I'm Jeremy Sheepard. >> And I'm Daniel. >> We use data to expose deceitful property experts and their marketing BS. >> This is the expert busting series. >> Welcome to episode 5 of the expert busting series, proximity to the CBD. Let's dive in.
Yeah, you may have heard some property investment professionals tell you that the closer you are to the CBD, the more capital growth you can expect. But historical data actually refutes that. And we'll go through uh some examples and explain why that's the case. And at the end, we might even show you some suggestions as to why it's actually worse to buy closer to the CBD. >> Flawed past research. >> Yeah.
So you may have seen some halfbaked research and reports in the past that uh suggested there is some relationship between higher growth and proximity to CBD. Uh but everyone that at least everyone that I've seen of those reports has been flawed in at least one major way. And these uh some of the reasons they've either chosen a a short time frame or a single time frame that pops up quite a lot or they've had ridiculously small sample sizes or simply a poor research methodology. The thing is there has been some research on this topic and unfortunately that misleads people further if that research hasn't been done appropriately >> and I believe a lot of firms would move their clients into these markets close to the CBD because they're it's in their post code that's where their office is. >> Certainly makes it easier if it's close to the office, doesn't it? Yeah.
>> Brings in more revenue, more turnover. Why would you go anywhere else? >> Yeah, that's the other thing. You've got the same suburbs. They're still close to the CBD. They haven't moved further away, have they?
All right. So, this first report uh that I want to debunk is from the Australian Housing Urban Research Institute or abbreviated as AHI. So, I'm just going to call them Ahuri. So, you may have seen this image before. Uh by the way, apologies to those uh listeners on audio only. Uh you'll have to check out uh the YouTube version of this presentation.
There are some great illustrations. So this is a map of Melbourne and it shows uh housing expansion corridors to the west, the north, the east, southeast and south. So Ahuri examined the growth of about 30 suburbs in Melbourne, splitting the group up into these five corridors. So straight away I can see some problems with uh with this analysis. Firstly, they've chosen only 30 suburbs in a city that has around 400. So the analysis doesn't even cover 10% of the city.
So what are the chances that the behavior of this 7.5% also reflects the behavior of the remaining 92.5%. Secondly, they have arbitrarily chosen specific corridors rather than a broader spread. And thirdly, along each cor corridor, they have again arbitrarily chosen certain suburbs uh that don't look to be evenly spaced out. So in the western corridor, for example, they chose Foots Gray, Sunshine, Deer Park, and Melton. Uh and then they they compared the growth of these suburbs. And that's the uh the next chart.
And >> before we move on, Jez, so that's good. But the when was this done by Uhuri? Do you remember the date? Uh well, it would have been around about 200. It could have been 2008 because that's the date they show on their charts, which is the next slide. >> There hasn't been anything more up to date than that.
>> Uh no. >> Okay. I wonder why that is. >> Uh well, it could have been a one-off. They might have been asked by uh government. It could have been a topic at the time then.
I I don't know what the reason was. >> And and I think I like your point. You don't want to just look at these small sample sizes or cherrypicked suburbs. You want to look at every suburb. >> Yeah, there's no reason why you can't look at every suburb. Increase the sample size, but bear in mind this was done back in the day where analysis and data wasn't uh what it is up to today.
So, >> I think they can be excused for this. Uh it's and it's something that you you wouldn't know unless you've had a lot of experience in data analysis on this specific topic what the issues are. So, I'm not pointing my finger at him. I think that they did some research and that's better than none. What we hear of far too often in the in this industry is just opinion. So, you know, hats off at least for doing some research.
All right. So, uh this is the chart that I'm uh talking about and it compares the growth of the four suburbs in the western corridor. So, you'll see the title of the chart there, Melbourne Western Corridor. >> So, we're looking at Footsgay, Sunshine, Deer Park, and Melton. >> Yeah. But you have a look at that horizontal axis where they are all listed.
>> And it's a bit of a bogus axis because each one of those four suburbs, although it's further from the CBD than the other, there are many suburbs along that corridor than just these four. So why only look at these four? Uh so that's the first thing. But look at the distance between each suburb. >> It's inconsistent. There there are 5 kilometers between the CBD and Foots gray but 7 kilometers between Foots Gray and Sunshine and then 5 km between Sunshine and Deer Park and then 18 km between Deer Park and Melton.
So your eyes are thinking that this is an even sort of scale uh because you've got a line you got three lines on the chart but really they should be just um there should be columns bars on the chart because that scale that horizontal scale is misleading. It looks as if there is an even gap between them on the chart but the kilometers differ. Uh so yeah why wasn't an even gap between suburbs chosen? uh you know at the very least they could have made the gap on the chart between the suburbs reflect their distance from the CBD. Uh instead they appear on the chart to be evenly placed and that um that is misleading. Uh and that makes the curves on the chart misleading.
Uh the bottom curve that's the pale pink one uh that shows the house price for each suburb at the start of the period of analysis which is 1981. And you can see that all four suburbs were around 150,000. The left vertical axis shows how expensive these markets were back in 1981. And the top curve that shows uh the house price at the end of the period of analysis, which is 2008. And you see that foot gray was the most expensive at 450,000 and Melton the cheapest at around 220,000. And there's a dotted line that shows the total growth for each suburb for the 27 uh 27-year period analyzed.
