House prices in DH9 (Stanley)

This article shows price per square metre data and various charts to help you understand the housing market in DH9 - stats were last calculated on 01 November 2024.

Defining 'DH9'

This analysis is limited to properties whose postcode starts with "DH9", this is also called the postcode district. There are no official postcode district names so I've just labelled it DH9, Stanley. It is shown in red on the map below.

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Price per square metre

Knowing the average house price in DH9 is not much use. However, knowing average price per square metre can be quite useful. Price per sqm allows some comparison between properties of different size. We define price per square metre as the sold price divided by the internal area of a property:

£ per sqm = price ÷ internal area

For example in September 2024, 46, Orwell Gardens, Stanley, DH9 6QA sold for £82,000. Given the internal area of 73 square metres recorded on the EPC, the price per sqm is £82,000 ÷ 73 sqm = £1,123.

England & Wales have been officially metric since 1965. However house price per square foot is prefered by some estate agents and those of sufficiently advanced age ;-). It is a huge pain to code the automatic conversion for square meters to square feet for all the graphs and charts on DH9 and elsewhere. All the conditionals turn my tidy code for into spaghetti. I will get around to it at some point, but for now you can just divide everything by 10 in your head, move a decimal place and you'll be close enough. If you want to be more precise 1 sqm = 10.76391 sqft.

Distribution of £ per sqm for houses vs flats in DH9

The chart above is called a histogram, it helps you see the distribution of house price per sqm in DH9 To make this chart we put all the sales data into a series of £ per sqm 'buckets' (e.g. £900 to £1,000, £1,000 to £1,100, £1,100 to £1,200 etc...) we then count the number of sales with within in each bucket and plot the results. The histogram is based on 1,116 sales that took place in DH9, in the last 24 months.

Generate a custom histogram like the one above but based on your own criteria.

You can see the spread of prices above. This is because although internal area is a key factor in determining valuation, it is not the only factor. Many factors other than size affect desirability; these factors could be condition, aspect, garden size, negotiating power of the vendor etc.

The spread of prices will give you a feel of the typical range to expect in DH9, Stanley. Notably, only 25% of properties that sold recently were valued at more than £1,560 sqm. For anything to be valued more than this means it has to be more desireable than the clear majority of DH9 homes.

Box plot of £ per sqm for DH9

Tip: click on the chart to see the values.

The chart above is called a boxplot (or a box-and-whisker plot). Box plots, like histograms, are used to graphically represent the distribution of data, showing the central tendency, spread of the distribution. In the context of £ per square metre property price distributions, box plots represent the variation in property prices within a geographic area e.g. Stanley. The chart above shows a boxplot for 'DH9' as well as the 'DH' postcode area.

  • Median: The horizontal line inside the box represents the median (£ per square meter). This is the midpoint of the data, meaning 50% of the prices are below this value, and 50% are above. The middle price per square metre in 'DH9' is £1,060.
  • Interquartile Range (IQR): The box spans from the 25th percentile (Q1) to the 75th percentile (Q3). This is the range where the middle 50% of the data lies, giving a good indication of the typical price spread. Of the 1,116 transactions in DH9, Stanley half were sold for between £740 and £1,560 per square metre.
  • Whiskers: In our case, the whiskers extend from the 9th percentile (at the lower end) to the 91st percentile (at the upper end), This provides a slightly broader view of the distribution by including the middle 82% of records. The whiskers capture most of the variation but exclude extreme outliers caused by data errors in recording sold house prices or internal area.
  • 'n=' is the number of property transactions the box plot is based on; 1,116 for DH9, Stanley.

    • Property price map for Stanley

    Have a look at the interactive price map I created for myself. Use it to explore 'DH9' house prices all the way down to individual property plots.

    Property price heatmap for Stanley
    House price map for Stanley

    Will DH9 house prices drop in 2025?

    I cannot tell what house prices will do in the future and don't believe anyone who says they can. However we can plot price trends, I have done this in the chart below for DH9 (Stanley) compared with the wider postcode area 'DH'. You can extrapolate from this based on your own views on future interest rates, inflation and other factors.

    House price index for DH9

    Tip: click on the legend items to show/hide different lines

    Download house price index as CSV (premium users only).

    The chart above shows changes in 'DH9' property prices over the last 20 years. The index is calculated from the average price paid per sqm for property in DH9 and is set to 100 in 2004. The chart compares trends for DH9, Stanley against those of the broader postcode area 'DH'. What is more interesting is to look at the difference between flats and houses, even those in the same area follow a very different trend, to get a robust enough sample size to see this we need to zoom out and look at house price trends for the entire County Durham local authority.

