Pubs, trams, schools: Framing PATRIZIA’s amenities insights through Manchester as a case study
02 / 03 / 23 - 5 minute read
The regulars at Coronation Street’s Rovers Return pub, who pop into their local every day to discuss the latest dramas, hardships and goings-on in their lives, are well served. The characters in the British TV’s long-running serial drama live practically on the pub’s doorstep, just a quick stroll down the cobbled street that runs through fictional Weatherfield in Manchester. In real life, the rents on their terraced houses would be steep: according to PATRIZIA’s research, the closer you live to a pub, the higher the rent charged.
It’s a guaranteed fact that people want to live close to specific amenities, whether a bar or handy transport links and most are willing to pay the extra price for that easy proximity. In a case study researching rents in Manchester, PATRIZIA applied machine learning algorithms to a dataset containing 38,000 residential listings and a direct connection to OpenStreetMap and Google Maps to measure the distance from each apartment to amenities and see how that influenced rental prices.
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Maybe it’s the urge to sip on a pint of Manchester’s famous Boddingtons beer or a yearning to let their hair down at one of the party city’s cool and quirky bars. Regardless, residents in Manchester city centre are clearly willing to pay more for accommodation located close to a bar. Interestingly though, the research showed that those living further away from the centre are less willing to splash out more on rent for the convenience of a nearby ‘watering hole’.
The Manchester research formed part of PATRIZIA’s Insight entitled ‘Location analysis and pricing of amenities – portfolio construction in the era of data intelligence’, which examines the attractiveness of a location and the impact on rental values based on the supply of local amenities. By combining its Amenities Magnet algorithm, which employs sophisticated machine-learning algorithms, with expert local knowledge, PATRIZIA can track how amenities develop over the years and which regions experienced an upswing regarding location attractiveness relative to the city.
“Amenities play a vital role in enhancing the desirability of real estate and are an important selection factor when choosing a property,” says PATRIZIA’s Head of Data Intelligence, PD Marcelo Cajias, who co-authored the Insight, alongside PATRIZIA Head of Global Investment Strategy, Research and Investment Solutions, Dr Mahdi Mokrane, and PATRIZIA Associate – Data Intelligence, Dr Anett Wins. “Amenities can positively enhance the quality of life for residents – and many people will seek out housing with certain local amenities located within an easy walking distance and are willing to pay more for that privilege.”
PD Marcelo Cajias
Rent increases closer to tram stops but picture not as clear for proximity to public schools
Diehard fans of ‘Corrie’ (the popular abbreviation for Coronation Street) will be familiar with ‘Weatherfield North’ – the tram stop which serves the residents of the fictitious residential estate. Here, fiction imitates fact, with Manchester notable for being one of only eight locations in the UK to still operate tramways/light rail systems.
This local transport solution is highly sought-after in the city. PATRIZIA’s explainable AI results show that living close to a tram stop is a major factor influencing the average asking price for rent in Manchester. Rent falls 2% if the nearest tram stop is 200m away or more. And every additional metre away from a tram stop further lowers the rental potential.
Those living in the heart of Manchester, within 8-12 km of the city centre, are keenest to live near a tram stop. If a tram stop is further away than 1.1 km, asking rents fall by 6%.
"Many people will seek out housing with certain local amenities located within an easy walking distance and are willing to pay more for that privilege.”
PD Marcelo Cajias, PATRIZIA Head of Data Intelligence
Every young family likes the idea of living within easy access to a good school. But what is close enough or even too close? Results show that property located between 200 and 800 metres away from a public school in Manchester tends to demand lower asking rents. This is more marked for assets situated 4-8km away from the city centre.
Easy readiness to withdraw cash doesn’t appear to be a crucial factor in determining people’s choice of property; results reveal that most people aren’t prepared to pay more for property close to an ATM – perhaps a reflection of the lessening need to carry cash. However, the potential asking price for rent does soar by almost 50 basis points if an ATM is close to assets within 8-12 km of the city centre.
City centre location costs more whilst outskirts experience stronger rental growth
It can be difficult to determine the driving factors behind rising rents, whether socioeconomic, based on property characteristics or other factors. Fortunately, machine learning algorithms can skilfully recognise the patterns and data forces that impact rents.
Looking at Manchester, rents grew by 3-4% per year on average between 2019 and 2021. But this varied depending on how close the property was to the city centre.
For the case study, PATRIZIA divided Manchester into four rings; each spaced 4km further away from the city centre – 0-4km, 4-8km, and so on. Between 2019 and 2020, rents increased by 0.5% to 1.5% for properties 4-8 km from the centre. For properties further away from the city centre, namely, 12-16 km away, rents grew by 4% to 5%. In 2021, the divergence was even more pronounced, with rents in the outer ring of Manchester growing nearly twice as fast as rents in the city centre.
Of course, the size of the property plays a role in how much rent is charged. As a general rule of thumb, the larger the apartment, the higher the monthly rent. However, significant increases, namely four percentage points, were shown for dwellings larger than 75m2.
For further insights (firmly rooted in reality), take a look at PATRIZIA’s ‘Location analysis and pricing of amenities – portfolio construction in the era of data intelligence’ report.