So that's from 1981 to 2008. So over on the right hand side, you'll see that there's uh a a scale there. So in the bottom left of the chart, you can see the Foots Gray house prices started out in 1981 at around 80,000. And if you look to the top left, you can see the foots gray house prices had grown to 450,000 by 2008. >> Is this from a huri or is this your analysis? >> This is from a hurry.
This is a hurri's chart. Yeah. So you see in the bottom right hand corner I've mentioned source hurri.edu.au. Uh you can go there and and see if you can find this yourself. All right. So Foots Gray is close to the CBD and is therefore on the left of the chart.
At the opposite end of the chart on the far right is Melton, 35 kilometers from the CBD. Melton started off with house prices around 110,000. That's back in 1981. That's the bottom right. And then prices only grew to around 220,000 by 2008. That's a growth of only around 100% if you follow the dotted line there that uh that growth curve.
So the important curve on the chart is actually that dotted line showing the percentage increase in values for each of the four suburbs that a hurri uh picked out. So the dotted line shows uh very high percentage increase in the price of properties in Footsgrave close to the CBD and that dotted line drops as we head further from the CBD to the suburbs towards the right of the chart. Uh the other curves can be a bit confusing. So if you just focus on that dotted line, that's the one that tells the story. But this is the chart that that Ahuri published. And the story that Ahuri was reporting was that the closer you are to CBD, the more growth you get.
Uh the dotted line is meant to show that there's a trend of decreasing growth rates the further you are away from the CBD. And it looks quite dramatic, but that slope has been exaggerated by the fault that I mentioned before with the horizontal scale. Melton is actually twice as far from the CBD as Deer Park. But that's but there's virtually no difference in their growth rates. Uh and more importantly and you'll see this pop up in other reports. This was for a single period of time.
If they had analyzed multiple periods of time, they would have realized that this trend actually reverses. And to prove that this is true, I replicated their chart using the exact same suburbs that they chose, but for a different time frame. uh and if you go to the next slide demo uh so this is now not a hur's data now this is uh our chart I've tried to replicate the same sort of thing although there's you know a little bit of a styling difference there uh so this is including the flawed horizontal axis for consistency but this chart picks up where the Ahuri chart left off so it starts at 2008 this new chart shows the growth that each suburb had over the 17 years from 2008 to 2025, which is when we're recording this. So you can see Foots Gray has actually been the worst performer out of all the four, yet it was the closest to the CBD. So at the left of the turquoise curve, you can see the Foots Gray house prices started at around 450,000 in 2008. That's where they left off at the end of the Hur's chart.
And then if you run your eyes up vertically you can see the purple curve shows that Foots gray houses finished uh 2025 is it at nearly a million. Okay. So house prices in Foots gray more than doubled in that period. Uh according to the dotted line it was about 105% growth but the growth was even higher in the outer three suburbs. Melton on the far right had 157% growth. That's despite it being so much further from the CBD.
Now imagine you're an investor. You see this Ahuri report back in 2008 and you decide to invest in Foots Gray uh on the belief because it's close to the CBD it will outperform Sunshine, Deer Park and Melton because it's close to CBD. Well, yeah, over those next 15 years, um, you would have been disappointed because the other three suburbs have outperformed. >> I think a lot of investors wouldn't even question it. I've made 105%. Fantastic.
>> Yeah, that's right. And you get a lot of people at the end of a boom saying, "I've done fantastically well." And they may have actually underperformed the national growth rate. >> A big difference. That's like close to what, 60% difference. So if you purchased in Sunshine Deep Park or Melton back in 2008, you would have um done very well over that period. >> Yeah.
Well, you 50% of let's say it was a $500,000 property that you bought. I think that's where the prices were in Footsay. >> Mhm. >> Um so let's just round it up to half a mill. 50% of that is is quarter of a million dollars. So you've taken some advice and 15 years later you're worse off by quarter of a million dollars.
And the other thing to mention is also the yield. The yields would have been typically better in Sunshine Deer Park and Melton than Foots Gray. You would think >> I've got a chart on that uh towards the end, but that's just one corridor. So let's have a look at the next slide which shows another one of the Ahuri charts. >> So you'll see in the bottom right hand corner there, the source is auri.edu.au. Um the same period, but this is just the northern corridor.
Uh so this time there are six suburbs instead of four which again seems a bit arbitrary and again the spacing between each suburb is inconsistent uh and it's not increasing consistently. So the dotted line in this corridor well it's not quite perfect like with the prior corridor in this chart. Carlton is the closest suburb to the CBD but it didn't have the most growth over the 27year period. But the overall trend in the chart clearly suggests that suburbs closer to CBD are supposed to have better growth. But again, it's just one period of time. So the next chart, I repeated the the same sort of analysis, but for a different period of time.
