansion will depend on what instrument is binding under the initial STE equilibrium.
Imperfect competition can result in higher quota fill rates. It can also alter the effects of
liberalization because of monopoly or monopsony “water” in the tariff and the interaction effects
between the two tariffs and the quota (Hranaiova and de Gorter2002, de Gorter and Hranaiova
20
2004). The effectiveness of market power increases with the tariff, but trade liberalization may
not increase social welfare. Regime switches may occur, with the possibility of losses in
efficiency and social welfare. Trade liberalization outcomes depend on the initial optimal
solution for the imperfect competitor (i.e. which tariff quota instrument is binding), the level of
the binding instrument, and the type and degree of trade liberalization (McCorriston and Sheldon
1994).
The import quota fill rate is not necessarily an indicator of economic efficiency. A quota
may be under-filled under perfect competition, yet can be fully filled under a monopoly solution.
For a monopsonist, there is no partial under-fill of the quota. A decrease in the in-quota tariff
may induce a switch in regimes from a price taker to a monopsonist.
Import quotas may be superior to a tariff in achieving the same level of protection in the
case of monopsony. This is because the domestic buyer can exercise full monopsony power at
low levels of tariffs, while an introduction of a quota increases welfare. The decrease in
economic efficiency due to a switch to a monopsonistic solution when sufficiently high tariffs
are introduced may offset any efficiency advantages of tariffs over quotas. For a monopolistmonopsonist, the outcome is further complicated by the possibility of two discrete changes in the
optimal solution and two supply curves to choose from.
The role of dynamic rent seeking
The widespread use of additional regulations in combination with each other and with
major quota administration methods can potentially impact trade in a dynamic rent seeking
context as well. For example, the rules governing entry of new firms can either increase or
decrease efficiency, depending on the administration method, the level of out-of-quota tariffs and
the regulations determining entry. Some firms, either high or low cost, may import at a loss to
21
build up an historical import level to then receive license under the historical share allocation
method or qualify to be either a bona fide importing firm (potentially relevant to all
administration methods) or fulfill the additional condition “past trading performance”
requirements for non-historical administration methods. Use it or lose it rules imply access to the
quota in the following year so firms may import – even though it does not pay – in order to have
access to excess rents in the future.
The costs to firms of a limit in the number of licenses it can receive (in foregoing
economies of scale) may be mitigated by rent-seeking activities. For example, firms will incur
costs to split their firms into smaller entities. Seasonal licenses are very common (quarterly or
semi-annual) and do not allow for the exploitation of seasonality in the gap between world and
domestic prices. This may be particularly important for developing countries where harvest
seasons are often different to that of countries in the North.
Time limits, once a license is allocated, introduce uncertainty and transactions costs. The
resulting inefficiency will also be depending on whether or not more conditions are required
(such as, the license will be lost and not reallocated later).
Domestic purchase requirements may result in consolidation of the importing and
domestic production sectors so rents are being dissipated and perhaps in an increase in the
domestic price. Rents can either increase or decrease.
No information is given in the notifications as to whether the licenses are permanent or
on an annual basis, or whether license trading to other firms within a year is allowed. These two
features can have significant impacts on the efficiency of quota administration methods.
Furthermore, Mexico has issued quarterly import permits (cupos) that were for imports into
22
specific regions of the domestic market. These and other undocumented regulations may have a
significant impact on efficiency and fill rates.10
Changes in administration methods
There have been significant increases in the level of the quotas for each administration
method category, especially for applied tariffs and licenses on demand, probably reflecting
relatively more minimum versus current access quotas designated in these administration
categories (WTO 2002c). Table 5.11 provides summary data on the number of tariff quotas that
changed away from one administration method to another. A total of 64 applied tariffs were
switched to other methods with most becoming historical importers or licenses on demand. The
highest number of net increases were registered in historical importers (6 away from but 44
added), licenses on demand, mixed, producer groups and auctions (the net increase in the latter
was only one). Tunisia and Venezuela have changed their applied tariffs to historical importers
for 100 per cent and 28 per cent of their quotas, respectively. Guatemala and Poland have
registered the highest number of changes from applied tariffs to licenses on demand. First come
first served has not registered any increases since 1995.
Potential domestic policy responses to TRQ liberalization
Import quotas give domestic firms, STEs or domestic governments more latitude in
fixing domestic prices and hence reducing the volatility of domestic prices. This means world
prices are more volatile except in some circumstances (Tyers and Anderson 1992). Imperfect
competitors can charge higher prices with a quota compared to tariffs, while STEs and producer
10
Mexico has also taken preliminary steps to initiate safeguard actions on dry beans and white corn. In addition,
Mexico alludes to suspending the issuance of import licenses for white corn except in times of short supply.
Administration methods are very often in a state of flux.
23
groups that control import licenses can do likewise. At the same time, governments often try to
stabilize domestic prices (albeit at levels sometimes much higher than world prices) through
several mechanisms, depending on the country and commodity. Both an expansion of the quota
and reductions in out-of-quota tariffs are the preferred methods of reducing the ability of
governments to use a quota to stabilize the domestic price at the expense of increased volatility
of world markets.
It is also possible that inefficiency increases with domestic policy responses to trade
liberalization (Schmitz, de Gorter and Schmitz 1995). In almost all cases, government employs
domestic policy price supports and other instruments in tandem with a TRQ. Canada has supply
management schemes while the European Union employs acreage restrictions, production
quotas, stockpiling and export subsidies. The US sugar program has the loan rate as the target
farm price and allocates “flexible marketing allotments” to farmers and accepts bids from
processors to obtain defaulted loans in exchange for reducing their production of sugar. The
European Union allocates production quotas and uses export subsidies to stabilize their domestic
prices for sugar. So the benefits of liberalizing TRQs can be at least partially offset by adjusting
domestic policy parameters.
To illustrate, consider Japan’s rice TRQ and domestic policy instruments. Not only in
Japan but in other Asian rice markets with TRQs, several domestic policy instruments are used
simultaneously to stabilize domestic prices. Mandatory acreage set-aside, purchase limits by the
STEs (or marketing controls), the importation of low quality rice (sometimes fed to livestock and
even destroyed in one country – see Choi and Sumner 2000) by that proportion of the TRQ
controlled by the STE, an increase in stocks year to year, and the use of exports as food aid
represent the portfolio of policy instruments used to stabilize prices. An example of this is given
24
in Table 5.12. Although imports increased substantially (from zero prior to the URAA), the
increase in supply to domestic markets has often been less than half the increase in imports.
