35 Years of Property Data: Debt vs Scarcity

35 Years of Property Data: Debt vs Scarcity

Did Australian house prices go up simply because there are not enough homes? The data shows that prices actually rose because the Reserve Bank dropped interest rates over 30 years, which massively expanded how much people could borrow.

Over a 30-year period, wages doubled and borrowing capacity tripled. Together, these factors drove property prices up by a factor of 6.

The expansion of the credit system is the main driver of Australian house prices, rather than just a shortage of supply. This means a house did not necessarily become six times more valuable. Instead, the availability of cheap credit allowed buyers to bid up prices with borrowed money.

Without tighter lending standards and tax reform, housing will likely remain a financial vehicle rather than affordable shelter.

Please Note: I (Craig Douglas) am not the author of the underlying research. The original author’s website features data from over 7 million property transactions spanning 35 years and covering every New South Wales suburb. The site features visualisations discussed in the article. You can view price cycles compared to long-term trends.

The author’s website also highlights transaction volume patterns, price-per-square-metre comparisons, and street-level breakdowns. The creator is currently adding new metrics in response to user feedback. You can explore the data at https://auspropertyinsights.app/.

THE ORIGINAL ARTICLE: I wanted to see what 35 years of property cycles actually looked like. Here’s Blacktown

I work as a data analyst and I’ve always wanted to see what a full property cycle looks like; not the 5 year charts you get from banks but actual multi-decade trends across complete boom/bust cycles.

I couldn’t find anything that showed this without paying for expensive subscriptions, so I just built it myself over a few weekends. I grabbed the NSW Valuer General data going back to 1990 (it’s public, just annoying to work with), cleaned it all up and got it into a database. It ended up with about 7.2 million sales records across 7000+ suburbs.

I started playing around with some visualisations and this is Blacktown.

Top chart is median price vs the long term trend line (6.7% pa for this suburb). The middle one shows how far above or below that trend we are at any point. The bottom is transaction volume.

A couple things I found interesting:

• The 2003 boom is wild in hindsight. Prices got to 35% above trend and then basically flatlined for nearly a decade. Anyone who bought at that peak was underwater in real terms until about 2014
• There’s this pattern where volume seems to spike before prices move. Look at 2001: a big volume jump, then 2003 price peak. Same thing 2015 before the 2016-17 run. It could be a coincidence, but it’s consistent. I might need to run some regression on this.
• Currently sitting just below trend, first time since the covid peak.

I have a bunch of other stuff I can pull from this: street-level breakdowns, price-per-sqm comparisons, settlement times, that sort of thing.

PART 2: I analysed millions of property sales over 35 years. House prices didn’t rise because of scarcity.

Think about your parents’ house. Maybe they bought it in 1995 for around $150,000, and today it’s worth $900,000. But did the house actually get six times better? It’s the same three-bedroom brick place, same kitchen, same backyard. If anything, it’s older and more worn out than it was back then. So what actually changed?

The standard answer you’ll hear from most people is that there simply aren’t enough houses. Too many people are immigrating to Australia, with not enough supply.

But what if that’s not really the story, or at least not the primary cause?

A Simple Analogy

Think about it this way: imagine you’re measuring your height, but the ruler you’re using keeps shrinking. On Monday, you measure 180cm, and by Tuesday, you’re suddenly 200cm. You didn’t grow 20 centimetres overnight. The centimetres themselves got smaller.

That’s essentially what’s been happening with house prices. When people say prices went up 600%, what they’re really describing is that it now takes six times as many dollars to buy the same house.

That could mean the house became six times more valuable, sure. Or it could mean each dollar shrank in value, like those centimetres. The data suggests it’s mostly the latter.

Three Things That Don’t Add Up

If houses had genuinely become scarce and valuable, we’d expect to see certain patterns emerge. But we don’t.

Take rent, for example. A $150,000 house in 1995 would have rented for about $200 a week. That same house, now worth $900,000, rents for around $600 a week. The purchase price went up six times, but rent only tripled.

