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University of New South Wales
School of Economics
Honours Thesis
Should the United Kingdom leave the European Union?
An analysis under different tariff arrangements
Author:
Luka Raznatovic
Student ID: 3418433
Supervisor:
Dr. Sang-Wook (Stanley) Cho
A.Prof Valentyn Panchenko
Bachelor of Economics (Honours)
3rd November, 2015
Declaration
I hereby declare that this thesis is my own original work, and to the best of my
knowledge, does not contain material or content by other authors except where I
have rightly acknowledged otherwise. This Honours Thesis has not been submitted
for the award of any other degree or diploma at the University of New South Wales,
or at any other educational institution.
Luka Raznatovic
November 2nd 2015
i
Acknowledgements
I would firstly like to thank my dedicated supervisor, Dr. Stanley Cho. His patience,
interest and knowledge in all related to the production of my Honours Thesis has
provided me with the strongest basis to complete this work. I want to specifically
thank him for the time he took out of his day for our meetings, in which he would
assist and guide me with my Thesis. His hard work did not go unnoticed and
has been immensely appreciated. A special thanks goes out to A. Prof Valentyn
Panchenko for his helpful comments and suggestions in the writing of this thesis.
I would also like to thank Dr. Tess Stafford, Dr. Evgenia Dechter, Dr. Scott
French, A. Prof Glenn Otto and Dr. Gabriele Gratton whose critiques and advice
of my presentation provided me with a fresh outlook on the direction of my thesis.
This helped in the expansion and development of the content of my thesis.
With this, I would like to thank the School of Economics for granting me the Honours
Scholarship. This financial help has been greatly appreciated over the course of this
Honours year. To the Economics Honours cohort of 2015, thank you for a great year.
Finally, I would like to thank my family. Their support throughout the year has
been nothing less than astounding and understanding.
ii
Contents
Declaration i
Acknowledgements ii
Table of Contents ii
Abstract viii
1 Introduction 1
2 Background 5
2.1 Possible Exit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 The UK-EU Trade Relationship . . . . . . . . . . . . . . . . . . . . . 5
3 Literature Review 8
3.1 Alternative Trade Scenarios . . . . . . . . . . . . . . . . . . . . . . . 8
3.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.3 United Kingdom Study . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Model 14
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.2 Domestic production firms . . . . . . . . . . . . . . . . . . . . . . . . 14
4.3 Final production goods firms . . . . . . . . . . . . . . . . . . . . . . . 15
4.4 Consumption goods firms . . . . . . . . . . . . . . . . . . . . . . . . 15
4.5 Investment good firm . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.6 Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.7 The Domestic Government . . . . . . . . . . . . . . . . . . . . . . . . 17
4.8 The Foreign Trade Partners . . . . . . . . . . . . . . . . . . . . . . . 18
4.9 Definition of equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . 19
5 Data and Calibration 22
5.1 Sectoral Disaggregation . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.2 Social Accounting Matrix . . . . . . . . . . . . . . . . . . . . . . . . 24
iii
5.3 Other Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.3.1 Trade Partners’ Income . . . . . . . . . . . . . . . . . . . . . . 25
5.3.2 Determination of the Tariff Rates . . . . . . . . . . . . . . . . 26
5.3.3 Elasticities of Substitution . . . . . . . . . . . . . . . . . . . . 30
5.3.4 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6 Results 32
6.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
6.2 Trade War . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
6.3 Free Trade Agreement . . . . . . . . . . . . . . . . . . . . . . . . . . 39
6.4 Import Elasticities of Substitution Differentiated by Sector . . . . . . 44
6.5 Tariff Revenue Rebate under Trade War . . . . . . . . . . . . . . . . 46
6.6 Optimal Tariff Argument . . . . . . . . . . . . . . . . . . . . . . . . 47
7 Conclusion 48
A Calibrated Parameters 50
B A2 52
C A3 53
D Bibliography 55
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List of Tables
2.1 EU’s Simple average MFN applied . . . . . . . . . . . . . . . . . . . . 6
5.1 Sectoral Disaggregation . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.2 Tariff rates in Benchmark Case . . . . . . . . . . . . . . . . . . . . . 27
5.3 Tariff rates in Trade War Scenario . . . . . . . . . . . . . . . . . . . . 28
5.4 Tariff rates in FTA Scenario . . . . . . . . . . . . . . . . . . . . . . . 30
5.5 Import Elasticities of Substitution (pm,j) . . . . . . . . . . . . . . . . 31
6.1 Effect of trade war on consumption good prices . . . . . . . . . . . . 33
6.2 Effect of trade war on domestic production . . . . . . . . . . . . . . . 37
6.3 Effect of trade war on Factor Prices . . . . . . . . . . . . . . . . . . . 37
6.4 Effect of trade war on Welfare . . . . . . . . . . . . . . . . . . . . . . 38
6.5 Effect of trade war on consumption good prices . . . . . . . . . . . . 39
6.6 Effect of a FTA on domestic production . . . . . . . . . . . . . . . . 42
6.7 Effect of a FTA on Factor Prices . . . . . . . . . . . . . . . . . . . . 43
6.8 Effect of a FTA on Welfare . . . . . . . . . . . . . . . . . . . . . . . . 43
6.9 Effect on Consumption Good prices (σm,i 6= σm,j) . . . . . . . . . . . 44
6.10 Effect on Factor prices (σm,i 6= σm,j) . . . . . . . . . . . . . . . . . . . 45
6.11 Effect on Welfare (σm,i 6= σm,j) . . . . . . . . . . . . . . . . . . . . . . 45
6.12 Effect of trade war with Rebate on consumption good prices . . . . . 46
6.13 Effect of a Trade War with Rebate on Factor Prices . . . . . . . . . . 46
6.14 Effect of Trade War with Rebate on Welfare . . . . . . . . . . . . . . 46
6.15 Effect of Trade War with Rebate on Welfare . . . . . . . . . . . . . . 47
A.1 Preference parameters θ - aggregate consumer and government . . . . 50
A.2 Domestic goods firm parameters (α, β) . . . . . . . . . . . . . . . . . 50
A.3 Armington Aggregators . . . . . . . . . . . . . . . . . . . . . . . . . . 51
C.1 Effect of Trade War on Exports (σm,i 6= σm,j) . . . . . . . . . . . . . . 53
C.2 Effect of an FTA on Exports (σm,i 6= σm,j) . . . . . . . . . . . . . . . 53
C.3 Effect of Trade War on Imports (σm,i 6= σm,j) . . . . . . . . . . . . . . 53
C.4 Effect of an FTA on Imports (σm,i 6= σm,j) . . . . . . . . . . . . . . . 54
v
C.5 Effect on Domestic Production (σm,i 6= σm,j) . . . . . . . . . . . . . . 54
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List of Figures
2.1 Export shares of the UK . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Import shares of the UK . . . . . . . . . . . . . . . . . . . . . . . . . 7
6.1 Effect of trade war on exports . . . . . . . . . . . . . . . . . . . . . . 34
6.2 Effect of trade war on imports . . . . . . . . . . . . . . . . . . . . . . 35
6.3 Effect of a FTA on exports . . . . . . . . . . . . . . . . . . . . . . . . 40
6.4 Effect of a FTA on imports . . . . . . . . . . . . . . . . . . . . . . . 41
B.1 Social Accounting Matrix for the UK, 2011 . . . . . . . . . . . . . . . 52
vii
Abstract
In recent years, the probability that the United Kingdom (UK) might withdraw their
membership from the European Union (EU) has gained momentum. Contingent on
the exit scenario, there will be certain implications on the tariff schedules that the
UK face and impose to the EU and the Rest of the World (RoW). It is precisely
under these tariff adjustments that this thesis will analyse the potential impact on
key economic variables in the UK economy. To conduct the analysis, the model of
choice is the Static Applied General Equilibrium model. Based on the UK’s supply
and use tables, I construct the Social Accounting Matrix (SAM) in order to calibrate
the model. The focus is on two exit scenarios: (1) the pessimistic case, the UK
engages in trade war with the EU, and (2) the optimistic case, the UK are successful
in signing a free trade agreement with the EU. Counterfactual simulations of the
UK withdrawal from the EU are then run by altering the tariff levels associated with
each exit scenario. Furthermore, additional numerical experiments are performed:
sensitivity analysis on the import elasticities differentiated by sector, an alternative
fiscal arrangement under trade war, and the validity of Johnson’s Optimal Tariff
(1954) argument for the UK economy. The results from the trade war scenario
indicate a social welfare loss of around 0.066%, while on the other hand, under a
FTA scenario, a social welfare gain of 0.065% is recorded. In conclusion, only under
a FTA scenario is there evidence that the UK should leave the EU.
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Chapter 1
Introduction
By the end of 2017, the United Kingdom (UK) is set to hold a referendum in
regards to their membership with the European Union (EU). Without focusing on
the political arguments, much debate has been centred on the possible implications
on UK’s trade if such a drastic policy transformation were to eventuate. As of 2014,
the EU still proved to be a particularly important trade partner in goods and services
with the UK. It accounted for 45% and 53% of UK’s trade of exports and imports,
respectively.1 However, over the last decade, the EU’s dominance in trade with the
UK is diminishing. This largely reflects the prominent rise of emerging economies in
global trade and the EU’s stagnation in growth after the Global Financial Crisis of
2007-08 (Hanson 2012). With this evident gradual shift towards the RoW in trade,
this prompts the question ‘Is EU membership important anymore?’
The core argument advocated by the UK’s Eurosceptics lies with the belief that
EU membership constrains their trade expansion with non-EU members (Springford
et al. 2014). This conviction stems from the fact that the EU follows a Customs
Union trade model, wherein trade between EU members is tariff-free. However, EU
members such as the UK, have limited influence in conducting their own external
trade policy. As a result, this prevents the UK in tapping the growing markets
outside Europe by signing FTAs whilst being required to impose the EU common
external tariff (CET) to third countries.
In this paper, I investigate two possible exit scenarios: (1) the pessimistic case,
the UK engages in trade war with the EU, and (2) the optimistic case, the UK
successfully signs a FTA with the EU and thereby acquires the ability to sign FTAs
with members of the RoW. One aspect of FTAs is the aim of eliminating tariff levels.
It is generally considered by economists that tariffs are distortionary. Therefore,
by implementing free trade, the efficient reallocation of resources leads to (in an
aggregate sense), a reduction in prices and an increase in domestic production in
that economy (Cho and Diaz 2011). Accordingly in this paper, I adjust the tariff
rates corresponding to each exit scenario and then analyse the potential impact on
key economic variables in the UK economy. It should be noted that other channels
1ONS UK trade data
1
that bring about benefits and costs of withdrawing from the EU are not explored.
The thought of the UK withdrawing from the EU has motivated many economists to
attempt to find the qualitative and quantitative effects of this on the UK economy.
Such examples include Hindley and Howe (2001), Pain and Young (2004), Milne
(2004) and Mansfield (2014). The results are quite mixed and are largely dependent
on the assumptions they assert. Most papers are discussion based and therefore
employ rather primitive methods in attempting to find an answer. On the other
hand, Ottaviano, Pessoa and Sampson (2014) employ a formal model and analyse
the impact of tariff changes on the welfare of the UK if they were to engage in a
trade war scenario with the EU. In the current literature, there is no study to the
best of my knowledge that investigates the potential economic and welfare impact
if the second scenario (FTA) were to occur for the UK. Thus, this will be one of
my contributions to the literature. Furthermore, different to Ottaviano, Pessoa and
Sampson (2014), I will also explicitly observe and analyse the economic agents who
gain and lose under both scenarios.
Whilst Cho and Diaz (2008) have already analysed the different welfare impacts of
Slovenia joining the EU customs union or signing a FTA, my study despite showing
similarities contains many differing aspects. In their paper, Slovenia began from
a position outside the EU. On the contrary, in this paper, the UK is already an
established member of the EU. Consequently, the determination of the tariff rates
(a key parameter) under a FTA scenario are quite different for both studies.
The model that is employed to conduct the analysis, is the Static Applied General
Equilibrium (AGE) model in the tradition of the work by Shoven and Whalley
(1984). The main motivation behind the use of this model is that many economists
have employed such a model for evaluating the impact of changes in trade policy, such
as trade liberalisation. As a point of emphasis, 11 out of the 12 studies presented
at a U.S International Trade conference in 1992 used the AGE model to analyse
the potential impact of the North American Free Trade Agreement (NAFTA) on
the relevant participating economies (Kehoe and Kehoe 1994b). The underlying
popularity of the model is that they highlight the resulting reallocation of resources
across sectors, thereby enabling the model user to observe and analyse the potential
winners and losers from a change in trade policy (Kehoe and Kehoe 1994a; Sobarzo
1992).
