Linked Consumer Registers

The linked consumer registers contain the names and addresses for adults in the UK as annual snapshots from 1997 onwards. They are compiled from reported outputs from linking public versions of the electoral roll and consumer registers (supplied by value-added resellers). The data represent a near-complete coverage of the adult population at an individual level.

Content

The Consumer Registers empower researchers to undertake individual level research on the adult UK population. As a set of geographic datasets available for several years, they can provide detailed estimates of local population change. They are also an invaluable tool for sample design. Research at the GeoDS has used this data base to create ethnicity estimations (using the ethnicity estimator names software) and also applied novel linkage analysis to produce estimations of origin- destination internal migration flows.

Our updated data licence agreements mean that these data, which are used extensively to build other service data products, are only available for access by internal users (staff or students) at UCL. Interested potential external users can contact the us via the email address listed below - access may be arranged as part of a formal academic collaboration with this data service.

It is anticipated that data will continue to be updated on an annual basis. Due to the imputation process, and with the aim towards continual improvement in the register across all years, each version of the register may be slightly different for older years as well as newer.

For detailed description of the columns contained within the data, see the Variable Dictionary - and for an overview of the characteristics of the data, see the Data Summary. These files can be downloaded from the bottom of this page.

Quality, Representation and Bias

As the data are inputted from several different organisations, it is possible that some names and addresses are inconsistently formatted between datasets. Despite applying bespoke rigorous address matching and name matching methodologies, it is still possible that same cases may not have matched. Thus the number of unique addresses is slightly overestimated.

Addresses are recorded as address lines (in a separate table). This might make address matching to other data quite difficult as the number and composition of address lines varies by addresses, and between different versions of the data too.

In addition, it is very difficult to determine the completeness of the data. The register has near complete coverage of the adult population for every year. However, for some addresses anonymised residents are imputed where a house sale is known to have occurred but no new households were detected (roughly 6% of addresses in 2016). In addition, the occupancy of households are brought forwards by a few years where no new data are obtained for an address. Data lags occur because individuals do not volunteer data every year. It is also possible that adults who reside in multiple addresses may have duplicate entries within the data.

Whilst the data providers have attempted to compile registers which are both as complete and accurate as possible, there are data biases that should be considered. Firstly, the electoral register is known to sufficiently under-represent the following groups: the younger age groups, the non-white British population and those in rented accommodation.

Further to this, research by the GeoDS using implied ethnic groups from names identified that there was a slight over-representation of White British names. Roughly 84% of individuals were classed as White British, compared to 81% from the 2011 Census for the UK. We have also identified that areas with higher proportion of adults in rented accommodation had the greatest underrepresentation within cities.

One of the inputs into the Linked Consumer Registers, the Registers of Scotland, is available via UBDC.

Internal

Data and Resources

Additional Info

Field Value
Source CACI UK Ltd, DataTalk Research Ltd, Electoral Roll Supplier
Author Lansley, Guy ; Van Dijk, Justin; Lan, Tian; Todd, James; Chi, Bin
Maintainer Maurizio Gibin
Last Updated May 8, 2025, 15:24 (UTC)
Created November 28, 2024, 19:35 (UTC)
Attribution The data for this research have been provided by the Geographic Data Service (geods.ac.uk), a Smart Data Research UK Investment: ES/Z504464/1.
Controller UCL
Entity Person living in a household
Frequency Year
Granularity UPRN
Spatial Coverage United Kingdom
Temporal Coverage January 1997 to January 2023