How Labour adding VAT on school fees will increase house prices near good state schools

With Labour enjoying a landslide victory in this past election, it’s no surprise that Sir Keir Starmer’s party will be looking to make some big changes in policy. One of the proposals outlined by Labour is an introduction of Value Added Tax (VAT) on private schools fees - which is already raising eyebrows. The ramifications of this policy extend beyond just tax, as it looks to impact the world of education and real estate, too. The relationship between the quality of schools and local property prices is well-documented, with families often willing to pay a premium to live near top-performing schools. So, in this article, we’ll discuss how adding VAT on private school fees might shift demand towards state schools, subsequently inflating house prices in these coveted areas.

Understanding the Policy Change

The Labour Party's proposal to impose VAT on private school fees is a significant shift in the funding model for education in the UK. Historically, private schools have been exempt from VAT, allowing them to operate as charitable institutions. The introduction of this tax would standardise the treatment of private education with other goods and services, subjecting it to the standard VAT rate of 20%. This move is anticipated to increase the cost of private schooling, potentially making it less accessible for a segment of its current demographic.

Expected Outcomes of Labour’s VAT Policy

The financial implications of this policy are expected to lead to a discernible shift in school enrolment patterns. As the cost of private education rises, it is anticipated that a proportion of parents will opt for state schools instead, particularly those that are performing well. This shift could lead to increased demand for places at top-performing state schools, potentially making admission more competitive. Over time, this could not only change the demographic composition of state schools but also pressure the system to accommodate a larger influx of students, prompting further discussions about capacity and quality assurance in public education.

The Demand Shift to State Schools

As private education becomes pricier with the added VAT, more parents are likely to consider state schools, especially the top-performing ones. This shift is anticipated to be reflected in enrolment statistics, with state schools seeing a rise in applications. The allure of high-quality education without the financial burden of private fees makes top state schools an attractive alternative for many families.

With that said, it appears as though the fallout from the VAT change hasn’t quite impacted private school enrolment as of yet. According to statistics from the Independent Schools Council, there were 593,486 students enrolled in private schools - an increase of over 24,000 students from last year.

Impact on Property Prices Near Good State Schools

The direct correlation between the quality of nearby schools and property prices is a key factor in real estate valuation. Areas boasting top-rated state schools are likely to see an uptick in demand, driving property prices up. Historical data from similar policy changes indicate that when school enrolments swell, local housing markets heat up, often resulting in increased property values and intensified competition for homes in these areas.

The idea that government policy can have an impact on property prices isn’t new. Prior to this current issue, other policies such as the help to buy scheme and stamp duty land tax have also directly impacted buying behaviour and property prices.

Market Trends and Economic Implications

Current housing market trends near esteemed state schools show a pattern of rising property values. Economic factors such as increased demand, limited housing supply, and the desirability of living in reputable school districts contribute to this upward trajectory. The long-term effects of this shift might bolster local economies but could also lead to market volatility and potential overvaluation.

According to the research published by the Department of Education, house prices near the 10th percentile of top performing primary schools are 8 % higher than surrounding areas. For secondary schools, this figure is around 6.8 % higher. To add context to these figures, the average home in 2024 is £298,000. Simply by living close to a high-performing primary school, the value of an average property in the UK would be almost £24,000 more, or about £20,000 more if it’s near a top-rated secondary school. Over time, this could have a profound effect on essentially pricing out lower-income households from reaching sought after catchment areas. For property investors, though, this could be a potential tool that can be used to find the best possible properties for your portfolio.

Strategic Considerations for Investors and Homeowners

Investing in properties near high-performing state schools can be particularly lucrative due to the consistent demand from families prioritising quality education. To identify such opportunities, you can use innovative tools such as those provided by Property Data. These analytic tools allow you to explore local data such as school performance metrics and trends. You should also look into things like exam results and Ofsted ratings to learn which schools are the most sought after.

Risk Assessment

While properties near top-rated schools generally appreciate over time, the market is not without risks. You should be wary of potential overvaluation, especially in areas where prices have spiked rapidly due to sudden shifts in school enrollment or policy changes. Conducting thorough market analysis, including comparative market analyses (CMA), can help discern if properties are priced reasonably based on local market conditions.

It's also important to consider broader economic factors that could impact real estate markets, such as changes in interest rates, employment rates, and the overall economic climate which might affect property values and rental demand.

Long-term Investment Strategies

To capitalise on policy-driven changes, such as the imposition of VAT on private school fees, investors and homeowners should adopt a long-term perspective. This involves not just looking for quick gains but also strategising for sustainable growth. Diversifying investments to include a mix of properties near multiple high-performing state schools can spread risk and increase potential returns.

Focusing on property improvements that appeal to families, such as adding bedrooms or updating facilities, can also enhance a property's attractiveness and rental yield. Staying adaptable to further changes in education policy and market conditions will be key to navigating and thriving in this dynamic investment landscape.