So here are the same six suburbs for the 17 years following 2008. Uh you can ignore the turquoise uh and purple lines, just focus on the brown dotted line. uh it is a bit volatile but it doesn't trend towards the right which is what we would expect to see if the theory of CBD proximity was true. So if anything the trend looks like it might have reversed a bit. Uh the best performer was actually the second furthest from the CBD Mil Park and the worst performer was the one closest to the CBD. So investors using proximity to CBD to help them choose where to buy would have been disappointed over the the last 17 years.
All right, next corridor, Melbourne Eastern corridor. So again, this is a hurries eastern corridor chart consists of Richmond, Hawthorne, Campbell, Boxill, Mitchum, and Bazewater. And the dotted line trend suggests the same sort of story that the closer the suburb is to the CBD, the better the growth. However, replicating that again for the following period, 17 years since 2008, again suggests a reversal of that earlier trend. The best performing three suburbs were the furthest from the CBD. And the worst three uh were closest to the CBD.
Boxill, Mitchum, and Bazewater all outperformed Richmond, Hawthorne, and Campberwell for that 17-year period. All right, so I won't bore you with the charts for the other two corridors. They tell the same story. The trend of the first 27 years reverses in the next 17. And that's one of the traps for the inexperienced when it comes to this kind of analysis. And the next slide uh shows a summary of the flaws in this Ahuri report.
So the distance between the suburbs was inconsistent, making it unclear what the uh relationship was between distance to the CBD and capital growth. But it didn't matter anyway because there were other problems like choosing too few suburbs, only one CBD. It's just Melbourne. And uh most importantly, there's only one period of time over which capital growth was calculated. I showed a different period of time tells the reverse story. And that's the trap that I was talking about for inexperienced analysts in this field.
And the next slide helps to illustrate the correct way to conduct this kind of analysis. back to finish to finish up on that point just for everyone that's um listening >> and they're not looking at the the visuals but the other ones like the two few suburbs considered which you mentioned too few closer to the CBD only looking at one time frame and I think that's really important for investors because that's what a company will show you or a firm hey this is how we've performed but they're only looking potentially at one time frame and they're handpicking markets they've maybe invested in but then what time frame Do you view this from would it be from inception of every suburb like when the first dwelling got laid down into the ground? But that'd be impossible. How far back can you go? >> Even if you go right back uh in time, like if you could go back a 100 years, you would still have a flawed approach >> uh if you used a single time frame. and uh the the technique that's used in data science.
In fact, if you go to the next slide, it'll it'll show you this. Um so this is this is a technique called cross cross validation. Uh for example, you could have analyzed the 20-year period from 1981 to 2001 and then the 20-year period from 1982 to 2002, the 20-year period from 1983 to 2003, and so on. And that would give you eight 20-year samples for that period of time. >> So if you saw the same trend in every 20-year period, in all eight of those 20-year periods, then you could be confident that your conclusion is somewhat timeless working in any era era. But if you saw different conclusions depending on which 20-year period was analyzed, then it means the theory can't be relied upon.
there's obviously some bigger trend uh that might uh span across a 20-year period and that's exactly what happened and we often see in historical data the next day decade behaves the opposite of the prior decade u but a hury used only one time frame so the conclusion that they drew from that time frame well it simply didn't apply to the future but like I said before to be fair it was published back in 2008 data analysis come a long way since then uh and a hurry are in uh good company to get it wrong as the next report has two very big names. Uh so here's a report that's put together by um well you'll see the names in the bottom left. You may have heard of the Reserve Bank of Australia. Yeah. And Real Estate Institute of Australia. So one big plus for this report is that it looks at Australia's five largest cities instead of just a single city of Melbourne.
>> However, it has some uh some downsides. You'll notice at the top of the chart speaks of the inner and outer ring median prices. So instead of establishing like a per kilometer relationship between capital growth uh and distance from the CBD, what they've done here, they've they've chosen two very blunt categories, either inner ring or outer ring. Uh and this report includes far more suburbs than the Ahuri report, but the Ahuri report had a better spread of distance from the CBD. Uh now in some corridors, the Ahuri report had uh six six different suburbs, other corridors only four. Uh this RBA REIA report has clumped all suburbs into only two categories, inner or outer.
So what the chart's doing is it's uh comparing the median values of houses in the inner ring to the median values of houses in the outer ring and then it calculates the ratio between inner and outer ring suburb median house prices. So each bar is not a median sale price, it's a ratio between median sale prices. Uh you can see this ratio on the left vertical yaxis. For example, the leftmost red bar shows that inner suburbs in Sydney had twice the value of outer suburbs. And this is back in 2006. So the red is 2006, uh, blue is 2004.
And you can see the left vertical axis has the number two right next to that red bar. >> So that's Sydney was a million dollars. That medium price was a million dollars in the inner ring and then the outer ring was 500,000. That's just you divide the million divided by 500 and that gives you two. >> Exactly. >> So it's like two times more being in the inner ring compared to the outer rings.
>> Yeah. And we don't know where they set that that boundary that ring. >> Do we know? Oh, we don't know what the outer ring is classified. >> Uh and it's a little bit blunt. One good thing about the Uhuri report, it had a little bit more variety.
