A scientific method to compare the value of suburbs

Some people base their buying decisions on an area's capital growth performance.

While this might work in the early stages of a boom, it is only in hindsight that people pick this. Above average performance is often not sustained (ie revert to mean), sales data is imperfect, there are significant time lags and the poor reputation of a suburb can conceal value.

The basic definition of value is what you get compared to what you pay.

As investors who want to make money (or at least preserve asset value) under all market conditions buying value increases the chance of success and reduces risk.

COMPARING FOR VALUE

The simplest method of assessing value is making comparisons. Buyers do this all the time.

1. Eg property A might be a similar home in the same area as property B but is $30k cheaper, so represents better value.

2. Or suburb A offers all the facilities of nearby suburb B and has similar housing stock but is on average $30k cheaper so may represent better value.

SUCH A THING AS AN $X VALUE SUBURB

Let's ignore housing stock and talk about a suburb's amenity, ie 2. above only. And let's suppose we can reduce that amenity to a single dollar amount so suburbs can be readily compared.

I believe there are such things as $200k suburbs, $400k suburbs and $800k suburbs.

An $800k suburb will obviously have more amenity and appeal than the average $400k suburb, which in turn will be 'better' than a $200k suburb.

One could use median house prices as an anchor to guage this, but this merely deals with tho status quo of existing house prices which are socially-determined. It does not deal with incontestible facts. Also an enclave of newish townhouses (asking $300k) in a $200k suburb does not change the fact that it's a cheap suburb with $200k facilities.

I am of the view that it is possible to use facts to determine if a suburb is a $200k, $400k or $800k. These can be found by looking at a small number of things that accounts for most of the differences between suburb value.

Equipped with this it is possible to compare this to house prices in the area. After allowing for property-specific factors like a discount for units (lower land value) or hovels (repairs needed), it should be possible to define value as being a property bought for less than the suburb's value.

DETERMINANTS OF SUBURB VALUE

The three biggest factors (in Melbourne) that seem to explain a suburb's value are:

a. Proximity to the CBD

b. Proximity to water (bay or river)

c. Tree cover (tree size or rainfall)

If you were told only these factors about a suburb then it should not be too hard to predict its value within (maybe) 20-30% in many cases. Tree cover was included to build in a skew to the eastern suburbs versus the north and west.

To make the assessment finer some lesser order factors are needed. I would suggest:

d. Prestige state or private schools (0, 1 or >1)

e. Transport (bus, frequent bus/tram or rail)

f. Other local facilities including shopping and recreation

SCALES AND WEIGHTINGS

The next thing is to assign a scale to each - say 0 to 5.

Then a weighting to each, noting that the first three have the highest weighting (weighting factor = y which might be 2) and the second three have lower weighting (weighting factor = z which might be 1). Including these would aid accuracy - maybe 10-20%, but in the end you need a single dollar answer for each suburb (or precinct of suburb).

x is a final factor to standardise to a reasonable price. It doesn't matter what it is but it must be the same across all suburbs.

Suburb Value might equal x(y(a + b + c) + z(d + e + f))

Fine tuning would involve a weighting factor for each variable - eg proxmity to the city might be more significant than tree cover.

It is emphasised again that this is 'suburb value' not 'house price' in that suburb.

The former needs to be adjusted for things like building size, quality, land area etc to get a reasonable 'fair house price' estimate.

USE

The main utility of this is to identify suburbs that are high amenity (based on the above six factors) but comparatively cheap so represent good value. Conversely it might indentify expensive suburbs that are low amenity so are best avoided.

The market is imperfect so amenity might not always be factored into prices and that creates opportunities as the market 'discovers' the amenity/value (you knew when you bought thanks to an assessment like the above) and pushes prices higher.

Some examples may follow - if I can be bothered as this post is too long already!
 
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As a newbie waiting to go into the market it is really insightful and nodding my head as reading ur post Spiderman, still abit vague to me though so plz keep the examples coming:D
 
Great post spiderman, your formular has the makings for a useful spreadsheet/program:p kudo's to you.
 
Thanks for sharing Spiderman. I'm going to re-read your post a couple of times to grasp all that you've raised. Some interesting perspectives there.
 
I'm not as scientific about it, but the exact process you describe is how I decide which areas I'm going to look at for my next investment. I look for apparent anomalies in price and amenity. If suburb X and suburb Y are adjacent, and suburb X costs twice what suburb Y does, then if it's not "twice as good", I predict people will be more likely to buy in suburb Y, and thus prices in Y will go up.

