House prices in IG7 (Chigwell)

This article shows price per square metre data and various charts to help you understand the housing market in IG7 - stats were last calculated on 16 October 2024.

Defining 'IG7'

This analysis is limited to properties whose postcode starts with "IG7", this is also called the postcode district. There are no official postcode district names so I've just labelled it IG7, Chigwell. It is shown in red on the map below.

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Price per square metre

Knowing the average house price in IG7 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 July 2024, 4 Radley Court, Fairview Drive, Chigwell, IG7 6HT sold for £295,000. Given the internal area of 59 square metres recorded on the EPC, the price per sqm is £295,000 ÷ 59 sqm = £5,000.

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 IG7 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 IG7

The chart above is called a histogram, it helps you see the distribution of house price per sqm in IG7 To make this chart we put all the sales data into a series of £ per sqm 'buckets' (e.g. £5,700 to £6,000, £6,000 to £6,300, £6,300 to £6,600 etc...) we then count the number of sales with within in each bucket and plot the results. The histogram is based on 354 sales that took place in IG7, 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 IG7, Chigwell. Notably, only 25% of properties that sold recently were valued at more than £6,370 sqm. For anything to be valued more than this means it has to be more desireable than the clear majority of IG7 homes.

Box plot of £ per sqm for IG7

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. Chigwell. The chart above shows a boxplot for 'IG7' as well as the 'IG' 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 'IG7' is £5,510.
  • 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 354 transactions in IG7, Chigwell half were sold for between £4,730 and £6,370 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; 354 for IG7, Chigwell.

    • Property price map for Chigwell

    Have a look at the interactive price map I created for myself. Use it to explore 'IG7' house prices all the way down to individual property plots.

    Property price heatmap for Chigwell
    House price map for Chigwell

    Will IG7 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 IG7 (Chigwell) compared with the wider postcode area 'IG'. You can extrapolate from this based on your own views on future interest rates, inflation and other factors.

    House price index for IG7

    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 'IG7' property prices over the last 20 years. The index is calculated from the average price paid per sqm for property in IG7 and is set to 100 in 2004. The chart compares trends for IG7, Chigwell against those of the broader postcode area 'IG'. 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 Epping Forest 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 IG7
    IG area IG7 district
    Nominal Real Nominal Real
    20 yr per annum 3.7% 1.1% 3.9% 1.2%
    20 yr total 108.5% 23.5% 116.1% 28.0%
    10 yr per annum 3.7% 0.9% 3.2% 0.4%
    10 yr total 44.4% 9.7% 37.6% 4.5%
    5 yr per annum 2.0% -2.0% 2.5% -1.5%
    5 yr total 10.3% -9.7% 13.3% -7.3%
    1 yr per annum -0.1% -4.1% -3.4% -7.3%
    1 yr total -0.1% -4.1% -3.4% -7.3%

    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, IG area have seen a 1.1% annual change when adjusted for inflation. This translates to a total change of 23.5% in real terms.
    • Over the past 5 years, IG7 district have seen a -1.5% annual change when adjusted for inflation. This translates to a total change of -7.3% in real terms.

    Most recent IG7 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
    Long Green, , IG7 4J 74 sqm £4,817 23
    Brocket Way, , IG7 4L 85 sqm £4,649 20
    Hazelwood Park Close, , IG7 4J 55 sqm £6,399 16
    Arrowsmith Road, , IG7 4P 86 sqm £4,835 16
    Retreat Way, , IG7 6E 82 sqm £5,261 15
    Brocket Way, , IG7 4E 95 sqm £5,016 14
    Trotwood, , IG7 5J 52 sqm £4,764 13
    Lechmere Avenue, , IG7 5E 105 sqm £6,446 13

    Search for your street here.

    Nearby geographies

    The table below shows how 'IG7' compares to the other postcode districts nearby 'IG7'.

    District Lower quartile Median Upper quartile Sales in last 2yr
    RM6 Romford £4,300 sqm £4,910 sqm £5,560 sqm 483
    RM5 Romford £4,220 sqm £4,750 sqm £5,390 sqm 348
    RM4 Abridge £4,800 sqm £5,440 sqm £6,900 sqm 88
    IG9 Buckhurst Hill £5,260 sqm £6,250 sqm £7,260 sqm 301
    IG8 Woodford Green £5,200 sqm £5,980 sqm £6,880 sqm 703
    IG7 Chigwell £4,730 sqm £5,510 sqm £6,370 sqm 354
    IG6 Ilford £4,600 sqm £5,380 sqm £6,070 sqm 428
    IG5 Ilford £4,460 sqm £5,250 sqm £6,000 sqm 212
    IG4 Ilford £4,060 sqm £5,150 sqm £5,850 sqm 122
    IG3 Ilford £4,240 sqm £4,820 sqm £5,400 sqm 355

    Raw data

    Our analysis of IG7 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
    4 Radley Court, Fairview Drive, £295,000
    Jul-2024
    		 59 5,000
    74, Trotwood, £160,000
    Jul-2024
    		 51 3,137
    56, Hazelwood Park Close, £400,000
    Jun-2024
    		 56 7,142

    See the entire list of all sales in IG7 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.