Exports as food aid have increased over the years, and stock changes have been always positive.
Acreage reduction requirements have been ratcheted upwards as well. Imports by private traders
represent a growing share of the import quota, but rents remain high for the STE. All of these
actions illustrate the potential for government policy responses to mitigate the positive
liberalization effects of TRQs.
Concluding comments
This chapter shows that TRQs protect over 50 percent of agricultural production and
approximately 43 percent of agricultural trade of developed countries, even though the total
number of tariff lines under TRQs is relatively low. Using applied tariffs, total tariff revenues
and quota rents are estimated to be in the order of $19.6 billion. We identify four key TRQ
regimes associated with the in-quota tariff, quota, out-of-quota tariff and over-quota imports that
determine the market equilibrium. There are a total of eight cases under these four regimes,
depending on whether there is exact fill, under-fill or over-fill of the TRQ. Data show that the
out-of-quota regime has the largest value of trade at $22.7 billion, followed by the over-quota
import regime at $7.5 billion and the quota binding regimes at $2 billion. The value of trade for
the in-quota tariff regime is $3 billion.
A reduction in out-of quota tariffs has the largest impact on trade liberalization. Our
analysis shows that out-of quota reductions increase the value of trade by $18.2 billion while a
quota expansion increases trade by $5.1 billion. But the outcome also depends critically on the
level of water in the tariff assumed, the relative values of tariff reduction versus quota expansion
(assumed to be 35 percent versus 50 percent, respectively) and the level of under- and over-fill in
25
each case. We also assume simple average bound tariffs are reduced (rather than trade-weighted
applied tariffs). The analysis shows that in-quota tariffs may stifle trade liberalization in the
quota expansion and out-of-quota tariff reduction scenario, the extent to which was not analyzed
empirically. Nevertheless, this highlights the importance of including in-quota tariff reductions
in the WTO negotiations, even though they are not officially bound and no in-quota tariff
reductions were required in the URAA. Furthermore, if countries were allowed to choose the
least-liberalizing of the two trade liberalization options, we show empirically that it is possible
that the increase in the total value of trade would only be 40 percent of that under the quota
expansion case for all countries and 25 percent of the trade expansion if all countries followed
the out-of-quota tariff reduction case only.
The trade-weighted fill rates were calculated by administration method and additional
regulation. Although applied tariffs represent 39 percent of total administration methods, it
represents only 14 percent of trade. Auctions, on the other hand represent 5.4 percent of total
administration methods but only 0.5 percent of the total value of trade. The importance of
licenses on demand, historical importers, first come first served and state trading enterprises
were highlighted with the latter actually having quota over-fill on average. There is a sharp bimodal distribution on fill rates, with many below 20 percent and many at 100 percent or above.
The average fill rate is 60.5 percent like that reported by the WTO (2002a,b) and the calculated
trade-weighted fill rate in this chapter is almost identical at 61.1 percent. We discuss how
licenses on demand and historical importer methods allow high-cost importers to operate; and
how first come first serve results in prices being lower earlier in the season, allowing for rent
appropriation by consumers and middlemen, or rent dissipation through producers trying to
circumvent the price declines. State trading enterprises can affect inefficiency as well, depending
26
on their objective function, constraints such as international obligations, and control of domestic
market parameters such as marketings, stocks or prices.
The interaction of additional regulations with each of these major administration methods
are also shown to be important in terms of their effects on either the fill rates or efficiency. Time
limits affect $7.6 billion of trade, past importing performance affects $3.7 billion, export
certificate affects $3.5 billion,, and $1.9 billion of trade requires domestic purchases as well.
Each of these regulations and others (including seasonal licenses and limit per firm) increase the
costs of importing and so inevitably impact on fill rates. Even applied tariffs have significant
regulations associated with them, resulting in a situation where pure tariff regimes do not exist in
many cases. More analysis is required on the extent to which additional regulations are pervasive
in either out-of-quota or an in-quota tariff regime before firm conclusions can be made as to how
much they limit the effects of trade liberalization.
We also present summary data on the levels of out-of-quota and over-quota imports and
quota under-fill by commodity and country. These data can be cross referenced to administration
type, additional regulation, minimum versus current access and other relevant indicators in
analyzing various aspects related to the factors that may impact TRQ fill rates. The total value of
TRQ trade is $35.4 billion, with net quota under-fill (after adjusting for over-quota imports) at
$13.7 billion or about 39 percent of total TRQ trade. Quota under-fill by itself totals $16.8
billion, amounting to 48 percent of the quota itself. The average applied tariff is 53.5 percent,
considerably lower than the average bound in-quota tariff of 59 percent and out-of-quota tariff of
115 percent. But this trade-weighted applied average tariff for TRQ commodities is much higher
than the average applied tariff for all of agriculture (World Bank 2003, Ch. 3).
27
We also determined that 41.7 percent of TRQ trade is under minimum access quotas,
which were required to expand during the URAA implementation time period. But the majority
of these are in regimes where a quota increase has no immediate impact on imports. We also
found significant number of changes in the TRQ administration methods away from applied
tariffs and towards licenses on demand and historical importer categories, both methods of which
are deemed fraught with inefficiencies (along with historical importers and state trading
enterprises). Consideration was given to the existence of several key additional regulations and
the ways in which some administration methods are implemented that can lead to dynamic rent
seeking and further inefficiencies of the quota administration system. Finally, we consider
potential domestic policy responses to TRQ liberalization that mitigate the effects of trade
liberalization, using the example of Japan’s state trading enterprise’s response to the introduction
of a TRQ for rice imports.
The data and analysis in this chapter cannot come to any definitive conclusion as to how
well the TRQs liberalized trade in agriculture, not least because of the assumptions that had to be
made and the further work required in analyzing the extensive database that has been developed.
In particular, analysis of a combination of tariff reductions and quota expansion is warranted,
along with an analysis of how in-quota tariffs stifle quota expansion. But more data and
information are required to get a better understanding of TRQs, especially on the exact levels of
water in the tariffs and tariff binding overhang. The impact of preferential tariffs also requires
investigation, as does the distribution of rents between importers and exporters. The analysis
here also does not analyze non-WTO TRQs, nor does it compare our results to non-TRQ imports
and tariffs.
