Guidance

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

Updated 23 May 2025

1. Introduction

This technical note sets out the Department for Business and Trade’s (DBT) preliminary estimates for the economic impact of the UK-India 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.

The department will publish an Impact Assessment (IA) of the UK-India FTA in due course. This will provide estimates of the economic impacts of a trade deal with India, 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 with a counterfactual of no agreement in place, while maintaining all other factors affecting the UK-India 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 estimated change each year resulting from a UK-India FTA, relative to a baseline of no FTA.

The model does not have an explicit time dimension. Nor does it provide results in pound sterling (£) values. To contextualise the modelling results in £ terms, we rely on 2040 trade and GDP projections. All £ values are derived based on the modelling outputs, expressed in percent change, and then converted to values in 2024 prices using projections in the 2023 Global Trade Outlook.^{[footnote 1]}

The modelled impacts presented in this technical note are preliminary estimates which may be subject to future revisions. 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 India after an FTA. Reflecting uncertainties underpinning the modelling and the potential that these results will be revised, this preliminary analysis is presented to 1 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	+ £4.8 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 India	+ £15.7 billion	+ 59.4%
Change in UK imports from India	+ £9.8 billion	+ 25.0%
Change in total trade between the UK and India	+ £25.5 billion	+ 38.8%

Source: DBT modelling

Table 3: Wage results

	£ billion change compared with 2024 data (in 2024 prices)	Percentage (%) change
Change in UK real wages	+ £2.2 billion	+ 0.2%

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 Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) 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 with a counterfactual of no agreement in place, maintaining all other factors affecting the UK-India economic relationship constant. Therefore, while 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 India.

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 the modelling can be found in Section 6, with full details in the ‘Uncertainty and analytical limitations’ section of the CPTPP 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 has used version 12p1 of the GTAP database for the CGE modelling. This is currently the most recent data set available for DBT’s CGE modelling, capturing global goods trade in 2019. The data set used is under pre-release and not publicly available at the time of modelling.

However, given updates 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 is used for this analysis. The database is currently being quality assured by GTAP ahead of eventual publication. Revisions made to the database for publication 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.

Adjustments to the database: the baseline counterfactual

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

As the analytical database reference year 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, including with Australia, Canada, Japan, New Zealand, Singapore and UK accession to the CPTPP
• India’s FTAs with Australia and United Arab Emirates
• updates to the Most Favoured Nation (MFN) tariffs imposed by the UK, under its Global Tariff (UKGT), for its largest trading partners

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.

Due to the uncertainty associated with tariff announcements made by the USA and other countries, these are not reflected within the baseline.

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 might 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.

Rules of Origin (RoO) adjustment

To access preferential tariffs as set out in the agreement, a good must meet the preferential RoO requirements. RoO requirements determine the source of a good and can vary between different goods. For example, one rule could require that a good is exclusively produced in the countries covered by the FTA, while another rule could require that a good is ‘sufficiently worked or processed’ from inputs. RoO requirements also set out what exporters must do to demonstrate their goods meet the requirements of these rules. Combined with the many factors that can influence an exporter’s decision to trade under preferential tariffs, estimating the cost of RoO compliance on exporters is difficult.^{[footnote 8]}

Econometric estimates of non-tariff trade cost reductions implicitly capture RoO effects in estimating how historical FTAs have impacted trade, on average. However, these estimates are based on past agreements and are not specific to those in the UK-India context, or RoO in the UK-India FTA. To account for changes in RoO negotiated in the UK-India FTA, the level of tariff liberalisation in the Indian schedule has been adjusted downwards where required.

4.2 Approach for estimating Non-Tariff Measures for goods and services

NTM reductions for goods sectors 

The Design of Trade Agreements (DESTA) database’s scores^{[footnote 9]} of historic FTAs (from 1 to 7) is used to proxy for the depth of NTM reductions in past agreements. The tariff-equivalent sectoral NTM reductions from past FTAs as captured in the DESTA dataset are estimated using an econometric model. The agreement is then scored as to its depth to determine which estimated reduction from past agreements is applied to each sector based on policy input. Full details of this approach are outlined in Annex 2 of the CPTPP IA.^{[footnote 10]} While the approach used for this analysis is consistent with that used in the CPTPP IA, the updated data used in the econometric model differs slightly.^{[footnote 11]}

To estimate the reduction in NTMs from this agreement, it is assumed NTMs are reduced in line with:

• a medium depth agreement for industrial sectors, as proxied by a 4 in the DESTA database^{[footnote 12]}
• a shallower agreement for the non-ferrous metals sector and agricultural sectors, that is equivalent to a DESTA 1
• no non-tariff trade cost reductions for the energy sector

NTM reductions in service sectors

The method used to calculate the NTM estimates for services is consistent with the approach used in the CPTPP IA. The Organisation for Economic Cooperation and Development’s (OECD’s) Services Trade Restrictiveness Index (STRI) is used to determine restrictiveness in the baseline and the scenario with an FTA. This change is inputted into an econometric model to estimate the reduction in service NTMs based on policy inputs. Further details on the approach can be found in Annex 2 of the CPTPP IA.^{[footnote 13]}

The methodology uses OECD estimates of India’s MFN STRI and commitments under the General Agreement on Trade in Services (GATS). It also uses an estimate of the change in the STRI and newly bound regime under a UK-India FTA.^{[footnote 14]} The latter has been proxied by modelling binding commitments equivalent to 30% of those found in CPTPP, alongside no change to the applied services regime for either party to the agreement. The STRI scoring of CPTPP is based on legal and policy judgments made by the OECD.^{[footnote 15]}

4.3 Summary of inputs 

The processes described 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 4 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.