Many recommend using historic price growth... I actually use this as like an "inverse" indicator of where to invest. If an area's had above-average growth for a long time, unless it's substantially changed it's amenity, I predict below-average growth for a long time - due to reversion to the mean. Conversely, if an area's under-performed for a long time, but still has the same relative level of amenity as it used to, then it's likely to do better than average in the next 5 or 10 years.

I'm interested to see how your thinking evolves, Spiderman. :)
 
This is a bit like do you give a man a fish or teach him to fish.

You can look at all the suggestions on where to buy in this section of the forum and be a sheep or you can use an accurate analysis like this one and do y our own thinking.

So thanks for your ideas on how to analyse suburbs.
 
In many respects Spider, all those questions have already been answered by the people who live in the burb of interest.

Which is why a suburb's demographic profile is such a meaningful piece of data.

Combine that with the town plan 1-10 years out, and you have a lot of info..
 
In many respects Spider, all those questions have already been answered by the people who live in the burb of interest.

While it is true that homebuyers may shop around and compare suburbs but compared to we investors their criteria are different and are often not financially-based.

Eg family or work are close by, they know people in the area, they want a child to go to a particular school, it's in the same corridor as they grew up, a certain affordability constraint or they just like a particular house.

These are all legitimate reasons to choose a home to live but don't realy apply to investors who have different criteria and wider choice of properties to buy (typically city-wide, but sometimes nation-wide).

Combine that with the town plan 1-10 years out, and you have a lot of info..

While it is good to look into the future and studying plans can assist this, it should be realised that town plans are drawn up by planners (government bureaucrats) and they go through various fashions.

These fashions are like a virus that sweep through planners of a particular generation. Hence plans for widely different cities have more similarities than differences.

Eg when cars became popular much city planning was concerned with knocking down buildings, accommodating parking and improving traffic flow. Dirty industry was moved away, railways were pulled up, light industrial uses went off into new estates and housing suburbanised. Zoning was the rule and land uses became more segregated by the new controlled-access highways, roundabouts and freeways built by traffic engineers.

Later on it was realised vibrant town centres require a density of activity that could not be accommodated through roads and parking alone. Commercially productive and dense centres imply high land values and efficient land use. Cities that were only offices and parking lots were seen as boring, dead and unsafe at night.

To make city and suburban centres alive and safe at all hours many plans now encourage inner-city living. They see a diverse city that contains other than daytime shopping and becomes a destination due to arts, theatre, a waterfront and recreation etc. Plans for major suburban centres often advocate a more urban style with better public transport, pedestrian amenity and more jobs and offices so more people can work locally rather than commuting to the CBD. Suburbs near a river or beach often try to make their centres address these features, typically by developing the waterfront or having a wide pedestrian, cafe and shopping boulevard to or along the beach (preferably to the old harbour or new marina). High amenity suburbs near facilities were seen as ideal locations for higher living densities, particularly where there is an ageing population and changing household structures.

The above paragraph is currently popular. Find a plan for any Australian city or major suburban subcentre and you are guaranteed to find elements of the above in any of them.

The other issues is capability of government who draws up the plans, but without private capital that puts up most of the buildings, has only limited ability to make it happen. Governments often flip-flop on major infrastructure that are needed to make a plan work and can't be trusted that much, for instance the NSW government and 'metro' lines.

Hence it's worthwhile looking at future plans, but they're a dime a dozen and a decision to invest in a suburb should still stack up even if the plans don't come to fruition.
 
If suburb X and suburb Y are adjacent, and suburb X costs twice what suburb Y does, then if it's not "twice as good", I predict people will be more likely to buy in suburb Y, and thus prices in Y will go up.

We are looking at this right now. Looking at buying land....building...living as PPOR and selling. In the last 2 weeks we have found that the "sheeple perception" is also worth factoring in. We can buy land in suburb X or Y (only about 10km's apart) for the excact same price..build the same price.. but the return between suburb X and Y has a difference of around 30% (based on what is currently for sale matching land size and similar house)
 
Agree with the 200k , 400k 800k suburbs, noticing their are 800k suburbs in a few localities, within a region, next burb accross or down are the 400k burbs, and then the 200k's in order,
ACT have alot of trees and little water, veiws are one or the inportent features in this town.
I like to target 300k homes in a 400k area, and value add to a quality that is similar to anything in the next suburb, being of value to 800k.
ps
Would you also see Australia as an 800k area, as i do! in comparison to the rest of the world,
 
I like your approach Spiderman, as an engineer I too like to try and break things down in an objective, formulaic way.