28
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33
Figure 5.1: In-quota imports with and without quota fill
(a) In-quota tariff with over-quota imports
Regime 1a
PW + t2
PW + t1
t1 revenues
PW
Over-quota
imports
quota
ED
imports
(b) In-quota tariff with quota under-fill
Regime 1b
PW + t2
PW + t1
t1 revenues
PW
quota
under-fill
imports
ED
quota
34
Figure 5.2: Imports with quota full or under-filled
(a) Quota filled
Regime 2a
PW + t2
water in tariff
Pd
quota rents
PW + t1
t1 revenues
PW
ED
Quota =
imports
(b) Quota under-filled
Regime 2b
PW + t2
water in tariff
Pd
quota rents
Pod
PW + t1
t1 revenues
PW
under
fill
Imports
ED
Quota
35
Figure 5.3: Out-of-quota imports with and without quota fill
(a) Out-of-quota imports with quota filled
Regime 3a
t2 revenues
quota rents
PW + t2
PW + t1
PW
out-of-quota
imports
t1 revenues
quota
ED
imports
(b) Out-of-quota imports with quota under-fill
Regime 3b
t2 revenues
quota
under-fill
quota rents
PW + t2
PW + t1
t1 revenues
in-quota
imports
PW
out-of-quota
imports
quota
ED
imports
36
Figure 5.3: Out-of-quota imports with and without quota fill (continued)
(c) Out-of-quota and over-quota imports
Regime 3c
t2 revenues
quota rents
PW + t2
PW + t1
PW
Over quota
imports
t1 tariff revenue
quota
implied
quota
ED
imports
out-of-quota imports
37
Figure 5.4: Over-quota imports
Regime 4
PW + t2
water in tariff
quota rents
Pd
PW + t1
PW
t1 tariff revenue
Over quota
imports
quota
ED
implied
quota
38
Table 5.1: Value of Production for TRQ versus non-TRQ Commodities in OECD Countries (year 2000 in mil. $US)
United States
European Union
Japan
Korea
Canada
Mexico
Turkey
Australia
Poland
New Zealand
Switzerland
Hungary
Czech Republic
Norway
Slovakia
Total Production
TRQ Share
Milk
Beef &
Veal
Pigmeat
Poultry
meat
Rice
Wheat
Maize
Oilseeds
Eggs
Other
Grains
Sugar
20,677
34,659
6,058
1,206
2,798
2,715
1,974
1,643
2,103
2,281
1,513
523
524
622
199
79,496
40.6%
31,226
15,959
5,388
2,085
3,660
2,061
1,418
3,320
252
832
675
93
203
283
68
67,522
80.7%
10,791
21,222
4,346
1,852
2,271
1,462
0
450
1,639
67
617
679
462
231
212
46,301
58.1%
16,861
7,906
1,900
644
1,088
2,098
918
617
327
100
114
426
165
77
76
33,318
38.4%
1,061
627
19,827
9,323
0
73
257
169
0
0
3
0
0
0
31,340
95.0%
5,848
11,533
938
1
2,297
531
2,684
2,533
1,005
37
245
363
323
76
101
28,517
59.6%
18,441
4,834
2
31
592
2,840
315
36
96
18
62
448
30
0
34
27,779
29.7%
12,549
2,676
173
251
1,642
23
269
352
178
0
32
83
133
1
40
18,403
4.2%
4,347
3,694
3,589
538
337
1,301
547
213
477
51
89
197
156
57
54
15,648
3.4%
1,557
6,002
267
172
798
773
952
899
700
29
83
89
121
181
39
12,660
2.8%
2,129
4,755
126
0
31
1,283
1,414
389
307
0
98
48
70
0
21
10,671
79.4%
Total
Sheepm
TRQ share
Production
eat
357
3,616
61
31
240
812
703
9
798
36
24
3
82
2
6,774
55.2%
125,845
117,482
42,676
16,103
15,546
15,399
11,562
11,325
7,092
4,213
3,563
2,975
2,190
1,611
847
378,429
42.9%
60.0%
63.3%
89.2%
63.3%
43.8%
0%
0%
90%
0%
43.1%
68.4%
47.3%
100%
47.1%
51.6%
Source: OECD (2003) http://ninetta.sourceoecd.org/vl=4320355/cl=54/nw=1/rpsv/statistic/s1_about.htm?jnlissn=16081056
Note 1: The darkly shaded cells represent tariff quotas while the lightly shaded cells have few tariff quota lines and so are not included as 'TRQs' in this table.
Note 2: The commodities are those covered by the OECD Annual Monitoring Report http://www1.oecd.org/publications/e-book/5103081E.PDF
39
Table 5.2: Value of Trade for TRQ versus non-TRQ Commodities in OECD Countries (year 2000 in mil. $US)
Japan
European Union
United States
Mexico
Korea
Canada
Turkey
Poland
Switzerland
Australia
Norway
New Zealand
Czech Republic
Slovakia
Hungary
Total Imports
TRQ Share
Oilseeds
Beef &
veal
Pig meat
Milk
Maize
Wheat
Poultry
meat
Sugar
Other
Grains
Rice
Sheep
meat
Eggs
1,993
4,347
378
1,144
410
213
233
45
42
58
96
14
24
14
19
9,031
28.6%
2,667
1,093
2,551
783
736
524
0.0
2.1
76
9
13
20
5.8
10
6.6
8,496
59.3%
3,502
172
1,040
338
263
187
0.1
56
72
87
29
23
29
20
32
5,849
11.5%
744
1,217
1,351
630
147
261
33
129
190
157
20
18
60
26
48
5,031
49.8%
1,887
466
174
548
933
170
147
59
10
0.1
3.1
1.7
10
31
11
4,453
45.4%
1,030
634
295
340
471
13
126
95
49
0.6
26
30
3.4
6.6
0.2
3,120
85.2%
1,400
773
48
285
80
221
1.0
15
109
1.0
0.9
13
24
12
5.9
2,989
47.4%
305
863
552
11
293
210
0.9
14
38
1.7
47
51
14
15
2.3
2,419
59.6%
556
49
261
511
56
5.0
8.4
61
17
0.1
6.9
10
12
6.8
9.2
1,569
4.0%
265
419
210
101
46
113
108
25
29
29
10
15
16
8.2
12
1,408
58.4%
68
713
238
46
5.1
48
0.003
0.2
61
0.7
6.5
4.8
0.6
0.0
0.4
1,193
60.4%
20
6.8
2.1
1.4
0.8
3.1
0.3
0.6
11
0.3
0.1
0.3
0.7
0.5
0
47
1.5%
Total
Imports
TRQ
Share
14,438
10,752
7,099
4,739
3,441
1,967
658
502
704
346
259
201
200
149
146
45,603
27.9%
47.7%
62.7%
25.0%
87.0%
51.8%
0%
88.0%
28.0%
0%
77.6%
0%
41.8%
37.4%
46.7%
43.7%
Source: FAO Statistics, Rome http://apps.fao.org/faostat/collections?version=ext&hasbulk=0&subset=agriculture
Note 1: The darkly shaded cells represent tariff quotas while the lightly shaded cells have few tariff quota lines and so are not included as 'TRQs' in this table.
