Analysis: UK House Price Index
Data Source: Office Of National Statistics
Period: Monthly
Graph: Showing December Yearly Prices
 Linear Trendline |  Polynomial Trendline (order 3) |
Observations (from the raw data):
Over the 19 years between YE 2005 and YE 2023, average UK house prices have increased from:
£160,209 in 2006 to £284,681 in 2023 or 78% with an average yearly increase of £6,551
The maximum Average House Price was: £288,784 in December 2022.
The drop from 2007 to 2008 of £28,239 is evident and goes against the positive trend relating to the 2007 financial crash. The drop from 2022 to 2023 of £4053 relates to the higher interest rates in the UK and the cost of living crisis.
Trendlines
If we add a linear regression line (left graph), to the data points, we get an R-squared score of 0.85%, meaning 85% of the variability of average house prices is accounted for by year, which is a pretty strong correlation as we would expect.
If we add the forecast based on the linear regression line equation (not included here), we get £303,618 in 2028.
(I’ve used the FORECAST.LINEAR() Excel function to generate the forecasts).
An alternative is to use the polynomial regression line which is used when there are peaks and valleys in the data. In this example, we are using an order 3 polynomial trendline which accounts for 2 peaks or valleys. This gives an R-squared value of 0.96, which appears to be a very good fit, but I’m somewhat hesitant as we’re right at the point of a 2nd drop. One could look back at the years following 2007 and apply the growth to the years following 2022. This would be similar to a seasonal adjustment, but I’m not sure what tool will pick this up at present (and of course, it’s not the same situation).
If we apply the forecasting from the Polynomial regression trendline, we get £389,243 for 2028.
So the linear regression forecast gives £303K for 2018 and the Polynomial regression method gives £389K, that’s a pretty big difference.
As you can see the polynomial regression is less impacted by the peaks and troughs than the regression line.
If we use the Excel forecast tool which uses the ‘AAA Exponential Triple Smoothing (ETS) algorithm’, for the next 5 years, we can see the forecast of £319,647 for 2028, however, the upper and lower (non-bold) lines indicate the confidence levels, which indicate we can the estimate will lie between £204,369 and £434,925 with 95% certainty, which is very uncertain.
Some of the reasons for this are that we only have 18 years (18 data points) to work with, we have 2 dips in the data, and a somewhat flat period, this doesn’t help the model and hence the confidence limit is less certain.
The algorithm is best used for linear seasonal fluctuating data, which isn’t quite what we have here.
To create a better model, we could create a multi-variate model, including additional features such as interest rate, population, housing supply, and region. We can also see if there is more data available pre-2005.