Skip to main content

Adam Al-Nuaimi, Head of Data Analysis and Lead Official for Statistics, Welsh Revenue Authority (WRA).

First published:
13 November 2020
Last updated:

In July 2019, we published our first annual statistics for Land Transaction Tax (LTT). This included data showing the numbers of land transactions that occurred in local areas across Wales, including data for local authorities; Senedd constituencies; areas of deprivation; and built up areas.

These statistics built on annual data produced previously by HMRC on Stamp Duty Land Tax (SDLT) for local authorities until 2018. HMRC was responsible for administering SDLT in Wales until 31 March 2018. We started collecting and managing LTT on 1 April 2018.

We published our latest data by local areas for April 2019 to March 2020 in July (2020). This provided detailed statistics on both residential and non-residential transactions for local authorities, alongside statistics for only residential transactions for the other geographic aspects.

Breaking down counts of tax transactions and the associated revenue into figures for each local area may appear relatively simple. To do this, we allocate transactions to each based on the location of property or land being taxed. While this is possible, there are some complex scenarios. For example:

  • when there are multiple land items involved in a transaction and they span several local areas
  • where the postcode of the land provided contradicts the local authority stated on the return, or is not provided at all

The quality section for the release explains how we’ve resolved these issues, and this article discusses some of the challenges in interpreting these statistics.

Interpreting the statistics: factors to consider

The statistics provide numbers of transactions in a particular year. That means:

  • the data relate to property that has changed hands during that year and should not be mistaken for a count of the entire stock of residential and non-residential property in any given area
  • with only 2 years’ worth of data, we cannot yet tell if transactions that take place in any given year are representative of the overall stock of property for each area. In short, any given year’s transactions may not be an unbiased sample of that overall stock

We can, however, use the data to highlight the extent of variation in the value of properties and the tax raised per transaction in each Welsh local authority area.

We can also analyse which types of transactions take place in each area and note, for example, that there are different profiles for residential and non-residential transactions across individual local authorities in Wales.

By relating residential transactions with sources that estimate the stock of residential property, such as the number of council tax dwellings (local authority data) or council tax stock of properties data (Valuation Office Agency), we can also identify areas where, for example, there are comparatively more transactions.

Higher residential rates of LTT: charges and when it applies

We’ve seen increasing interest in understanding how and when higher residential rates apply to LTT. When they do apply, an additional percentage of the purchase price is part of the tax. The additional percentage was effectively an additional 3% on the main residential rates. On 27 July 2020, the main rates starting threshold was temporarily increased to £250,000 until 31 March 2021. However, this change does not apply to higher residential rates transactions. This has effectively increased the additional rate to between 3% and 4%, depending on the value of the property.

There are several reasons why the higher rates of tax applies depending on whether the buyer is an individual(s) or a company. The 3 main reasons are:

1. Not a main residence

Higher rates applies to all individuals who buy property that is not to be their main residence, including:

  • residential property that is not used by the owner as their main residence - this might include, for example, a residence used for weekends, for holidays, on a seasonal basis or during the working week to facilitate access to a place of work
  • homes bought for the purpose of renting to other people for short and long-term use - this might include residential letting or holiday letting, with the latter possibly combined with occasional use by the owner as well
  • homes acquired for relatives; for example, elderly dependants, children or students
  • homes bought to be developed or renovated for onward resale

2. Bridging

Higher rates applies to an individual buying a property as a new main residence, where they have not sold their previous residence at the time of purchase. However, if the taxpayer sells their former main residence within 3 years, the individual is eligible for a refund of the higher rates element of the tax. In these cases, the transaction is changed to main rates residential at the point the refund is claimed.

3. Companies

Higher rates applies to any company or organisation purchasing residential property for any purpose. For example, companies buying property for letting purposes, or for redevelopment.

It’s important to note that if certain conditions are met, a tax relief applies to some of the company cases which may fully or partially cover their liability when purchasing residential property. Examples of relieved transactions in this context include:

  • movement of property between different parts of the same group of companies
  • purchases by social housing providers
  • companies providing certain alternative finance mortgages
  • part exchange purchases by housebuilders and in other circumstances

These transactions still form part of the higher rates transaction counts.

We publish different statistics for higher rates transactions, including the total revenue raised and the number of refunds made each month. At a local area level, we publish the annual percentage of residential transactions for which the higher rates applies.

Using higher rates of LTT data accurately

The higher rates of LTT often applies when the taxpayer is buying a property that is not to be their main residence. These data are sometimes used to comment on and highlight differences in second home ownership across Wales. Why may this not be appropriate?

First, there’s not a common understanding of a second home and different definitions are often relevant in different circumstances.  We can broadly look at 2 scenarios:

  • a wider definition applies and may include any property that is not lived in by the owner as their main residence. However, it may be lived in by others, such as private renters, or other family members
  • a narrower definition of properties used only by the owner for only part of the year

There’s also the added complication of how using the property as part of a holiday letting business might interact with these definitions.

Second, the system used to administer the tax does not need to directly distinguish between the reasons for charging higher rates. It simply asks whether the higher rates applies. It’s not possible to directly identify these elements within the data, although we can do something here, as explained later.