    The dashed lines show nominal house price changes, the solid lines show the same data adjusted for inflation. Economists call this the 'real' price change. You have to take inflation into account when comparing prices over time. It's calculated using the formula:

    Real Rate of Return = (1 + Nominal Rate) ÷ (1 + Inflation Rate) – 1
    In this formula, the nominal rate is the rate of change before any adjustments, and the inflation rate is taken from the Consumer Price Index. The real rate of return is a more accurate measure of change in value, because £1 today does not have the same buying power as £1 in the past. For example, if a savings account pays an interest rate of 3% per year and the inflation rate is 5% per year, the real rate of return is -2%. This means that the investment's value is shrinking by 2% each year.

    Historic returns for DH9
    DH area DH9 district
    Nominal Real Nominal Real
    20 yr per annum 1.6% -1.0% 1.7% -0.9%
    20 yr total 37.3% -18.7% 41.1% -16.4%
    10 yr per annum 2.1% -0.7% 3.0% 0.2%
    10 yr total 23.1% -6.6% 34.6% 2.2%
    5 yr per annum 2.8% -1.2% 3.5% -0.6%
    5 yr total 14.7% -6.1% 18.6% -2.9%
    1 yr per annum -0.8% -4.7% 4.5% 0.3%
    1 yr total -0.8% -4.7% 4.5% 0.3%

    This table complements the house price index chart above, presenting the data in a more detailed format. It breaks down the information into 20-year, 10-year, 5-year, and 1-year periods, further categorized by property type. For each period, we display both a per annum rate of change and a total rate of change.

    The total rate of change represents the overall change over the entire period. The formula for total return is:

    Total return = (Index at end of period ÷ Index at start of period) - 1

    The per annum rate of change is the annualized rate of change over the period. This is equivalent to the annual bank savings rate you would need to achieve the same total return over the given period. This annualized return is also known as the Compound Annual Growth Rate (CAGR). The formula for CAGR is:

    CAGR = (1 + Total return) ^ (1 ÷ Number of years) - 1

    Some specific examples:

    • Over the past 20 years, DH9 district have seen a -0.9% annual change when adjusted for inflation. This translates to a total change of -16.4% in real terms.
    • Over the past 5 years, DH9 district have seen a -0.6% annual change when adjusted for inflation. This translates to a total change of -2.9% in real terms.

    Most recent DH9 sales

    For the most recent sales activity, rather than a summarized average, it is better to see the underlying data. This is shown in the chart below, where blue dots represent individual sales, click on them to see details. If there is an obvious trend you should be able to spot it here amid the noise from outliers.

    Tip: hover over dots to see details

    Street level data

    Street Avg size Avg £sqm Recent sales
    Orchard Grove, , DH9 8N 107 sqm £1,883 34
    Murray Park, , DH9 0P 121 sqm £1,712 23
    Kielder Drive, , DH9 6A 91 sqm £1,749 22
    Poplar Street, , DH9 7A 75 sqm £609 18
    Charlotte Street, , DH9 7A 67 sqm £682 16
    Orwell Gardens, , DH9 6Q 69 sqm £1,442 15
    Twizell Lane, , DH9 6S 100 sqm £1,174 15
    Cloverhill Court, , DH9 6B 105 sqm £1,835 13

    Search for your street here.

    Nearby geographies

    The table below shows how 'DH9' compares to the other postcode districts nearby 'DH9'.

    District Lower quartile Median Upper quartile Sales in last 2yr
    NE39 Rowlands Gill £1,370 sqm £2,040 sqm £2,620 sqm 193
    NE16 Whickham £1,670 sqm £2,170 sqm £2,800 sqm 649
    NE11 Gateshead £1,440 sqm £1,910 sqm £2,380 sqm 399
    DH9 Stanley £740 sqm £1,060 sqm £1,560 sqm 1,116
    DH8 Consett £1,070 sqm £1,530 sqm £2,020 sqm 1,020
    DH7 Sacriston £1,090 sqm £1,520 sqm £2,090 sqm 1,060
    DH6 Bowburn £930 sqm £1,360 sqm £1,980 sqm 1,175
    DH5 Hetton Le Hole £880 sqm £1,420 sqm £2,020 sqm 635
    DH4 Houghton Le Spring £1,110 sqm £1,770 sqm £2,260 sqm 902
    DH3 Birtley £1,270 sqm £1,750 sqm £2,310 sqm 661

    Raw data

    Our analysis of DH9 is derived from what is essentially a big table of sold prices from Land Registry with added property size information. Below are three rows from this table to give you an idea.

    Address Paid sqm £/sqm
    46, Orwell Gardens, £82,000
    Sep-2024
    		 73 1,123
    Southlea, , £380,000
    Sep-2024
    		 179 2,122
    16, Betjeman Close, £124,995
    Sep-2024
    		 96 1,302

    See the entire list of all sales in DH9 here.

    About

    I created HouseMetric because I wanted to see this data and analysis myself, I also wanted to teach myself to build a website. Please give me feedback or spread the word about it. I'm constantly tinkering and adding more stuff to it.