One comment I would have is that with your weighting factors, be careful that you don't end up 'curve-fitting' the formula to your pre-existing assumptions about a suburb, otherwise the formula may appear to fit for suburbs you are familiar with but not be effective when you apply it to other suburbs.

Cheers
Nick
 
I like your approach Spiderman, as an engineer I too like to try and break things down in an objective, formulaic way.

One comment I would have is that with your weighting factors, be careful that you don't end up 'curve-fitting' the formula to your pre-existing assumptions about a suburb, otherwise the formula may appear to fit for suburbs you are familiar with but not be effective when you apply it to other suburbs.

Yep, that's the main downfall of the approach as well as how it works over time as fashions change.

Plus the value attached to certain traits like proximity to water or the CBD are not constant. Eg at one time inner-city suburbs like Richmond or Collingwood were scummy low-rent areas as people prefer to leap over them to 'garden suburbs' further out.

Much more recently we've seen the same thing with new homebuyers skipping over cheap Noble Park or Doveton, preferring to go way out to Narre Warren instead. Ditto with Braybrook/Sunshine/St Albans versus the shiny boxes of Sydenham, Derrimut or Hillside.

But eventually the closer-in 'hole' suburbs seem to pick up despite the terribly low incomes, the demographics and their reputation.
 
Without sounding like a racist or biggot do you look at what percentage of different nationalities and religions live in certain areas? For instance Springvale & Noble Park arn't in too bad a location but have problems with ethnic gangs.

BV, I'm broadly aware of the demographics of suburbs, but I'm not sure that factoring it in is going to improve accuracy or be useful.

This is for several reasons:

1. What measure does one use? If one is worried about crime or 'gangs', there's much more correlation between crime and crime statistics than ethnicity. So why not use crime stats? Or even unemployment rates, educational attainment, health statistics if one wanted to guage how 'disadvantaged' an area is (others have already done this).

2. Even if one did the above, it is only useful in describing suburbs as they are. To a large extent this is reflected in existing prices. Since my formula aims to identify high-amenity areas that are relatively cheap (and low amenity areas that are overpriced) putting something like this in the formula would just reinforce existing beliefs about an area and dilute the formula's ability to uncover unrecognised value.

3. Demographics of migrants are diverse and include refugees (with comparatively little money), family reunion (who have established family here) and skilled or business migrants (who might have to bring a certain amount of money in). Some established migrant groups have average or better incomes and are growing faster in number than the general population. These people may wish to live near family so their demand could actually be supporting house prices and contribute to future capital growth. Conversely there exist low socio-economic suburbs that are home to new migrants (often refugees) and poor Australian-born but are going backwards since the first thing that successful migrants when they get a good job is move out.

4. I don't think there is even much evidence that your 'gang suburbs' like Springvale or Noble Park have appreciated slower than other areas. Even places like Dandenong or Sunshine haven't done too badly. Plus, where the area is well-located with many facilities (like Brunswick or Coburg) gentrification can take place. Yet at one time those areas didn't have the highest of reputations.

5. While only anecdotal, a resident of Noble Park North (who likes it) mentioned that he thought that migrants there typically wanted to better themselves through work and study. This compares to Aussie 'ferals' in places like Frankston North or Moe that were in a cycle of welfare dependency.

So in conclusion, demographics are interesting, but it's difficult to plug them into some sort of objective 'area value and amenity' formula.
 
That you can "scientifically" work out which suburbs will boom more than others is mainly a delusion.
Just like working out which stocks will go higher than others.