Note 2: The commodities are those covered by the OECD Annual Monitoring Report http://www1.oecd.org/publications/e-book/5103081E.PDF
40
Table 5.3: Value of Trade by Regime (mil $US)
In-Quota Imports
Regime
#
Total % min. Over- Underaccess quota* quota*
Tariff**
Out-ofquota
imports
In-quota
Out-ofquota
Tariff Revenue
In-quota Out-ofquota
Quota
Rents
Tariff Revenue
Trade
(applied
tariffs)
weighted
applied tariffs
In-quota Tariff
Regime 1a
Regime 1b
Total
1,953
1,104
3,057
15.4
75.0
1,161
0
1,161
0
846
846
0
0
0
138%
193%
-
177%
233%
-
1,146
587
1,733
0
0
0
0
0
0
73.7%
50.9%
-
2,003
842
2,845
362
1,706
2,068
3.1
70.4
0
0
0
0
3,064
3,064
0
0
0
29%
40%
-
98%
126%
-
189
248
438
0
0
0
66
233
299
40.6%
42.1%
-
147
716
863
27.5
51.6
15.5
492
1,784
6,029
926
8,739
0
0
206
206
0
12,014
0
12,014
5,487
7,515
988
13,990
24%
27%
41%
-
132%
111%
198%
-
82
773
194
1,049
5,622
12,999
796
19,417
3,827
6,873
810
11,510
82.0%
36.1%
11.8%
-
5,967
4,887
233
11,086
87
7,560
36.9
1,735
821
0
62%
176%
3,411
0
4,182
64.7%
4,888
21,424
41.7
3,102
16,744
13,990
59%
115%
6,631
19,417
15,991
53.5%
19,682
216
224
440
Quota Binding
Regime 2a
Regime 2b
Total
16
86
102
Out-of-quota Tariff
Regime 3a
Regime 3b
Regime 3c
Total
74
386
32
Over-quota Imports
Regime 4
Total
1,121
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
* Over-quota imports are defined as in-quota imports minus quota while under-quota imports equal quota minus in-quota imports.
** This column and the next column refer to simple average official in-quota tariffs and bound out-of-quota tariffs.
41
Table 5.4: Effects of Trade Liberalization on Value of Trade (mil. $)
Regime
35 % reduction
in out-of quota tariffs
%
∆ value
50% increase in quota
∆ value
Minimum
# of TRQs
Value
of Trade
216
224
440
1,953
1,104
3,057
493
426
919
9.1
13.4
-
-
-
16
86
102
362
1,706
2,068
149
97
246
14.8
2.1
-
680
920
1,600
67.8
24.1
-
149
97
74
386
32
492
7,271
13,543
1,914
22,729
5,274
9,128
1,468
15,870
26.2
24.3
27.7
-
85
1,115
129
1,329
1.2
8.2
6.8
-
85
1,115
129
87
7,560
1,215
5.8
2,203
29.1
1,215
1,121
35,414
18,249
51.5%
5,132
14.5%
2,789
%
In-quota Tariff
Regime 1a
Regime 1b
Total
Quota Binding
Regime 2a
Regime 2b
Total
Out-of-quota Tariff
Regime 3a
Regime 3b
Regime 3c
Total
Over-quota Imports
Regime 4
Total
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
42
Table 5.5: Estimates of Water in the Tariff for Selected TRQs
Tariffs (%)
TRQ
#
Canada
2
Canada
3
Canada
1
European U 83
European U 84
European U 38
European U 7
European U 11
European U 64
European U 69
European U 70
Hungary
38
Hungary
41
Hungary
43
Hungary
42
Hungary
46
Hungary
52
Hungary
7
Hungary
2
Hungary
4
Hungary
3
Hungary
5
Hungary
11
Hungary
13
Hungary
16
Hungary
37
Hungary
14
Hungary
30
Hungary
32
Hungary
65
Hungary
45
Iceland
80
Iceland
82
Iceland
83
Iceland
81
Iceland
84
Iceland
87
Japan
14
Japan
1
Japan
2
Japan
3
Japan
4
Korea
42
Korea
41
Korea
63
Korea
1
Korea
10
Korea
12
Korea
15
Korea
19
Korea
49
Korea
21
Norway
224
Norway
173
Norway
228
Norway
91
Norway
93
Poland
69
Poland
27
Slovak Rep 17
Switzerlan 9
Switzerlan 17
United Sta 21
United Sta 2
United Sta 4
United Sta 5
United Sta 8
World
Price
$/unit
Chicken, live, meat and produ 1.65
Turkey, live, meat and produc 2.86
Broiler hatching eggs and chic 2.27
Husked (brown) rice
859
Semi-milled or wholly milled
412
Raw cane sugar, for refining
633
Meat of bovine animals, froz 1,828
Meat of sheep or goats, fresh
3,578
Poultry cuts and offal other th 2,134
Eggs yolks
2,069
Egg albumin
1,893
Wheat
338
Maize (corn)
2,311
Cereal grains
280
Rice
279
Sunflower-seed oil
538
Other sugars
788
Milk and cream
1,488
Bovine animals and meat
1,217
Sheep and goats
3,476
Swine
1,416
Poultry
482
Eggs not in shell
1,178
Potatoes, fresh or chilled
139.89
Cabbages
105.91
Pepper
2,192.12
Tomatoes
357
Grapes
507
Apples, pears
311
Extracts, essences and concen
na
na
Locust beans, seaweeds ..., su
Meat and edible offal of bovine animals
Meat and edible offal of sheep 0.00
Meat and edible offal of sheep 0.00
Meat and edible offal of swin
0.00
7.00
Meat and edible offal of poult
Eggs
16
Wheat, meslin, triticale and th 187.88
2
Skimmed milk powder (schoo
Skimmed milk powder (other
2
Milk powder
na
Evaporated milk
2
Grain sorghum (For seeds)
168
Rice in the husk - ST-Annex 5 0.32
Oil-cake and other solid resid 155.80
Milk cows (Pure-bred breedin 101.04
Other milk and cream, (Evapo 649.00
Birds' eggs (Not in shell/Not d 1,801
Silkworm eggs
0.00
Potatoes (Excluding seed pota
0
Potato Starch...