That’s a significant gap, and it matters because rent is a much better reflection of the actual value of housing as shelter. If houses had truly become scarcer, you’d expect both figures to move in roughly the same direction.

Then there’s wages. Back in 1995, median household income was around $50,000 and the median house price was $150,000, so about three years’ worth of income. Today, income is roughly $110,000 and the median house price is $900,000, which is more like eight years’ worth.

It now takes nearly three times as many years of work to buy the same house, even though wages have gone up too. And debt tells its own story. Australian household debt sat at about 60% of annual income in 1990. By 2024 it had ballooned to 180%.

That means we didn’t suddenly become three times wealthier; we just borrowed three times more (Source: RBA Household Sector debt).

That’s the Math. Over a long enough time frame, the picture becomes clear:

Wages doubled over 30 years, borrowing capacity tripled, and together, they’ve driven prices up by 6x. Your parents’ $150k home… now $900k.

But Why Did Borrowing Capacity Triple?

The Reserve Bank slashed interest rates, and it did so dramatically over a long period. In 1990, rates were sitting at 17%. By the end of 2020, they had dropped to 0.10%, and they’re around 3.60% now (Source: RBA Cash Rate). Lower interest rates don’t just make individual loan repayments cheaper. They fundamentally increase how much people can borrow in the first place.

To put that in concrete terms: in 1995, someone earning $50,000 a year could comfortably afford about $1,500 a month in repayments at an 8% interest rate, which translated to a maximum loan of roughly $150,000.

By 2020, that same household, now earning $110,000, could afford $3,300 a month at a 2% interest rate, which meant a maximum loan reaching $900,000. Twice the salary, six times the buying power.

So when buyers started showing up to auctions with budgets six times larger than a generation ago, prices naturally rose. The houses themselves hadn’t changed, but everyone was suddenly holding a lot more money, even if most of it was borrowed.

What Happens When We Use a Different Ruler?

If you measure house prices in gold instead of dollars, the picture looks very different. Gold is something that can’t be easily manipulated the way currency can, so it’s a more honest centimetre.

A median Sydney house cost 377 ounces of gold in 1995, and in 2025 it costs 330 ounces. In gold terms, Sydney house prices have not moved at all in 30 years (in fact, they fell 12%).

But What About Supply and Immigration?

It’s a fair question, and population growth is real. Building approvals have been frustratingly slow in a lot of areas. But if supply constraints were the main thing driving prices up, you’d expect rents to be rising just as fast as purchase prices, but they’ve risen at about half the rate.

And you’d expect building approvals to substantially lag, but they haven’t, instead increasing by 55% in the last 30 years (Source: ABS Building Approvals), more or less in line with population growth over the period.

Supply and immigration play their parts, but they are not the primary cause.

What Would Actually Fix It?

The most direct fix would be to stop inflating people’s borrowing capacity. That means keeping interest rates at more normal levels and tightening lending standards, bigger deposits, and stricter income tests. But this would hurt a lot in the short term.

On top of that, grants and government schemes that effectively push prices higher should be rethought, and the tax advantages that treat housing as an investment vehicle rather than shelter deserve to be removed.

Building more housing is also part of the answer, but only if it’s paired with addressing the credit side of the equation. More supply combined with unlimited cheap credit just means prices keep rising anyway. More supply combined with tighter credit is what could actually move affordability in a meaningful way.

The problem is that almost no one in a position to make these changes has any real incentive to do so. The average age of a federal MP is in their mid-50s. Most of them own property, and in a lot of cases more than one. A policy that meaningfully brought house prices down would hit their own balance sheets.

Then there’s the electoral side of it. A huge chunk of the voting population are homeowners, and a big chunk of those voters are sitting on paper wealth they’re not keen to see disappear.

Any politician who ran on a platform of deliberately cooling the housing market would be telling a massive block of voters that their biggest asset is about to lose value, not a winning election message.

