Guidance

Technical note of the preliminary economic impacts of the UK-GCC Free Trade Agreement

Published 20 May 2026

1. Introduction

This technical note sets out the Department for Business and Trade’s (DBT) preliminary estimates for the economic impact of the UK-Gulf Cooperation Council (GCC) free trade agreement (FTA). It presents estimates for the impact on gross domestic product (GDP), bilateral trade and wages.

The results are not a full and holistic assessment of the impacts of the FTA. They are a preliminary assessment to provide an initial understanding of the general magnitude and direction of impacts on trade, the economy and wages.

DBT will publish an impact assessment (IA) of the UK-GCC FTA in due course. This will provide estimates of the economic impacts of a trade deal with the GCC, including estimates of the sectoral, regional and environmental impacts.

2. Preliminary modelling results

These preliminary results are not forecasts. They represent the marginal economic impacts of the agreement compared to a counterfactual of no agreement in place, while maintaining all other factors affecting the UK-GCC economic relationship constant. A comparative static model is used which means that a comparison can be made of the economy before and after the introduction of the agreement, focusing on the long-term impact. The results therefore represent the change in the long run level of GDP that the country will gain permanently, each year, relative to a baseline of no FTA.

To estimate the figures, the analysis uses a Computable Generable Equilibrium (CGE) model (see section 3 for further details). The model does not have an explicit time dimension. Nor does it provide results in pound sterling (£) values. Instead, the model presents results as a percentage change of GDP, which are then converted to £ values in 2024 prices by using GDP and trade projections in the 2025 Global Trade Outlook^{[footnote 1]}.

The modelled impacts presented in this technical note are preliminary estimates which may be subject to future revisions. The analysis within this technical note does not take into account the conflict in the Middle East and any long-term implications of this. In particular, the results take no account of recent announcements on tariffs by the United States of America (USA) and other countries. These are not included in the modelled baseline and are not accounted for in the projections used to derive the £ values.

2.1 Macroeconomic results

The preliminary estimates for GDP and bilateral trade are modelled increases compared with their level absent of an FTA expressed in projected 2040 values. This provides an indication of the overall picture of the economy and trade with the GCC after an FTA. Reflecting uncertainties underpinning the modelling and the potential these results will be revised, this preliminary analysis is presented to one decimal place. Further detail on projections can be found in section 5.

Table 1: GDP results

	£ billion change applied to 2040 projections (in 2024 prices)	Percentage (%) change
Change in UK GDP	£3.7 billion	0.1%

Source: DBT modelling

Table 2: Bilateral trade results

	£ billion estimate, applied to 2040 projections (in 2024 prices)	Percentage (%) change
Change in UK exports to the GCC	£14.3 billion	22.6%
Change in UK imports from the GCC	£1.3 billion	8.2%
Change in total trade between the UK and the GCC	£15.5 billion	19.8%

Source: DBT modelling

Table 3: Wage results

	£ billion change compared to 2024 data (in 2024 prices)	Percentage (%) change
Change in UK real wages	£1.9 billion	0.2%

Source: DBT modelling

2.2 Combined impact of UK-India and UK-GCC FTAs

The UK has recently agreed a trade deal with India (May 2025). When the UK-India FTA is considered jointly with the UK-GCC agreement, the combined economic impact on UK GDP is estimated to be around 0.2% compared to the baseline of no agreements in place. When compared to UK GDP projections in 2040 that amounts to a gain of over £8 billion gained permanently, each year.

Table 4: GCC-India joint scenario GDP results

	£ billion estimate, applied to 2040 projections (in 2024 prices)	Percentage (%) change
Joint India-GCC GDP impact	£8.5 billion	0.2%
GCC deal only GDP impact	£3.7 billion	0.1%
India deal only GDP impact	£4.8 billion	0.1%

Source: DBT modelling

3. Model description

3.1 Computable General Equilibrium (CGE) model

The analysis uses a Computable General Equilibrium (CGE) model developed by Purdue University, referred to as a Global Trade Analysis Project (GTAP) model throughout this technical note^{[footnote 2]}. In line with international standards, CGE modelling is the best available technical framework for estimating the overall long run-impacts of a trade agreement. CGE modelling captures both direct impacts of an agreement and impacts due to interdependencies between sectors^{[footnote 3]}.

This analysis uses a standard multiregional, multisectoral, comparative static GTAP model with perfect competition and constant returns to scale. Further details on the model structure can be found in annex 1 of the UK-India FTA IA^{[footnote 4]}.

The interpretation of the results

The estimated preliminary results are not forecasts. They represent the marginal economic impacts of the agreement compared to a counterfactual of no agreement in place, holding all other factors affecting the UK-GCC economic relationship constant. Therefore, whilst this modelling provides insights on the expected orders of magnitude of the economic impacts, it does not capture all possible factors affecting the future trading relationship between the UK and the GCC.