You know, four to six suburbs. Interestingly though, if you look at Sydney, Melbourne, Brisbane, Perth, Adelaide over that 2006 up to 2014, those inner ring markets outperformed or got a little bit more deer than all the outer rings. So, >> exactly. >> It would have been better to invest closer to the CBD through that period. Is that what I'm getting from this? >> Yes.
Yes. If you had this data available to you in 2006, but of course you couldn't. this had to be published after 2014. >> Uh you would have led to been led to the conclusion that the inner ring outperforms >> um but in 2014 uh see that blue bar. Well actually just stay on this chart for a bit. So I just want to highlight that blue bar for Sydney.
So that ratio is increased nearly 2.5%. So as you said uh it means that the inner suburbs of Sydney were nearly 2.5 times more expensive than outer suburbs at 2014. So 2016 they were only two twice as expensive as inner. Uh they've increased by the in the eight years that followed. So yeah like you said it's it's um better performance on the inner ring suburbs for this period. So if you see a blue bar that's taller than the red bar for a city, then it means that inner suburbs for that city had more growth than outer suburbs for the period of 2006 to 2014.
>> And as an investor, like you could go to a company, let's say, look, I'm starting my journey 2014. You go to a buyers agent, they show you this beautiful presentation. I'm buying close to the CBD. >> Yeah. Well, if you weren't so experienced with data analysis, I mean, someone's done it for you. Here's two very trustworthy names in the industry.
>> Um, I mean, you can understand why people have this mistaken belief, but I'll I'll go on and show the big flaw of this report is one once again, it's the use of a single time frame. Um, and so to prove that, I'm showing uh yeah, this new chart. I I replicated what they did, but for a different time frame. So this chart has the same five cities, same length of time, 8 years, which is what they used. Uh the same vertical y-axis, it's a ratio between inner and outer rings, but it's for a different 8-year period. So this is the 8 years before the RBA REIA chart.
That is the 8 years ending in 2006, not starting in 2006. Um now although the colors have changed, uh I've kept the concept the same. So the turquoise bar on the left reflects the ratio between inner and outer ring medium values at the start of the period which is 1998 and the purple bar to its right reflects the ratio between inner and outer ring median values at the end of the period which is 2006. So in the previous chart the ratio increased over that 8year period but in this case uh that only happened for one city Brisbane. Uh so what this means is that in most cities the outer ring closed the gap. Yeah.
It outperformed and closed that gap between itself and the inner ring. And the problem with the design of this growth comparison is it only compares start year to the end year. It doesn't show a trend over time using multiple years. So let's see how these ratios have changed for each city over a long history rather than two points in time. All right. So this chart shows the same five cities, but instead of a red and a blue bar for the ratio at the start year and the ratio at the end year, this chart shows a continuing ratio for every year starting from 1990 to 2025.
So quite a uh long period of time there, 35 years. Uh Sydney is the easiest one to see. It's a bit busy. I'm sorry. Uh that's the red line uh at the top. So you can see on the left of the chart, the inner suburbs are about 2.5 times more expensive than the outer suburbs.
>> That's in 1990. So 1990 and then it shoots up to what about 4.1 >> four times by 2012. >> And uh if you're only looking >> is that right? >> Uh around 200 two, right? Yeah. So if you're only looking at those um what is that 12 years uh you'd think you were on to a winner but the next 12 years showed the reverse and that cycle repeated.
>> So from 2000 to 200 maybe 12 that maybe let's call it 12 year period the outer rings were receiving better capital growth than the inner rings. >> That's right. Yeah they they caught up. Yeah the ratio came down. So it went up over some certain period of time and then went down over another period of time. And this is the cyclical nature of the property market.
So if you pick a specific start and end period, uh you may run into a problem if you're not familiar with those sort of cycles. >> What if my office is in the northern beaches of Sydney? >> Uh just just keep talking it up, talking it up every every decade. And you'll see Melbourne in blue. It's similar. It's less pronounced, but it is similar.
Uh Adelaide is perhaps the smallest city and it looks like it is the most uh consistent. So it is a 35 year period. Although the ratios have changed over the years, they seem to return to roughly the same spot. Uh that means inner suburbs are not showing any signs of outperforming outer suburbs. So if closeness to the CBD truly was an indicator of future higher growth, we would expect the ratios for all cities to be climbing the chart from the bottom left corner up towards the top right corner. But instead uh despite the volatility, the lines for every city show no uh clear trend or that the trend is is flat.
So although they go up and down from time to time, they end up showing a mostly flat trend. So there are eras when suburbs closer to CBD have better growth than those further away and there are eras where the opposite is true. So overall we cannot say from this chart the closeness to the CBD is a growth driver. >> Interestingly like let's say 2019 when co happened there's a bit of a drop off there. So Sydney was really picking up some steam. I know that they had the election over here where Labour was going to sort of negate that negative gearing and all of that happened.
So that sort of stagnated that period, but you see this drop through here and I think this is where a lot of people are getting over living in the city. Like if their jobs aren't there, maybe they're moving more regional to have a bit more of that lifestyle if they can work from home. So I wonder if that's had or it clearly has had an impact especially even um Melbourne. Well, Melbourne was hit hardest by CO, but um maybe a lot of those inner ring markets stagnated while these regional markets went a little bit better potentially. I don't know. But there's surely something in when CO happened with a lot of these markets.