The people who’d benefit most from lower prices, renters and younger people trying to get a foot in the door, tend to vote less and have less political sway than the property-owning demographic that dominates the electorate.

First SUMMARY

Australian house prices didn’t rise because homes became more valuable or scarce. When the RBA dropped rates from 17% down to 3% over the course of 30 years, it massively expanded how much anyone with a mortgage could borrow.

That flood of new money didn’t spread evenly through the economy. It flowed in through the credit system, through mortgages and loans and investments, and it hit asset prices first: houses, stocks, anything you could buy with borrowed money.

Over a long enough time frame, the picture becomes clear: Wages doubled over 30 years, borrowing capacity tripled, and together, they’ve driven prices up 6x. Your parents’ $150k home… now $900k.

The official inflation figures (CPI), will tell you we only had 2-3% inflation per year, and that’s true for everyday consumer goods like bread and milk.

Consumer inflation for the most part has a relationship with wage growth, which is why wages only doubled in 30 years (equivalent to 2.3% pa). But it doesn’t capture what happened to houses, stocks, or anything you typically buy with a loan.

Supply matters, and we should absolutely build more and cut back on red tape. But supply alone can’t solve a problem that’s fundamentally about monetary policy.

If people can borrow enormous sums, they will bid up whatever’s available. The housing crisis was created by monetary policy, and it can only really be fixed by addressing monetary policy. Everything else is just a band-aid.

Thanks for sticking with me through this long read. I hope the data-driven perspective has been useful. Keen to hear your thoughts, counter-arguments, or personal experiences in the comments.

PART 3: I analysed 35 years of Australian property data. Here’s what the next two decades might look like.

I posted an analysis of property sales over 35 years. What I saw was that house prices didn’t rise because homes became much more scarce or more valuable. Supply was certainly a factor, but the primary reason was that the RBA dropped rates from 17% to 3% over 30 years, which tripled borrowing capacity while nominal inflation doubled household wages.

A $150k house in 1995 became $900k because wages doubled over that period, borrowing capacity tripled, and prices went up 6x.

A lot of people agreed with the data but asked: “OK, so what does this mean for the future, and what would fix it?”

This is the longer answer. It covers how bank deregulation in the 1980s expanded credit access, how the banking system absorbed dual incomes into lending assessments, why AI might accelerate these trends, and what Singapore does differently to achieve 90% homeownership while Sydney sits at around 67%.

1980s deregulation changed the housing market

Before the 1980s, getting a mortgage in Australia worked nothing like it does now. You didn’t walk into a bank and ask how much you could borrow. You had to prove you could save first.

Banks wanted to see a consistent savings record, usually 12 to 24 months of regular deposits into an account held with that same bank. The branch manager reviewed your application personally, and the relationship mattered. If you’d been a loyal customer for years, you had a better shot.

Credit was rationed. Banks could only lend from the deposits they held, and the government forced them to park up to 70% of those deposits in government securities through “prescribed assets ratios.” What was left for mortgages was a small pool, and it ran out regularly.

Median prices sat around $32,000 against average earnings of $8,000, and a typical household faced a strict $25,000 loan limit. The deposit gap was roughly equal to a full year’s total salary. Restrictive? Yes. But it also meant house prices couldn’t outrun wages by much. There just wasn’t enough credit in the system to push them higher.

Source: BIS Papers No. 46, Household Debt in Australia

Then the Rules Changed

The 1981 Campbell Report recommended dismantling most financial regulations. The Hawke-Keating government ran with it: floated the dollar in 1983, removed interest rate ceilings, and from 1985 onwards granted licences to sixteen foreign banks. The 1984 Martin Review pushed things further in the same direction.

Under the old system, banks rationed a fixed pool of deposits across borrowers. After deregulation, they competed for deposits, tapped wholesale funding markets, securitised loans, and grew their books as fast as they could find borrowers. The question went from “how much money do we have to lend?” to “how many borrowers can we find?”