No economic model is able to fully capture the complexity of the real world and country-specific behaviours. Therefore, the model used, like all economic models, is based on several assumptions and stylised simplifications which must be considered when interpreting the figures.

A more detailed discussion of the uncertainties and limitations of CGE modelling can be found in section 6, with full details in the ‘Uncertainty and analytical limitations’ section of the UK-India FTA IA^{[footnote 5]}.

Database

The GTAP model requires a dedicated analytical database that includes a complete picture of national economies based on countries’ input-output tables, bilateral tariffs and trade flows, and a robust and comprehensive set of modelling parameters. The GTAP centre compiles the analytical databases combining raw source data from various sources, economic literature and additional in-house adjustments^{[footnote 6]}.

DBT uses the most recent GTAP dataset available (GTAP version 12p1) at the time of modelling, which relies on goods trade data from year 2019, services trade data from 2017, and UK input-output tables from 2019. The data set used was under pre-release and not publicly available at the time of modelling.

However, given the update in both reference year trade data from the current public database (2017) and the UK’s input-output (IO) table, using this data set ensures the most up-to-date data available is used for this analysis. The database is currently being quality assured by GTAP ahead of eventual publication. Revisions made to the published database may lead to changes in the preliminary estimates. The direction of this change is uncertain.

The GTAP database is disaggregated into 65 goods and services sectors (GTAP sectors)^{[footnote 7]}.

As all CGE models need data on all trade routes and national production across all regions, they operate at an aggregated level. This may miss many of the nuances of supply chains and interlinkages that can provide a comprehensive understanding of the impacts of an FTA.

3.2 Adjustments to the database: the baseline counterfactual

The impacts of the agreement are assessed against a counterfactual baseline where the UK and the GCC do not have an agreement with each other. 

As the analytical database reference year used is 2019, the baseline is adjusted to reflect the relevant recent trade policy developments not captured in the data.

This means incorporating:

• the UK exiting from the European Union
• the UK’s FTAs with Australia, Canada, Japan, New Zealand, Singapore, India and UK accession to the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP)
• the United Arab Emirates’ (UAE) FTA with India
• updates to the Most Favoured Nation (MFN) tariffs imposed by the UK, under its Global Tariff (UKGT), for its largest trading partners

Recent deals signed by the GCC and its member states, such as the UAE-New Zealand and GCC-Korea deal have not been included in the baseline because of insufficient tariff line information at the time of modelling to properly reflect in the baseline.

To the extent there are other recent sizeable changes in the levels or patterns of trade that are not captured in our baseline adjustments, their impact might not be captured in the modelling.

The UK’s recently agreed landmark economic framework with the USA has not been included in the baseline. Other tariff announcements made by the USA and other countries, have also not been reflected in the baseline, due to the continued uncertainty.

4. Modelling inputs

The preliminary modelling results are produced by inputting estimates of changes in tariffs and non-tariff measures (NTMs), as a result of the agreement, into the CGE model.

Due to the preliminary nature of these estimates, they may be revised for the publication of a final IA.

4.1 Changes in tariffs

For a given GTAP sector, a trade weighted tariff is estimated based on expected changes to each country’s tariff schedule. Where appropriate, adjustments are made to capture effective barriers to liberalisation.

The modelled tariff assumptions are liberalisation in 91% of tariff lines by the GCC, covering 93% of GCC imports from the UK. The modelling also assumes that the UK liberalises 100% of tariff lines and imports from the GCC.

4.2 Approach for estimating NTMs for goods and services 

NTMs, including regulatory restrictions for services, are any policy measures outside of tariffs that can influence trade costs and flows. Not all NTMs are aimed at restricting trade and often serve legitimate policy objectives. However, they may still have an impact on trade flows.

NTMs can only be imperfectly observed directly. For this assessment, they are estimated using an econometric gravity model. Gravity modelling is an econometric framework for estimating the determinants of bilateral trade; it is consistently able to explain patterns of international trade. Building upon best practice in the academic literature, a gravity model is used to provide estimates of non-tariff measures in goods and services in various countries.

The estimates are expressed in ad valorem equivalent (AVE) terms, that is, in terms of the equivalent tariff reduction that would create a similar magnitude trade response. Therefore, estimated percentage point reduction in NTMs of 4, would translate to an equivalent trade response of a tariff reduction of 4 percentage points also. Note, unlike with tariff reductions, NTM reductions enter the model as improvements in bilateral trade productivity shocks.

