![]() ![]() Assessment of the CACI Acorn data using the Administrative Data Quality Assurance Toolkit ![]() Each month, the latest version of the Acorn classification is matched to the latest set of property transactions (using the postcode variable as the match key) with the resultant data then used in the production of the latest month’s house price index. Summary of processĪn updated version of the Acorn classification is provided by CACI on an annual basis for use in the UK HPI, to ensure the classification used remains representative of changes in neighbourhoods and to capture new postcodes that become available as new property is built. The reasoning (and importance) for using such a classification is that the location of a property should influence the price people are willing to pay and as such is an important price determining characteristic that should be accounted for when modelling house prices. ![]() For the purpose of the UK HPI, the Acorn group is used to classify property according to the postcode where it is situated, for example, a property (based on the postcode) could be classified in Acorn category ‘lavish lifestyles’ through to category ‘difficult circumstances’. Acorn provides a general understanding of the attributes of a neighbourhood by classifying postcodes into a category, group or type. Acorn is a segmentation tool which categorises the UK’s population into demographic types. This document will focus on the Acorn classification, which is produced by CACI. For the production of the UK HPI this data is obtained from a variety of administrative data sources that cover the price paid for transacted property (such as the Price Paid Dataset collected by HM Land Registry for England and Wales), the attributes of a property (such as the Council Tax Valuation List maintained by the Valuation Office Agency) and characteristics related to the location of the property (such as the type of neighbourhood where the property is situated, defined by the Acorn classification from Consolidated Analysis Centers, Inc. The hedonic regression approach requires detailed information on the characteristics of property sold, both regarding the physical attributes of the property (such as size, floor space for example) and the location of the property (what type of neighbourhood, where in the country for example). ![]() In simple terms, hedonic regression is a technique which accounts for the changing quality of property transacted each period to isolate only pure price change, so that the change in price is not distorted by differences in the composition of property sold (for example, you cannot directly compare the price of a one bedroom property sold in one period with a three bedroom property sold in another). A number of different administrative datasets are used in the production of the monthly UK HPI using a technique known as hedonic regression. The UK House Price Index ( UK HPI) measures the change in the price paid to purchase residential property in the United Kingdom. This is the Quality assurance of administrative data (QAAD) of the data source in Acorn consumer classification ( CACI) used the production of the UK House Price Index ( UK HPI) and Northern Ireland House Price Index (NI HPI). ![]()
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