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1 – 1 of 1The purpose of this paper is to provide a comprehensive overview of the geography of mortgage lending in Great Britain. It uses a new mortgage dataset as a way to shed light on…
Abstract
Purpose
The purpose of this paper is to provide a comprehensive overview of the geography of mortgage lending in Great Britain. It uses a new mortgage dataset as a way to shed light on the spatial distribution of mortgage finance and to highlight the different lending patterns of seven major UK banks. It also examines the relationship between the distribution of mortgage finance and socio-economic status at the local level.
Design/methodology/approach
The methodology is based on simple quantitative techniques, including spatial analysis, location quotient analysis and socio-economic classification. Lending data for Great Britain’s 10,000 postcode sectors are the basis for analysis here.
Findings
The results suggest that some banks lend significantly less than others in poorer areas, but, owing to a lack of data, it is not possible to say why. It is possible to identify banks that appear to change their lending patterns in areas with different socio-economic characteristics. The paper concludes by reflecting on key messages and by making a small number of recommendations to improve transparency in the sector.
Research limitations/implications
In the absence of demand-side metrics, it is not possible to determine which banks lend disproportionately high or low amounts in poorer areas.
Practical implications
This paper has implications in relation to increasing financial transparency in the residential mortgage sector. The most important implication would be to highlight the fact that this new data – whilst a welcome development – is a long way from providing proper transparency in the mortgage lending sector.
Originality/value
This paper fills a gap in the international literature in relation to our understanding of the geography of mortgage lending in a major world economy. It also highlights important differential lending patterns in relation to socio-economic status at the sub-national level.
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