Even Brisbane, um look, Brisbane's been strong. >> Well, all the markets have been quite strong, but if you have a look at Brisbane around that 2019, those outer rings have had more growth than those inner rings and they would have had better yield. So it's interesting to see when an event happens um that you >> I think that uh yeah co probably just triggered what was coming anyway because how do you explain the one at the turn of the century uh where similar sort of thing happened. So what you can have is is a market just has an exceptional amount of capital growth and now it looks overpriced overvalued and then the others look cheaper by comparison. Sydney. Sydney's an interesting one because out of all of them and maybe because the scaling is a bit different, Sydney sort of started the most like the the inner city markets were a lot dearer than the outer market.
So you're already starting at the front at 2 and a half and Melbourne was second at about one and a half times >> those amounts. But if you look over that what's that? Uh 35 year period it's about three times. So it's still ahead. You could argue, well, you know, if I bought in Sydney and held on from 1990, like the outer markets have still outperformed. But then if you look at the other major cities, there hasn't been much difference at all.
It just shows the gap with inner city Sydney, how expensive things are. >> Yeah. Well, yeah, Sydney is a uh a massive city. I think there about 700 suburbs, but yeah, it is it is interesting. That is quite a a noticeable difference when we're talking about a ratio. Uh whereas it's uh not very different for Adelaide.
>> Yeah, Adelaide's here a lot more. I wonder why that would be maybe um not as many people, not as much demand. It's interesting. >> Yeah. Yeah. Uh good pick up.
So there is a variety of of ratios across the cities and Adelaide is significantly smaller than Sydney >> and it's all these like you said there's markets that they all sort of like the inner markets and you'll have that ripple effect and those outer markets. So the city will grow and so will those outer markets because it will push that demand sort of further out with owner occupiers and investors. So if you are buying for example in the outer ring like the inner ring is still going to most probably have some capital growth. It's a matter of which one is better and that's where you need to look at the data when you're purchasing your next property to make sure you can increase your probability. >> Yeah. Yeah.
It's all about increasing probability >> because no one's got a crystal ball and that's what a lot of these uh a lot of professionals would say and I hope that they don't but it's all about educating yourself and your clients. There needs to be some accountability >> and and given these reports you can understand why people were were misled. Uh so yeah, although if just want to finish off on that chart, I just want to point out that um the problem with this RBA REA chart, uh it still isn't the best analysis. Um and what I've done isn't the best analysis. Uh this chart that you're looking at now has a flaw. Um a suburb is classified as either inner or outer.
So it's just a bit too blunt. So for this example I used 10 km as the boundary uh between inner and outer. Um now I did try 20 km and 30 km and the chart barely changed. Uh but it does highlight another way in which we could perhaps more accurately estimate the relationship. Uh and the next chart is where I tried uh is where someone tried to do this. So this is >> grainy, isn't it?
The image is a bit grainy. >> Yeah, I'm sorry about that. This is from SGS economics and planning and I this is the um highest resolution image I could I could find of this on the interweb. Um but what's good about this chart is that along the bottom horizontal x-axis you can see a list of distances from the CBD ranging from zero to about 80 kilometers. And what's bad about this chart is they've only considered one city, Melbourne. So anything that could be gleaned from this chart will only apply to Melbourne.
And once again, they've only looked at a limited number of time periods, only two in this case. It is two though rather than the Ahuri report and the REA REI RBA and REIA report. They they both only looked at one time frame whereas there's two considered here. So it's um although you see three lines is it's the gap between those. Um >> yeah, like from so 2009 to 2010, they just taken that one or two years. It could be one year potentially.
How do you know they haven't taken it from June 2009 to June 2010? >> Yeah. Well, it's the it's the change in the slope of the curve between the two um tiny uh periods. >> Okay. >> Yeah. So assume that they're just there's a snapshot, three snapshots in time.
With three snapshots, you can look at two changes between those three snapshots. So this is just trying to get across it. Inner city is always better or always dearer I guess. >> Yeah. Well from this chart the conclusion was that uh the closer to the CBD you are the the more capital growth you will have because the difference in around 1990 is less than the difference in 2010. >> But um uh oh I found a more upto-date one actually.
It's on the next slide. Yeah. So, this is the same company SGS Economics and Planning. Sorry, I don't have that on the chart there. Uh, so it's a step up in that they've added an extra point in time. So, you can see four curves there instead of three on the pri previous one.
Uh, unfortunately, it's still only for Melbourne. And for some reason, they've reduced the time frame to even less years. Uh, so in the prior chart, um, now it only covers 15 years instead of 20 from the prior chart. So uh the report this chart uh was found in it it mentioned or suggests that there is more growth in in the Melbourne suburbs closer to the CBD than in suburbs further away. But again uh they've chosen a limited time frame and only uh four points in that time frame. Uh another shortcoming of this chart is that they uh left the the left vertical axis is in dollars rather than in growth peranom which is what we're after as investors.
