Flexible and welfare consistent tariff aggregation
ETSG Annual Meeting 2014, Munich
Mihaly Himics, Wolfgang Britz
ILR – University of Bonn, Germany
13.09.2014
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Aggregation in applied modelling is inevitable
1. Data availability issue
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Trade policies are typically available at the tariff line
BUT not other crucial information, e.g. commodity balances
2. Numerical problem
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Numerically infeasible to calculate over tariff lines and bilateral
trade globally
3. Management problem
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costly to maintain, validate, analyse results, etc.
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The background
Ko, J.-H. and Britz, W. (2013) “ Does Regional and
Sectoral Aggregation Matter? Sensitivity Analysis in
the Context of an EU-South Korea FTA”
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Impact assessment of the EU-South Korea FTA
Different geographical representation for the EU
Using two different equilibrium models:
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GTAP, Computabel General Equilibrium (CGE) model
CAPRI, partial multi-commodity/multi-market (PE)
equilibrium model
Main finding: the estimated impact increased with the
regional disaggregation of the EU
“We find these results disturbing. Obviously, it is possible
to increase trade and welfare effects [. . . ] by increasing
the dis-aggregation.”
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Is that effect really systematic?
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The context
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Having a bias introduced by aggregation is not new
E.g. endogeneity bias for trade weighted averages:
P
mi ti
τ = Pi
w
i mi pi
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tariff ↑, weight ↓ ⇒ underestimated border protection
several dimensions of aggregation: commodities (tariff lines),
geographical and intertemporal
Here we observe the bias from a specific angle:
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EU is a large country group, but still homogeneous in terms of
trade policies
Large differences in export composition among the EU
countries
⇒ aggregated tariffs on EU exports varies by member states
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Research objective
Define a tariff aggregation that is (1) welfare-consistent
and (2) flexible with respect to the geographical
representation of the EU
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Flexible: invariant to geographical resolution
Welfare-consistent: invariant in terms of the welfare definition
in the modelling framework
All applies in the general equilibrium framework
Why welfare?
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to narrow down the subject to one specific model outcome
might be a proxy for negotiation outcomes
If found, would this tariff aggregator answer the original
question?
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yes. ⇒ regional aggregation does matter.
more precisely: it is the tariff aggregation technique that
matters.
⇒ conventional trade weighted averages introduce a bias in
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flexible regional aggregation
Flexible regional aggregation?
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Customize global models for the specific purpose of a
simulation (e.g. trade agreement)
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Largely facilitated in the last decade by:
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change easily the regional structure in model databases
→ aggregate model inputs in a flexible way (commodity
balances, prices, trade policy instruments)
flexible equation structure
improved global statistical databases
more efficient software
more computational power
But current aggregation softwares (GTAPAgg, TASTE) base
their tariff aggregation routines on fixed weight aggregators
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⇒ inherit the endogeneity bias
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Starting points for our research (1)
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Anderson and Neary’s (1994) Trade Restrictiveness Index
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Equivalence measure of trade restrictions
Overcomes the endogeneity bias by assuming particular
behavioural structures
Start with a trade balance (E (p, v , u) = e(p, u) − r (p, v )) :
B(p, v , u, p ∗ ) ≡ E (p, v , u) − (p − p ∗ )0 Ep = b
| {z } |
{z
}
expenditure
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tariff. rev.
. . . allowing us to define a compensating variation measure of
welfare impacts:
∆B = B(p 1 , u 0 ) − B(p 0 , u 0 )
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“How much money we would have to give to consumers to get
them back to the same utility level after trade reforms”
Make utility exogenous and define TRI as a uniform tariff that
does not alter welfare accidentally:
t ∆ : B((1 + t ∆ )p ∗ , v , ū) = B(p, v , ū)
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Handles NTMs, too
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Starting points for our research (2)
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Bach and Martin (2001) ‘Would the Right Tariff Aggregator
for Policy Analysis Please Stand Up?’
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Welfare consistent tariff aggregator(s) in the general
equilibrium framework
Simplified balance of trade condition: domestic production is
indepent of trade policies −→ eliminated from b.o.t.
