Granularity in Trade in Value Added Data for Key Sectors

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Granularity in Trade in Value Added Data for Key Sectors

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Summary

UK exports of goods and services contain inputs from many other countries. Therefore, 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 direct domestic trade in value added 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 broad 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.

Overview

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. We developed disaggregated measures of exports and domestic value added from exports data for selected industries, in order to be able to answer these three key questions.

Methods

Gross value added (GVA) is a key concept in the National Accounts; it 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). In our analysis, GVA can be constructed for each firm and then summed together to calculate the aggregate GVA for the sector as a whole. 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 Jack Pilkington and Jeremy Rowe. For the other services sectors we used the ONS Annual Business Survey and International Trade in Services Survey, as well as company accounts data.

Impact

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 revisions in the way that ONS present financial services trade.

External project papers

Ebell, M., Pilkington, R., 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 https://doi.org/10.1177/002795011724200111

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