0
Garlic (Fresh or chilled)...
1
Meat and edible offal of swin
2
Other preserved meat - of turk 4,750.00
4.36
Meat and edible offal of duck
Apples, pears and quinces, fre 722.08
Apples, pears and quinces, fre 722.08
Locust beans, seaweeds and o 15,807.31
Tomatoes, fresh or chilled.
654.35
Other sugars
0.00
Śufs en coquille
1.33
Trois phases - Pommes, poire
0.92
Raw cane sugar
0.41
Milk and cream, fluid or froze 1.34
Dried milk, whether or not co
1.95
Dried milk and dried cream, w 2.25
Milk and cream, condensed o
1.01
In-quota
4.3
5
0.3
31.1
0
0
20
0
0
19.34
11.6
10
3
50
25.0
8
60
30
18
18
20
25
35
10
12
40
12
40
25
60
30
32
32
32
32
32
32
19
0
20
30
30
3
5
5
0
20
30.0
8
30.0
8.0
50.0
137
65
160.0
0.7
1
68
20.0
50.0
25.7
6.4
4.0
0.0
1.5
4.5
2.9
Tariff Equivalent teQ
Out-of-quota
Actual
Max
246
161
238
73.7
123
118
153
92.3
83
38.7
24.1
30.1
26.0
38.4
58
31.6
61.5
51.2
56
26.5
47.2
36
38.3
44.2
32.0
44
46
48
49
51
30
511
372
0
470
529
406
201
174
198.0
0.0
388.3
779
0
63
89
50
42
18
304.0
325.2
360
363
330.5
425
94.3
94.3
148
224.3
28.3
191
86
94
0
40
72
37
298
200
283
73.7
133
118
153
92.3
83
84
79
38.4
32.0
38.4
63.4
39.1
63.8
51.2
72
26.5
51.9
39.0
38.3
44.2
32.0
44
46
51
49
51
30
511
372
220
470.00
529
460
692.50
174.0
198.0
388.3
779
63
89
176
89
18
304
320
360
363
331
425
188
188.0
96.0
40.0
60.0
244
145
94
58
44
72
49
Actual
0.01
0.01
0.2
0.53
0.53
0.87
5.45
1.17
0.84
0.06
0.06
0
-0.2
-0.07
0.00
-0.11
0.10
0.3
0
0
0
0
2
0
0
0.00
0.00
0.00
0.00
0.00
0.00
0.99
0.13
0.13
0.18
4.36
2.14
2.80
2.75
2.75
2.75
2.75
2.39
4
1
1.82
1.82
0.14
0.14
0
0
0.28
0.2
1.72
1.72
0.00
0.00
0.95
0.00
0.39
3.28
0.00
1.32
0.93
0.93
0.93
0.93
Assumed
Average Max
1.25
0.83
1.19
0.52
0.62
0.59
0.86
0.46
0.42
0.29
0.18
0.20
0.15
0.44
0.41
0.20
0.61
0.41
0.37
0.22
0.34
0.30
0.37
0.27
0.2
0.42
0.29
0.44
0.37
0.56
0.30
2.7
2.02
0.16
2.51
2.81
2.19
1.10
0.87
1.09
0.15
2.09
3.91
0.03
0.34
0.45
0.35
0.36
0.13
1.67
1.67
2.05
2.50
1.98
2.93
0.48
0.48
1.08
1.22
0.39
1.08
0.46
0.49
0.00
0.21
0.38
0.20
1.51
1.02
1.42
0.52
0.67
0.59
0.86
0.46
0.42
0.52
0.45
0.24
0.18
0.44
0.44
0.24
0.62
0.41
0.45
0.22
0.36
0.32
0.37
0.3
0.2
0.42
0.29
0.46
0.37
0.56
0.30
2.71
2.02
1.26
2.51
2.81
2.46
3.56
0.87
1.09
0.15
2.09
3.91
0.03
0.34
0.45
0.98
0.60
0.13
1.67
1.64
2.05
2.50
1.98
2.93
0.94
0.94
0.82
0.30
0.55
1.35
0.76
0.49
0.29
0.23
0.38
0.26
Water in the Tariff
Actual
Average Max
2.45
1.6
2.18
0.2
0.7
0.32
-3.92
-0.25
-0.01
0.33
0.18
0.31
0.42
0.45
0.58
0.43
0.52
0.25
0.42
0.43
0.69
0.24
-1.14
0.2
0.3
0.44
0.46
0.48
0.49
0.51
0.30
4.11
3.59
-0.13
4.52
0.94
1.92
-0.79
-1.01
-0.77
-2.75
1.13
5.40
-4.09
0.01
-0.93
-1.33
0.27
0.04
3.04
3.25
3.32
3.39
1.58
2.53
0.94
0.94
0.53
2.24
-0.11
-1.37
0.86
-0.38
-0.93
-0.54
-0.22
-0.56
2.97
1.98
2.63
0.2
0.8
0.32
-3.92
-0.25
-0.01
0.78
0.73
0.40
0.48
0.45
0.63
0.50
0.54
0.25
0.57
0.43
0.73
0.27
-1.14
0.2
0.3
0.44
0.46
0.51
0.49
0.51
0.30
4.11
3.59
2.07
4.52
0.94
2.46
4.13
-1.01
-0.77
-2.75
1.13
5.40
-4.09
0.01
-0.93
-0.06
0.75
0.04
3.04
3.20
3.32
3.39
1.58
2.53
1.88
1.88
0.01
0.40
0.21
-0.83
1.45
-0.38
-0.36
-0.49
-0.22
-0.44
Error
Assumed
Average Max
1.21
0.78
1.19
0.21
0.62
0.59
0.66
0.46
0.42
0.10
0.06
0.10
0.12
-0.06
0.16
0.12
0.01
0.11
0.19
0.05
0.14
0.05
0.02
0
0
0.02
0.17
0.04
0.12
-0.04
0.00
2.39
1.70
-0.16
2.19
2.49
1.87
0.91
0.87
0.89
-0.15
1.79
3.88
-0.03
0.29
0.45
0.15
0.06
0.05
1.37
1.59
1.55
1.13
1.33
1.33
0.47
0.47
0.40
1.02
-0.11
0.83
0.40
0.45
0.00
0.19
0.34
0.17
1.47
0.97
1.42
0.21
0.67
0.59
0.66
0.46
0.42
0.32
0.34
0.14
0.15
-0.06
0.19
0.16
0.02
0.11
0.27
0.05
0.16
0.07
0.02
0
0
0.02
0.17
0.06
0.12
-0.04
0.00
2.39
1.70
0.94
2.19
2.49
2.14
3.37
0.87
0.89
-0.15
1.79
3.88
-0.03
0.29
0.45
0.78
0.30
0.05
1.37
1.56
1.55
1.13
1.33
1.33
0.94
0.94
0.14
0.10
0.05
1.09
0.70
0.45
0.29
0.21
0.34
0.23
Average Max
-1.24
-0.82
-0.99
0.01
-0.08
0.28
4.58
0.71
0.42
-0.23
-0.12
-0.21
-0.31
-0.51
-0.41
-0.31
-0.51
-0.14
-0.22
-0.39
-0.55
-0.18
1.16
-0.1
-0.2
-0.42
-0.29
-0.44
-0.37
-0.56
-0.30
-1.72
-1.89
-0.03
-2.33
1.55
-0.05
1.70
1.88
1.66
2.60
0.66
-1.52
4.07
0.28
1.37
1.47
-0.21
0.01
-1.67