Yeah. So uh another report fatally flawed in um in the conclusions that it was hoping to make or attempting to make draw u but you can begin to understand why so many investors uh and even professionals uh have got it wrong. You see a report like this and uh it leads you to a certain conclusion. It's all the same uh and unfortunately they've all been uh flawed in one way or another. Uh in the following charts I show analysis that takes care of the shortcomings of these all these prior reports. So this chart I put together uh it more clearly shows what's going on for Melbourne.
You can see in the legend at the top of the chart, I've split up Melbourne's suburbs into seven different groups. Uh the first group of suburbs are within 10 kilometers of CBD. The second group are within uh 10 and 20 kilometers of CB CBD. And the last group of suburbs are between 60 and 70 kilometers from the CBD. So unlike the Ahuri report, this approach considers a lot of suburbs, not just half a dozen. Uh there are dozens of suburbs in each of these rings.
And you'll notice that along the bottom horizontal x-axis uh the period of growth measured is from 1990 to 2025. So it's a 35 year period. And the uh red curve on the chart that represents the growth of the set of suburbs furthest from the CBD over the last 35 years. The green curve represents the growth of the set of suburbs closest to the CBD and the blue curve is the second furthest. Purple is the second closest. Now, lots of people will look at a chart like this and go to the top right to see who won the growth race and it looks like, you know, the red, but uh that misses the insight that this chart shows.
The insight is that the the that there are crossovers along the way. So if we set the finish line 5 years earlier, there's no clear winner. If we set the start line 10 years later, the blue chart, the blue line uh would have won. So the winner in a capital growth race is more determined by when you set the start and finish lines, not where you've bought a property. Uh and the obvious thing to notice here is that there is no exponentially widening gap between any of those groups. If being close to the CBD had even a relatively uh small influence on growth, then over a long time like three and a half decades, we would expect the green curve to rise to the top, separate itself from the purple and continue to widen that gap.
But instead, as you can see, the outer rings have kept up with the inner curves, inner rings, sorry. Um, and the best performance over the last 35 years has actually come from the suburbs that are furthest from the CBD. And yeah, second furthest had the third highest growth. So yeah, what is important to understand from this chart is is not who won that race at the end date, but that the curves did not spread out over that 35 year period. They should have spread out if there was anything in this this theory of buying close to the CBD. So this means there is no rule that investors can follow about distance from the CBD to achieve higher growth over the long term.
Well, at least not in Melbourne anyway. So I did restrict this just to Melbourne. Uh so the next step in the research is to uh expand this to include more cities that have CBDs. >> Why did you pick Melbourne? >> Uh just because a huri started with with Melbourne. I thought I'd just look at >> Is there something special about Melbourne?
No. >> There's no growth uh that outperforms when you're close to the CPD. My observation is like you said if you picked it a start date of 1990 and you said okay finish at 2000 you would have said inner city wins because it clearly is the winner. But then if you look at up until 2025 like I would say that's a pretty big gap. It might be hard to see but that's maybe like 50% maybe better off for maybe what 40 maybe 30 40% better off >> over that 35 year period if you bought back in 19 90. And um like you said, the yields would be typically better being a little bit further out over that period too.
So that factors into your returns. >> Yeah. And if you just change the period of analysis, let's say you were at uh 1998. >> So the green is already well ahead of the red. So the red has outperformed by even more than the green. >> So it really depends on when you pick uh the start and finish of the race.
What's more important is not who who won the race but how was the race won. Were was there a spreading out in these curves and there wasn't. So this is um combining uh data from Australia's 10 largest cities. Uh so technically the term is the 10 largest significant urban areas and this chart considers thousands of suburbs. So, we're really getting a clear idea now of the general relationship between proximity to CBD and long-term capital growth. And uh because the closest suburbs to CBD do not diverge exponentially away from the outer ring suburbs, we can conclude that there is no relationship between proximity to CBD and higher capital growth.
And uh this chart on its own uh shows there's no harm buying close to the CBD, but something you were talking about on the next chart uh shows another reason why you might not want to um buy in those inner ring suburbs and that's yield. So this chart shows the difference in gross yield the further the suburb is away from the CBD. So up the left vertical yaxis is yield. uh the higher the bars are on the chart, the higher the yield. The left uh well the horizontal x-axis, if you look over in the bottom left, it shows the distance from the CBD. Uh suburbs further away from the CBD are to the right of the chart.
So the chart considers all suburbs within top five largest cities in Australia. And yeah, the shortest bar on the chart is on the far left. Uh that's all the suburbs within 5 kilometers of their city's CBD. Uh the median yield for these uh suburbs just under 3%. Chart shows that as you go further from the CB CBD, the yield gets higher. Uh but admittedly, that's a pretty flat dotted line there.
So there's not a lot in it. Uh so this is not a really good enough reason to deliberately pursue suburbs in outer rings. Uh but growth and yield are not the only considerations. >> So this list here is this all the suburbs in the major cities distance from the CV. >> I for these cities I only picked the top five. So that's Sydney, Melbourne, Brisbane, Perth and Adelaide.
>> Okay. So a big data set that you're looking at. >> Yeah, it's it's quite significant. Yeah, that's um thousands of suburbs. >> How long does it take you to get these presentations up? It's a good point because um I mean just researching what others have done, you know, there's some time involved there.
