This paper outlines different approaches with the aim of analysing the robustness of outcomes of the Brexit in varying model assumptions. The paper first is concerned with the methodology and gives a brief overview of the possible Brexit scenarios and summarizes the results and the appropriate robustness checks estimated by Dhingra et al. (2017). Section 5 begins by laying out theoretical approaches of the research and discusses how the results change as the models extend by GVC and network effects.
Over the past century, there has been a dramatic increase in economic integration. Policy makers continued signing trade agreements after decades of war and political isolation. In 2016, the British decided to leave the EU and initiated a turnaround in political framework. Recent developments in Europe signal that the EU could be under pressure if the consequences of leaving the EU are insignificant. Therefore, these developments have heightened the need for scientific studies on trade integration and trade disperse. The individual per capita benefits of trade liberalisation have been studied by many researchers. There is a growing body of literature that recognises new quantitative trade models and fill them with the latest input output data.
Table of Contents
1 List of Abbreviations
2 Introduction
3 Estimations of Dhingra et al. (2017)
3.1 Empirical Method
3.1.1 Model Assumptions
3.1.2 Gravity Equation
4 Scenarios of Leaving the EU
4.1 Summary of the results
4.1.1 Robustness Checks
4.2 Input-Output Data
5 Critical Assessment
5.1 Baseline Model
5.1.1 Melitz Model Extension of Jafari et al. (2020)
5.1.2 Aggregation Bias
5.2 Global Value Chains
5.2.1 Network effects
5.2.2 Results of Cappariello et al. (2020)
6 Conclusion and Outlook
7 Appendix
7.1 Additional equations
7.2 Figures
8 List of Illustrations
9 Bibliography
1 List of Abbreviations
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2 Introduction
Over the past century, there has been a dramatic increase in economic integration. Policy makers continued signing trade agreements after decades of war and political isolation. In 2016, the British decided to leave the EU and initiated a turnaround in political framework. Recent developments in Europe signal that the EU could be under pressure if the consequences of leaving the EU are insignificant. Therefore, these developments have heightened the need for scientific studies on trade integration and trade disperse. The individual per capita benefits of trade liberalisation have been studied by many researchers. There is a growing body of literature that recognises new quantitative trade models and fill them with the latest input output data.
Dhingra et al. (2017) use a general equilibrium framework based on the Armingtion model to estimate welfare effects in counterfactual analysis. The most frequent appearing scenarios for the Brexit are the Soft Brexit and the Hard Brexit. In the optimistic Soft Brexit, the UK stays in the Single Market and has similar trade conditions as Norway (Dhingra et al., 2018). The Hard Brexit scenario incorporates trade barriers amounting from WTO trade conditions (Dhingra et al., 2018). By the 1st of January 2021, the Brexit finally realised in the form of the ‘No Deal’ what is comparable to the Hard Brexit scenario. Nonetheless, this paper will not examine the details of the ‘No Deal’. Instead, this review paper mainly refers to the paper by Dhingra et al (2017) and the predictions of welfare changes due to external shocks. Considering the Brexit scenarios, Dhingra et al. (2017) calculate a welfare loss of 1.3% in the optimistic and 2.4% in the pessimistic scenario. In addition, Dhingra et al. (2017) find that the welfare loss is distributed equally to the income deciles. However, these results tend to be underestimated as they do not incorporate the latest data and dynamic effects driven by FDI or GVC. This paper outlines different approaches with the aim of analysing the robustness of outcomes in varying model assumptions. Overall, these results indicate that the Brexit will have a negative effect on Europe and especially on the UK.
This paper is organised in the following way. The paper first is concerned with the methodology used by Dhingra et al. (2017). Chapter 4 gives a brief overview of the possible Brexit scenarios and summarizes the results and the appropriate robustness checks estimated by Dhingra et al. (2017). Section 5 begins by laying out theoretical approaches of the research and discusses how the results change as the models extend by GVC and network effects. Finally, chapter 6 concludes and gives an outlook.
3 Estimations of Dhingra et al. (2017)
In this section this paper summarizes the underlying empirical approach to quantify the welfare effects of leaving the EU. The model gets different outcomes for the highlighted scenarios resulting from changes in trade. Over all the estimations lead to negative welfare effects across the income distribution.