One aggregator for the expenditure function, one for the tariff
revenues:
t e , t tr : B(p, v , u, p ∗ ) = e((1 + t e )p ∗ , v , u) − (t tr p ∗ )0 ep
{z
} | {z }
|
expenditure f.
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tariff rev.
Anderson (2009): further simplification for calculating the
tariff aggregators
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combination of two tariff aggregators in the balance of trade
condition
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What we already answered with our research. . .
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Can we make the Anderson framework suitable for flexible
regional aggregation? Yes!
Can we include other trade barriers than simple tariffs? Yes!
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Introduction of Tariff Rate Quotas (TRQ)
TRQ defines a preferential (lower) tariff rate up until a quota
is filled → generates economic rent
Empirical application to the Korean dairy market
By splitting up the exporter region, the technique is suitable
for analysing bilateral FTAs
First includes explicit TRQ mechanism in consistent tariff
aggregation (important on agrifood markets)
The basic idea is to apply a combination of six tariff
aggregators in a modified balance of trade condition:
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Extended ‘balance of trade’ condition
E(
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X
ϕn (p ∗ )
ϕ1 (p ∗ )
ϕr (p ∗ ) a
,
.
.
.
,
,
u)
−
E
(Tr + TrR )
ϕ
r
δ
1 − Tnδ
1
−
T
1 − T1δ
r
r
X
ϕr (p ∗ ) a,corr
−
Eϕr
(Tr
+ TrR,corr ) + Tq = b
δ
1
−
T
r
r
(ϕ1 , . . . , ϕn ) : regional aggregator functions
Tiδ : true average tariff (regionally extended)
Tia : trade weighted average tariff
TiR , TiR,corr : terms covering quota rent under TRQ
Tia,corr : correction term for trade weighted average tariff (out
of quota)
Tq : correction term for trade weighted average tariff (in
quota)
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Empirical example
Korean dairy market in the EU-South Korea FTA
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First of the EU’s so called comprehensive trade agreements
EU is the 3rd largest supplier of dairy products (14% market
share, following the US and New Zealand)
Korean dairy market is heavily protected by TRQs
The FTA includes gradual tariff reduction and TRQ expansion
for dairy products over 16 years
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Model structure
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Small country equilibrium model both (1) at the tariff line and
(2) using product aggregation
Nested Armington approach for modelling imports (2-level
CES nest, product differentiation)
21 HS6 tariff lines, 12 of them are protected by TRQ
21 tariff lines + domestic good (dairy) aggregated into one
single consumption composite good
Rest of the World is split into: EU (4 biggest exporter + Rest
of EU), other countries agg.
Simulations under fix utility → compensating variation
measure for welfare changes
Simulations for two selected years: 2016,2026
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Demand structure
Composite Good
U1 = u1 (D, U2 )
Domestic good (D)
Imported Composite
U2 = u2 (x1 , . . . , xn )
x1
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x2
...
xn
D : domestic good (dairy)
xi : dairy products at the tariff line (imported goods)
U2 : imported composite good
Separable homotheticity assumed throughout (CES)
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Results I. Derived tariff aggregators
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True Average Tariff:
Would imply the same change in consumer
expenditures as the single tariff lines
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Tariff revenue aggregator
Would imply the same change in tariff revenues as
the single tariff lines
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Trade weighted aggregator
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weighted with actual trade shares
MacMap-type aggregator
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underlying e.g. the GTAP database
corrects endogeneity bias with a heuristic rule
quota regimes (underfilled, filled and prohibitive, overfilled)
based on quota fill rate
fill rate (95%, 99%) then applied tariff is halfway between inand out-of-quota rate
sets quota rents arbitrarily
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Derived tariff aggregators (results)
True Average Tariff
(Anderson ext.)
Tariff revenue agg.
(Bach-Martin)
Trade weighted agg.
(Anderson ext.)
MacMap-type agg.
2010
Belgium
Germany
France
Netherlands
Rest of EU
EU
131%
152%
68%
88%
61%
109%
Belgium
Germany
France
Netherlands
Rest of EU
EU
118%
137%
48%
64%
34%
101%
Belgium
Germany
France
Netherlands
Rest of EU
EU
97%
129%
39%
46%
26%
95%
79%
47%
52%
22%
34%
26%
40%
69%
73%
31%
47%
38%
79%
39%
42%
11%
20%
10%
34%
56%
58%
15%
25%
14%
68%
25%
36%
6%
7%
5%
29%
39%
50%
8%
10%
9%
60%
2016
66%
2026
54%
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Simulated welfare results at the tariff line
Total consumer expenditure, at dometic p.