The way they assessed borrowers changed, too. If your income covered the repayments, you got the loan. Banks worked backwards from your income to find the maximum repayment you could handle, then sized the loan to match.

Non-bank lenders in the 1990s took it further. Aussie Home Loans and RAMS didn’t take deposits at all. They funded mortgages by packaging them into securities and selling them to investors.

The total pool of mortgage credit was no longer tied to bank deposits. It was tied to how many loans could be packaged and sold, which in practice meant no real limit.

The household debt numbers tell the story. In 1980, total household debt was about 40% of household income. By 2006 it hit 160%. Today it’s around 190%. As I said before, a $150k house in 1995 became $900k because of the availability of credit.

Sources: RBA, “Australia’s Experience with Financial Deregulation” (2007); RBA, Household Debt: What the Data Show (2003)

Effect of Dual-Income

After the 1966 repeal of the “Marriage Bar” (which had prevented married women from working in the public service) and the Equal Pay cases of the early 1970s, women entered the workforce by choice. Households had more money.

Then the banks noticed. By the late 1980s, they were factoring dual incomes into borrowing assessments. Property prices adjusted upward to absorb the new maximum bids. The second income stopped being a bonus and became a prerequisite for market entry.

Mortgage repayments now eat 92% of the median monthly salary. In the 1970s, it was 44%. Single-income earners qualify for loans 42% smaller than dual-income pairs with the same combined earnings. If you’re buying alone, you’re basically locked out.

Common objection: “This is just an argument against women working. Dual incomes are a good thing.”

Women entering the workforce was obviously a positive development. The point is narrower: the banking system factored the second income into loan assessments, which increased maximum loan sizes, which translated into higher auction bids, which set a new price baseline.

A significant portion of that additional income ended up being absorbed by the property market rather than staying with households.

The clearest evidence is that 92% debt-servicing figure. If dual incomes had genuinely made households richer in a lasting way, you’d expect the share of income going to housing costs to stay flat or fall as incomes rose. Instead, it nearly doubled. The second income didn’t make housing more affordable because the market simply absorbed it.

The Denominator Problem

To understand price appreciation, you need to separate the numerator (the physical dwelling) from the denominator (the Australian dollar). When the denominator loses value, the numerator appears more expensive.

The clearest way to see this is to measure house prices against the money supply itself. The RBA publishes broad money data monthly in Monetary Aggregates Table D3. Since 1995, the median Sydney house has gone from roughly $200k to $1.4M, an increase of about 600%.

Over the same period, Australia’s broad money supply went from $394 billion to $3.4 trillion, an increase of about 760%. The “growth” of house prices is mostly the dollar losing value (the denominator).

CPI measures things bought with income. It doesn’t capture the expansion of the money supply used to buy assets with credit. That’s why CPI shows 2-3% annual inflation while broad money grows at 8-9%. The gap between them flows into asset prices.

This shows up at the suburb level too. I track 35 years of sales across NSW, and even the suburbs people think of as strong performers are growing slower than the money supply. Mosman houses have a 20-year CAGR of 4.1%. Bondi is 5.5%. Manly is 4.9%. Broad money has grown about 8% over the same period. The price growth most people see is their house roughly keeping pace with monetary expansion, or falling behind it.

Common objection: “Isn’t the RBA aware of broad money growth? They look at more than just CPI.”

They do. The Financial Stability Review discusses housing valuations, and APRA periodically tightens macroprudential settings in response to credit growth. But awareness isn’t mandate. The RBA’s legislated mandate is price stability (CPI of 2-3%), full employment, and economic prosperity. It has no formal obligation to target asset prices. When it has tried to lean against asset price inflation, most notably in 2017-18 when APRA tightened lending standards and prices fell, there was significant political pushback. The tightening was partially reversed within two years. A central bank that explicitly targets asset price deflation is telling the 67% of Australians who own property that their primary store of wealth is a policy target. No RBA governor has held that position for long.

Common objection: “This sounds like a hard-money argument dressed up in academic language.”