In NOV 07 API had a special with the "100 Top spots... tipped for best capital growth over 12 mths".
Here's a few of the picks predited to boom:

Allanson WA: predicted 32.9%, med07=347, med08=222, med09= 282

Ashby WA: predicted 34.3%, med07=450, med08=435, med09= 454

Ball Bay Qld: predicted 35.2%, med07=385, med08=320, med09= 300

Bertram WA: predicted 32.2%, med07=397, med08=375, med09= 370

Blanchetown SA: predicted 35%, med07=125, med08=130, med09= 117

Butler WA: predicted 36.6%, med07=455, med08=430, med09= 403

Capella Qld: predicted 32%, med07=275, med08=305, med09= 340

Djugun WA: predicted 55.4%, med07=590, med08=662, med09= 605

Dysart Qld: predicted 46.5%, med07=322, med08=380, med09= 420

Grantville Vic: predicted 35.7%, med07=180, med08=194, med09= 217

Hammond Park WA: predicted 49.5%, med07=480, med08=471, med09= 410

Keppel Sands Qld: predicted 32.6%, med07=353, med08=471, med09= 410

Annandale NSW : med07=750, med08=750, med09= 759

Campbelltown NSW: med07=255, med08=245, med09=257

They may be experts who believe they are using scientific methods, but RE obviously is'nt their area of expertise.
 
That you can "scientifically" work out which suburbs will boom more than others is mainly a delusion.
Just like working out which stocks will go higher than others.

I agree. Too much is made of terms like 'boom suburbs', 'hot spots' or 'top 100' in magazines like API, presumably to excite readers, appeal to their greed and sell more copies.

This thread though is boringly different. Instead it's about buying well while accepting uncertainty and reducing risk, as follows:

As investors who want to make money (or at least preserve asset value) under all market conditions buying value increases the chance of success and reduces risk.

We know the 'money' part reasonably from asking and selling prices for a property or suburb.

But what is less certain is what you get, especially when it comes to drawing comparisons. An approach to roughly calculate this (for Melbourne) from verifiable facts has been proposed, with only some numbers and multipliers needed to make it testable.

Combine the two and you get value and can assess different areas for possible investment suitability.
 
I think Spider's info and criteria help in stacking the odds in our favour as investors. Our vehicle is property. As Piston Broke mentioned the analogy of trying to work out which stocks will go higher than others in the stock market is likened to delusion.....our influence as individual investors/traders over market direction is nil......as a herd, well that's another matter :p

We do however endeavour to stack the odds in our favour as investing in shares is at the end of the day a probability game. Whilst there is some applicability of this notion to direct property, the fact that it is less liquid as an asset class and hence using some criteria to rank suburbs and properties in our own mind (not necessarily Spiderman's, although they are logical and fairly comprehensive) assists in stacking the odds in our favour also. Being less liquid and with higher enrty and exit fees to transact, property needs some type of logical analysis, whether weighted or not and obviously with subjectivity involved as each persons scroring will be different to anothers. As long as the same person rates the various properties some uniformity may ensue........subjective quantification ;)

I've enjoyed this thread and the responses.
 
Yep, that's the main downfall of the approach as well as how it works over time as fashions change.

Plus the value attached to certain traits like proximity to water or the CBD are not constant. Eg at one time inner-city suburbs like Richmond or Collingwood were scummy low-rent areas as people prefer to leap over them to 'garden suburbs' further out.

Much more recently we've seen the same thing with new homebuyers skipping over cheap Noble Park or Doveton, preferring to go way out to Narre Warren instead. Ditto with Braybrook/Sunshine/St Albans versus the shiny boxes of Sydenham, Derrimut or Hillside.

But eventually the closer-in 'hole' suburbs seem to pick up despite the terribly low incomes, the demographics and their reputation.

I guess the trick is to have a model that takes in all of the various influences.

Another curve ball is retirement hotspots like Rosebud.

Terry Ryders 'hotspot creator categories' might be a good place to check for these variables. But I suppose if you were going to use those variables you might as well pay him $90 for his reports.

I think the more restricted you made it the more accurate you would be. Focus just on metro areas for example rather than statewide, or had a formula for picking the next best holiday house spot (not that that's an area I'd invest in).

Maybe a good place to look is also to see what areas have done well in the past and work out why. Then look for those areas with those 'whys' yet are still good value.

Time in the market will smooth all this out, but if you can get an extra few % earlier on in your journey this can have a multiplier effect at the end. The other question is is this better achieved through the more well trodden path of doing value adds?

Other option is you could just choose places in metro Melbourne with higher yield, not only does this reduce risk from a cashflow perspective and enable you to duplicate this way it may also highlight small value gaps in the market. Renters are indicating there is good amenity in the area, although that may just indicate the place is a good 'short term' place to live like a mining town or CBD apartment. I wonder if there is anything in this?