Due to the unavailability of the Social Accounting Matrix (SAM) for the UK, I
construct one myself mainly based on the UK’s supply and use tables. The SAM
2
together with several other data sources, provides the necessary data to calibrate
the parameters of the model to match the UK economy. From here, I conduct two
comparative statics experiments: the benchmark simulations. The first experiment
is the simulation under a trade war scenario, where both the UK and the EU raise
tariffs on each other’s imports. The magnitude of the tariff barriers imposed is based
on the current EU’s CET. The UK tariff rates to the RoW are assumed to remain
the same. The second case is the FTA arrangement, where the UK and EU trade
remains tariff free but the UK now has the power to sign FTAs with members of
the RoW. This new ability effectively reduces the tariff rates the UK impose to the
RoW as a whole. The determination of the FTAs that the UK manage to ratify with
the RoW after EU withdrawal is based on the success of the FTAs that Switzerland
have been able to attain. Under both simulations, once the tariff shock occurs, the
effects on prices, sectoral production, foreign trade and welfare are observed and
analysed.
Most UK sectors are both export and import intensive and as a result, the expected
outcome following either exit scenario is not always clear at times. For the trade war
scenario, the results show that for most sectors, there is moderate increase in the
price of consumption goods. The textiles, footwear and clothing sector experiences
the largest gain in price, rising by 0.59%. This reflects the fact that this becomes
the most protected sector under the trade war scenario, with an effective tariff rate
of 9.22%. Since tariffs rise, imports subsequently become less price competitive in
the foreign market and as a result, we observe a fall in bilateral trade with both the
EU and the RoW by 17% and 2.5%, respectively. In terms of welfare, consumers
experience a welfare loss of 0.47% while on the other hand, the government records
a gain of 1.22%. This gain arises due to the newfound tariff revenue from the EU
imports. Overall, social welfare falls by 0.066%, highlighting the negative impact if
the UK were to participate in such a situation.
Under an FTA scenario, the change in the price of consumer goods are quite small for
most sectors. The explanation is based on the distinction between a final good and
a consumption good in the model. Nevertheless, the textiles, footwear and clothing
sector, which experiences the largest reduction in tariffs with the ROW, records the
largest decline in price by 0.75%. An interesting result from this scenario is that
although bilateral trade grows with both the EU and the RoW, many disaggregated
sectors suffer from trade diversion. This is especially evident from the import side as
UK consumers switch to the more efficient producers in the RoW. As the disposable
incomes of consumers rise, so too does their welfare, which shows a gain of 0.10%.
This time, the government welfare falls by 0.065% as they lose tariff revenue from
3
the RoW imports. Still, the social welfare increases by 0.065%, meaning that the
UK can gain from this trade arrangement with the EU.
In the benchmark simulations, the elasticity of substitution of imports were set to be
the same across the sectors. Thus, I perform a sensitivity analysis where the values
of the import elasticities are differentiated by sector. Following the methodology
employed in Rolleigh (2013), I obtain the data from Martins, Scarpetta, and Pilat
(1996), and then I calculate the import elasticities for the UK. With a higher average
import elasticity, the results from both scenarios in general follow the same pattern
as in the benchmark simulations, but with greater magnitude. Notably, the social
welfare impact becomes insignificant under both scenarios.
Furthermore, two additional scenario-specific experiments are performed. First,
we notice that under a trade war, the government tariff revenue increases by 267%.
Therefore, we conduct a numerical experiment where the government hands over
this additional tariff revenue by lowering the direct aggregate tax rate imposed
on consumers’ income. The results show that the loss in consumers’ and social
welfare is lower when compared to the trade war benchmark simulation. Therefore,
this demonstrates that different fiscal arrangements can be beneficial under a
change in trade policy. The final experiment involves testing the validity of the
Johnson’s Optimal Tariff hypothesis (1954) for the UK under the FTA scenario.
This hypothesis states that optimal tariff should become zero as the parameter
governing the export elasticity approaches one. From the results, we find that the
hypothesis holds for the UK; the social welfare improves as the export elasticity
approaches one.
4
Chapter 2
Background
2.1 Possible Exit
The victory of the Conservative Party at the UK general election of May 2015
reignited the question of the UK’s membership with the EU. It is planned that
by the end of 2017, the United Kingdom (UK) will hold an “In-Out” referendum.
At the time of writing this thesis, the European Union Referendum Bill 2015-16
passed the second reading in the House of Lords at the UK parliament. According
to the YouGov Survey results (the largest UK poll surveyed in 2015 with 11,171
participants), they reported that 40% wish to leave while 38% want to remain in
the EU. Thus, this slight advantage demonstrates that UK withdrawal from the
EU is a real possibility in the near future. The contemporary debate the UK’s
membership with the EU is based on a range of issues such as trade, investment,
EU regulation, EU fiscal contribution and immigration (Springford et al. 2014). In
this paper, the focus will be on trade.
2.2 The UK-EU Trade Relationship
The UK relationship with the EU has always been a bit turbulent. In 1973, the
UK finally entered the European Economic Community (a precursor to the EU).
It was only 2 years later that the UK had a referendum about its membership,
where 67% voted in favour of staying. From there the level of trade integration
between the UK and the EU increased. To truly comprehend this relationship,
it is vital to understand the purpose and characteristics of the EU. Aside from
political motivations inherent in the EU, the EU also aims to bring about economic
integration among its 28 members. Through the EU Single Market, there is free
movement of goods, services, labour and capital. From a trade perspective, the
EU follows a customs union model, which has important implications for the UK.
Trade between custom union members is tariff free. However, in terms of external
trade, members must follow the EU Common External Tariffs (CET). Table X below
shows the average tariff rates EU members apply to nations to which the EU has
no preferential agreement.
5
Sector EU(%)Agriculture 12.2Non-Agriculture 4.2Total 5.3
Source: WTO trade policy review
Table 2.1: EU’s Simple average MFN applied
These tariffs can manipulate the trade pattern of the UK. By placing higher tariffs
towards the RoW, this enables many non-efficient EU producers to gain a larger
market share in imports to the UK. This is especially prevalent in the agriculture
sector where the Common Agricultural Policy is implemented. In fact, prior to 1973,
the UK had stronger trade ties with the RoW than the EU.
Figure 2.1: Export shares of the UK
Figure 2.1 shows the share of UK exports in goods going to the EU and the RoW
from 1996 to 2014. From this graph it is clear the EU dominated this aspect of
trade for most of the years. However we notice the rise of the share of UK exports
going to the RoW. After 2011, the RoW surpasses the EU in terms of the share of
UK exports. There are a number of explanations for this fall in EU dominance. As
documented in Hanson (2012), the global financial crisis (GFC) of 2007-08 brought
into focus the changing nature of global trade. The EU’s stagnation and the rise of
emerging economies such as China has lead to this recent change in trade patterns.
This has been the general trend after the GFC, however, with some highly developed
6
nations, trade with the UK has increased dramatically. For instance, Switzerland,
a European non-EU nation, was a major factor in the sharp rise in the RoW share
of exports from 2013 to 2014.
Figure 2.2: Import shares of the UK
Figure 2.1 shows the share of UK imports in goods from the EU and the RoW
from 1996 to 2014. While the share of imports has been fairly close from the EU
and the RoW, we notice that after the GFC, the RoW share rises. Again, this is in
line with the global trend in trade. Unlike the export side, the EU share of imports
manages to surpass the RoW’s share in 2012. This can be mainly attributed to the
recent growth in imports arriving from Germany and the Netherlands. From both
graphs, we can observe the gradual shift in bilateral trade towards the RoW. This
fall in EU dominance has called into question the EU’s important as a trade market
for the future. As part of a EU Customs Union, the UK cannot sign FTAs with
members of the RoW. Instead, they must wait for the EU to sign such agreements.
As a result, Eurosceptics believe that the EU constrains their trade with the growing
markets around the world.
7
Chapter 3
Literature Review
3.1 Alternative Trade Scenarios
There are a number of different possible trade arrangements the UK can partake
in with the EU at the time of its withdrawal. Based on Springford, Tilford and
Whyte (2014), these scenarios include: membership of the European Economic Area
(EEA), a series of bilateral agreements, membership of the customs union, a free
trade agreement (FTA), or trade under WTO rules (Trade War). In this paper,
I investigate the cases of the UK participating in a Trade War and an FTA with
the EU. These scenarios are regarded, respectively, as the pessimistic and optimistic
case. This will in turn provide valuable information in answering the question,
‘should the UK withdraw from the EU?’ Below, I discuss all five trade arrangements
in further detail with particular emphasis on trade impacts due to the focus of this
paper. Furthermore, in the discussion I also offer reasons as to why trade war is
considered the pessimistic case, and why the FTA is the optimistic and most likely
case to ensue after UK withdrawal from the EU.
UK membership of the EEA (made up of EU members, Norway, Iceland and
Liechtenstein) is a trade option that would require the UK to adopt several EU
policies in order to enable them to have unimpeded access to the EU Single Market
(a notable EU policy exception includes the common agricultural policy). As a
result, UK agricultural exports to the EU would face tariffs. The EEA is not part
of the EU customs union and as a result the UK would be able to conduct their
own external trade policy. However, there are a number of issues with this trade
option. In order to have access to the EU Single Market, the UK would still need to
abide by the EU law and regulations. Yet, the UK will have no formal access to the
EU decision making bodies. As a result, with no input in the EU regulation, they
would suffer from the problem of ‘regulation without representation’ (Springford
et al. 2014, p. 30), an issue, which alone seems quite intolerable for the UK to
accept from a political perspective. Another issue is that the EU rules of origin
would apply to the UK. The rules of origin, as defined by the WTO, encompass
the criteria needed to determine the national source of a product. If a particular
component of the product is produced from a third country (one with no EU trade
agreement) then the EU tariff rates are applied to that component. They can be
8
quite complex and as revealed in Cadot (1992), they can impose substantial costs
to the UK exporters.
Another arrangement proposition would see the UK enter into a series of bilateral
agreements with the EU, similar to the current EU-Switzerland trade relationship.
Based on the particular agreements, this would determine the level of access into the
EU Single Market. Switzerland for example, have free trade in goods with the EU
but have no such agreement in terms of services. This is an important aspect to take
into account for the UK, given the importance of the UK financial sector. Similar to
the EEA scenario, the UK would still have to comply with the EU regulation with
no input. Unlike the EEA, the UK would essentially be able to pick and choose
between the agreements which best suit their interests. The UK would be able
to conduct their own external policy, however, the EU rule of origins would still
apply. A major issue in this trade relationship is that the EU might not permit
such a proposal. This EU-Swiss trade relationship was intended to be a temporary
measure, as it was hoped that the Swiss would one day enter the EU (Fernekess et
al. 2014). The second major reason is that this type of trade relationship needs
constant renegotiation and as a result the EU has become increasingly frustrated
(Springford et al. 2014). Therefore, this option might not even be possible for the
UK.
The third trade option is for the UK to join the EU Customs Union. It needs
to be emphasised that being a member of the EU and a member of the EU Customs
Union are vastly different in definition and entitlements. If a country is an EU
member, they are automatically part of the EU Customs Union however the reverse
is not true. Nations part of the latter category include Turkey, Andorra and San
Marino. Under this arrangement, the UK would have access to the EU Single Market
but would still have to apply the CET to imports from countries with no EU trade
agreements. The disadvantages from the first two options would still hold. Another
disadvantage is that the UK would have to allow free access to goods from countries
with which the EU has an FTA, despite that same country not having to reciprocate
by allowing free access to goods from the UK. This is the one-sided benefit. If the
UK join the EU Customs Union it would seem that this will defeat the purpose of
them leaving in the first place. This instance is also argued by Springford, Tilford
and Whyte (2014) and Fernekess, Paleviciene and Thadikkaran (2014), and thus
seems highly unlikely to occur.
The optimistic trade option involves the UK signing an FTA with the EU on its
withdrawal. An FTA would enable trade with the EU to remain tariff-free. Unlike
9
a Customs Union member, the UK would be free to set its own trade polices to
the RoW without applying the EU CET rates. Even though the EU origin of rules
would apply, the UK would not be required to implement EU laws (Fernekess et
al. 2014, p. 42). One such example is the South Korean-EU FTA. This model of
trade essentially provides lesser integration with the EU, unlike the other models,
whilst it enables the UK to still enjoy free trade. There are number of reasons as to
why this is considered to be the most likely scenario to eventuate. Firstly, the other
models do not exactly solve the issue of the UK leaving the EU in the first place.
Secondly, this option may seem the least desirable to the EU as they allow for the
UK to essentially reap the benefits of EU trade with less integration. However, as
noted in Fernekess (2014, p. 42), the UK is an important import destination for the
EU exports. This, together with the fact that the UK is currently running a trade
deficit with the EU provides evidence that such an agreement would be in their
self-interest to accept in the long term (Mansfield 2014; Hindley and Howe 2001)
Furthermore, as demonstrated, this is considered by Eurosceptics to be the most
preferred case (The Economist 2015).
