Survey Variable: Types of Property Owned

Figure 1. See also Table A1.

As mentioned when considering income, that concept needs to be distinguished from wealth, which is the assets that one holds (less one’s liabilities). Assets might take the form of savings, investments, art or, most commonly, property. The latter was asked about in the survey, and respondents indicated whether they owned five types of property: residential (owned outright), residential (with a mortgage), buy-to-let, land, and commercial. Such assets constitute an important part (and often the bulk of) of people’s wealth, and we can assume that people who own more types of property are likely to be wealthier than people who own fewer types of property.

Figure 1 (above, using weighted data) shows that almost a third of people (32.4%) own a residential property with a mortgage, most likely the homes that they live in. A further three in ten (31.1%) own residential property with a mortgage, and we can again assume that these are likely to be their own homes. Ownership of properties for other purposes is far less common: fewer than one in twenty people (4.3%) own a buy-to-let property whilst slightly more than one in a hundred (1.1%) own commercial property, and an even smaller group (0.6%) own land. Thus, whilst home ownership is widespread, owning other types of property is much less common.

The rarity of owning property other than one’s home is also apparent when we look at how many types of property people own, as shown in Figure 2 (below, also using weighted data). More than three fifths of people (62.3%) own one type of property, whilst a further third (34.5%) own none, meaning that fewer than one in thirty (3.2%) own more than one type of property. In this light, we can safely assume that owning ‘investment property’ is not commonplace, and the vast majority of people can afford to buy one property or less. This suggests that most people’s wealth is tied up in the property that they reside in, and having property that one can simply sell to maximise returns is beyond the reach of most.

Figure 2. See also Table A2.
Variable namesec_property_resown, ec_property_resmort,
ec_property_buytolet, ec_property_plotland,
ec_property_notsure, ec_property_none
Number of cases1,405
Number of categories2
Categories to code as missing1 (‘Yes’) on ec_property_notsure
Cases to code as missing9
Recoded variable nameec_propro_b, ec_proprm_b, ec_propbl_b,
ec_proppl_b, ec_propco_b, ec_prop_c
Number of cases1,396
Number of categories2
New and old categoriesPeople who selected ‘Yes’ (1) on the original
ec_property_notsure variable (presented as
the ‘Not sure’ option to respondents) were
coded as missing on the new binary variables,
which also replace 2 with 0 to represent the
‘No’ category.

The responses to the new binary variables
were then added together to create the new
count variable (ec_prop_c). As such, a 0 on
the count variable indicates that the
respondent owns none of the types of
property, whilst a 5 indicates that they own
all of the types.
Details of the original and recoded types of property owned variables.

Published by joegreenwoodhau

Joe Greenwood-Hau is a Lecturer in Politics in the School of Social and Political Science at the University of Edinburgh, where his teaching focuses on Introduction to Political Data Analaysis and he is wrapping up the Capital, Privilege and Political Participation in Britain and Beyond project.

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