Uber Alleys

The news on Friday that Transport for London (TfL) had denied Uber an Operator Licence for the capital has stirred up some intense feelings. TfL announced Uber “not fit and proper” to hold a private hire licence and that the company had shown a “lack of corporate responsibility” in relation to public safety. As soon as the judgment was announced the company stated its intention to challenge the ruling in the courts and a petition was launched which is now well on the way to reaching 800,000 signatures. TfL are now saying Uber needs to rethink its approach.

Uber claim that 3.5 million Londoners rely on them to get around London, so we thought that we would look to see exactly where these Londoners are using the App. To do this we used Uber’s own API to get waiting times from 1000 randomly selected locations across Greater London that were within a 50 km radius of Charing Cross and cross referenced it against some known property metrics.

Uber Response Rates

Please click the map above to view our reactive study maps. You can click on the maps to reveal information, and double click on them and select areas.

So what did we find? Well overall across the random sample of 1000 covering the most of Greater London, the average response time was 432 seconds, or 7 min 12 seconds, however the attached visualization shows that much like property values, response times lengthened dramatically for a few postcodes the further away from Central London you travelled. This is not so surprising, you would expect more Ubers to be located in the busy central areas.

Please click the map to view our reactive study maps

However what is interesting is that actual response rates were very similar over a much larger area of London than you would expect and pretty fast too, with 2 to 3 minutes not unusual. The second chart shows the average price per square meter for properties in the same postcode areas. So if Uber were just used in central areas, you might expect the same distribution of response times as say, property prices/housing density, but as you can see, it is clearly not. In fact, response times in Outer London are very similar to Inner London and spread quite evenly, suggesting Ubers really are used by Londoners at pretty consistent levels all across the capital.
Uber Response Times Central London vs Outer London Please click the chart above to view our reactive study maps

As the chart above shows, even if you live in outer London (Green) you can have response times that are as fast as the most well served and expensive central areas (Red). So it would be very fair to say that if you are living in the most exclusive part of London, or indeed the cheapest bargain basement, in both cases your access to Uber in London's streets and alleys is about the same. That makes it a egalitarian mode of transport. This, all too often, is not the same for other modes of transportation across the capital that serve Londoners and suggests that TfL will need to rethink as much as Uber will have to smarten up its operations.

If you would like to see where the location you live ranks in London for Uber, or how other areas compare then please feel free to try out this link for our interactive charts on transportation and London property .

An extract of this blog post was written for http://www.jamesdearsley.co.uk/

House prices on the up

According to this month’s Halifax house price index, House prices in June, July and August were on the up, 0.1% higher than in March, April and May. This means that the annual house price growth has picked up to 2.6%. Just don’t be too quick to shout hurrah.

Russell Galley, Managing Director, Halifax Community Bank, said: “The annual rate of growth increased from 2.1% in July to 2.6% in August with the average house price now £222,293, which is just above the previous high of December 2016 (£222,190). “

Unemployment is also at a 43 year low. The Office of National Statistics16th August Bulletin states that “The employment rate (the proportion of people aged from 16 to 64 who were in work) was 75.1%, the highest since comparable records began in 1971.”

There has also been an increase in mortgage approvals, and according to Bank of England seasonally adjusted figures, nearly reversed all the falls seen so far this years.

So this seems sunny news, however, wage growth is still lagging. The cost of your weekly shop has also gone up. If you look at your standard 800g white loaf, for example. it was 97p in April and is now £1.04. It doesn’t sound a lot, but add 7p to every item in your weekly shop and it soon adds up to a sizeable increase. With inflation outstripping wage growth, this puts a significant strain on the household budget. New house or avocado toast?
The HMRC say that property sales are on the up, however the RICS monthly report, shows that new instructions for home sales fell for the 17th consecutive month in July, and that the average number of properties on estate agents’ books are close to an all-time low, making that instruction from any vendor all the harder to secure.