Econometric inputs

To determine the NTM reduction inputs for goods and services sectors, a gravity model is used to estimate the level of NTMs across 65 sectors in all GCC countries and the UK^{[footnote 8]}. As such an actionability assumption of 50% and 33% (goods and services sectors respectively) is used to acknowledge the fact that an FTA cannot remove NTMs in their entirety^{[footnote 9]}. A percentage reduction assumption is then applied to calculate the reduction in the actionable NTM we can expect as the result of the FTA^{[footnote 10]}. This is assumed to be 10% in agri-food and services sectors (in line with scenario 1 in the published scoping assessment) and 20% in manufacturing (midway between scenarios 1 and 2 from the scoping assessment). These percentage reduction assumptions yield NTM inputs of a similar magnitude to those used in the modelling of past UK FTAs.

4.3 Summary of inputs

The processes described above are used to estimate a reduction in tariff and NTMs that reflect the expected provisions in the agreement for each GTAP sector. These are then fed into the CGE model. Table 5 shows the average reductions by broad sector categories, weighted by the relative trade in GTAP sectors that make up the broad sector, with the simple average reduction by broad sector presented in brackets.

Tariff line inputs for the modelling have used 2019 trade data and have been calculated using the UK and GCC’s Most Favoured Nation (MFN) tariff schedules.

Table 5: Trade weighted average sectoral applied percentage point reduction in tariffs and NTMs (simple average in brackets)

Sectors	UK imports from GCC	UK imports from GCC	UK exports to GCC	UK exports to GCC
	Reductions in tariffs​	Reductions in NTMs​	Reductions in tariffs​	Reductions in NTMs​
Agri-food​	3.7 (4.0)	1.8 (2.3)	5.8 (2.7)	1.4 (1.3)
Industrial goods​	0.4 (2.0)	0.6 (3.1)	2.3 (3.3)	1.6 (2.0)
Services​	Not applicable	1.9 (1.5)	Not applicable	2.2 (1.6)

5. Method for calculating pound figures from modelling outputs  

The preliminary macroeconomic impact results presented in this document have been expressed in pound sterling (£) values. These are derived from the modelling outputs which are expressed in percentage changes. The methods used to calculate these preliminary macroeconomics impacts £ figures are the same as those used in the UK-India FTA IA and can be found in annex 1 of the UK-India FTA IA^{[footnote 11]}.

The data sources used to calculate the pound values are shown in table 6. These metrics do not account for the tariff announcements made by the USA and other countries.

Table 6: Data sources used to convert CGE modelling impacts into pound sterling (£) values 

Key metrics	Data used
GDP	CGE model % impacts Office for Budget Responsibility (OBR) GDP data[footnote 12] OBR short[footnote 13] and long-term economic determinants (for 2040 estimates)[footnote 14] [footnote 15] Office for National Statistics (ONS) GDP Deflators[footnote 16]
UK total trade and trade with GCC (exports and imports)	CGE model % impacts Global Trade Outlook 2025 projections of UK total exports and imports (for 2040 estimates)[footnote 17] For bilateral trade between the UK and the GCC in 2040, it is further assumed that both the UK and the GCC share of partner import demand evolves in line with their share of global import demand (as projected in the Global Trade Outlook 2025) ONS GDP Deflators[footnote 18]
Wages	CGE model % impacts ONS total UK wages data[footnote 19]

6. Method for assessment of impacts on tariffs

This section sets out the method for estimating tariffs paid (duties) on existing trade between the UK and the GCC, and duties corresponding to lines which are liberalised under the agreement.

6.1 Method for estimating duties 

UK exports to Partner Country

Estimated duties on the GCC’s imports from the UK are calculated by multiplying partner country MFN tariff rates as of 2022 by the GCC’s imports from the UK in 2024 at the harmonised system 6 (HS6) level (split equally across the tariff line level) or 8-digit product classification level, dependent on data availability^{[footnote 20]}. For countries where HS6 data is used, the lowest MFN tariff within the HS6 subheading is taken to conservatively estimate duties. Using the agreement’s preferential tariff schedule, it is then possible to identify tariff lines subject to immediate (where tariffs are removed at entry into force) and long-term tariff reductions (immediate tariff reductions plus tariff reductions on goods that are subject to staged tariff removal), and aggregate corresponding estimated duties collected in these lines.

UK imports from Partner Country 

To estimate annual tariff reductions on UK imports from the GCC, the applied UKGT tariff rate in 2022 is multiplied by UK imports from the GCC in 2024 at the 8-digit product classification level. For UK imports from the GCC, His Majesty’s Revenue and Customs (HMRC) import data by preference is used, which provides a more detailed breakdown of the tariff regime by which a product enters the UK.

Using the agreement’s preferential tariff schedule, it is then possible to identify tariff lines subject to immediate (where tariffs are removed at entry into force) and long-term tariff reductions (immediate tariff reductions plus tariff reductions on goods that are subject to staged tariff removal), and aggregate corresponding estimated duties collected in these lines. The data are also grouped into intermediate or final consumption goods using the UN’s Broad Economic Categories (BEC5).