Table 4: Trade-weighted average sectoral applied percentage point reduction in tariffs and NTMs (simple average in brackets)

	UK imports from India		UK exports to India
Sectors	Reductions in tariffs​	Reductions in NTMs​	Reductions in tariffs​	Reductions in NTMs​
Agri-food​	2.9 (5.1)	2.3 (2.0)	95.5[footnote 16] (8.4)	1.9 (2.2)
Industrial goods​	2.3 (1.6)	2.7 (2.6)	5.2 (7.4)	2.6 (2.6)
Services​	Not applicable	2.2 (2.5)	Not applicable	7.3 (5.4)

5. Method for calculating pound figures from modelling outputs

The preliminary macroeconomic impacts 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 macroeconomic impacts £ figures are the same as those used in the CPTPP IA and can be found in Annex 1 of the CPTPP IA.^{[footnote 17]}

The data sources used to calculate the pound values are shown in Table 5. These metrics do not account for the tariff announcements made by the USA and other countries.

Table 5: 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 18] OBR short[footnote 19] and long-term economic determinants (for 2040 estimates)[footnote 20][footnote 21] Office for National Statistics (ONS) GDP Deflators[footnote 22]
UK total trade and trade with India (exports and imports)	CGE model % impacts Global Trade Outlook 2023 projections of UK total exports and imports (for 2040 estimates)[footnote 23] For bilateral trade between the UK and India in 2040, it is further assumed that both the UK and India share of partner import demand evolves in line with their share of global import demand (as projected in the Global Trade Outlook 2023). ONS GDP Deflators[footnote 24]
Wages	CGE model % impacts ONS total UK wages data[footnote 25]

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 India, 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 India’s imports from the UK are calculated by multiplying partner country MFN tariff rates as of 2022 by India’s imports from the UK in 2022 at the 8-digit product classification level. 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 India, the lower of the applied UKGT tariff rate and general framework of the UK’s Generalised Scheme of Preferences (where applicable) for developing countries (both applied in 2022) is multiplied by UK imports from India in 2022 at the 8-digit product classification level. For UK imports from India, 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 preliminary 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 2022 trade and tariffs 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 businesses require 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
• trade data by region does not account for inter-UK trade and may distort the picture as to where the actual gains are realised

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1. Global Trade Outlook February 2023 ↩

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. CPTPP: Impact Assessment, July 2023. ↩

5. CPTPP: Impact Assessment, July 2023. ↩

6. Databases - Global Trade Analysis Project. ↩

7. Sectoral List - Global Trade Analysis Project ↩

8. Factors that can influence an exporters decision to trade under preferential tariffs can include awareness and understanding of the agreement, the degree to which the incentive of preferential tariffs outweigh the associated costs of the usage of preferences and rules of origin. ↩

9. Dür, Andreas, Leonardo Baccini and Manfred Elsig. 2014. “The design of international trade agreements: Introducing a new database”. Review of International Organizations, vol. 9, pp. 353-375. ↩

10. CPTPP: Impact Assessment, July 2023. ↩

11. The econometric model uses data from the USA International Trade Commission’s International Trade and Production Database for Estimation on the sectoral trade flows between 243 countries for the years 2000 to 2016. This data is mapped to 65 GTAP sectors (the level at which the regressions are run) and combined with HS6 tariff data from the World Integrated Trade Solution. Time-consistent networks of product codes have been used to ensure that product definitions stay constant in our tariff data, despite changes to HS reporting nomenclatures during our sample. ↩

12. A medium level of liberalisation represents an agreement that goes far in alleviating the impacts of non-tariff barriers to trade but does not remove all non-tariff barriers businesses face when exporting. ↩

13. CPTPP: Impact Assessment, July 2023. ↩

14. STRI ↩

15. The Regional Trade Agreements STRI ↩

16. As these average reductions are trade weighted, this figure represents the large reduction in tariffs on beverages and tobacco, which makes up the majority of exports in the agri-foods sector. ↩

17. CPTPP: Impact Assessment, July 2023. ↩

18. OBR, Economic and fiscal outlook (March 2025) ↩

19. Short-term determinants – OBR, Economic and fiscal outlook (March 2025) ↩

20. Long-term determinants – OBR, Economic and fiscal outlook (May 2024) ↩

21. OBR, Fiscal risk and sustainability – July 2023 ↩

22. GDP deflators at market prices, and money GDP, ONS, March 2025 ↩

23. DBT, Global trade outlook – February 2023 ↩

24. GDP deflators at market prices, and money GDP, ONS, March 2025 ↩

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