Very interesting stuff, if anyone can put out a 'value finder' model like this it would be SS.
 
I guess the trick is to have a model that takes in all of the various influences.

Another curve ball is retirement hotspots like Rosebud.

The worry I have with retirement places is it's one-shot. You'll get one good cycle, but long term you'll have a high proportion of 'urgent' sales due to deceased estates or relocations to nursing homes. Admittedly prices will be supported by people selling up and buying in places like Rosebud, but that's pretty much it.

I'm taking a guess here, but many (not all) retired residents have neither the budget nor the inclination to value-add their homes. And as they're not working their incomes are often fixed and aren't growing. This limits what they can spend in the local shops and restricts commercial development and jobs in the area.

I would suggest that a decent cohort of working people is desirable for a suburb to grow. Now it might be that some suburbs regenerate with younger working people on good incomes moving in to replace those who die.

This has certainly happened in some inner suburban areas and even as far out as Mandurah (WA) with its high-speed rail link to Perth. However remote retirement areas away from jobs are unlikely to attract this demographic, and I'd be cautious about expecting above average long-term capital growth from such areas (though there might be other opportunities, eg trailer parks!).

I think the more restricted you made it the more accurate you would be. Focus just on metro areas for example rather than statewide, or had a formula for picking the next best holiday house spot (not that that's an area I'd invest in).

Agreed. I've kept mine to Melbourne.

Maybe a good place to look is also to see what areas have done well in the past and work out why. Then look for those areas with those 'whys' yet are still good value.

I like this :)

Time in the market will smooth all this out, but if you can get an extra few % earlier on in your journey this can have a multiplier effect at the end. The other question is is this better achieved through the more well trodden path of doing value adds?

The beauty is it's not either/or - one can do both.

There's an old post about 'five percenters' which is based on doing several things (eg value area, good negotiating, value-adding) that alone might generate a modest 5% increase in value over amount paid, but added together give a good increase.

Other option is you could just choose places in metro Melbourne with higher yield, not only does this reduce risk from a cashflow perspective and enable you to duplicate this way it may also highlight small value gaps in the market. Renters are indicating there is good amenity in the area, although that may just indicate the place is a good 'short term' place to live like a mining town or CBD apartment. I wonder if there is anything in this?

I think you're onto something.

While suburban comparisons of houses prices are frequently in the papers (as big lift outs), when was the last time you saw something similar for rents (except as a story on a 'rental crisis')? The yield stats in API are probably a reasonable place to start, but to do it properly you need to do like for like comparisons (eg the 'average house for rent' might be different to the 'average house sold', so stats could be misleading).
 
Part II: Calculation of ratings for each factor

Thanks for all the nice comments and PMs.

...to continue from the first post....

With the basic formula described, next thing is how to do the ratings.

I'm not precise enough to reduce quite complex differences between areas to a fine scale like a percentage score or number of out 10. So instead I went with a 0-4 scale, with 4 being best and 0 being worst. 5 possible shades is enough!

Scoring guides for each factor are:

* Proximity to CBD

2–5km = 4, 5-10 = 3, 10-20 = 2, 20-30 = 1, >30 = 0

* Proximity to water

<0.5km beach or river = 4, 0.5-1km beach or river =3, 1-3km beach or river = 2, 3-10km beach=1, >10km beach=0. Lessen for smaller rivers.

* Tree cover

Dense tree cover = 4, Medium tree cover = 2, No trees = 0.

* Prestige schools

2 or more = 4, 1 = 2 (within 2km)

* Transport

<1km multiple train+tram=4, <1km Train=3, <1km tram=2, <2km train or good bus=1, regular bus=0

* Local facilities

<2km supermarket+shops+library+park=4, <2km 3 of above=3, <2km 2 of above=2, <2km 1 of above=1

For simplicity I did not weight any factors and all six are equal status when added. The maximum possible score is a 4/4 for each of the six factors, or 24 out of 24.

A million dollar suburb is pretty swish so the above score is multiplied by $40k to come up with a 'suburb value'. This puts a ceiling of a bit under $1m, but this doesn't matter as this method is only intended for ordinary mainstream suburbs.

Results range from under $200k to over $800k for various Melbourne suburbs. While of a similar magnitude to house prices, it is not to be confused with them. It's purely a figure of merit for suburbs and makes no assumptions about housing stock, character or heritage value.
 
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