Finally, the last option suggests that the UK leave the EU without any trade
agreement in place. Consequently, as stipulated by the WTO rules, the UK and
the EU must apply the Most Favoured Nation (MFN) tariff rates on each other’s
imports. Since both nations are raising tariffs on one another, this scenario is labelled
as Trade War. Regardless of their complete freedom in determining their internal
and external policies, the possibility that the UK exporters might face the EU CET
is the reason this case is considered the pessimistic case. It may seem unlikely that
both parties would want such a relationship but as argued by Ottaviano, Pessoa and
Sampson (2014) this is a possibility in the short term and as stated in Mansfield
(2014), there only needs to be one EU member to block the UK from signing an
FTA.
3.2 Methodology
A common model used to study trade policy is the AGE model, as it quantifies the
impact of different trade arrangements. Given the focus of this paper, the model of
choice for my analysis is the static applied general equilibrium (AGE) model. The
general equilibrium model’s theoretical foundation is based on Arrow and Debreu’s
(1954) model that formalised and proved the existence of the Walrasian general
equilibrium structure. In order to evaluate policy, this abstract representation of the
economy needed to be converted through the use of specifying parameters into actual
10
economies that reflected real world data (Shoven and Whalley 1992). The numerical
application started with Leif Johansen (1960), who developed the first empirically
based, price-endogenous model with multiple sectors (Shoven and Whalley 1984).
This model was calibrated to the Norwegian data from 1950, and was employed to
analyse the resource allocation and thereby identify the sources of economic growth
in Norway during the period of 1948-53. Another prominent early work in the
numerical application field was Arnold Harberger (1962). Harberger focused on tax
policy by producing a two sector model calibrated to the US data from the 1950s
(Kehoe and Prescott 1995).
An important development in the field of AGE modelling occurred when Scarf (1967,
1973) successfully formulated a computational algorithm to find the fixed points that
satisfied the conditions of Brouwer’s fixed-point theorem. This essentially enabled
the numerical calculation of economic equilibria. This work was quite influential as
it inspired a whole generation of Yale graduate students to work with AGE models
(Kehoe 1996). Two prominent Yale graduates were Shoven and Whalley, who were
one of the first to employ the computational general equilibrium (see Shoven and
Whalley (1972)). With the advancement in computers, this has made the use of
such a model more widely available at a lesser cost.
An AGE model consists of various artificial economic agents where in the com-
puter simulations, they conduct the same transactions as that observed by their
counterparts in the real world. In this paper, the economic agents will be composed
of consumers, producers, a government and foreigners. The model itself is quite
flexible, enabling many extensions. One such extension is the specification based on
the Armington (1969) assumption. By employing such a specification, this accounts
for the large amount of cross hauling evident in the trade data. If there ceased
to be an Armington assumption (therefore goods are homogenous) then this could
potentially cause extreme results where countries would completely specialise in a
product (Kehoe 1994a). This model can either be calibrated following the likes of
Kehoe (1996) or can resemble the statistical methods employed by Jorgenson (1984)
or Mansur and Whalley (1984). In this paper, I follow the calibration method
due to the unavailability of data for the UK. Once the calibration is completed,
the comparative statics methodology is conducted where the simulation is run by
changing the policy parameter (in this case, the tariff rates) and analysing the post
shock equilibrium. The variables in focus are the prices, sectoral production, trade
and national welfare which are then analysed to determine the move the UK should
appropriate in regards to leaving the EU.
11
The main motivation behind the use of this model is that they highlight the resulting
reallocation of resources across sectors, thereby enabling the model user to observe
and analyse the potential winners and losers from a change in trade policy (Kehoe
and Kehoe 1994a; Sobarzo 1992). Many studies have employed the AGE model to
analyse different forms of trade policy. At the U.S International Trade conference in
1992, 11 out of the 12 studies presented used the AGE model to analyse the potential
impact of the North American Free Trade Agreement (NAFTA) on the relevant
participating economies (Kehoe and Kehoe 1994b). Other examples include the
evaluation of the Tokyo Round Trade Agreement (Whalley 1982), Morocco signing
an FTA with the EU (Rutherford, Rutstrom, and Tarr 1993) and Australia signing
an FTA with India (Cho and Yoon 2013). Most studies have focused on trade
liberalisation through FTAs. Though I also explore an FTA with the EU in the
second scenario, given that it requires leaving the Customs Union, my situation is
quite different to the above literature.
One study that does explore the issue of Customs Union versus the FTA is Cho
and Diaz (2011). In this paper they look at the case of Slovenia and their entrance
into the EU. What they notice is that for some sectors the EU CETs here higher
than the Slovenian tariff to the RoW. Thus by joining the EU, they would become
more protectionist towards the RoW. As a result, they look at the alternative trade
arrangement where they sign an FTA with the EU while maintaining their initial
tariffs with the RoW. Whilst they find that under both scenarios there is a gain in
Slovenia’s national welfare, the Custom Union case has the higher welfare mainly
due to the additional tariff revenue from RoW imports the government collected.
Thus, the conclusion is that Slovenia should join the EU. This study is similar to
the FTA scenario investigated in this paper however there is one key distinction;
Slovenia is entering the EU, meaning that the level of tariff rates that Slovenia were
using prior to accession, is readily available. In my case, the UK are already part
of the EU so the tariff rates the UK government decides to impose on imports at
withdrawal is not known with certainty. Thus one of my contributions is to develop
a method in which I attempt to work out the tariff rates.
3.3 United Kingdom Study
The thought of the UK withdrawing from the EU has motivated many economists to
attempt to find the qualitative and quantitative effects of this on the UK economy.
Such examples include Hindley and Howe (2001), Pain and Young (2004), Milne
(2004) and Mansfield (2014). The results are quite mixed and are largely dependent
12
on the assumptions they assert. Apart from Pain and Young (2004), there is an issue
with these papers as they do not utilise a formal economic model to support their
claims; they rely on discussion. Pain and Young (2004) assess the macroeconomic
consequences of UK withdrawal from the EU under endogenous fiscal and monetary
policy. They find that due to the predicted fall in the level of inward foreign direct
investment, this will have an adverse impact on the living standards in the UK.
However, in this paper, the emphasis is on the role of tariffs. Ottaviano, Pessoa and
Sampson (2014) employ a formal model and analyse the impact of tariff changes
on the welfare of the UK if they were to engage in a trade war scenario with the
EU. The standard static AGE model with multiple sectors is employed. Their main
finding is that due to an increase in the EU-UK Tradable Tariffs, the prediction is
that the UK will experience a static loss of around 0.14% of GDP.
The analysis conducted in this thesis differs in many ways. In the current literature,
there is no study to the best of my knowledge that investigates the potential
economic and welfare impact if the second scenario (FTA) were to occur for the
UK. This may very well be due to the complexity and uncertainty of the FTA
scenario. Hence this will be my main contribution to the literature. Furthermore, in
Ottaviano, Pessoa and Sampson (2014), the impact on different sectors in the UK
following this policy shock is not explicitly stated. I will investigate this impact and
thereby determine the economic agents who gain and lose under both scenarios.
13
Chapter 4
Model
4.1 Overview
In this paper, the model of choice is the Static Applied General Equilibrium model
in the tradition of the work by Shaven and Whalley (1984). More specifically,
the model follows the framework employed in Cho and Diaz (2008). In order to
quantify the potential sectoral effects if the UK were to leave the EU, I disaggregate
the British Economy into seven sectors, namely: Food and Beverages, Primary
Goods, Textiles, Clothing and Footwear, Machinery, Chemical products, Services
and Other Manufactures.1 In this British model economy, we invent several agents
that interact with each other in order to capture what is observed in the data.
These agents include a representative household, four different types of producers,
a domestic government and two foreign trade partners. The foreign trade partners
are composed of the European Union and the aggregate of the rest of the world2. A
much more thorough explanation of these agents are provided below.
4.2 Domestic production firms
Under the Armington assumption, we assume in this model that the final goods are
produced by combining a locally-produced component and an imported component.
Thus the role of the domestic production firms is to produce this locally-produced
component of the final good. In order to produce such output, these firms’
production function contains two essential ingredients. Through a Leontief-
type production function, the firm uses the intermediate inputs from the seven
disaggregated sectors in fixed proportions and through a Cobb-Douglas Production
function, the firm employs labour and capital. Thus, for the domestic firm producing
good i, the total production function is:
yi,d = min
{xd1,iad1,i
, ...,xdi,iadi,i
, ...,xdn,iadn,i
, βikαii `
1−αii
}(4.1)
1Section 4.1 explains the disaggregation.2For this analysis Croatia is not included because the data is from 2011 and Croatia was not
part of the EU.
14
with 0 < α < 1, ∀i = 1, ..., n ∈ GP ,the set of production goods; yi,d is the output
of the domestic firm i, xdm,i is the amount of intermediate inputs of good m used in
the production of good i, adm,i is the unit-requirement of intermediate good m in the
production of good i, and ki is the capital input and `i is the labour input used to
produce good i. pi,d is the price of the domestic good i.
4.3 Final production goods firms
In this tatic applied general equilibrium model, goods and services are distinguished
by their industry and by their country of origin. In order to take this into account,
the final production good firm produces the final production good i by combining
the locally produced component with the imported component using an Armington
aggregation technology:
yi = γi
[δi,dy
ρm,ii,d +
∑f∈T
δi,fyρm,ii,f
] 1ρm,i
where σm,i = 1/(1 − ρm,i) is the elasticity of substitution between domestic and
imported goods, yi is the output of the final good i, yi,d is the domestic component in
the final good i and yi,f is the imported component from each of the trade partners
mentioned above. It is also worth noting that when ρm,i → 0, the production
function takes a standard Cobb-Douglas form, i.e. yi = γi
[yδi,di,d ×
∏f∈T y
δi,fi,f
].
Imports of good i from country f are subject to an ad valorem tariff rate τi,f . It is this
rate that will be altered in the experiments that we conduct. The price of the final
good i is pi while the foreign prices (p̄i,f )i∈GP ,f∈T are assumed to be exogenous. As
termed by Cox and Harris (1985), this is the almost small-country assumption. This
refers to the case where a country such as Britain, is not large enough to influence
world prices. However with the Armington assumption, domestic UK producers have
some market power, and as a result they can vary the prices of their domestic goods.
4.4 Consumption goods firms
In this model, we differentiate between the goods that the production firms purchase
in their inter-industry transactions to the goods that households purchase. The
latter is labelled as ‘consumption goods’ and it is exclusively bought by households.
Compared to the goods that production firm purchases, we assume that these
15
consumption goods contain a high service component embedded in them. To offer
intuition to such a case, an example is the difference between buying goods from a
retailer to buying directly from a wholesaler. At a retailer, the tomato consumers
buy have a high service component compared to the tomatoes producers buy in
order to produce ketchup. This high service component can be thought of as the
sales assistant contribution in the sale of that product. The consumption goods firms
combine the final production goods using a fixed proportions technology. Thus this
Leontief-type production function for the consumption of good i firm is:
yi,c = min
{xc1,iac1,i
, ...,xci,iaci,i
, ...,xcn,iacn,i
}
where {1, 2, ..., n} are the goods in GC , the set of consumption goods. Moreover, we
make an additional assumption where xCi,j for i 6= j, services. Therefore, this implies
that for consumption good i, the consumption firm only uses final goods of its own
sector and services as inputs. This follows from the fact that consumption goods
contain a high service component in them. The pc,i is the price of consumption good
i.
4.5 Investment good firm
The way savings is incorporated is one of the main differences between a dynamic
and static model. In a dynamic model, agents save in order to be able to purchase
more consumption goods in the future. Given that our model is based on a static
set-up, in order to take account of this savings observed in the data, we include
an investment good that agents can purchase. By purchasing such a good, agents
derive utility similar to the utility derived from the purchase of consumption goods.
The investment good firms combine the final goods as intermediate inputs using a
fixed proportions technology. Thus this Leontief-type production function for the
investment good i firm is:
yinv = min
{x1,inv
a1,inv
, ...,xi,invai,inv
, ...,xn,invan,inv
}
The pinv is the price of the investment good.
16
4.6 Households
In the UK economy, there is a representative household that derives utility from the
purchase of consumption and investment goods. As mentioned above, investment
goods represent household saving in the observed data. Household preferences over
these goods are governed by a Cobb-Douglas utility function. Thus, the household
utility maximization problem of the form:
max∑i∈GC
θilog ci + θinvlog cinv +∑f∈T
θinv,f log cinv,f
s.t.∑i∈GC
pc,ici + pinvcinv +∑f∈T
ef p̄inv,fcinv,f = (1− τd)(w ¯̀+ rk̄)
where ci is the consumption of good i by the representative household and pc,i is the
price of consumption good i. In the budget constraint, the right hand side represents
the disposable income of the household where τd is the direct tax rate imposed on
the household income, w and k are, respectively, the wage rate for labour and the
rental rate of capital, and finally ¯̀and k̄ are, respectively, the endowments of labour
and capital. Given the method of representing household saving in a static model,
then cinv represents the purchases of the investment good while pinv is the price of
the investment good.