Expenditure on imports, domestic p.
Expenditure on imports, world p.
Expenditure on domestic good, domestic p.
Tariff revenues, at dometic p.
Quota rents, at dometic p.
Balance of trade*
TRI
Mio.EUR
Mio.EUR
Mio.EUR
Mio.EUR
Mio.EUR
Mio.EUR
Mio.EUR
%
2010
2016
2026
1003
727
439
276
277
11
439
186%
976
715
469
262
235
11
454
198%
954
704
498
250
196
10
471
211%
* A decrease would indicate welfare improvement.
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Reproducing welfare changes at the aggregate level (test)
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Is our approach really consistent with regard to welfare
impacts? Difference to ‘true’ values
Domestic expenditure
Import expenditure
Consumer expenditure
Gov. revenue
Balance of trade
from
Belgium
Germany
France
Netherlands
Rest of EU
Rest of the World
Total
from
Belgium
Germany
France
Netherlands
Rest of EU
Rest of the World
Total
MacMap type
(uniform across exporters)
MacMap type
(different across exporters)
Anderson’s combination
Anderson’s combination
regional extension
-23%
-24%
0%
0%
17%
51%
-63%
-50%
-73%
5%
-8%
45%
82%
16%
20%
-14%
-26%
-9%
27%
64%
-60%
-46%
-70%
15%
0%
0%
0%
0%
0%
0%
0%
0%
-12%
-13%
0%
0%
20%
46%
30%
2%
11%
4%
8%
32%
59%
28%
22%
9%
-15%
-4%
11%
35%
21%
-6%
3%
-3%
0%
0%
0%
0%
0%
0%
0%
0%
-31%
-25%
0%
0%
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Under/over-estimation of welfare results
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Literature usually finds underestimation of welfare gains using
conventional tariff aggregators
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Laborde et al. (2011): welfare gains from global trade lib.
are underestimated by 76% (in real income terms, using the
LINKAGE CGE model)
Anderson (2009): efficiency gains from a unilateral trade
lib. in India are dramatically underestimated (1/4 to
1/50th of true gains), using two-country CGE and similar
approach as ours
In our special setting (lot of quota expansions) the
MacMap-type aggregators overestimate welfare gains (!)
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Fix import shares combined with quota expansion −→ big drop
in applied rates −→ overestimation of liberalization impacts
again, the main reason is the aribtrarily set quota rents
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Conclusions
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Deriving welfare-consistent tariff aggregators is numerically
feasible even for larger equilibrium models
The Anderson approach is flexible enough to handle both
heterogeneous exporter regions and complex (non-tariff)
trade policies
Our aggregation technique is an alternative to the current
approaches for flexible regional aggregation (GTAPAgg,
TASTE) if welfare impacts are of special interest
Further research
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Applicability in CGE models
Relaxing strong behavioural assumptions on the supply side
Exploring necessary conditions for welfare consistent
aggregation
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References
Anderson, James E., and J. Peter Neary. (1994)
Measuring the Restrictiveness of Trade Policy.
The World Bank Economic Review 8 (2): 15169.
Anderson, James E. (2009)
Consistent Trade Policy Aggregation*.
International Economic Review 50 (3): 90327.
Bach, Christian F, and Will Martin. (2001)
Would the Right Tariff Aggregator for Policy Analysis Please Stand Up?
Journal of Policy Modeling 23 (6): 62135.
Horridge, Mark. (2008)
GTAPAgg: Data Aggregation Program (Chapter 5).
In Global Trade, Assistance, and Production: The GTAP 7 Data Base.
Horridge, Mark, and David Laborde. (2008)
TASTE a Program to Adapt Detailed Trade and Tari...
In 11th Annual Conference on Global Economic Analysis, Helsinki, Finland.
Laborde et al. (2011)
Measuring the Impacts of Global Trade Reform with Optimal Aggregators of Distortions
Discussion Papers.
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Sensitivity analysis
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Sensitivity analysis
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