No. Pointing out that broad money grows faster than CPI, and that the gap flows into asset prices, is a description of how the current system works. It’s documented in RBA research papers and BIS working papers. The observation that CPI is an incomplete measure of monetary expansion is a mainstream position held by economists across the political spectrum. You don’t have to believe in hard money to accept that the money supply is expanding faster than consumer prices and that the difference is showing up somewhere. The data shows it’s showing up in assets.

What I think happens next: AI, monetary expansion, and the K-shape

Here’s where I think we are headed. AI will probably suppress consumer prices by automating white-collar services and reducing labour costs. On the surface that sounds positive, since wages would buy more goods and services.

But lower CPI gives the RBA room to keep interest rates low and continue expanding the money supply. The mechanism is straightforward: the RBA targets 2-3% CPI. If AI pushes consumer prices below that band, the textbook response is to cut rates to bring inflation back toward target. Lower rates mean cheaper credit, more borrowing, and money supply growth.

Central banks also have a strong institutional bias against deflation (Japan being the cautionary example), so they tend to err toward easing. The problem is that the new money flows into assets rather than consumer goods, so CPI stays low even as broad money keeps growing.

That gives the RBA further justification to keep easing. It becomes a self-reinforcing cycle where technological deflation leads to more monetary expansion, which shows up in asset prices rather than consumer prices.

And AI may simultaneously compress wages in the professional cohorts (legal, financial, analytical) that currently drive mortgage demand. McKinsey’s 2023 report on generative AI found that current AI technologies could automate work activities absorbing 60-70% of employees’ time, with the greatest impact on knowledge work tied to higher wages and educational requirements. That’s precisely the cohort driving Australian mortgage demand.

The result is a K-shaped economy. If you own assets, your wealth grows in nominal terms alongside the money supply. If you depend on wages and don’t own assets, your cost of living rises (particularly shelter) while your income stagnates or declines.

Common objection: “If AI deflates everything, shouldn’t house prices fall too?”

Different things. AI deflates the price of things produced by labour: services, software, analysis, content, admin work. Those show up in CPI.

It doesn’t deflate things that are scarce and used as stores of value. Land in a desirable location can’t be automated or replicated. Its supply is fixed by geography and planning law. As long as the monetary base keeps expanding (which AI’s CPI-suppressing effect encourages), capital looking to preserve purchasing power keeps flowing into it. AI deflates the things CPI measures, which gives the RBA room to keep monetary conditions loose, which inflates the things CPI doesn’t measure. The gap between them is the K.

Common objection: “If people are unemployed or earning less, who’s buying these houses?”

This is the question that matters most. The assumption is that the housing market has one type of buyer: the income-dependent mortgage borrower. Remove that buyer, demand collapses, prices fall. But the market has a spectrum of buyers.

At the bottom are first home buyers using maximum leverage. In the middle are upgraders deploying equity from existing properties. At the top are cash buyers, institutional investors, SMSFs, and intergenerational wealth transfers.

AI-driven wage compression primarily removes buyers from the bottom. It doesn’t remove the cash buyer, the equity-rich downsizer, or the investor deploying capital that has itself been inflated by the same monetary expansion pricing renters out.

Monetary expansion disproportionately benefits the top of the buyer spectrum. Broad money has grown at roughly 8-9% per year since the RBA started tracking it in 1976 (Monetary Aggregates D3). Existing asset holders see their capital base grow at roughly that rate. They don’t need income to buy. They need capital, and the expanding money supply continuously increases that capital in nominal terms.

Prices don’t collapse because buyers disappear. The type of buyer changes: fewer young people with big mortgages, more cashed-up owners rolling equity or deploying capital. Prices in desirable areas stay supported by concentrated wealth chasing limited real assets. About 28% of Australian property purchases already happen without a mortgage, and that share has been rising.

The K-shape also plays out geographically, and you can already see it in the data. The divergence shows up most clearly over the last 10 years.