In the data, the UK has a trade surplus with on of the trade partners, the rest
of the World. The way we incorporate this into model is by introducing a foreign
investment good. By purchasing this foreign investment good, UK households are
effectively saving abroad. As a result, cinv,f represents the purchase of the investment
good from country f while the price of the foreign investment good p̄inv,f is assumed
to be exogenous, and ef is the bilateral real exchange rate.
4.7 The Domestic Government
The method of incorporating the government in the static applied general equilib-
rium model is by assuming that the government is yet another agent that gains utility
from consuming the production goods and the investment good. The motivation
behind the inclusion of the government in our model is primarily due to the fact
that from the UK national accounts in 2011, the government made purchases of
some goods and ran a fiscal deficit. In order to purchase such goods, the government
17
must finance these expenditures by the revenues collected from three main sources,
namely, direct and indirect taxes, and tariffs imposed on imports. The government
utility maximization problem takes the form of:
max∑i∈Gp
θgi log cgi + θginvlog cginv
s.t.∑i∈GC
picgi + pinvcinv = τd(w ¯̀+ rk̄) +
∑i∈GC
tc,i +∑f∈T
∑i∈Gp
ti,fef p̄i,fyi,f
From the left side of the government budget constraint, the first term represents the
expenditure of final goods while the second term is the purchase of the investment
good. From the right side of the budget constraint, the four terms represent the total
government revenue: the first term is the direct taxes collected from the households’
income; the second and third terms (that make up the indirect taxes) are the
revenues from taxing the domestic and consumption goods firms, respectively; and
the last term represents the tariff revenue collected from the imports of the two UK
trading partners.
4.8 The Foreign Trade Partners
Given the objective of this paper, the disaggregation of foreign trade is composed
of two partners: The European Union (26 members) and the rest of the World.
The way the foreign sector is incorporated in this model is by constructing a
representative household from both trading partners f ∈ T , where T = (EU,ROW ).
This foreign representative household, similar to the domestic representative
household, gains utility by purchasing imported goods xj,f (j ∈ Gp) from Britain,
and from consuming their local good xf,f . Furthermore, if the trade partner has a
trade surplus with the UK (such as the EU according to the data), we model this as
foreign purchases of the UK investment good xinv,f (foreign savings into the domestic
economy). In country f , the problem faced by the representative household takes
the form of:
18
max
∑j∈Gp
θj,fxρxj,f + θinv,fx
ρxinv,f + θf,fx
ρxf,f
− 1ρx
s.t.∑i∈GP
(1 + τ fi )pixi,f + pinvxinv,f + efxf,f = efIf
As mentioned before from the almost small country assumption, the UK is not large
enough to influence the foreign prices and foreign income. Given that all the relevant
variables in the model are not entirely determined exogenously, this effectively means
that this particular model is something less than a full general equilibrium model.
4.9 Definition of equilibrium
An equilibrium for this economy is a set of prices for the domestic goods
(pi,d)i∈GP ; prices for the final goods (pi)i∈GP ; a price for the investment good
pinv; prices for the consumption goods (pc,i)i∈GC ; factor prices w and r; bi-
lateral exchange rates (ef )f∈T ; foreign prices (p̄i,f )i∈GP f∈T ; a consumption plan
for the representative household (ci, cinv, cinv,f )i∈GCf∈T ; a consumption plan for
the government (cgi , cginv)i∈Gp ; a consumption plan for the representative house-
hold in country f (xi,f , xinv,f , xf,f )i∈GP f∈T ; a production plan for the domestic
good i firm (yi,d, xd1,i, ..., x
dn,i, ki, `i); a production plan for the final good i firm
(yi, yi,d, ..., (yi,f )f∈T ); a production plan for the investment firm (yinv, x1,inv, ..., xn,inv);
a production plan for the consumption good i firm (yi,c, xc1,i, ..., x
cn,i); such that, given
the tax rates and the tariff rates:
− The consumption plan (ci, cinv, cinv,f )i∈GCf∈T solves the problem of the repre-
sentative household.
− The consumption plan (cgi , cginv)i∈Gp solves the problem of the government.
− The consumption plan (xi,f , xinv,f , xf,f )i∈GP f∈T solves the problem of the
representative household in country f .
− The production plan (yi,d, xd1,i, ..., x
dn,i, ki, `i) satisfies
19
yi,d = min
{xd1,iad1,i
, ...,xdi,iadi,i
, ...,xdn,iadn,i
, βikαii `
1−αii
}and
(1 + tp,i)pi,dyi,d −∑j∈Gp
pjxdj,i − w`− rk ≤ 0,= 0ifyi,d > 0
− The production plan (yi, yi,d, (yi,f )f∈T ) satisfies
piyi − pi,dyi,d −∑f∈T
(1 + τi,f )ef p̄i,fyi,f ≤ 0,= 0ifyi > 0
where yi,d and (yi,f )f∈T solve
min(1 + τp,i)pi,dyi,d +∑f∈T
(1 + τi,f )ef p̄i,fyi,f
s.t.yi = γi
[δi,dy
ρm,ii,d +
∑f∈T
δi,fyρm,ii,f
] 1ρm,i
− The production plan (yinv, x1,inv, ..., xn,inv) satisfies
yinv = min
{x1,inv
a1,inv
, ...,xi,invai,inv
, ...,xn,invan,inv
}and
pinvyinv −∑j∈GP
pjxj,inv ≤ 0,= 0ifyinv > 0
− The production plan (yi,c, xc1,i, ..., x
cn,i) satisfies
20
yi,c = min
{xc1,iac1,i
, ...,xci,iaci,i
, ...,xcn,iacn,i
}and
(1 + τc,i)pi,cyi,c −∑j∈GP
pjxcj,i ≤ 0,= 0ifyi,c > 0
− The goods market clear:
yi =∑j∈GP
xdj,i +∑j∈GC
xcj,i + xi,inv + cgi +∑f∈T
xi,f
yi,c =ci
yinv =cinv + cginv +∑f∈T
xinv,f
− The factor markets clear:
∑i∈Gp
`i = ¯̀
∑i∈Gp
ki = k̄
− The balance of payments condition for each trade partner country f is satisfied:
∑i∈GP
ef p̄f,iyi,f +∑i∈GP
ef p̄inv,fcinv,i =∑i∈GP
pixi,f + pinvxinv,f
21
Chapter 5
Data and Calibration
5.1 Sectoral Disaggregation
In this paper, I analyse the potential quantitative impact that a UK withdrawal
from the EU would have on the different productive sectors of the UK economy.
Given this objective, finding the correct level of sectoral disaggregation is critical to
our investigation. The procedure that I employed in order to determine the specific
sectors involved forming a criterion. This criterion included: the relative importance
of that sector in the total economy; the relative importance of that sector in total
trade, exports and imports; the level of tariff protection that the sector enjoys; the
tariff rates applied by the trading partners on UK goods and services; and I look at
the different trade scenarios and their associated tariff rates. As a result, the chosen
level of sectoral disaggregation for the UK is shown in Table 5.1. Below provides a
detailed explanation as to why I chose each sector.
Sectors
Food & BeveragesPrimary Goods
Textiles, Footwear & ClothingMachineryChemicals
Other ManufacturesServices
Table 5.1: Sectoral Disaggregation
The first of our disaggregated sectors is the food and beverages sector. When looking
at the trade data, this sector’s total imports are more than twice (214%) their total
exports, and from an import perspective, the EU makes up 75% of the imports.
Furthermore, this is the second most protected sector in the UK, with the average
effective tariff rate of 4.4%.1 When I conduct the second simulation where the UK is
able to sign numerous FTAs with the RoW, the food and beverages sector becomes
the most protected sector in the UK economy. For the primary goods industry, 75%
1Tariff levels shown in Section 4.3.1
22
of the exports arrive to the EU while 70% of imports come from the RoW. In terms
of the HS code, the primary goods industry contains the ‘Mineral fuels, mineral oils
and products of their distillation; bituminous substances; mineral waxes’ (HS code
27) item. This particular trade item is the largest export item to the EU and the
largest import item from the RoW. Another interesting aspect of this sector is that
the the effective UK tariff rate is 0.21% while for the RoW, the tariff rate is 3.12%,
meaning that this sector has the highest tariff rate differential.
The most protected sector in the UK economy is the textiles, clothing and footwear
sector, with an effective tariff rate of 6.6%. In the first simulation (where the EU
place tariffs on UK goods), the EU effective tariff rate for this sector is 9.15%,
making it also the most protected sector in the EU economy. In terms of UK
trade, the total imports are nearly two and a half (245%) times the size of the total
exports. As for the machinery sector, this sector was extracted due to the fact that
it accounts for 26% of total UK imports as well as 24% of total UK exports. In
the HS code, this sector would include items such as: vehicles other than railway
or tramway rolling-stock, and parts and accessories thereof (HS code 87), nuclear
reactors, boilers, machinery and mechanical appliances; parts thereof (HS code 84),
and electrical machinery and equipment and parts thereof; sound recorders and
reproducers, television image and sound recorders and reproducers, and parts and
accessories of such articles (HS code 85). All three of these items are in the top
six export and import items from both the EU and the RoW, highlighting the
importance of these items to UK Trade.
Next, the chemical products sector accounts for roughly 11% of total UK exports
and 9% of total UK imports. The pharmaceutical products (HS code 30) and organic
chemicals (HS code 29) are two significant items under the chemical product sector
with the former item being the third largest export item to the RoW, with the
latter being the sixth largest export item to the EU. The remaining manufacturing
sectors that were not part of the sectors mentioned above were placed under ‘Other
manufactures’. Finally, the services sector was integrated in our analysis due to the
fact that this sector alone makes up 75% of the UK Economy.2 Not only that, it is
also the largest export sector and the second largest import sector for the UK. The
revealed comparative advantage lies in the services sector (BIS 2012). It is worth
noting that under all experiments conducted in this paper, the tariff rates applied
by the UK, EU and RoW are all zero for the services sector.
2ONS Data
23
5.2 Social Accounting Matrix
Once the level of sectoral disaggregation is selected, the next step in the development
of the AGE Model is the use of the Social Accounting Matrix (SAM). The
SAM matrix is an organized matrix representation that records all the economic
transactions that take place within an economy by all the institutional agents. In this
paper, the timeframe that the SAM covers is one year, specifically 2011. Therefore,
this SAM essentially provides a ‘snapshot’ of the UK economy. The design of the
SAM is such that the entries along a row represent the receipts of a particular agent
while the entries down a column display the payments made by these agents.
As presented in section 4, all of the different economic agents are governed by
the parameters of their associated functions. Thus, in order to construct the
AGE Model, these parameters need to be calibrated in such a way that in the
benchmark equilibrium produced, the artificial economic agents conduct the same
transactions as that observed by their real world counterparts according to the SAM
(Kehoe 1994a). By using the optimality and market clearing conditions, most of the
parameters can be directly calibrated from the SAM (Kehoe 1996). The input
shares and total productivity scale parameters in the production functions and the
parameters in the agents’ utility function are such examples. Appendix A shows the
values of the calibrated parameters for the UK economy. For those parameters that
cannot be calibrated from the SAM, we explain in subsection 5.3 how I obtained
those values.
A SAM for the UK that suits my level of sectorial disaggregation is not readily
available. As a result, I construct one myself tailored to the seven disaggregated
UK sectors. The construction of a SAM requires the use of data from a variety of
sources. The main source stems from the supply and use tables. For the UK, the
latest available supply and use table is from 2011 (Timmer et al. 2015). Based on
the OECD definition, the supply table records how the supplies of different kinds
of goods and services originate from domestic industries and imports, with further
information on indirect taxes and margins on goods. On the other hand, the use
table shows how this supply of goods and services are utilised in the economy.
Such uses include: as intermediate inputs in the firm’s production process, as part
of household and government consumption, as investment and as exports to the
world. Next, these tables are then combined to form the balanced input-output
matrix. Developed by Leontief (1941), the input-output matrix provides detailed
information on the inter-industry transactions that occur in the economy and the
payments to factors of production. There are 59 industries and 59 product groups
24
in the input-output table that I aggregate into seven industries.
To further disaggregate certain components of the SAM, other data sources were
exploited. Given the emphasis of UK trade in this model, the foreign sector was
split between the EU and the RoW. This required data on the inter-EU and intra-
EU trade, which I obtained from the Trade Statistics unit produced by the HM
Revenue & Customs. Additionally, from the HM Revenue & Customs database, I
was able to also find the values for the direct tax revenue and the value added Tax
(VAT) revenue. Finally, from the UK Socio-Economic Accounts provided by the the
World Input-Output Database, the payments to the factors of production were split
between Labour and Capital. The completed SAM is presented in Appendix B.3
5.3 Other Parameters
In this section we look at the parameters that could not be explicitly calibrated
from the SAM. Below, we demonstrate how we obtain the values for these particular
parameters.