3.1 Empirical Method
As in the last decades computing power steadily increased and researchers apply the data to international trade, the amount of trade models increased as well. Modern Computable General Equilibrium Models allow to do comparative statistics and connect simulated exogenous shocks with the current data. Dhingra et al. (2017) use the Eaton-Kortum general equilibrium model specified by Costinot et al. (2014) that fundamentally bases on the Armington model.
3.1.1 Model Assumptions
The baseline trade model consists of four assumptions additional to the following restrictions on a macro perspective: (i) trade is balanced, (ii) aggregate profits are a constant share of aggregate revenues, (iii) the import demand system exhibits CES (Dhingra et al., 2017).
First, the authors assume that the representative household underlies a Dixit-Stiglitz model explained by a CES utility function (Dhingra et al. 2017). Since the elasticity of substitution s>1 the function exhibits convex monotonic preferences (Ottaviano, 2014). Second, the model simulates a one factor economy where total expenditures 𝐸𝑗 equal the sum of labour income. Therefore, trade must be balanced since the aggregate budget constraint is binding (Dhingra et al. 2017). Furthermore, balanced trade implies the same level of overall expenditures, income 𝑤𝑗𝐿𝑗 , and trade flows 𝑋𝑖𝑗 (Dhingra et al., 2017).
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The two missing assumptions are as follows: linear cost functions and perfect competition (Dhingra et al., 2017).
So far, we know that a household receives utility from consumption and that its expenditures come from labour income. The model estimates welfare in terms of real consumption given by the equation below.
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Real consumption 𝑐𝑗is computed by the household’s expenditures divided by the nation’s price index 𝑃𝑗. In equilibrium expenditures and income must equal (Dhingra et al., 2017).
3.1.2 Gravity Equation
On a macro perspective we want to examine bilateral trade flows and their sensitivity regarding changes in trade costs. It is obvious that countries located near to each other trade a lot more than countries with a long distance between their borders. However, countries with comparative advantages in production are more efficient so that cost differences can carry iceberg costs resulting from long distances and trade barriers (Costinot et al., 2014). This model suggests that there is no opportunity for arbitrage as prices equal marginal costs (Dhingra et al., 2017). To quantify the gains from international trade, economists use gravity equations.
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The outcome 𝑋𝑖𝑗 states the overall contribution going from country 𝑗 to country 𝑖. This is measured by country 𝑗’s dependency on import goods of country 𝑖 multiplied with cumulative expenditures. Dhingra et al. (2017) combine the country’s aggregate expenditures 𝐸𝑗, trade obstacles 𝑑𝑖𝑗 and the exporter’s effectiveness in supplying goods in the home market 𝐻𝑖(𝑤𝑖)−𝜃 (same as the parameter Φ𝑖𝑗). Where 𝐻𝑖 refers to the technological standard in country 𝑖 and 𝑤𝑖 the respective income level (Dhingra et al., 2017). A percentage change in bilateral trade barriers leads to a percentage change in 𝑋𝑖𝑗given by the elasticity of trade 𝜃 (Dhingra et al., 2017). The outcome is positive correlated with a higher 𝐻𝑖, 𝐸𝑗 and is negative influenced by a rise in 𝑑𝑖𝑗, 𝑤𝑖 and F 𝑗 (the sum of Φ𝑖𝑗)(Dhingra et al., 2017).
To better combine the model with real data, Dhingra et al. (2017) conduct model adaptions. The modified real consumption1 grants for a valid comparative analysis of several scenarios. The authors add trade in intermediates, allow for more than one sector and compute with revenue generating ad-valorem tariffs (Dhingra et al., 2017). This paper will not summarize the equation including the model extensions mentioned above in detail because of space.
4 Scenarios of Leaving the EU
There are many possible scenarios how Brexit could take place. This section wants to emphasize the versions discussed by Dhingra et al. (2017). In the optimistic Soft Brexit Scenario, the United Kingdom stays as a member of the EEA in the Single Market and tariffs between the EU und the UK are equal to zero. In the following sections this paper will use the 1The Appendix provides the structural form for more details. term ‘Norway Model’ as a substitute to Soft Brexit Scenario. It allows for free movement of goods and services as well as preserve the passporting rights (Dhingra et al., 2018). Passporting rights give financial institutions, not headquartered in the targeted market, the opportunity to offer services without further contributions. Leaving the EU and staying in the EEA incorporates on the one side a fiscal saving of about 0.09% for the UK due to a lower contribution to the EU budget and on the other side a fiscal loss of 0.015% for the remaining EU countries (Dhingra et al. 2017).