Um getting all the data together, coming up with uh the best way to present it. You know, this when I originally did this back in, I think 2018. >> Uh from memory, it took me about two months of sort of part-time work. Uh, and yeah, I think there's an issue in the industry where it takes you two hours to put your opinion down >> on piece of paper and blog it or whatever. And we've got billions of opinions. They're in over supply.
But this sort of research is the true value because then you do understand what the truth is. You cut through all that clut clutter. And the problem, the reason why there's so little of this research because it takes so much time. It's much easier from a marketing perspective to just go, you know, blah blah blah. My opinion is >> well, it is a lot easier. You just put it to the side and market.
At the end of the day, they want to drive revenue, don't they? Like where is your best time spent? I guess if you're a small business, I get it. Like you want to have business and spending a lot of time on this, you sacrifice um revenue for the business and running the business. No. >> Yeah.
Well, the reason that what triggered me to do this research is cuz I'm an investor. I I need to know I need to know what the true drivers are of capital growth. Uh yeah. So this um we've gone through growth and we've gone through yield. Another consideration for uh investors, what about risk? So the chart you see in the top top left >> top left >> top left uh shows that suburbs close to the CBD are more expensive than those further away.
Dah everyone's saying so buying close to CBD will mean more eggs in one basket >> uh and it would be less risky to diversify and split say you've got a million dollar budget you could buy two properties for $500,000 possibly in two different cities so um oh and also expensive suburbs close to CBD have a history of greater volatility and that's the chart in the bottom left this comes from Kotality uh sorry it says core logic in bottom right. That's because when this was published, they were known as Core Logic. So, they started out as RP data, then they become Core Logic. Uh now they're Kotality. What's what's your guess for 10 years from now? What will they be called?
Who knows? Um I don't know why the name changes but uh yeah so that the this chart uh it shows that the top 10% of suburbs by price have had greater volatility than the lowest 10%. So volatility is a measure of how rapidly and frequently prices fluctuate. So you'll see uh they bounce up and down in value on on the uh on the chart. >> So that blue line for example, talk me through this one. So it's first.
So what's that mean? >> Uh the first is so the I think they used to have a decile uh report. So this is the Yeah, the bottom bottom 10%. So the cheapies the cheapies are the blue curve. >> Oh so first. So where you got >> Yeah.
So they've ordered it by price. >> Okay. >> Yeah. So the first um decile the first 10% are the blue and the last 10% the 10th decile is the the most expensive markets. >> Okay. So 10 so the 10th is the most okay the most expensive markets within all those major cities.
>> That that's right. Yeah. Combined capital. So there's more volatility. So which one's got the most volatility? >> Well, apart from that blue spike there around 2003.
uh there's more volatility in the gray curve. So you have a look from 2013 to 2018, that 5-year period, the blue curve is almost flat there. Uh but you can see the the gray curve. >> Uh and then there's that massive dip in May 2008 of the gray curve. >> And you'll also notice the horizontal straight line, that gray thin horizontal straight line, that's 0% growth. So the um more expensive markets dip comfortably below that.
So we had some periods in this in this in this um in this history where uh the entire nation went backwards >> where it dips below that line. >> So you got the dip. >> So there's one, two, three, there's there's four of them. >> But in the blue line there's only one. So the cheaper markets went negative only once in that history. and they show less volatility.
It's interesting though if you look at that whole period from 98 to 2018 what a 20-y year period there's barely any time where at um there's like below 0% growth rate through the periods like there's a higher period there where >> growth is consistent like every year you're getting growth from 98 99 2000 you're getting growth growth growth and you just go go below 0% for a year around what maybe 2004 maybe 2005 and then picks up again and then there's another period around that was the GFC so 08 09 10 and then it picked up again and there was another drop off and then it's been pretty consistent from about 2014 so it just shows why everyone loves property people need somewhere to live and they just love it from a nest egg don't they >> yeah and uh Australia internationally is very great you know it's one of the best countries in the world to live some of our cities are mentioned in livability index taxes. Um, yeah. So, >> and that risk perspective that you talk about, like you're right, you could have bought maybe two 500s instead of maybe that million-doll property, the only risk there is it does take time. It's not like you buy a share and you click a button and you buy a stock. With property, there is a bit of upfront work like dealing with the conveyances, um, the buyers agents, going through the properties. So, there is a bit of time injection up front, but once you purchase the property, rent it out, forget about it, let that growth happen.
>> Yeah. Yeah. Yeah. And the reason why I wanted to show this this chart is there are a number of considerations for investors. We talked about growth, talked about yield. Another consideration is is risk.
And >> in the share market, volatility is a measure of risk. >> Uh and more expensive suburbs have greater volatility than cheaper suburbs. Um there's more eggs in one basket. So you could argue that uh closer to CBD you not only have uh lower yield you have higher risk and you don't get any better growth. >> All right. So um other considerations >> yeah there might be a case where you need to uh sell your property.
Um you might not need all of the funds of the sale proceeds. So, if that was not a million-doll property, but two $500,000 properties, you could sell half your portfolio. But if it's all in one, if all the eggs are in one basket, then you have got to sell that whole basket. So, that's another consideration, flexibility. I'm calling it flexibility. So, yeah, you can't sell half an expensive property, but you can sell uh half of a portfolio of cheaper properties.