5.3.1 Trade Partners’ Income
As mentioned earlier, the two trade partners are the EU and the RoW. The Gross
Domestic Product (GDP) is used as a measure of their associated income. This data
is obtained from the International Financial Statistics published by the International
Monetary Fund (IMF). The GDP values are taken from the calendar year of 2011
in order to remain consistent with the data from our SAM. Another issue is that
GDP values are expressed in US Dollars while the data in the SAM are all in British
Pounds. Consequently, adjustment is necessary. In 2011, the US Dollar-UK Pounds
exchange rate was US$1.60360 per British Pound (Timmer et al. 2015). With
this conversion rate, the GDP of EU was £9,667,804.58 million. With World GDP
at £43,659,067.1 million, the GDP of the RoW was calculated as £32,459,104.52
million.
3T construct the SAM for the UK, I followed asimilar approach to Kehoe (n.d.)
25
5.3.2 Determination of the Tariff Rates
The tariff rates are an essential component of this counterfactual analysis. The
policy shock in our model is precisely this change in tariff rates. In this section, we
demonstrate how we derive the tariff rates from the benchmark case and from the
two hypothetical scenarios that we explore.
The benchmark case reflects the current state where the UK is a member of the
EU. As an EU member, the UK has access to the EU internal market (or EU
Single Market). With such access, trade between the UK and the rest of the EU
is tariff-free. To see the tariffs that the UK impose on the RoW imports, it is
important to understand that the EU follows the customs union trade model. In a
customs union, there is internal free trade but externally, members must apply the
EU common external tariff (CET). This means that the UK must impose the EU
CETs to the RoW. From the supply table, if we divide the tariff revenue with the
value of their associated import, we are able to extract implicitly the tariff rates
that the UK impose on the RoW imports. Given this methodology, these calibrated
tariff rates are effective rates rather than nominal rates. For the other tariffs in this
analysis, we cannot use this method to determine their rates (eg the UK tariff rates
in the two counterfactual scenarios). As a result, I employed another method to find
the effective tariff rates.
The distinction between effective and nominal tariff rates plays an important role
in this different methodology. For the nominal tariff rates, I was able to obtain the
2011 EU applied Most Favoured Nation (MFN) tariff rates from the World Trade
Organization (WTO) database. The products with their associated MFN tariff rate,
were classified according to the Harmonised System (HS). Thus, I had to make a
concordance of these products with my seven disaggregated sectors. If we were
to simply apply these rates to the total import value of a particular sector, the
calculated tariff revenue would be overstated. The reason is that these rates are not
applied to all members of the RoW. The EU has numerous FTAs and preferential
arrangements with many members of the RoW. As a result, this needs to be taken
into account in order to receive the effective tariff rates. What follows next is an
outline of the steps I took to determine the effective UK tariff rates for each sector
imposed on the RoW imports.
1. For each product (HS 4-digit level), the country of origin was found in order to
determine the trade value (data from HM Revenue and Customs) and the specific
tariff rate imposed on them by the UK.
26
2. With such information, I was able to determine the trade-weighted tariff rate on
that particular product.
3. As mentioned above, the products were allocated under the seven disaggregated
sectors. Within each sector, the aggregate trade value of each product was used as
weights, which were then multiplied by the tariff rates derived from Step 2.
4. Adding up all the values from Step 3 for a particular sector, we finally derive the
effective tariff rate for that sector.
5. Complete Steps 1-4 for every sector.
It is worth noting that the trade weighted average was preferred to the simple
average in the calculation of the effective tariff rates. In the data, there were some
products that have large tariff rates but with relatively little trade to the UK (eg
Tobacco products had an average of 40%). If the simple average metric was used,
this would overstate the tariff rate in the food and beverage sector.
In calculating the RoW tariffs on imports from the UK, I assume that the tariffs
are a trade weighted average of the tariffs imposed by the top 10 export trading
partners of the UK.4 By descending rank of value, these partners are the United
States of America, Switzerland, China, Hong Kong, Canada, India, Japan, Russia,
United Arab Emirates and Australia. The tariff rates imposed by the UK and the
RoW are shown in Table 5.2.
Sector UK (%) RoW (%)
Food & Beverages 4.4 5.92Primary Goods 0.21 3.12Textiles, Footwear & Clothing 6.6 6.41Machinery 1.95 3.57Chemicals 2.00 3.52Other Manufactures 0.98 2.26Services 0 0
Table 5.2: Tariff rates in Benchmark Case
In the first counterfactual scenario, the UK would leave the EU without any trade
agreement in place. As explained in section 3, this is a possibility, especially in
the short-run. In this paper it is viewed as the pessimistic case. In this situation,
as stipulated by the WTO rules, the UK and the EU must apply the MFN tariff
rates on each other’s imports. As seen in the benchmark case, the current UK and
4Similar assumption employed in Cho and Yoon, 2013
27
EU MFN tariff rates are identical. Therefore, similar to Ottaviano, Pessoa and
Sampson (2014) and as argued by Mansfield (2015), an assumption is made that,
even after an exit, the UK will still apply the same EU MFN tariff rates. However,
the effective sector tariff rates imposed by the UK and the EU in this scenario are
slightly different. The difference stems from the fact that within a sector, the UK
and the EU have different trade weights attached to their products. The new tariff
rates raised by the UK and the EU are shown in Table X.
Sector UK (%) EU (%)
Food & Beverages 5.41 4.2Primary Goods 2.23 0.65Textiles, Footwear & Clothing 9.22 9.15Machinery 3.6 3.3Chemicals 2.72 2.07Other Manufactures 2.6 2.45Services 0 0
Table 5.3: Tariff rates in Trade War Scenario
From the UK-RoW trade perspective, we assume that the UK is successful in keeping
the same FTA with certain members of the RoW as argued by Mansfield (2015).
Therefore, the tariffs that the UK and RoW impose on each other are the same as
shown in the benchmark case.
Under this hypothetical scenario, the UK sign a free trade agreement (FTA) with the
EU on its withdrawal. An FTA would enable trade with the EU to remain tariff-free.
Unlike a custom union member, the UK would be free to set its own trade polices to
the RoW without applying the EU CET rates. By signing new FTAs, this effectively
facilitates the UK to tap in to growing markets around the world. This is actually
one of the more prominent arguments put forward by Eurosceptics (Springford et
al. 2014). This is the optimistic scenario and the one which contributes the most
to literature.
What will be the effective tariff rates that the UK impose on the RoW imports?
To answer this critical question, I considered a number of factors. First, many in
the UK feel that the EU is slow in generating new FTAs with the RoW (especially
FTAs more suited to the UK economy). Accordingly, to see the possible FTAs the
UK might have upon withdrawal, I conducted research on the European Free Trade
Association (EFTA) members, Switzerland, Norway, Iceland and Liechtenstein (The
UK was part of the EFTA original outer seven until 1973), and observed their
28
contemporary FTAs with the RoW. All four members participate in the EU’s Single
Market and have the freedom to participate in FTAs with the RoW (Mansfield,
2014). In fact, the EFTA members have been successful in signing more FTAs with
the RoW compared to the EU.
Out of the EFTA members, I narrowed my focus on Switzerland as they were
the most successful in negotiating FTAs with the RoW. Switzerland managed to
attain FTAs with major economies like China and Japan. In this paper, I assume
that upon exit, the UK will also be able to sign FTA’s with the same nations
as Switzerland. Stanley (2015) argues that the UK can surpass the success of
Switzerland. Switzerland is a highly developed economy with many similarities
to the UK (Mansfield 2015). Both have a revealed comparative advantage in the
services sector, especially that relating to finance (Fourie and Von Fintel 2009).
According to the Global Enabling Trade Report in 2014 (which looks at the quality
of facilitating the free flow of goods over borders and to their destination-definition),
the UK and the Swiss were positioned 5th and 6th, respectively. Furthermore,
looking at the specific countries in the Swiss FTAs, four countries (China, Hong
Kong, Japan and Canada) are in the top 10 bilateral trading partners of the UK. This
highlights the relevance and suitability of these Swiss FTAs for the UK economy.
As in the first scenario, we once again assume that the UK will apply the same EU
MFN tariff rates. Together with UK’s new FTAs, we can determine the effective
tariff rates imposed on the RoW. With this new information, the methodology
follows the same procedure as outlined above. The effect of these FTAs is that
now more countries are excluded from the MFN tariff rate and as a result, the
effective tariff rate will be reduced for that sector. The magnitude of the reduction
depends on the trade weight of the countries involved in a FTA with the UK.
As in the benchmark case, the RoW tariffs on British goods are assumed to be the
trade weighted average of the tariffs imposed by the top 10 export trading partners
of the UK. The data come from most recent editions of the trade policy reviews by
the WTO. The UK will now have FTAs with 5 of the 10 partners (the four news
ones and the old one, Switzerland). Taking this into account, the calculated tariff
rates imposed by the UK and the RoW are shown in Table 5.4.
29
Sector UK (%) RoW (%)
Food & Beverages 4.20 4.53Primary Goods 0.2 2.58Textiles, Footwear & Clothing 3.48 3.36Machinery 1.825 2.15Chemicals 1.03 2.74Other Manufactures 0.88 1.66Services 0 0
Table 5.4: Tariff rates in FTA Scenario
5.3.3 Elasticities of Substitution
A crucial component of the AGE model is the elasticity of substitution for exports
and imports. Given the static nature of this model, we can not directly calibrate the
values of these parameters from the SAM. Therefore, in this paper, we apply different
sets of values for these parameters. As assumed by Cho and Diaz (2011), for the
benchmark case, we set pm,j = 0.8∀j ∈ Gp and px = 0.9, meaning that the elasticity
of substitution of imports and exports take the values of 5 and 10, respectively.
Given that these values are estimates, we conduct a sensitivity analysis for both
parameters by looking at the literature.
As documented by Rolleigh (2013), the econometric estimates (the traditional
method) of these parameters, often produced values that were too low. Taking
a different approach, Rolleigh (2013) calibrated these parameters by choosing values
of the elasticises to match the sectoral gross output mark ups in that sector. In this
article, the US economy is analysed and the estimates of the sectoral gross output
mark-ups are obtained from Martins, Scarpetta, and Pilat (1996). Since the data
for the sectoral gross output mark-ups for the UK are also available from Martins,
Scarpetta, and Pilat (1996), I employ Rolleigh’s (2013) method to calibrate the
values of the pm for each disaggregated sector.
The concordance of Martins, Scarpetta, and Pilat’s (1996) sector specification to
our level of sectoral disaggregation was completed. Next, the simple average of the
sectors within our level of sectoral disaggregation were taken to obtain the UK sector
import elasticity. 5 Furthermore, the values for the services sector was not included
in both articles, and as a result we apply the same values as in the benchmark case.
The final values are shown in Table 5.5.
5This approach is similar to Cho and Diaz (2011)
30
Sector Rolleigh (2013)
Food & Beverages 0.72Primary Goods 0.91Textiles, Footwear & Clothing 0.94Machinery 0.83Chemicals 0.91Other Manufactures 0.89Services 0.8
Table 5.5: Import Elasticities of Substitution (pm,j)
In the sensitivity experiments of the import elasticity, the parameter governing the
elasticity of export substitution px, is fixed to be 0.9 for both cases. In section 5.6,
we conduct a sensitivity analyses of this parameter under the FTA scenario. The
motivation is twofold. First, there is a lack of data for the export elasticity of UK
sectors. Second, we test the Johnson’s Optimal Tariff (1954) argument where the
optimal tariff should be set to zero as the parameter px approaches one.
5.3.4 Simulation
As seen in section 4, the Static AGE model is a system of non-linear equations.
With the use of MATLAB to solve this system, and with the numerical specification
of the parameters of the static AGE model, I was able to produce the benchmark
equilibrium. Given the nature of the static AGE model, the comparative statics
methodology is employed to analyse the impact of the different UK trade policies
following a withdrawal from the EU. The exogenous shock in our analysis is the
change in the tariff schedule associated with the Trade war and FTA scenarios.
With this exogenous shock, a new steady state equilibrium will be produced where
we can observe and analyse the changes in certain endogenous variables. Under
both scenarios, the benchmark equilibrium is the point of comparison (all other
parameters remain the same). Next, we show the results of these simulations.