As a part of the EEA the UK loses political impact and the right to participate in the European Customs Union. In addition, non-tariff barriers potentially arise, and the UK is not able to profit from the future economic integration anymore. Dhingra et al. (2017) calculate that non-tariff costs would increase by 2.77% in the optimistic scenario. Sectors with global value chains face rising costs due to the rules of origin requirements mean for UK-EU trade (more about GVC in the discussion part).
Alternatively, the UK and the EU agree with a pessimistic scenario, the Hard Brexit option where trade between the two parties is regulated under WTO conditions. Without further free trade agreements, UK exports get more expensive as they must deal with Most Favoured Nation tariffs. The UK will be excluded from the Single Market and its contributions to the EU budget fall. That leads to 0.31% savings of UK GDP (Dhingra et al., 2017). Furthermore, non- tariff barriers will have an increase in this pessimistic scenario (Dhingra et al. 2017). In addition, the UK will not be able to participate in the ongoing economic EU integration.
Concluding this part, the paper wants to highlight the different changes of NTB and intra-EU trade costs. The authors point out that non-tariff barriers take an important cornerstone in the predictions of trade effects (Dhingra et al., 2017). Therefore Dhingra et al. (2017) use NTB cost between the EU and US as a tariff equivalent, stating an overall weighted average of 20.4% NTB costs. Depending on political negotiations the share of NTB can be reduced up to a fraction of 54% (Dhingra et al., 2017). On the one hand NTB costs expand by 2.77% in the Soft Brexit Scenario and on the other hand inflate by 8.31% in the Hard Brexit Scenario (Dhingra et al., 2017). The UK will face higher NTB costs while the remaining EU countries benefit from a progressing cost decline. Dhingra et al. (2017) vary in the assumptions for the speed of the NTB cost decrease. In the optimistic scenario NTB costs fall by 20%, whereas in the pessimistic scenario NTB costs diminish by 40% compared to the rest of the world (Dhingra et al., 2017).
As the Brexit negotiations still are ongoing, the results of Dhingra et al. (2017) in the different Brexit scenarios are possible predictions. In the following sections this paper summarizes the calculations and its robustness checks.
4.1 Summary of the results
As mentioned before, Dhingra et al. (2017) compute the resulting welfare effects in terms of real consumption per capita. The results will be contrasted in the household’s discounted future consumption and the change in fiscal transfers in both cases, respectively (Dhingra et al., 2017). This paper expects that an increase in trade barriers will decrease exports leading to a decline in imports as well as real labour income, equivalently real consumption per capita (Dhingra et al., 2017).
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Table 1: UK welfare change due to Brexit
The table above shows the results of Dhingra et al.’s (2017) estimations in the two scenarios. The table content comes from Dhingra et al. (2017), the layout is made by the author of this paper. The optimistic scenario leads to a decline in consumption per capita of 1.34% what illustrates a lower annual income of 893 pounds (Dhingra et al., 2017). Although the UK can save fiscal costs in the Hard Brexit Scenario, total welfare decrease is higher than in the Soft Brexit Scenario. This implies that the profits from trading as an EU member are higher than the fiscal contributions going to the EU budget. A 2.66% change in real consumption is defined by an income change of £1,773 per household on average (Dhingra et al., 2017).
Due to the fact that the fiscal flows going from the UK to the EU diminish in both scenarios, the EU budget has a lack that needs to be filled by the remaining members proportional to their GDP. In addition, European trading partners of the UK will also face higher trade costs and therefore a welfare loss after Brexit. Dhingra et al. (2017) compare the welfare losses of the EU countries and indicate two groups that are more affected from the Brexit than others. First of all, the authors name countries that import high amounts of British goods and intermediates such as Ireland, Belgium, and the Netherlands (Dhingra et al., 2017). Secondly, Dhingra et al. (2017) point out a group of countries whose traded UK goods refer to a sector with low trade elasticity. Consequently, goods referring to those sectors are heavily substitutable within the EU countries and cause higher welfare effects to the corresponding importers (Dhingra et al., 2017). However, there are also countries that could benefit from the Brexit especially outside the EU. As a result of the Brexit, this paper expects that the UK wants to enhance foreign affairs with trade partners outside the EU in order to compensate rising trade costs. Dhingra et al. (2017) evaluate a 0.01% and 0.02% positive change in welfare for Non-EU countries. Obviously, the worldwide gain from Brexit does not compensate arising welfare losses.