Reduced duties also reflect an equivalent reduction in government tariff revenues on these products, which may be partly offset by increased tax revenues from higher economic activity in the UK.

6.2 Limitations

Following a similar approach widely applied in the literature, the calculations aim to provide an indication of the magnitude of duties applicable to tariff lines that are liberalised.

These estimates are subject to a number of limitations:

• they are based upon 2024 trade or the latest available year and do not take into account the likely changes in trade patterns resulting from tariff liberalisation
• these estimates assume full utilisation of all available preferences, which is unlikely to be the case in practice as business require take time to adjust and utilise preferential trade agreements
• generally, it is businesses that pay tariffs and therefore save the cost of tariffs paid. These savings may be passed on to consumers, however, the proportion passed through to consumers is uncertain

7. Method for assessment of wage impact per worker

Underlying economic theory suggests that FTAs can generate tangible effects for workers, including through changes in wage levels. These impacts may arise through several channels, including increased export opportunities for domestic firms, which can lead to productivity gains and higher demand for labour creating a rise in firm-level efficiency. FTAs may cause structural shifts in the economy, causing demand for some types of workers to increase, and declines for other types of workers that might be in sectors that face direct competition from imports^{[footnote 21]}.

These dynamics can contribute to upward pressure on wages, particularly in sectors which experience growth, or downward pressure on wages for other workers whose jobs are either outsourced or are in sectors facing increased competition from cheaper imports.

This section sets out the method for estimating the wage impact for UK workers following the UK-GCC FTA. The estimated wage impact for UK workers is an average across all individuals in work. In reality, the impact of the FTA on all workers will vary depending on the firm or sector they’re employed within.

7.1 Method for the wage impact 

The aggregate estimated change in wages following the FTA is calculated by multiplying the ONS aggregate wages and salaries data for the UK economy by the modelled CGE wage impact percentage presented in table 3. To contextualise the economy-wide wage impact in £ terms, this value has been divided by the number of workers in the UK economy using ONS employment and employee-types data. The results of this methodology are presented in table 7.

Table 7: Average increase in wages per worker per year

	£ change compared with 2024 data (in 2024 prices)
Change in UK real wages per worker	+£60

Source: DBT modelling

The UK-GCC FTA is estimated to increase real wages by around £1.9 billion (0.2%) annually, when applied to 2024 levels. This reflects workers benefiting from the gains from lower trade barriers, with wages in expanding sectors seeing greater gains. For working individuals, when applied to 2024 levels, the average estimated increase in real wages is around £60 per person, per year in the long run.

---

1. Global Trade Outlook (June 2025). ↩

2. For this analysis, DBT used RunGTAP user interface, which itself relies on GEMPACK software. ↩

3. Trade Modelling Review Expert Panel Report (January 2022). ↩

4. UK-India Free Trade Agreement: impact assessment (July 2025). ↩

5. UK-India Free Trade Agreement: impact assessment (July 2025). ↩

6. Databases: Global Trade Analysis Project. ↩

7. Global Trade Analysis Project ↩

8. Further detail on the model specification can be found in annex 2 of the India IA. ↩

9. These actionability ratios are subject to a high degree of uncertainty. DBT’s assumptions are broadly inline with previous studies (see EU-US Transatlantic Trade and Investment Partnership: detailed appraisal of the European commission’s impact assessment, European Parliament, 2014). ↩

10. Empirical evidence on precise NTM reductions following an FTA is limited. Existing assessments, such as the European Commission ex-post analysis of the EU-Korea FTA, however largely estimate it to be in the region of 10% to 25%.  ↩

11. UK-India Free Trade Agreement: impact assessment (July 2025). ↩

12. OBR, Economic and fiscal outlook (March 2026). ↩

13. Short-term determinants - OBR, Economic and fiscal outlook (March 2026). ↩

14. Long-term determinants - OBR, Economic and fiscal outlook (March 2025). ↩

15. OBR, Fiscal risk and sustainability (July 2025). ↩

16. GDP deflators at market prices, and money GDP, ONS (March 2026). ↩

17. DBT, Global trade outlook (June 2025). ↩

18. GDP deflators at market prices, and money GDP, ONS (March 2026). ↩

19. UK sector (S.1): Wages and salaries (D.11): Resources: Current price: £million: Seasonally adjusted (December 2025). ↩

20. GCC import figures are sourced from International Trade Centre (ITC) Trademap, using 2024 data for all countries except Oman, which relies on 2023 figures due to data availability. For Oman, Qatar, and the UAE, HS‑6 level import values are allocated evenly across all corresponding tariff lines. ↩

21. Not all firms will decline within sectors that experience increased competition as this depends on a number of factors such as the structure of the market and efficiency of firms within those markets. ↩