31
Chapter 6
Results
6.1 Overview
In this section, the simulated results of the UK partaking in alternative trade
arrangements with the EU are presented and analysed. Trade war and the FTA
are the two alternative trade arrangements explored in this paper. The ‘Trade
War’ scenario examines the hypothetical case where the UK withdraws from the
EU without any trade agreement in place. This effectively means that both parties
must abide by the WTO rules and thus apply the effective MFN tariffs on each
other’s goods. With the ‘FTA’ arrangement, the UK is successful in signing an FTA
with the EU and therefore has the power to set their own tariff policy with the
RoW. These two experiments are known as the Trade War and FTA benchmark
simulation, respectively.
With these new tariff rates, we run the simulation and analyse the changes in
consumption and factor prices, domestic production, foreign trade and welfare. The
results are expressed as the percentage deviation from the values in the benchmark
case. In terms of the welfare analysis, economists usually measure welfare by using an
index based on income in order to overcome the problem of utility having no natural
units (Kehoe 1994a). More specifically, in this paper, the welfare measure is based on
an aggregate consumer real index and a government real index that are combined to
form the social real income index. The consumer real income index is given by∏
j cθjj ,
where j ranges over the consumption goods and the investment good. Similarly, the
government real income index is given by∏
j cθg,jg,j , where j ranges over the production
goods and the investment good consumed by the government. The social real income
index is defined as∏
j CΘjj where Cj = cj + cg,j and Θj =
cj+cg,j∑j cj+
∑j cg,j
. This type
of measure, known as the equivalent variation, seeks to find how much additional
income consumers would need when faced with the base prices in order to achieve
the same level of utility as in the benchmark simulation.
Given the hypothetical nature of the FTA scenario, I conduct a sensitivity analysis to
determine the robustness of the benchmark simulation when the UK tariff rates are
altered. The second sensitivity analysis is performed on the elasticity of substitution
of imports. From the benchmark simulation, the Armington import elasticises were
32
set to be the same across the sectors. Now, we repeat the simulation, except this time
allowing the values to be differentiated by sector. These sectoral import elasticity
values were calculated based on the method employed in Rolleigh (2013).
Next, in the trade war scenario, the government tariff revenue will increase
significantly (due to the rise in the tariff rates) which leads to an increase in
government welfare. In this experiment, we look at the case where the government
passes this additional revenue to consumers by reducing their direct tax payments.
This tariff rebate setup can provide policy makers useful insights into different fiscal
arrangements under certain trade arrangements.
Finally, we determine whether the Johnson’s Optimal Tariff (1954) hypothesis is
valid for the UK case. This hypothesis states that optimal tariff should become
zero as the parameter governing the export elasticity approaches one. Thus this
experiment involves conducting a sensitivity analysis where the export elasticity
values are changed, and then observing the reaction of the social welfare index. It is
through this welfare measure that we base our conclusion on whether this hypothesis
holds for the UK.
6.2 Trade War
The table below is a presentation of the results of the Trade War simulation.
Sector Price Change (%)
Food & Beverages 0.578Primary Goods 0.053Textiles, Footwear & Clothing 0.594Machinery 0.532Chemicals -0.157Other Manufactures 0.041Services -0.265
Table 6.1: Effect of trade war on consumption good prices
The percentage change in the price of consumption goods after the UK and the EU
engage in trade war are shown in Table 6.1. For the majority of sectors, there is a
moderate increase in the price of consumption goods. To understand this movement
in prices, it is paramount to recognise the chain of production of the consumption
goods. As explained in Section 4, the consumption goods content is composed of the
final goods from their own sector and the services sector. However, the final goods
33
producer combines the locally produced component with the imported component.
Thus, when trade costs increase (due to tariff rates rises), this effectively increases
the price of imported goods which in turn leads to an increase in the price of final
goods 1. Since final goods are a key input in the production of the consumptions
goods, this rise in input cost adds pressure to increase the price of consumption
goods. The two sectors that become the most protected industries under the trade
war scenario are the textiles, footwear and clothing sector and the food and beverages
sector, as they experience the largest increases in prices, rising by 0.59% and 0.58%,
respectively. The machinery sector, which is the biggest importer sector from the
EU, has the third highest rise in prices.
It is interesting to note that for the services sector there is a modest fall in price.
This is the UK’s main export sector and the only sector where tariff barriers are not
placed. Since the service sector contributes to the production of every consumption
good, this price decline places downward pressure on the price of all consumption
goods. It is for this reason that prices of consumption goods are lower than the
prices of final goods. Furthermore, this is the cause for the chemical sector actually
experiencing a fall in price. Unlike other sectors, where the services component
makes up 25-35% of the consumption good, the service component accounts for
89% of the chemical consumption good (see SAM). Thus, the price decline in the
services sector outweighs the rise in price of the final goods from the chemicals sector.
Figure 6.1: Effect of trade war on exports
1this is corroborated with our results for the percentage change in final goods price
34
From Figure 6.1, every sector (except for services), experiences a significant fall in
exports to both the EU and the RoW. Under this scenario, the EU place tariffs
on UK goods. The effect of such a policy is that now, UK exports have become
effectively more expensive to the EU consumers. This makes UK products less
price competitive in the EU market and consequently EU consumers shift their
consumption to the EU products. As a result of this substitution effect, the level
of UK exports to the EU decline. The largest fall in exports occurs in the Textiles
sector, falling by 62%. This reflects the fact that this sector becomes the most heavily
protected sector in the EU with a tariff rate of 9.15%. Furthermore, the second and
third most protected sectors in the EU, (food and beverages and the machinery
sector), experience the second and third largest fall in exports, respectively. The
only sector to experience a gain in exports to the EU is the services sector. This is
UK’s main export sector and the only sector where tariff barriers are not placed.
UK exports to the RoW fall even though the RoW tariff levels on UK goods remain
unchanged from the benchmark case. The final goods produced by the UK are
the exports to both the EU and the RoW. Since a key input in the final good
production is imports, the increased tariff levels increase the price of final goods.
Such an increase means that these products become relatively less price competitive
in the RoW market. Similar to the EU customers, the RoW customers will switch
to the RoW goods and consequently UK exports to the RoW decrease. From the
prices of final goods, the machinery sector experiences the largest gain in price and
as a result, the largest decrease in exports to the RoW.
Figure 6.2: Effect of trade war on imports
35
From Figure 6.2, every UK sector experiences a significant fall in imports from the
EU. The explanation is quite similar to the case of exports above except now, the
perspective is from the UK consumers. By the UK placing tariff barriers on EU
imports, they effectively raise the price of EU products. Through the substitution
effect, the level of EU imports into the UK fall. The largest fall in imports takes
place in the textiles,clothing and footwear sector, falling by 39%. This reflects the
fact that this sector becomes the most heavily protected sector in the UK with a
tariff rate of 9.22%. Furthermore, the second and third most protected sectors in
the EU (food and beverages and machinery sector) experience the second and third
largest fall in imports, respectively.
From the graph above, we also notice a fall in RoW imports in most sectors, despite
the UK maintaining their tariff policy with the RoW. As shown above, there is an
overall decrease in exports to both trading partners. As a result, UK consumers,
who are the owners of the factors of production, experience a loss in income. With
less income they have less money to spend on imports from the EU and the RoW.
Thus it is through the income channel that RoW imports for many sectors fall.
The food and beverages sector is the only sector that experiences a gain in imports
from the RoW. This trade diversion represents the UK shifting their source of food
imports to the more efficient producer, the RoW. Prior to this scenario by having
no tariffs, the EU (the relatively less efficient producer) were able to export to the
UK (Springford et al. 2014).
Under trade war, the total bilateral trade flow volumes for the UK with the EU
and the RoW decrease by 17% and 2.5%, respectively. In terms of the composition
of goods trade by destination, the share of UK’s export to the EU falls from 53%
to 49%, while the share of import from the EU falls from 48% to 44%. With such
information, this signifies the shift in trade that the UK makes with the RoW even
though there is a loss in trade from both trading partners. On a global scale, the
UK bilateral trade falls by 9.2%, highlighting the overall negative impact of Trade
War on UK trade.
Table 6.2 shows the effect of trade war on domestic production in the UK. The
change in domestic production is influenced by the changes in the demand for final
goods and imports. This is because the final goods producers combine the imported
component with the domestically produced component. For example, in a particular
sector, if there is an increase in the demand of the final good that outweighs the
increase in import value, then this gap is filled by increasing the production of the
36
Sector Change (%)
Food & Beverages 1.041Primary Goods 0.141Textiles, Footwear & Clothing -3.883Machinery -3.622Chemicals -5.293Other Manufactures -1.734Services 0.309
Table 6.2: Effect of trade war on domestic production
domestic firm. In our scenario, the main driver of demand of final goods is exports.
Thus the change in the trade balance plays a major role in determining the change
in domestic production. With the rise of tariff levels, both imports and exports fall
for most sectors, as shown above. As a result, if import value falls by more than the
export value (trade balance improving), then there is upward pressure on increasing
domestic production.
From the results, every sector that experiences an improvement in their total
trade balance also sees an increase in their domestic production and vice-versa.
Additionally, another channel of demand for the final good comes from the
Government spending. With tariff revenue increasing, Governments expenditure
on services increases (governments only purchase services, see SAM) and therefore
domestic production in services, expands. The major ‘winners’ from this trade
environment include the food and beverages, primary goods and services sectors
where the food sector expands by 1.05%. On the other hand, the rest of the sectors
experience a loss in production with the chemicals sector attaining the largest loss
of 5.3%.
Sector Factor Price (%)Rental Rate -0.253Wage -0.561
Table 6.3: Effect of trade war on Factor Prices
Table 6.3 shows the change in the price of the wage rate of labour and the rental rate
of capital. The main determinant of change in factor prices stems from the change
in demand from the domestic production firms. Domestic firms employ labour and
capital to produce their output. Therefore, given that under Trade War, there is
an overall decline in domestic production, these firms in general will demand less
resources which in turn induces a negative change in factor prices. In terms of value,
37
the relatively labour intensive sectors (machinery and other manufactures) display
the largest losses in domestic production. This leads to a disproportionate decrease
in wages compared to the rental rate where wages fall by more than twice the fall
of the rental rate.
Sector Change (%)
Aggregate consumer welfare -0.466Government welfare 1.169Social welfare -0.066
Table 6.4: Effect of trade war on Welfare
Finally, I analyse the impact of trade war on social welfare. As mentioned earlier,
social welfare is a weighted sum of the welfare from the aggregate consumer and the
national government. From the consumer perspective, the fall in disposable income
(as demonstrated by the decrease in rental rate and wages), leads to a loss in welfare
of 0.47%. On the other hand, the government records a significant gain in welfare,
rising by 1.17%. Since tariff rates increase under this scenario, the tariff revenues
collected by the government rise by 267% compared to the benchmark case. This
additional revenue enables the government to expand their expenditure, thereby
facilitating the attainment of a higher welfare. Taking both welfare results together,
social welfare shows a slight loss of 0.07% (more weight is placed on the consumer
welfare). With such a result, this provides evidence that trade war with the EU can
have a negative impact, even if small, on the UK economy as a whole.
Ottaviano, Pessoa and Sampson (2014) measure of welfare was based on the change
of real GDP. They found that in a trade war scenario, the UK would produce a static
loss of 0.14% of GDP. In order to make a comparison, I also measure the change in
real GDP based on my results from the trade war simulation. I find a static loss of
0.128% of UK GDP. With such a small difference compared to Ottaviano, Pessoa and
Sampson (2014), this provides credibility in the results I produced. Furthermore,
this result also corroborates with the result produced by the social welfare measure.
The impact on the UK economy is negative but small.
38
6.3 Free Trade Agreement
In this section, I present the results from the simulation of the FTA setup.
Sector Price Change (%)
Food & Beverages 0.030Primary Goods & -0.021Textiles, Footwear & Clothing -0.748Machinery 0.010Chemicals 0.040Other Manufactures 0.007Services 0.065
Table 6.5: Effect of trade war on consumption good prices
The percentage change in the price of consumption goods after the UK signs a
FTA with the EU are shown in Table 6.5. For many sectors, there is little price
increase which may seem contradictory given that the tariff levels with the RoW
have dropped. To explain this, the chain of production of the consumption goods
outlined in the trade war scenario, needs to be emphasised and reiterated. When
tariff levels decrease, the trade costs drops which in turn places pressure for the
prices of the final goods to decline. For the final good prices, we observe a decline
in every sector (except for the services and food and beverages sector). For the
services sector, there is no reduction in tariff barriers (since it is already zero) and
for the food and beverages sector, not only is it the smallest import sector from the
RoW, but only 25% of imports actually come from the RoW. Similar to study for
the Trade War scenario, the price rise in the services sector places upward pressure
on the price of consumption goods. Since the tariff reductions in many sector are
particularly small, it is for this reason that the prices of consumption goods for many
sectors become positive.
