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    Review of 'A new attribute-linked residential property price dataset for England and Wales, 2011 to 2019'

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    5
    A new attribute-linked residential property price dataset for England and Wales, 2011 to 2019Crossref
    An innovative open source house price data ready for wider applications
    Average rating:
        Rated 5 of 5.
    Level of importance:
        Rated 5 of 5.
    Level of validity:
        Rated 5 of 5.
    Level of completeness:
        Rated 5 of 5.
    Level of comprehensibility:
        Rated 5 of 5.
    Competing interests:
    None

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    A new attribute-linked residential property price dataset for England and Wales, 2011 to 2019

     Bin Chi (corresponding) ,  Adam Dennett,  Thomas Oléron-Evans (2021)
    Current research on residential house price variation in the UK is limited by the lack of an open and comprehensive house price database that contains both transaction price alongside dwelling attributes such as size. This research outlines one approach which addresses this deficiency in England and Wales through combining transaction information from the official open Land Registry Price Paid Data (LR-PPD) and property size information from the official open Domestic Energy Performance Certificates (EPCs). A four-stage data linkage is created to generate a new linked dataset, representing 79% of the full market sales in the LR-PPD. This new linked dataset offers greater flexibility for the exploration of house price (/m 2 ) variation in England and Wales at different scales over postcode units between 2011 and 2019. Open access linkage codes will allow for future updates beyond 2019.
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      Review information

      10.14293/S2199-1006.1.SOR-ECON.ABI2UO.v1.RMGBOB

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

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      Review text

      The lack of house price per square metre data has caused serious problem in comparing the UK and international housing markets and proposing suitable policies to tackle the domestic housing crisis.

      The publication presents an exciting academic research in this area and filled an important research gap well documented by reviewing related literature on developing and applying related house price datasets.

      Based on technically advanced linking and cleansing methods, the research illustrats how to generate a comprehensive house price dataset covering around 90% properties including flats within a house. It also takes account of various property attributes like energy efficiency. Meanwhile, it illustrates in great details how to link, clean and update data which paves a way for wider academic use.

      One highlight of this publication is its state-of-art data linkage method. It involves a matching method containing a four-stage (251 matching rules) linking various sources with algorithm testing the matching efficiency.

      The publication is also well-written with properly displayed figures and logically organised chapters. The authors manage to illustrate the complicated process via a workflow figure which greatly facilitates understanding of an interested academic.

      While it is quite difficult to pick a weak point from the publication, some suggestions are provided if the authors are interested in further related research. Instead of manual correction, there might be possibility of adopting some natural language processing or other text analytical tools to deal with name mismatch issue mentioned in Section 5. The potential automation process may not only improve efficiency but also provide opportunities for text-based attribute analysis. Secondly,the authors can point a lot of areas in which this research can be used. For example, a detailed up-to-date analysis of energy efficiency analysis can be based on the updating data set. The data sets also generate great potential for international comparation studies.

      In summary, the publication clearly presents an innovative house price dataset and technically advanced methodology, which will generate huge research impact on the related research area.

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