Granularity in Trade in Value Added Data for Key Sectors


Granularity in Trade in Value Added Data for Key Sectors


UK exports of goods and services contain inputs from the UK and many other countries. If UK exports were just re-packaged imports, they would add little value to the UK economy. Standard trade statistics tell us little about the value added in the UK, and hence jobs, associated with UK exports. We developed experimental estimates of domestic value added from exports, that would allow identification of the industries in the UK that are most likely to be vulnerable to changes in access to international markets. The aim was to provide timely estimates of the proportions of direct value added from exports destined for EU and non-EU countries for a range of highly disaggregated sectors, by relying on simple methodologies and alternative data sources and surveys.


This project aimed to build a detailed evidence base for setting priorities in negotiating future trade deals with EU and non-EU countries. Three key questions were addressed: 1. How important are exports for each industry? 2. How much domestic value added is related to exports for each industry? 3. To what extent is each industry embedded in a global supply chain; that is, to what extent does it currently rely on imported inputs? While broad-brush answers to these questions can be obtained from currently available international Supply and Use Tables, and the trade in value added data derived from them (such as the World Input-Output Database and OECD Trade in Value Added (TiVA) database), this does not provide a sufficiently granular evidence base for trade negotiations, which typically operate at very detailed levels. We developed disaggregated measures of exports and domestic value added from exports for selected detailed industries, in order to be able to answer these three key questions.


To estimate the domestic gross value added (GVA) of exports in each industry we estimated domestic GVA from exports for each firm, and then summed it up within each industry.  GVA is calculated for each firm or industry as the difference between the value of production (output) and the value of goods and services consumed as inputs to the process of production (intermediate consumption). To calculate this for each firm, we needed data on turnover, intermediate inputs, and exports, and had to make assumptions about how the intermediate inputs were used. The conceptual approach that we applied was common across all sectors that we analysed. However, its specific implementation varied to account for the specificities of the different data sources. Our analysis of manufacturing companies relied on the individual tax returns and customs data from HMRC. Analysis for a key financial services sector utilised Bank of England data and was developed with Bank of England and ONS colleagues. For the other services sectors we used the ONS Annual Business Survey and International Trade in Services Survey, as well as company accounts data.



The project has produced a range of very detailed industry results, allowing analysis for whichever industry is of relevance to trade negotiators and policy makers. The granularity of the results demonstrate the heterogeneity between adjacent industries in their degree of trade-involvement. For instance, there is substantial variation within the car manufacturing industry: the manufacture of electrical and electronic equipment for motor vehicles is more import- and export-intense than other parts of the industry, although manufacturing of motor vehicles (the assembly of the cars themselves) is the largest of the sub-industries by far. For the monetary financial institutions industry (i.e. banks), only about 40% of their exports in 2016 constituted direct domestic GVA, although this is a lower bound. A little over half of this came from exporting outside the EU. Explore the results for a range of details industries in the papers.


The methodologies developed showed that it is feasible to deliver more granular and timely estimates of the direct value added of exports than currently available. However, the quality of those estimates is closely linked to the underlying data and there are important differences between the estimates that can be calculated for manufacturing and services industries. For manufacturing sectors, HMRC data were used to calculate yearly estimates at the four-digit industry classification level. The same exercise for business services was more difficult due to data availability and quality issues.

This project benefitted greatly from the direct involvement of the Bank of England and ONS. It has generated interest across government departments and with the UK manufacturing association Make UK. The project has led to improvements in the way that ONS present financial services trade.


Mion, G. (2018) ‘Constructing estimates for exports, imports and the value-added from exports of the car industry and other manufacturing industries in the UKESCoE Technical Report Series, TR-02.

Mion, G ‘Brexit: which sectors are worth fighting for?‘ ESCoE Blog, 27 July 2018

Pilkington, J. and Rowe, J. (2018) ‘Constructing estimates for exports and the value-added from exports of monetary financial institutions in the UK‘. ESCoE Technical Report Series, TR-01.

Ebell, M., Pilkington, J., Rowe, J. and Srinivasan, S. (2017) ‘Value added from trade for key business and financial service industries: initial estimates‘. National Institute Economic Review, Vol 242, Cambridge University Press



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