From Table 5.4, we notice that tariffs are not completely eliminated but are rather
reduced to a certain degree. This magnitude of reduction plays a key role in the
determination of prices. The textiles sector experiences the largest fall in tariff level
with the RoW and consequently, experiences a relatively large decline in prices of
0.75%. The chemicals industry experiences the second largest fall in tariff levels,
however records a positive gain in prices. As mentioned earlier, 89% of the content of
the chemical consumption good is made up of services and since the price of services
increases, this outweighs the negative impact from tariff levels and thus increases
in prices (in fact from the final goods price, chemicals record the second largest fall).
39
Figure 6.3: Effect of a FTA on exports
From Figure 6.3, every sector (except for services), experiences a significant rise
in exports to both the EU and the RoW. The manner in which tariffs impact UK
exports, is again similar to the explanation provided under the Trade War scenario.
The difference is that now, under the FTA scenario, the RoW reduce tariffs on UK
goods. By the RoW reducing their tariffs, UK products become more competitive in
the RoW market as they can sell their product at a lower price to the RoW customer.
Consequently, the RoW consumers shift their consumption to the UK products and
thereby increase the level of UK exports to the ROW. The largest rise in exports
occurs in the textiles, clothing and footwear sector, rising by 45%. This reflects the
fact that this sector enjoys the largest reduction in tariffs from 6.41% to 3.36%. The
only sector to experience a loss in exports to the RoW is the services sector. This is
the UK’s main export sector and the only sector where tariff reductions do not occur.
UK exports to the EU rise even though EU tariff levels on UK goods remain zero.
The decrease in the price of the final goods caused by tariff reduction on imports
makes the UK products relatively more price competitive in the EU export market.
Similar to the RoW customers, the EU customers will switch to the UK goods and
thereby increase the level of UK exports to the EU. From the graph, the textiles,
clothing and footwear and chemicals sectors experience the largest rise in exports
to the EU. This can be attributed to the fact that both sectors exhibit the largest
declines in the price of their final goods.
40
Figure 6.4: Effect of a FTA on imports
From Figure 6.4, every UK sector experiences a significant upsurge in imports from
the RoW. By UK reducing tariff barriers on RoW imports, the price of RoW imports
become effectively cheaper. Through the substitution effect, the level of RoW
imports into UK rise. The largest increase in imports takes place in the textiles
sector, rising by 16%. This reflects the fact that this sector enjoys the largest
reduction in tariffs from 6.6% to 3.48%. The chemicals sector, which enjoys the
second largest reduction in tariff from 2% to 1.03%, experiences the second largest
increase in imports from the RoW. This is followed by the machinery sector which
is the biggest import sector from the RoW.
For four sectors, there is a small rise in the level of EU imports. Again, this
arises due to the income effect. As exports increase, this brings in new income
to which the UK consumers are able to extend their purchases of imports from the
EU. However under this scenario, trade diversion is more evident. Three sectors
namely the primary, textiles, clothing and footwear and services, exhibit declines
in imports from the EU. Even if the RoW had a product where they were more
efficient in producing than the EU, the fact that tariffs were applied to the RoW
before and not to the EU, enabled many non-efficient EU producers to hold a large
market share in imports to the UK. Now that we have a reduction in tariff rates,
this advantage to the EU is reduced Hindley and Howe (2001).
Under an FTA, the total bilateral trade flow volumes for the UK with the EU and
the RoW increase by 1.07% and 4.05%, respectively. In terms of the composition
41
of goods trade by destination, the share of UK’s export to the EU falls from 52.5%
to 51.7%, while the share of import from the EU falls from 48.2% to 47.5%. With
such information, this signifies the shift in trade that the UK makes with the RoW.
On a global scale, the UK bilateral trade increases by 2.5%, highlighting the overall
positive impact of a FTA on UK trade.
Sector Change (%)
Food & Beverages 0.381Primary Goods 0.076Textiles, Footwear & Clothing -0.719Machinery 2.462Chemicals 1.399Other Manufactures 0.448Services -0.159
Table 6.6: Effect of a FTA on domestic production
Table 6.6 shows the effect of an FTA on domestic production in the UK. As
demonstrated previously, trade balance plays a major role in determining the change
in domestic production. Unlike the trade scenario, tariff levels drop for most sectors
and consequently both imports and exports rise, as shown above. As a result, if
export value increases by more than the import value (trade balance improving),
then there is upward pressure on increasing domestic production.
From the results, every sector except the primary goods sector that experiences
a deterioration in their total trade balance also sees a decrease in their domestic
production. The primary goods sector on the other hand records a gain in
production. This highlights the fact that the primary goods sector is an important
intermediate good for the domestic production in both the food and beverages and
other manufactures sector. Since domestic production increases for both of these
sectors, this demand on the primary goods outweighs the loss in the deterioration
in their total trade balance.
This time, tariff revenue for the government falls. Consequently, there is a decline in
government expenditure in the services sector which augments the loss in domestic
production for the services sector. The major ‘winners’ arising from a FTA
include the machinery, chemicals, food and beverages and other manufactures. The
machinery sector expands the most, by 2.5%. On the other hand, the rest of the
sectors experience a loss in production with the textiles sector attaining the largest
loss of 0.72%. Analysing the two possible scenario after UK withdrawal from the EU,
42
shows that the food and beverages and primary goods sector will experience a gain
in domestic production while the textiles will experience a loss under both scenarios.
Sector Factor Price (%)Rental Rate -0.001Wage -0.152
Table 6.7: Effect of a FTA on Factor Prices
Table 6.7 shows the change in the price of the wage rate of labour and the rental rate
of capital under an FTA. While we do observe a rise in total domestic production,
the resulting changes in factor prices are mixed. This is mainly due to the change
in disaggregated domestic production patterns. There is a major shift in resources
from the service sector (the second most capital intensive industry) to the more
labour intensive machinery sector. As a result, the wage rate grows while the rental
rate experiences an insignificant fall.
Sector Change (%)
Aggregate consumer welfare 0.105Government welfare -0.065Social welfare 0.065
Table 6.8: Effect of a FTA on Welfare
Finally, I analyse the impact of an FTA on the national welfare of UK. Since wages
make up 70% of consumers’ income, the increase in wages outweighs the loss in the
rental rate, thereby producing a rise in disposable income for consumers. With
additional income, consumers can purchase more which leads to a rise in their
welfare. This time, the government records a loss in welfare, declining by 0.065%.
Since tariff rates are reduced under this scenario, the tariff revenues collected by the
government fall by 20% compared to the benchmark case. With less total revenue,
governments cannot make as many purchases as before. Taking both welfare results
together, social welfare shows a slight gain of 0.07%. Therefore, if the UK were able
to successfully sign a FTA with the EU and the numerous nations in the RoW (as
stated in section 4), then the UK can enjoy a positive but small impact on their
economy. In terms of the welfare measure based on the change of real GDP, I find
a static gain of 0.04% of GDP. Again, corroborating with the social welfare result,
that under this type of trade policy, the impact on the UK economy is positive but
43
fairly small.
Given the nature of this scenario, a sensitivity analysis of the tariff rates was
conducted. To conduct the sensitivity analysis, the difference between the
benchmark tariff and the adjusted tariff was halved. Then I add and subtract
this value from the adjusted tariff rate. The results follow the same pattern as in
the benchmark simulation except with different magnitudes. For every variable it
shows a 50-100% change compared to the FTA benchmark simulation. In terms
of the welfare analysis it records a 0.03-0.10% positive gain. Therefore, the result
seems robust.
6.4 Import Elasticities of Substitution Differentiated
by Sector
In the above benchmark simulations, the elasticity of substitution of imports were
set to be the same across the sectors. Thus, I perform a sensitivity analysis where
the values of the import elasticities are differentiated by sector. Following the
methodology employed in Rolleigh (2013), I obtain the data from Martins, Scarpetta,
and Pilat (1996), and then I calculate the import elasticities for the UK case. The
motivation behind such analysis is to check the robustness of the benchmark results
by using more realistic values. In the benchmark case, the average was assumed
to be 0.8 while with these new values the average is 0.87. In terms of the export
elasticity, this is assumed to be fixed at 0.9 for each case 2
Sector Trade War (%) FTA (%)
Food & Beverages 0.575 0.038Primary Goods 0.044 0.021Textiles, Footwear & Clothing 0.350 -0.784Machinery 0.480 0.029Chemicals -0.139 0.035Other Manufactures 0.030 0.030Services -0.229 0.055
Table 6.9: Effect on Consumption Good prices (σm,i 6= σm,j)
Table 6.9 shows the change in consumption good prices under both scenarios when
2For results of other variables see Appendix C
44
conducting a sensitivity analysis. For both scenarios the pattern is quite similar
to the corresponding benchmark cases. Under a case where tariffs fall, when a
sector has a higher import elastic compared to another one, the impact should be
larger on its price of consumption goods compared to the benchmark simulations.
However, as can be seen from table X, this is not always the case. A possible reason
is that the UK are in many sectors, both export and import intensive. For most
sectors under the FTA scenario, the change in prices are a lot larger in magnitude
compared to the FTA benchmark simulation. The textiles, clothing and footwear
has the largest import elasticity of 0.94. Though it has the largest change in terms
of absolute quantity, the other manufactures experience a 3.54 times larger change
than the benchmark simulation. For the trade war scenario, most changes are lower
compared to the benchmark simulations.
Sector Trade War (%) FTA (%)
Rental Rate -0.189 -0.007Wage Rate -0.483 0.114
Table 6.10: Effect on Factor prices (σm,i 6= σm,j)
For the Trade War scenario, the factor prices for both the rental rate and wage
rate improve when compared to the Trade War benchmark simulation. This result
is mainly driven by improvement in domestic production 3. On the other hand,
the factor prices in the FTA scenario both decrease more than the corresponding
benchmark simulation. This time the domestic production does not grow as much.
Sector Trade War (%) FTA (%)
Aggregate Consumer welfare -0.393 0.077Government 1.201 -0.202Social Welfare -0.003 0.009
Table 6.11: Effect on Welfare (σm,i 6= σm,j)
The most interesting result arising from this experiment is the change in welfare.
While for both scenarios the social welfare heads in the same direction as in their
corresponding benchmark simulation, the result becomes insignificant. As a result,
3See Appendix C
45
the results form the benchmark simulation do not seem as robust as we hoped for.
6.5 Tariff Revenue Rebate under Trade War
From the trade war simulation, I noticed that the UK government tariff revenue
increases by 267% and Social welfare falls by 0.06%. As a result, it would be
interesting to conduct a numerical experiment where the government hands over this
additional tariff revenue to the consumers by lowering the direct aggregate tax rate
imposed on consumers’ income. If the situation improved after such a policy, then
this type of tariff revenue rebate setup can provide policy makers useful insights into
different fiscal arrangements under certain trade arrangements. In order to eliminate
the additional gain in tariff revenue, the direct tax was decreased by 1.95%. Here
we only include the change in prices of consumption goods, factor prices and welfare.
Sector Price Change (%)
Food & Beverages 0.579Primary Goods 0.054Textiles, Footwear & Clothing 0.596Machinery 0.534Chemicals -0.158Other Manufactures 0.043Services -0.266
Table 6.12: Effect of trade war with Rebate on consumption good prices
Sector Factor Price (%)Rental Rate -0.253Wage -0.561
Table 6.13: Effect of a Trade War with Rebate on Factor Prices
Sector Change (%)
Aggregate consumer welfare -0.119Government welfare -0.228Social welfare -0.034
Table 6.14: Effect of Trade War with Rebate on Welfare
In comparison to the benchmark simulation, there are no significant changes in the
price of consumption goods and factor prices. In terms of welfare, consumers’ welfare
46
does not fall to the extent experienced in the benchmark simulation. The reason for
the difference being that consumers under this new fiscal arrangement have less tax
to pay, which improves their disposable income. As for the government, the welfare
improves but not as much as that shown in the benchmark simulation. Overall the
social welfare still experiences a loss of 0.034%. Nevertheless, when comparing to
the benchmark simulation, this indicates an improvement of nearly 48%. Therefore,
this demonstrates that different fiscal arrangements can be beneficial under a change
in trade policy.
6.6 Optimal Tariff Argument
The final experiment involves testing the validity of the Johnson’s Optimal Tariff
(1954) hypothesis for the UK under the FTA scenario. This hypothesis states that
optimal tariff should become zero as the parameter governing the export elasticity
approaches one. Thus this experiment involves conducting a sensitivity analysis
where the export elasticity values increase incrementally, at which point I observe
the reaction of the social welfare index. The motivation behind this test is twofold.
Since we do not have export elasticities for the UK, this test indirectly provides a
sensitivity analysis to this scenario. Second, given the history of the UK’s attitude
towards free trade, this test might provide evidence that the UK should implement
a unilateral free trade policy (Booth and Howarth 2012; Srpingford et al. 2015)
Sector 0.8 0.85 0.9 0.95
Aggregate consumer welfare 0.079 0.090 0.104 0.127Government welfare -0.167 -0.132 -0.064 0.142
Social welfare 0.019 0.036 0.065 0.133
Table 6.15: Effect of Trade War with Rebate on Welfare
From Table 6.15, we do indeed find that the hypothesis holds for the UK; the social
welfare improves as the export elasticity approaches one. As a result, if the export
elasticity of substitution increases, then it would become optimal for the UK to set
tariffs to zero.