With wages stagnating and food bills increasing it is not hard to see why people are less eager to upgrade, so there are fewer properties coming onto the market, and thus the market value increases.

Without making but the slightest nod to Brexit, house prices will fluctuate, wages and food prices go up and down. Yesterday the Telegraph reported that “soaring house prices in the UK mean that one in every 76 Britons is now a millionaire, up from one in 84 last year.” Somehow that diminishes the value of being a millionaire, it just bumps up the stamp duty. If your prospect is a millionaire purely because their house is worth a million, it means very little if they have no immediate intention of selling it. Whether they live in a large house In Belgravia or a 2 up 2 down in Sunderland the value of their home increasing means nothing. Its just the roof over their head. It only matters when they decide to move.

This is a good place to state that the Big Data that feeds our AI includes the house price index. So whether house prices go up or down you can be confident that Houseprice.AI and our Estate Agents app, Horizon, will back up your own knowledge with the most current and fair price for any vendors property.


What is Houseprice.AI?

This video explains how Houseprice.AI is at the forefront of Proptech innovation by developing a machine valuation model that draws on Big Data and AI to predict astonishingly accurate valuations.

What's the fair price? Houseprice.AI.

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If you would like to know more information about Houseprice.AI or our Estate agents' App Horizon, please feel free to contact us through the online chatbox or by email at support@houseprice.ai.

Factoids and Snippets about Property Valuation Methods

Marie-Esprit-Léon Walras (1834 –1910)

While delving into the history behind the development of AVMs, we came across this interesting pioneer. Léon Walras was a French economist who formulated the marginal theory of value (independently of William Jevons and Carl Menger) and pioneered development of general equilibrium theory.

“I say that things are useful whenever they can be put to any use at all” - Léon Walras

In the early 1870s the theory of marginal utility started a brand new microeconomics. The main impact on future development of AVMs was the theory of value. Before these bright sparks, the classical thought was that exchange value was based on building costs, particularly labour. Marginalist theory linked value with use and demand. So, if you flood the market with new property, the demand is diluted and the cost becomes almost irrelevant.

Initially Walras enrolled at the School of Mines in Paris but didn’t like engineering and quit. He tried several diverse careers. These include, but are not limited to: a journalist, a railway clerk, a bank director, and even a published romantic novelist! He applied for economics posts in France but was under qualified, and complained that the orthodox French economists passed on their chairs to their relatives. Finally he obtained tenure at the University of Lausanne in Switzerland.

Whilst Jevons was lauded in England, just as Menger was in Austria, poor Walras was in Switzerland where the academic appreciation of economics did not have a major role. However, Walras continued his dedication to his theories, and simulated an artificial market process that would get the system to equilibrium, a process he called “tâtonnement” (French for “groping”). He hypothesised that tâtonnements in the markets for productive services and for consumer goods are interrelated.

In 1895 Walras’s successor to the chair of economics at Lausanne, Pareto, presented Walras’s ideas in his own books, and finally began their widespread dissemination.

In 1904, Walras wrote to old friends about his future:
“I have not the least doubt about the future of my method and even of my doctrine; but I know that success of this sort does not become clearly apparent until after the death of the author”. then in 1909 a celebration of his jubilee was held by the University of Lausanne. He was honoured as the first economist to establish the conditions of general equilibrium, thus founding the School of Lausanne.

Walras's prediction of success proved accurate. His theory of general equilibrium has been developed further in the 20th century and these have become an integral part of mainstream modern economics.

For sheer genius, and intuitive power in divining the underlying structure of fundamental economic relationships and their extensive interdependencies and consequences, Walras has been surpassed by no one.

Acknowledgements: The Concise History of Economics 2nd Edition, Léon Walras: The life of Léon Walras and perspectives on his thought edited by John Cunningham Wood, Advances in Automated Valuation Modelling edited by Maurizio d'Amato, Tom Kauko,