-1.67
-1.77
-2.26
-0.25
-1.20
-0.48
-0.48
-0.13
-1.22
0.00
2.19
-0.46
0.83
0.93
0.73
0.55
0.73
-1.50
-1.01
-1.22
0.01
-0.13
0.28
4.58
0.71
0.42
-0.46
-0.39
-0.25
-0.34
-0.51
-0.44
-0.35
-0.52
-0.14
-0.30
-0.39
-0.57
-0.20
1.16
-0.1
-0.2
-0.42
-0.29
-0.46
-0.37
-0.56
-0.30
-1.72
-1.89
-1.13
-2.33
1.55
-0.32
-0.76
1.88
1.66
2.60
0.66
-1.52
4.07
0.28
1.37
0.84
-0.45
0.01
-1.67
-1.64
-1.77
-2.26
-0.25
-1.20
-0.94
-0.94
0.13
-0.30
-0.16
1.93
-0.76
0.83
0.65
0.70
0.55
0.67
43
Table 5.6: Value of In-quota Trade and Fill Rates by TRQ Administration Method (mil. $US)
Administration Method
Applied Tariff
Licenses on Demand
First-Come, First-Served
Historical Importers
Auctioning
State Trading Enterprises
Mixed Allocation
Non-Specified
Total
# of
TRQs
Share (%)
#
value
Quota fill < 20
#
Value
Quota fill ≥100
Fill Rate (%)
Simple Weighted
#
Value
Weighted
fill rate (%)
Total In-quota Imports
Value
Fill Rate (%)
Truncated Weighted
Quota
underfill
(Net)
Tariffs (%)
In-quota
Out-ofquota
440
310
138
105
60
29
11
28
39.3
27.7
12.3
9.4
5.4
2.6
1.0
2.5
14.4
18.1
16.8
18.8
0.5
12.2
4.6
14.9
104
129
56
18
24
3
0
5
91
94
145
14
1
0
0
39
5.0
3.8
3.8
4.7
4.2
1.1
0
5.5
12.1
1.3
3.7
1.0
5.6
1.1
0
8.6
230
63
37
44
8
10
8
7
1,982
2,340
878
2,927
7
1,028
945
885
241
141
107
146
120
897
114
100
3,057
3,874
3,581
4,026
116
2,585
985
3,200
68
48
52
73
46
79
91
65
111
34
46
85
75
152
111
56
-315
7,635
4,151
679
39
-886
-96
2,545
166
35
20
37
56
31
40
23
206
110
72
143
210
286
200
150
1,121
-
100
339
384
4.0
-
407
10,993
-
21,424
60.6
60.9
13,753
59
115
Note 1: "Simple" refers to the simple average fill rate defined as the average of the ratios of the value of in-quota imports over the value of the quota (can be > 100 percent if over-quota
imports dominate under-fill)
Note 2: "Truncated" is the simple average fill rate as defined above except it takes a maximum value of 100 percent (ignores over-quota imports)
Note 3: "Weighted" refers to the trade weighted fill rate defined as the sum of the value of in-quota imports divided by the sum of the value of the quota (can be > 100 percent)
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
44
Table 5.7: Value of In-quota Trade and Fill Rates by TRQ Additional Regulation (mil. $US)
Additional Regulation
Time Limit
Past Trading Performance
Limit per Firm
Seasonal
Domestic Purchase Requirement
Provision for entry
Use it or Lose it
Export Certificate
License Fee
Provision for Unused Licenses
Non-Use Penalty
Refundable Down Payment
No Description
None of Above were Identified
Total
# of
TRQs
247
170
133
101
44
30
35
26
26
23
13
4
422
173
1,447
Share (%)
#
Value
17.1
11.7
9.2
7.0
3.0
2.1
2.4
1.8
1.8
1.6
0.9
0.3
29.2
12.0
Quota fill < 20
Fill Rate (%)
# Value
Simple Weighted
25.7
12.9
2.4
0.5
6.6
4.1
1.6
12.0
2.2
0.4
0.2
0.1
13.3
17.9
76
53
48
49
4
5
14
6
8
10
3
1
109
46
66
174
30
39
1
0
2.7
5.2
17
1.4
0
0
131
20
5.1
5.6
4.5
3.7
7.4
0.0
2.5
3.5
10.0
6.2
6.2
3.6
4.7
2.6
100
432 489
4.0
1.84
2.72
0.92
0.99
3.26
0.00
6.02
0.45
1.35
10.87
17.61
0.00
6.37
2.52
#
Quota fill ≥100
Weighted
Value
fill rate (%)
78
36
14
8
25
16
15
6
14
1
3
0
205
63
4,865
1,050
148
28
1,692
942
468
2,782
347
0
44
0
1,349
2,643
484
16,361
127
131
134
100
207
100
119
136
207
0
113
0
372
147
Tariffs (%)
Total In-quota Imports
Quota
Fill Rate (%)
under-fill In-quota Out-of-quota
Value
Truncated Weighted
7,686
3,783
851
150
1,946
1,203
479
3,519
654
111
45
25
3,886
5,256
60.9
56.9
52.7
40.6
78.5
75.7
54.3
59.6
68.6
40.3
64.2
53.9
64.4
63.2
69.5
37.4
17.6
3.6
143.8
92.2
106.5
77.4
36.5
46.1
111.2
0.0
54.7
93.2
3,313
6,336
3,330
3,992
-593
102
-29
1,025
1,141
129
-5
22
3,222
380
20.5
23.9
31.3
26.8
86.6
21.8
20.7
13.3
37.6
239.6
31.1
30.0
169.4
35.0
129.6
105.1
101.6
49.8
183.9
193.0
94.7
128.9
92.3
400.5
55.8
49.5
212.4
93.3
29,592
60.6
60.9
22,365
59
115
Note 1: "Simple" refers to the simple average fill rate defined as the average of the ratios of the value of in-quota imports over the value of the quota (can be > 100 percent if over-quota
imports dominate under-fill)