Um, and then there's capital gains tax, CGT. So if the occasion arose to sell your property, you would have to pay CGT. >> Uh the CGT would be based on your marginal tax rate as for the year in which you sold that property. But if you had instead bought two properties at say half the price, you could sell one on June 30 of the first financial year and then one the other on July 1st of the next financial year and then you spread out that CGT over two years reducing the amount of tax that you pay. And not even that, let's say you're coming close to retirement or when you you want to cut back or whatever your game plan is at the back end. But if you've got two, if you just got one and let's say you let your bank drop, like you're just living off maybe funds in your bank account and then let's say you get to 100,000 and just decide to sell, there's going to be a massive, like you said, a bigger capital gain.
But then you've got no exposure to property anymore. But if you had two, you could sell one and keep the other one and that's still ticking in the background. You move the money to the offset. you're still collecting rent, but at least you've got exposure to the asset class. Otherwise, if you did sell everything, you'll go buy again, but that's why it's good to have several properties in the portfolio. >> Yeah, that's another one.
Uh, and then there's stamp duty. So, that's based on property price. And most states have a bracketed stamp duty. So, the more expensive properties have higher stamp duty rates than cheaper ones. So buying close to the CBD, you pay more in stamp duty than buying say two properties uh further away from the CBD. Uh and then there's yeah timing your entry.
This is an interesting one. So ideally you you want to buy before the market takes off before the next growth phase. And quite often you'll see growth phases happening in entire cities like we've got Perth at the moment. Um there was there was the boom in Adelaide and there was the one in Hobart before that Sydney and you you you do have some suburbs that outperform others within that city. But how do you know when uh that city is is about to boom and quite often in the past at least we've seen booms start in most expensive areas and then ripple outwards. Now it might be less less so nowadays where people are just um targeting affordable uh areas but if that still applies then you can use the growth that you see in those expensive ideal markets as a trigger.
Hey, this city is about to boom. Whereas you don't see that start in the outer suburbs and then go in. Although >> that trend could be reversing now. You know, everything changes. But yeah, timing entry is another consideration. Another thing that I didn't mention is that outer suburbs have a higher frequency of subdivisions.
So, in the inner city, you're more you're less likely to see a block of land subdivided than in outer suburbs. Now, let's say that um 10 years ago, uh there's a suburban got all these 4,000 square meter blocks and they're all selling for $200,000. 10 years later, they've all been subdivided and they're still selling for $200,000. That doesn't mean they haven't had any capital growth. >> They've actually doubled in value in that period of time, but they've h haveved in size. >> So, one thing that I didn't do in my calculations is take into consideration like any change in block size.
So, that has unfairly underestimated the capital growth of outer suburbs. So, all of those charts, I don't know by how much, but you could actually estimate a slightly higher capital growth for the outer suburbs. And even with the charts as they are unaltered that there's no correlation. >> Well, you can maybe look at an example like now maybe look north Kellyville all those areas where they'll like >> sort of subdivide a lot of those blocks and it's a fortune there. Now it's coming up to like $2 million suburb. >> So fortune for a small block out there now >> even out west like Penri way also even parts of the north and south coast of New South Wales.
Um yeah, I definitely agree that that land value is you see a lot of these 400 square mters or 300 square mters even and they're uh the demand's there. >> Yeah. Yeah. So that's another one I I forgot to put in there, but this um All right. So in conclusion, you don't need to buy closer to CBD. Uh don't stress out.
Don't uh push yourself your budget too hard to try and buy a more expensive property. There's no such thing as like these uh blue chip investment grade suburbs that are closer to CBD. Historical data shows uh there's nothing in it. Uh but I would caution buying in a genuine fringe suburb that is surrounded by loads of vacant land where developers could go berserk and you could see uh large over supply and you see those tiny blocks in Greenfield estates. So, but anything in the uh middle ring uh middle rings should should do fine. >> And I urge I guess companies out there and investors like do a bit of research.
Um if you've got questions, reach out to us, but hopefully this presentation helps as I guess all the other episodes in the expert busting series. So, I think is that a wrap, J for episode five of the expert busting series? >> Yeah. So if if you have found this uh helpful, give us a thumbs up and there may be someone you know who uh believes in this close to the CBD thing. If you are going to share this uh link with them, just be diplomatic about it because uh you know if you go look you're wrong, uh they're not going to uh accept this this sort of intel. U we do want to help the the industry learn and investors learn as we go and putting uh people's ego on edge isn't going to help.
I think putting data first. So like I said, if you see something that we don't reach out like Jeremy, you'll do the analysis, won't you? This is what you love doing. >> I'm happy to accept some correction, but I I'm not interested in opinion. I am interested in analysis or data. Uh there could have been flaws you saw in how I performed this analysis.
Happy to do some more analysis, but uh yeah, not not interested in just an opinion. >> Perfect. So that wraps up episode five of the expert busting series. Join us next time for episode 6. Why high salary doesn't mean high growth. Thanks for watching.