Third, the point made earlier that these statistics only apply to change in a given year - and may not be representative of all property in the area - is pertinent, for 2 reasons:

  • only a relatively small share of residential properties (less than 5%) change hands each year, and with only 2 years’ worth of data so far, it is unknown whether higher rates properties transact more often than other residential transactions. If that is the case, it is unlikely that conclusions drawn from that higher rates data can be reliably applied to the entire stock of property in a given area
  • we cannot routinely tell whether properties were already in one of the categories to which higher rates applies before the transaction. As such, it’s not possible to argue that transactions in a given year change the ownership profile over the stock of property. For example, a transaction may already be a holiday home sold to a person who will again use it as a holiday home, or sold from one buy-to-let landlord to another

Finally, when considering breakdowns of higher rates transactions, there will inevitably be some averaging out within different geographical areas. For example, when looking at local authority data, there will be areas where the categories above apply to differing degrees, and the effect of any single factor may be reduced across the entirety of the local authority. However, it’s worth noting that some parts of Wales are likely to have relatively high concentrations of more than one factor (e.g. those with both student populations and popular tourism locations).

Using the data accurately: advice

Any use of these statistics should reflect the fact we are referring to ‘in-year’ transactions of properties and not the total stock of properties, as well as being clear about what is included. Ideally, the data should be combined with other information- for example, knowledge of the private rented sector market in an area.  Referring to both data sets will create a more complete picture than using our LTT data in isolation.

If the LTT data are being used in isolation, however, we’d advise that this is done with careful consideration of the information we publish. One thing we know already is that most of the higher rates transactions fall into the “bought for use other than as a main residence by the owner” category, whether bought by an individual or a company.

How to express the statistics: examples

We can legitimately use the data to make statements like:

In 2019-20, … properties in … were subject to the higher rates of LTT, most of which were bought for use other than as a main residence by the owner.

In 2019-20, … was the area with the highest proportion of sales subject to the higher rates of LTT. Most of those were bought for use other than as a main residence by the owner.

However, it’s not accurate to use the data to make statements like:

…% of property in … are second homes.

This is incorrect on 2 counts because it’s:

  • making an assertion about all property - not just those which were sold in-year
  • incorrectly stating that all higher rates transactions relates to second homes

This is especially problematic where the term ‘second homes’ has different meanings in different contexts.

It’s best not to make assertions around higher rates transactions changing the profile of stock in an area. This can only be done reliably with estimates of the whole stock, because as stated earlier, it’s quite possible that many of the higher rates transactions were in categories to which higher rates applied anyway before the transaction took place. 

For users particularly interested in stock of residential property, the council tax data referred to earlier is a useful source of information at local authority level.

Can we improve our data?

We recognise that there’s growing appetite for these data. As such, we’ve started to experiment with the data.

1. Analysing the effect of bridging

By looking at the cases from 2018-19 that have been refunded since, we have been able to model the effect of bridging within the data we published for 2019-20. A person can reclaim the higher rates tax if they dispose of their former main residence within 3 years of the date they acquire their new main residence, but most will occur within the first or second years. 

2. Breaking out company data

We have split the company purchase element out from the data and reported this using 2 categories:

  • the first is those purchases relating to the public sector, generally in the social housing space plus those which relate to intermediate temporary purchase (certain alternative mortgage providers or part exchange by housebuilders etc.) plus those which are moved around companies – all of these are generally relieved
  • the second is everything else in the company purchase terms which is more likely to be relevant to use in the buy to let sector, but may also be relevant in the second or holiday home context (but for which we have limited information currently)

3. Individuals buying property for use other than own main residence

By excluding from the total an estimate of transactions which are expected to be bridging and the 2 types of company purchases, estimated above, we’re essentially left with individuals buying property for uses other than their own main residence. We can now refine the first of the statements made earlier to be a little more direct, for example:

In 2019-20, approximately … properties in … were bought by individuals not using it as their own main residence

Note the use of the word “approximately”, however. We’d always recommend using “approximately” as there is a level of estimation involved.

The chart below summarises how this extra detail is reflected in the 2019-20 data we published on 7 July in our annual LTT statistics. The attached spreadsheet sets out all the data and provides fuller details around the methods used.

Chart 1 shows the different types of higher rate transactions stacked as a percentage of all residential transactions for each local authority and Wales.  The data are sorted according to the data for individual purchase not bought as a main residence.


What’s next?

This analysis work is in progress. One of the things we’d like to investigate is further separation within the ‘bought by individuals for uses other than as a main residence’ or the ‘wider company purchase’ elements of the data.

We hope that if we can link to data from the Welsh register of landlords then separating out longer-term rentals will be possible. This might mean the remainder might represent more closely the narrower definition of second homes mentioned earlier, although this will also need to be informed by wider work, reflecting definitions used in the second home context at the time.

We’d also like to extend the modelling to our other geographic datasets, including Senedd constituency areas; areas of deprivation; or possibly different groupings of local areas based on other common characteristics.

We’d welcome your feedback

If you think any of this further analysis will be useful or, have any comments on the data we already publish on either LTT or Landfill Disposals Tax, we’d be interested in hearing from you. If you have any comments or queries about using our data, please email us: