House prices in CM19 (Harlow)

This article shows price per square metre data and various charts to help you understand the housing market in CM19 - stats were last calculated on 01 November 2024.

Defining 'CM19'

This analysis is limited to properties whose postcode starts with "CM19", this is also called the postcode district. There are no official postcode district names so I've just labelled it CM19, Harlow. It is shown in red on the map below.

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Price per square metre

Knowing the average house price in CM19 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, 128, Taylifers, Harlow, CM19 5RG sold for £400,000. Given the internal area of 94 square metres recorded on the EPC, the price per sqm is £400,000 ÷ 94 sqm = £4,255.

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 CM19 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 CM19

The chart above is called a histogram, it helps you see the distribution of house price per sqm in CM19 To make this chart we put all the sales data into a series of £ per sqm 'buckets' (e.g. £3,800 to £4,000, £4,000 to £4,200, £4,200 to £4,400 etc...) we then count the number of sales with within in each bucket and plot the results. The histogram is based on 343 sales that took place in CM19, 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 CM19, Harlow. Notably, only 25% of properties that sold recently were valued at more than £4,540 sqm. For anything to be valued more than this means it has to be more desireable than the clear majority of CM19 homes.

Box plot of £ per sqm for CM19

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. Harlow. The chart above shows a boxplot for 'CM19' as well as the 'CM' 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 'CM19' is £3,940.
  • 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 343 transactions in CM19, Harlow half were sold for between £3,500 and £4,540 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; 343 for CM19, Harlow.

    • Property price map for Harlow

    Have a look at the interactive price map I created for myself. Use it to explore 'CM19' house prices all the way down to individual property plots.

    Property price heatmap for Harlow
    House price map for Harlow

    Will CM19 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 CM19 (Harlow) compared with the wider postcode area 'CM'. You can extrapolate from this based on your own views on future interest rates, inflation and other factors.

    House price index for CM19

    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 'CM19' property prices over the last 20 years. The index is calculated from the average price paid per sqm for property in CM19 and is set to 100 in 2004. The chart compares trends for CM19, Harlow against those of the broader postcode area 'CM'. 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 Harlow 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 CM19
    CM area CM19 district
    Nominal Real Nominal Real
    20 yr per annum 3.4% 0.7% 3.5% 0.8%
    20 yr total 93.3% 14.5% 98.4% 17.5%
    10 yr per annum 3.8% 1.0% 4.2% 1.3%
    10 yr total 44.8% 9.9% 50.4% 14.2%
    5 yr per annum 2.2% -1.8% 2.5% -1.5%
    5 yr total 11.6% -8.6% 13.2% -7.3%
    1 yr per annum -1.9% -5.9% -1.4% -5.3%
    1 yr total -1.9% -5.9% -1.4% -5.3%

    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, CM area have seen a 0.7% annual change when adjusted for inflation. This translates to a total change of 14.5% in real terms.
    • Over the past 5 years, CM area have seen a -1.8% annual change when adjusted for inflation. This translates to a total change of -8.6% in real terms.

    Most recent CM19 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
    Tithelands, , CM19 5N 87 sqm £3,446 27
    Sycamore Field, , CM19 5R 73 sqm £3,475 24
    Collins Meadow, , CM19 4E 98 sqm £3,774 24
    Northbrooks, , CM19 4D 79 sqm £3,375 23
    Church End, , CM19 5P 74 sqm £3,613 23
    Milwards, , CM19 4S 77 sqm £2,876 22
    Peacocks, , CM19 5N 58 sqm £4,354 21
    Jerounds, , CM19 4H 77 sqm £4,422 20

    Search for your street here.

    Nearby geographies

    The table below shows how 'CM19' compares to the other postcode districts nearby 'CM19'.

    District Lower quartile Median Upper quartile Sales in last 2yr
    SG12 Ware £4,460 sqm £5,090 sqm £5,880 sqm 641
    EN9 Waltham Abbey £4,270 sqm £4,800 sqm £5,410 sqm 478
    EN11 Hoddesdon £4,060 sqm £4,670 sqm £5,230 sqm 500
    CM9 Heybridge £3,600 sqm £4,210 sqm £4,790 sqm 813
    CM8 Witham £3,380 sqm £3,880 sqm £4,520 sqm 990
    CM77 Great Notley £3,740 sqm £4,200 sqm £4,700 sqm 316
    CM7 Braintree £3,270 sqm £3,860 sqm £4,420 sqm 1,187
    CM6 Dunmow £3,780 sqm £4,360 sqm £4,940 sqm 759
    CM5 Ongar £4,350 sqm £5,030 sqm £5,850 sqm 223
    CM4 Ingatestone £4,920 sqm £5,630 sqm £6,730 sqm 229

    Raw data

    Our analysis of CM19 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
    128, Taylifers, £400,000
    Sep-2024
    		 94 4,255
    Promina, 1a, Burnett Park, £705,000
    Sep-2024
    		 186 3,790
    141, Mallows Green, £198,000
    Sep-2024
    		 59 3,355

    See the entire list of all sales in CM19 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.