47
Chapter 7
Conclusion
This paper analyses the potential quantitative effects of the UK withdrawing from
the EU. The focus is on two possible exit scenarios the UK could face: (1) the
pessimistic case, the UK engages in trade war with the EU, and (2) the optimistic
case, the UK successfully signs an FTA with the EU and thereby acquires the
ability to sign FTAs with members of the RoW. The second scenario in particular is
important as based on the literature it has been done before due to the uncertainty
and complexity of the situation. In order to conduct our analysis, a static AGE
model that is calibrated to the constructed UK SAM is employed. Dependent on
the exit scenario, the tariff parameter is altered and the simulation run. From here,
I find the predicted effects on prices, trade, domestic production, and welfare of the
UK economy.
The results from the trade war scenario, show that overall, prices increase, domestic
production falls and bilateral trade with both the EU and the RoW decline. In
terms of welfare, consumers experience a welfare loss of 0.47% due to the fall in
factor prices, while on the other hand, the government records a gain of 1.22%.
This gain arises due to the newfound tariff revenue from the EU imports. Overall,
social welfare falls by 0.066%, highlighting the negative impact if the UK were to
participate in such a situation. This result is corroborated with Ottaviano, Pessoa
and Sampson (2014).
For the FTA scenario, the overall effect on prices, domestic production and bilateral
trade with the EU and the RoW are the reverse in direction compared to the trade
war scenario. For both scenarios, the primary, food and beverages sector always gain
in domestic production. Furthermore, in most variables the largest impact occurs
on the textiles, clothing and footwear sector due to the fact that it experiences the
largest change in tariff rates from both scenarios. An interesting result from this
scenario is that although bilateral trade grows with both the EU and the RoW, many
disaggregated sectors suffer from trade diversion. This is especially evident from the
import side as UK consumers switch to the more efficient producers in the RoW.
In the FTA arrangement, as the disposable incomes of consumers rise, so too does
their welfare, which shows a gain of 0.10%. This time, the government welfare falls
48
by 0.065% as they lose tariff revenue from the RoW imports. Still, the social welfare
increases by 0.065%, meaning that the UK can gain from this trade arrangement
with the EU. However, this result must be taken with caution. The magnitude is
quite small and as I performed a sensitivity analysis on the import elasticities, the
social welfare showed to be insignificant, highlighting that the magnitude of this
gain is not as robust.
This paper set out to provide an answer to the question ‘Should the UK leave
the EU?’ with a focus on tariff rates. But in reality, membership with the EU
implies many other aspects that need to be considered with which this model does
not capture. For example, due to the static nature of the model, the dynamic
phenomena such as capital flows and foreign direct investment (FDI) under different
trade policies are not captured. For instance, FDI is considered to be major potential
cost to leaving the EU for the UK economy. The City of London is Europe’s largest
financial centre and an integral part of the UK economy. Thus if their position was
threatened due to withdrawal from the EU, this can have substantial costs to the
UK economy. Thus, a model that incorporates these dynamic aspects will provide
a more accurate effect of withdrawal. Other issues not addressed explicitly in this
analysis include the EU rules of origin, EU regulation, UK’s fiscal contribution to the
EU and migration flows. Analysing the impact of these aspects if the UK withdrawal
were to happen are interesting questions for future research.
One limitation of my results is that the actual tariff rates that the UK might impose
on foreign goods are not known with certainty. The results produced are quite
dependent on the assumption made. This is expected given the hypothetical nature
of the alternative scenario. Though a sensitivity analysis was performed, employing
completely different methods in determining the effective tariff rates can show how
robust the results are.
An interesting extension to this analysis that can be studied is the welfare impact a
UK withdrawal from the EU has on differentiated households. In order to conduct
this analysis, the UK Living Costs and Food Survey must be acquired 1. Households
can be differentiated by: age, education and/or income. Specific for the UK,
households can be differentiated by their country (England, Scotland, Wales and
Northern Ireland). Such future research can provide important information and
inform the UK public when the planned referendum arrives.
1Data is only available to UK residents.
49
Appendix A
A1
Sector Price change Government
Food & Beverages 0.0945 0.0000Primary Goods 0.0170 0.0000Textiles, Footwear & Clothing 0.0547 0.0000Machinery 0.0739 0.0000Chemicals 0.0202 0.0000Other Manufactures 0.0936 0.0000Services 0.5120 0.9090Investment Goods 0.1290 0.0910
Table A.1: Preference parameters θ - aggregate consumer andgovernment
Sector α β
Food & Beverages 0.2024 7.7930Primary Goods 0.6485 2.7419Textiles, Footwear & Clothing 0.0029 8.7604Machinery 0.0260 3.9378Chemicals 0.2475 6.7437Other Manufactures 0.1028 5.2029Services 0.3102 3.5703
Table A.2: Domestic goods firm parameters (α, β)
50
Sector γ λdom λEU λRoW
Food & Beverages 2.7395 0.4257 0.3141 0.2601Primary Goods 2.8760 0.3980 0.2656 0.3362
Textiles, Footwear & Clothing 2.9935 0.3616 0.2888 0.3495Machinery 2.9706 0.3592 0.3286 0.3121Chemicals 2.9359 0.3742 0.329 0.2967
Other Manufactures 2.7520 0.4310 0.273 0.296Services 2.2431 0.5197 0.2386 0.2416
Table A.3: Armington Aggregators
51
Appendix B
A2
Pro
du
ctio
nC
on
sum
pti
on
Des
c1
23
45
67
12
34
56
7L
KC
IFI
GX
X (
EU)
X (
RO
W)
Tota
l
Pro
du
ctio
n1
. Fo
od
an
d B
ever
ages
16
17
42
65
91
26
16
10
24
54
30
93
79
65
90
00
00
00
00
01
06
01
77
36
10
86
56
87
11
59
95
9
2. O
ther
Pri
mar
y1
16
89
79
21
31
38
53
22
82
89
32
29
00
70
71
00
00
00
00
02
91
70
28
49
22
13
83
71
09
11
93
41
3. T
exti
les,
Clo
thin
g &
Fo
otw
ear
10
22
43
96
73
54
30
16
75
57
30
04
38
47
00
00
00
00
47
00
11
68
18
06
63
61
56
63
22
4. M
ach
iner
y9
02
12
11
70
51
77
93
90
95
25
80
91
00
04
67
62
00
00
00
04
85
60
01
10
40
34
96
22
60
78
03
19
12
0
5. C
hem
ical
51
21
55
64
23
19
48
16
76
95
70
22
50
52
00
00
22
06
00
00
00
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49
80
22
77
60
22
04
11
03
97
0
6. O
ther
Man
ufa
ctu
res
68
64
37
37
26
12
89
16
25
89
53
62
47
87
08
00
00
06
81
97
00
00
01
31
90
07
03
06
35
25
43
50
52
32
63
92
7. S
ervi
ces
34
13
91
06
01
20
68
93
90
12
23
36
74
73
23
84
03
56
25
70
53
53
01
92
67
29
51
91
83
57
31
99
15
26
98
10
00
01
55
57
73
47
66
51
66
18
06
60
67
10
01
13
23
40
25
9
Co
nsu
mp
tio
n1
. Fo
od
an
d B
ever
ages
00
00
00
00
00
00
00
00
11
05
20
00
00
00
11
05
20
2. O
ther
Pri
mar
y0
00
00
00
10
53
64
10
60
16
31
14
76
28
12
05
63
10
01
88
52
69
81
00
19
81
90
00
00
01
98
19
3. T
exti
les,
Clo
thin
g &
Fo
otw
ear
00
00
00
00
00
00
00
00
63
96
10
00
00
06
39
61
4. M
ach
iner
y0
00
00
00
00
00
00
00
08
64
22
00
00
00
86
42
2
5. C
hem
ical
00
00
00
00
00
00
00
00
23
66
10
00
00
02
36
61
6. O
ther
Man
ufa
ctu
res
00
00
00
00
00
00
00
00
10
94
57
00
00
00
10
94
57
7. S
ervi
ces
00
00
00
00
00
00
00
00
59
84
65
00
00
00
59
84
65
Lab
ou
r2
05
60
16
19
94
22
34
93
86
11
65
65
79
73
80
59
22
00
00
00
00
00
00
00
00
96
59
20
Cap
ital
52
17
29
88
11
21
31
63
83
36
64
43
62
37
70
00
00
00
00
00
00
00
04
09
28
0
Ho
use
ho
lds
00
00
00
00
00
00
00
96
59
20
40
92
80
00
00
00
01
37
52
01
Go
vern
men
t 2
57
42
-78
49
79
04
51
47
96
04
09
57
-58
92
51
55
92
16
84
71
01
41
30
98
92
68
71
48
40
00
00
00
00
17
61
79
Dir
ect
Tax
00
00
00
00
00
00
00
00
20
62
80
00
00
00
20
62
80
Ind
irec
t ta
x2
53
26
-79
26
66
02
41
36
66
54
04
82
-58
92
51
55
92
16
84
71
01
41
30
98
92
68
71
48
40
00
00
00
00
17
26
03
Tari
ff(T
ota
l)4
16
77
13
02
10
10
29
54
75
00
00
00
00
00
00
00
00
03
57
6
Tari
ff(E
U)
00
00
00
00
00
00
00
00
00
00
00
00
Tari
ff (
RO
W)
41
67
71
30
21
01
02
95
47
50
00
00
00
00
00
00
00
00
35
76
Cap
ital
(Sa
vin
gs)
00
00
00
00
00
00
00
00
15
07
99
00
34
79
33
52
28
35
22
80
22
08
21
CF
00
00
00
00
00
00
00
00
58
17
00
00
00
0
Imp
ort
(To
tal)
38
00
95
30
64
28
64
61
41
10
14
39
84
84
51
69
46
90
00
00
00
00
00
00
00
00
48
40
11
Imp
ort
(EU
)2
85
46
16
39
38
92
28
93
02
29
22
33
60
32
45
82
90
00
00
00
00
00
00
00
02
54
24
7
Imp
ort
(R
OW
)9
46
43
66
71
19
72
45
18
00
14
76
14
84
84
48
86
10
00
00
00
00
05
81
70
00
00
23
55
81
Tota
l1
59
81
81
19
20
56
63
23
31
92
58
10
41
09
32
63
92
23
40
26
01
10
51
91
98
17
63
96
18
64
22
23
66
11
09
45
75
98
46
59
65
92
04
09
28
01
37
52
01
58
17
22
08
21
38
24
58
48
98
28
25
42
47
23
55
81
0
Figure B.1: Social Accounting Matrix for the UK, 2011
52
Appendix C
A3
Sector EU (%) RoW(%)
Food & Beverages -40.790 -7.868Primary Goods -10.626 -1.841
Textiles, Footwear & Clothing -61.914 -8.969Machinery -36.019 -9.545Chemicals -25.544 -6.861
Other Manufactures -24.924 -1.571Services -0.658 2.955
Table C.1: Effect of Trade War on Exports (σm,i 6= σm,j)
Sector EU (%) RoW(%)
Food & Beverages 0.179 13.165Primary Goods 0.466 4.806
Textiles, Footwear & Clothing 12.866 49.427Machinery 0.376 14.065Chemicals 1.859 8.746
Other Manufactures 0.327 5.327Services -0.0467 -1.061
Table C.2: Effect of an FTA on Exports (σm,i 6= σm,j)
Sector EU (%) RoW(%)
Food & Beverages -16.693 -0.852Primary Goods -18.899 -0.821
Textiles, Footwear & Clothing -75.265 0.723Machinery -19.472 -3.123Chemicals -24.394 -2.496
Other Manufactures -19.967 -2.493Services 0.727 -1.240
Table C.3: Effect of Trade War on Imports (σm,i 6= σm,j)
53
Sector EU (%) RoW(%)
Food & Beverages 0.536 1.588Primary Goods 0.042 1.270
Textiles, Footwear & Clothing -14.963 41.855Machinery 2.967 4.324Chemicals 0.416 12.910
Other Manufactures 0.658 2.494Services -0.135 0.365
Table C.4: Effect of an FTA on Imports (σm,i 6= σm,j)
Sector EU (%) RoW(%)
Food & Beverages -0.628 0.544Primary Goods 1.199 0.333
Textiles, Footwear & Clothing 3.879 -12.765Machinery -3.504 2.994Chemicals -1.789 0.933
Other Manufactures -1.027 0.713Services 0.185 -0.161
Table C.5: Effect on Domestic Production (σm,i 6= σm,j)
54
Appendix D
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