Note 2: "Truncated" is the simple average fill rate as defined above except it takes a maximum value of 100 percent (ignores over-quota imports)
Note 3: "Weighted" refers to the trade weighted fill rate defined as the sum of the value of in-quota imports divided by the sum of the value of the quota (can be > 100 percent)
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
45
Table 5.8: Fill Rate by Administration Method and Additional Regulation (most recent year reported) (mil. $)
Additional Regulation
time limit
past trading performance
limit per firm
seasonal
domestic purchase requirement
provision for entry
use it or lose it
export certificate
license fee
provision for unused licenses
non-use penalty
refundable down payment
no description
none of above were identified
Total
# of
TRQs
#
247
170
133
101
44
30
35
26
26
23
13
4
422
173
0
11
7
0
1
0
0
0
11
6
1
0
369
41
1,447
Applied Tariff
Weighted
Value
fill rate (%)
723
37.6
19.0
0
16.9
0
0
0
37.6
1.6
44.0
0
1,402
851
447 3,132
97.9
145
96.1
0
110
0
0
0
145
18.5
113
0
124
108
Licenses on demand
Weighted
# Value
fill rate (%)
85
104
75
100
30
3
26
18
0
4
1
4
22
22
2,321
963
197.8
149.7
729.9
5.7
229.7
1,299
0.0
101.2
0.7
24.8
150.7
217.8
494
6,392
49.0
22.8
5.8
3.6
121.0
81.2
97.0
48.1
0
46.9
82.7
0
13.1
44.4
First-come, first-served
Weighted
# Value
fill rate (%)
46
18
17
1
1
0
1
5
0
0
0
0
1
59
200
260
184
0.1
44
0
0.1
238
0
0
0
0
1
2,830
49.3
7.9
75.8
1.1
98.2
0
1.1
55.0
0
0
0
0
0
81.1
149 3,758
#
Auction
Weighted
Value
fill rate (%)
4
0
22
0
1
0
0
0
0
10
0
0
11
22
0.4
0
14.8
0.0
1.4
0
0
0
0
4.8
0.0
0.0
6.5
93.1
70
121
13.2
0
60.1
0.0
100
0
0
0
0
41.7
0.0
0.0
0.0
82.0
Historical importer
Weighted
Value
#
fill rate (%)
STEs and producer groups
Weighted fill
Value
#
rate (%)
71
32
10
0
0
23
8
3
15
3
11
0
3
18
3,224
1,022
272.7
0
0
291.6
249.3
1,981
616.7
3.0
0.4
0.0
101.2
435.8
14
4
0
0
1
0
0
0
0
0
0
0
0
10
98.9
1,497
0
0
396.9
0
0
0
0
0
0
0
0
592.0
197
8,198
29
2,585
83.1
96.5
88.9
0
0
74.6
120.5
140.7
34.9
77.1
44.0
0.0
148.7
102.5
121.0
99.7
0
0
2,164
0
0
0
0
0
0
0
0
607.8
Note 1: "Simple" refers to the simple average fill rate defined as the average of the ratios of the value of in-quota imports over the value of the quota (can be > 100 percent if over-quota
imports dominate under-fill)
Note 2: "Truncated" is the simple average fill rate as defined above except it takes a maximum value of 100 percent (ignores over-quota imports)
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
46
Table 5.9: Value of TRQ Trade by Country (mil. $)
Country
# of
TRQs
In-quota
Out-of-quota
Quota under-fill
(net)
Fill Rate %
Imports
Truncated Weighted
Tariffs %
In-quota
Out-of-quota
Australia
2
90.0
100
65.7
86.1
0.3
9
25
Barbados
5
80.0
69
0.6
0.0
0.3
125
125
Brazil
1
100.0
2,824.8
177
0
-170
13.5
29
Bulgaria
62
40.2
37.1
115
46.2
196
25.9
71
Canada
20
85.0
106.5
703
183
-42.6
4.0
179
Chile
0
0
0
0
0.0
0
0
0
China
10
29.5
29.7
2,338
214
5,533
0
0
Chinese Taipei
22
60.6
72.1
98
56.6
37.9
0
0
Colombia
56
74.9
187
952
40
-444
133
135
Costa Rica
10
29.5
184.6
14.8
1.8
-6.8
47.5
111
Croatia
0
0
0
0
0.0
0.0
0
0
Czech Rep.
24
54.5
49.1
72
93.9
75.0
28.4
49.1
Dominican Rep.
7
73.8
140
65
0
-18.6
0
0
European Union
72
56.0
71.9
4,500
7,710
1,759
15
67
El Salvador
11
67.0
44
52.3
4.2
66
34.1
68.4
Ecuador
8
53.1
14.9
10.2
52.3
58.2
28.6
42.0
Guatemala
22
81.9
149
146
15.3
-48.2
31
121
Hungary
65
47.6
2
81
391
3,619
25.3
40.1
Iceland
49
82.8
66.5
21.4
4
10.8
32.4
187.0
65
185
Indonesia
2
100
584
659
0
-546
Israel
0
0
0
0
0
0
0
0
Japan
18
69.6
89.5
1,851
415
218
20.2
536
Korea
67
68.1
78.7
1,807
1,746
488
19.8
277
Latvia
3
33.4
7.9
0.2
0.5
1.8
25.0
47
Lithuania
0
0
0
0
0
0
0
0
Malaysia
16
40.4
53
107
16.0
93.4
103
233
Mexico
11
87.4
122
887
0
-158.4
45.5
152
Morocco
3
100.0
100
185
1.2
0.0
115
115
New Zealand
3
33.7
1.7
1.1
0.0
65.6
0
6.1
Nicaragua
8
91.5
0
52
0
-51
42.5
66.9
219
63.7
96.2
194
111.0
7.8
296
319
Norway
Panama
19
49.4
88.2
29.0
3.7
3.9
15.0
84
Philippines
13
65.6
45.8
0.4
296
0.4
34.6
35.4
Poland
36
26.4
4.7
61
267
1,244
37.0
81
Romania
7
9.6
4.5
2.0
0.9
41.9
97
249
Slovak Rep.