Before this paper continues with the robustness checks on the results, there are dynamic and distributional effects that will not be skipped. Dhingra et al. (2017) find that distributional effects following from Brexit are shared equally through the different income deciles. This is quantified by real income losses because of augmenting prices (Dhingra et al., 2017). Institutions like the EU set main targets for instance lower price levels in participating countries. Next to written objectives, dynamic effects have a high relevance. Dynamic welfare gains of trade liberalization evolve over time and are not part of the static analysis shown before. That is why Dhingra et al. (2017) expect their results to be underestimated. In the next section this paper examines robustness checks regarding the results of this model.
4.1.1 Robustness Checks
Table 2 illustrates the robustness checks conducted on the model explained in the sections above. The table content comes from Dhingra et al. (2017), the layout is made by the author of this paper. Dhingra et al. (2017) use an alternative way to prove that the model is valid. In general, the model generates negative outcomes in both scenarios. In order to analyse those outcomes and check for robustness Dhingra et al. (2017) introduce several supplementary situations different to the Soft and Hard Brexit Scenario. The robustness checks show that the overall direction of the welfare effects is the same. Apart from that fact the results differ in absolute terms for the reason of changing assumptions. The following paragraphs provide the information of models with smaller and higher welfare losses.
The Swiss model refers to the bilateral agreement between the Switzerland and the EU. In contrast to the Norway Model, in this option the UK withdraws from the Single Market partially as it would allow for free movement of people and free trade in goods but not free trade in service (Dhingra et al., 2018). On the one hand the fiscal contribution going to the EU budget is smaller than in the Soft Brexit Scenario. On the other hand, the UK has similar to the Norway Model no impact on the EU decision making (Dhingra et al., 2018). This model leads to a 1,44% loss in real consumption per capita (Dhingra et al., 2017).
Panel A includes another alternative scenario, the Big Bang. Dhingra et al. (2017) define the Big Bang as the most negative Brexit scenario with a 3.84% change in welfare. In contrast to the Hard Brexit Scenario, the Big Bang situation incorporates the whole share of reducible NTB costs (Dhingra et al., 2017). To sum it up, the estimated model has too positive assumptions. The discount factor is challenging to define because of changing interest rates. Nonetheless, Dhingra et al. (2017) suggest an interest rate of 4% what appears to be too high and leads to a lower welfare effect. That is why Dhingra et al. (2017) swap the discount factor to prove robustness what is Illustrated in Panel C. An adjustment of the interest rate to 1% results in a 1.47% or 2.91% loss in real consumption per capita in the Soft or Hard Brexit Scenario respectively (Dhingra et al., 2017).
The most striking observation to emerge from the robustness comparisons is that only two panels (B, D) conclude in lower welfare losses than the estimated model. Panel B indicates a scenario where the UK removes all its trade barriers as a reaction to increasing trade costs followed by the Brexit. Dhingra et al. (2017) consider the status quo as the UK already has import tariffs on average of 3% so that the impact of further liberalisation is trivial. Panel D discusses the unlikely situation that the UK solely trades with final goods instead of a mix with trade in intermediates (Dhingra et al., 2017). The output shows that trade in intermediates is heavily affected by trade costs as omitting intermediates result in minor welfare losses compared to the baseline model (Dhingra et al., 2017).
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Table 2: Robustness checks
An additional check for robustness is the fact that FDI will fall, and the static analysis made by Dhingra et al. (2017) does not incorporate this case. FDI have direct and indirect effects on an economy namely a higher productivity, higher wages and better technological know-how (Dhingra et al., 2017). Especially multinationals drive FDI in order to profit from locational advantage and EU integration. Dhingra et al. (2017) conclude that arising tariffs will deflate the interest in investing to the UK and therefore influence UK GDP negatively. Taken together, these results suggest that the results are underestimated as the impact of FDI is not included.
The robustness checks have shown the main limitation of this study. As the estimations predict future welfare effects on a Brexit negotiation that is still ongoing, it is impossible to compare the predictions with real data and check for validity. Nevertheless, Dhingra et al. (2017) prove that the main analysis is valid by comparing the conclusions after a change in assumptions. The findings are always that Brexit has negative welfare effects on the UK. In order to ensure a better understanding of the results, this paper will have a look at the data in the following sub-section.
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