Case Studies and Real-Life Examples

Examining neighbourhoods that have undergone similar transformations due to policy changes provides valuable insights. For instance, areas around schools that recently improved their Ofsted ratings have seen marked increases in property values. Testimonials from investors and homeowners in these regions underscore the significant impact of school quality on real estate markets, with many experiencing notable financial gains.

Conclusion

The introduction of VAT on private school fees by Labour could significantly influence local property markets, particularly near high-performing state schools. As this policy potentially shifts the educational landscape, it is imperative for stakeholders to stay informed about market trends and economic conditions. Strategic considerations are essential for those looking to make the most of these changes, be it through investment or homeownership.

To help you make the most informed decisions for your investment, Property Data is an indispensable tool that gives you the power to analyse, research and source the best investment opportunities. To find out more, please contact the team at Property Data today or sign up for a free trial.

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Transparent data promise

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

Averages shown are the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How do you know the square footage of properties?

We use proprietary technology to read the square footage of properties from agent floorplans. Although we cannot determine the square footage for all properties, we can usually get sufficient coverage. Agents are sometimes known to inflate square footage, and this should be borne in mind as a weakness of this data.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property "price paid" data provided by the Land Registry.

How often is the data updated?

Once per month when released by the Land Registry, typically towards the end of each calendar month covering up to the end of the previous calendar month.

What time period does the data cover?

You can customise the time period using the filter at the top of the view. The default time period is up to 9 months back from today's date. The latest data covers the period up to 2024-09-30, although some sales that took place before this date may still be added in the coming months.

How is the raw data processed?

No additional processes are applied to this data.

What are the statistics used?

Averages shown are the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property "price paid" data provided by the Land Registry, and Energy Performance Certificate (EPC) data provided by Department for Levelling Up, Housing & Communities.

How do you know the square footage of properties?

We match the Land Registry data to EPC data provided by the Department for Levelling Up, Housing & Communities. Due to the fact that not all properties sold have had an EPC and vagaries of addressing in the UK, we are not able to determine the square footage of all properties, but we can usually get sufficient coverage.

How often is the data updated?

The private paid data is updated once per month when released by the Land Registry, typically towards the end of each calendar month covering up to the end of the previous calendar month. The energy performance certificate database is updated monthly.

What time period does the data cover?

You can customise the time period using the filter at the top of the view. The default time period is up to 9 months back from today's date. The latest data covers the period up to 2024-09-30, although some sales that took place before this date may still be added in the coming months.

How is the raw data processed?

No additional processes are applied to this data.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Room let listings on SpareRoom, the UK's biggest room letting website.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from SpareRoom, they are soon removed from this tab.

How is the raw data processed?

Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded. Yields are calculated by comparing only properties with the same number of bedrooms, e.g. 3-bedroom properties for rent with 3-bedroom properties for sale.

What is the yield calculation used?

The calculation used is (average_weekly_asking_rent * 52 / average_asking_price), expressed as a percentage. It is a top-line gross yield, meaning no expenses are considered.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from Zoopla, Rightmove or Spareroom, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Yields are calculated by comparing only properties with the same number of bedrooms, e.g. 3-bedroom properties for rent with 3-bedroom properties for sale. For the SpareRoom data, hypothetical properties consisting of two to six average double rooms with shared bathrooms are used to derived average rent. For all sources, listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What is the yield calculation used?

The calculation used is (average_weekly_asking_rent * 52 / average_asking_price), expressed as a percentage. It is a top-line gross yield, meaning no expenses are considered.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property "price paid" data provided by the Land Registry.

How often is the data updated?

Once per month when released by the Land Registry, typically towards the end of each calendar month covering up to the end of the previous calendar month.

Zoopla Zed-index

What time period does the data cover?

The data covers transactions in the last six years

How is the raw data processed?

No additional processes are applied to this data.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The listings data is updated in near real-time. The Land Registry data is updated once per month when released, typically towards the end of each calendar month covering up to the end of the previous calendar month.

What time period does the data cover?

The price paid data shown goes back to January 2015. The listings data is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the calculations used?

Average sales per month are for the last 3 finalised months. Turnover is average sales per month divided by total for sale. Inventory is 100 divided by turnover.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The listings data is updated in near real-time. The Land Registry data is updated once per month when released, typically towards the end of each calendar month covering up to the end of the previous calendar month.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

Where does the raw data come from?

We receive data on the extent and corporate ownership of all land titles in England & Wales from the Land Registry.

How often is the data updated?

The data is updated once per month when released, typically in the first few days of each calendar month.

What time period does the data cover?

This is an ownership snapshot - the data represents ownership as recorded by the Land Registry at the last monthly export.

How is the raw data processed?

No additional processes are applied to this data.

Where does the raw data come from?

We source different expert forecasts Savills, Knight Frank, OBR

How often is the data updated?

The data is updated annually when new forecasts are released, typically towards the beginning of the year.

How is the raw data processed?

We calculate a consensus forecast using a simple mean average.