24
33.4
28.9
19.0
131
46.9
28.2
41.9
Slovenia
20
37.9
112
46
38
-5.1
18
67
South Africa
42
66.6
85.5
217
77
37
20
60.2
Switzerland
27
89.4
105.6
1,581
10
-83.5
41
205
Thailand
23
40.3
166
688
68.8
-273
28.4
97.9
Tunisia
13
58.5
82.0
186
106
40.8
25.9
99.6
United States
41
70.1
79.6
2,508
1,075
613
7
64
Venezuela
60
58.7
40.9
929
727
1,345
36.9
101
1121
60.6
60.9
21,424
13,990
13,753
59
115
Total
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/
agric_e.htm and Agricultural Market Access Database (AMAD) http://www.amad.org/
47
Table 5.10: Value of Trade by Commodity (mil.$)
Commodity
Fill Rate (%)
# of
TRQs Truncated Weighted
Tariffs (%)
Under-fill
In-quota
Quota
Overquota
Out-ofquota
Total
Net
In-Quota
Out-of-Quota
Beverages
Cereals
Coffee, tea …
Dairy products
Eggs and egg products
Agricultural Fibers
Fruit and Vegetables
Meat products
Other agricultural products
Oilseeds products
Sugar and sugar products
Tobacco
27
185
44
144
19
12
281
205
45
106
42
11
43
58
62
63
34
41
66
52
55
67
67
76
16
53
92
78
21
48
64
76
55
75
89
78
536
5,420
128
2,402
77
932
3,160
3,900
70
2,775
1,574
451
3,283
10,197
138
3,048
359
1,950
4,937
5,099
128
3,689
1,771
579
0.5
1,027
31
318
10
78
309
270
21
882
72
84
90
4,372
101
715
8
246
2,903
4,153
79.7
288
961
72
2,747
5,804
41.2
964
293
1,096
2,086
1,469
78
1,796
269
212
2,746.8
4,777
10.1
646
283
1,018
1,777
1,199
57
915
197
128
66
91
48
57
75
17
110
105
145
46
55
110
114
155
121
152
126
101
170
174
255
115
104
337
Total
1121
60.6
60.9
21,424
35,178
3,103
13,990
16,856
13,753
59.0
115.0
Note 1: "Simple" refers to the simple average fill rate defined as the average of the ratios of the value of in-quota imports over the value of the quota (can be > 100 percent if
over-quota imports dominate under-fill)
Note 2: "Truncated" is the simple average fill rate as defined above except it takes a maximum value of 100 percent (ignores over-quota imports)
Note 3: "Weighted" refers to the trade weighted fill rate defined as the sum of the value of in-quota imports divided by the sum of the value of the quota (can be > 100 percent)
Sources: WTO notifications and International Data Base (IDB) http://www.wto.org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
48
Table 5.11: Changes in Administration Methods
Away From (1995)
To (most recent)
# of TRQs
Applied tariffs (AT)
Historical Importers
Licenses on Demand
Mixed Allocation
Auctioning
Total
36
20
7
1
64
Licenses on demand (LD)
Applied Tariff
Historical Importers
Auctioning
Mixed Allocation
Other
10
3
2
2
2
Producer Groups
Total
2
21
Historical Importers (HI)
Applied Tariff
Producer Groups
Mixed Allocation
Licenses on Demand
Total
3
1
1
1
6
Other (OT)
Historical Importers
Total
5
5
Mixed (MX)
Applied Tariff
Licenses on Demand
Total
1
3
4
State Trading (STE)
Licenses on Demand
Total
3
3
Auction (AU)
Licenses on Demand
Total
2
2
Producer Group (PG)
Licenses on Demand
State Trading Enterprises
Total
1
1
2
Not specificed (NS)
Applied Tariff
Licenses on Demand
Total
Applied Tariff
Total
1
1
2
1
1
First come first served (FC)
Total number of changes
110
Increases in Administration Methods
Method
Historical Importers
Licenses on Demand
Applied Tariff
Mixed Allocation
Producer Groups
Auctioning
Other
State Trading Enterprises
Non-Specified
First-Come, First-Served
Total
Number of increases in
44
31
16
10
3
3
2
1
0
0
110
Sources: WTO notifications and International Data Base (IDB) http://www.wto.
org/english/tratop_e/agric_e/agric_e.htm
Agricultural Market Access Database (AMAD) http://www.amad.org/
49
Table 5.12: STE, Domestic Policy Responses and Rice Tariff Quota in Japan
Year
1995-96
1996-97
1997-98
1998-99
1999-2000
2000-01
2001-02
2002-03
Minimum Access Imports
Rate2
Quantity
Rate1
(1000 tonnes)
(%)
(%)
43
51
60
68
72
77
77
77
4.0
4.8
5.6
6.4
6.8
7.2
7.2
7.2
4.2
5.0
5.9
6.9
7.3
7.9
8.0
8.1
Supply to Domestic Markets
Private
Total
(1000 tonnes)
12
31
23
38
34
37
34
25
STE
Exports as
Food Aid
EndingStock Flow Period Stocks
Quota Rents3
Total
Private4
Acreage
Control
% of quota
(1000 tonnes)
(1000 tonnes)
(1000 tonnes)
(1000 tonnes)
(1000 tonnes)
mil. $
(%)
(%)
27.9%
60.8%
38.3%
55.9%
47.2%
48.1%
44.2%
32.5%
1
1
5
12
12
12
10
10
11
30
18
26
22
25
24
15
0
12
34
28
26
21
23
20
31
8
3
2
12
19
20
32
31
39
42
44
56
75
95
127
33.7
27.9
47.2
60.8
70.8
78.7
77.5
75.8
8.4
9.7
28.8
74.8
56.3
47.6
37.9
36.3
24.3
28.5
28.7
34.8
35
35.2
37.2
37.4
1. Rate of base period consumption
2. Rate of current period consumption
3. In-quota and out-of-quota tariffs are zero
4. Rents to private traders are higher than share of import quota because of higher quality imports that have higher margins
Source: Takayuki Kimura
50
51