Inner-ring suburbs where cash buyers and equity-rich purchasers dominate have kept growing. Northbridge houses ($5.39M) have a 10-year CAGR of 7.7%. Paddington ($3.65M) is 6.7%. Concord ($3.3M) is 6.4%. Marrickville ($2.2M) is 6%. At these price points, buyers are rolling equity from previous properties or buying outright. They don’t need wages to keep up.

Compare that to outer suburbs, where first home buyers are closer to their maximum borrowing limit. Liverpool houses have a 10-year CAGR of 0.5%. Basically flat for a decade. Penrith is 2.2%. Wentworthville is 0.1%. Mount Druitt is 4.1%. These suburbs are almost entirely mortgage-dependent. When credit tightens or wages compress, there’s nobody else to step in and buy.

What we can do about it?

At this point, housing in Australia functions more as a monetary hedge than as shelter. Without structural changes, homeownership increasingly becomes something passed down rather than something earned.

If you want to see what credit-side reform actually looks like in practice, look at Singapore. They have a 90% homeownership rate. Australia’s is ~67% and falling. Singapore’s median house price-to-income ratio is 4.2, while Sydney is at 13.8. A city-state with a fraction of Australia’s land and one of the highest population densities on earth has housing 3x more affordable than Sydney by this measure.

If you’re a Singaporean citizen buying your first home, you pay zero Additional Buyer’s Stamp Duty. Buy a second property and you pay 20% ABSD on top of the purchase price. A third? 30%. Foreigners pay 60%. They also cap LTV at 45% for second properties (down from 75% for your first), and total debt servicing can’t exceed 55% of gross income.

In Australia, the tax system works in the opposite direction. Negative gearing and CGT discounts reward owning multiple properties. Singapore treats a second property as a luxury and taxes it accordingly.

Australia lets you deduct investment losses against your salary and offers a 50% CGT discount when you sell.

The result: Singapore’s median HDB resale flat costs about S$628,000 against a median household income of S$12,000/month. In Sydney, you need roughly $280,000 household income to afford the median house.

Specifically, reform here means addressing the credit side:

• Tighter lending standards. Stricter income-to-loan ratios and higher assessment buffers to cap aggregate borrowing capacity.
• Tax reform. Remove or significantly taper negative gearing and CGT discounts that incentivise treating housing as a financial vehicle rather than shelter. The RBA’s submission on home ownership acknowledged that Australia’s treatment of property investors “is at the more generous end of the range of practice in other industrialised economies.”
• Broad-based land tax. Increase the carrying cost of unproductive land to encourage efficient use.
• Supply paired with credit restriction. Direct supply increases toward the bottom of the market while restricting the credit that otherwise absorbs new supply into higher nominal prices.

Final Summary

The credit side, not supply, is the main driver of Australian house prices.
Before the 1980s, you needed a savings record, a relationship with your branch manager, and banks could only lend from a small fraction of their deposits.

After deregulation, banks competed to grow loan volume as fast as they could find borrowers, non-bank lenders securitised mortgages with no deposit limits, and household debt went from 40% of income to 190%.

The three-bedroom brick house didn’t change but the amount of credit chasing it did. Dual incomes were absorbed into borrowing assessments, turning the second salary into a prerequisite rather than a bonus. Mortgage repayments went from 44% of median monthly salary in the 1970s to 92% today.

House prices haven’t really gone up in real terms.
Since 1995, the median Sydney house rose about 600%, but the broad money supply rose about 760%. The “growth” is mostly the dollar losing value faster than houses gain it.

AI will probably make this worse, not better.
AI suppresses consumer prices (which shows up in CPI), giving the RBA cover to keep rates low and money supply growing. But it also compresses wages in the professional cohorts that drive mortgage demand.

The result is a K-shape: asset owners keep up with monetary expansion, wage earners fall behind. This already shows up geographically. Inner Sydney suburbs (Northbridge 7.7%, Paddington 6.7% 10-year CAGR) are pulling away from outer suburbs (Liverpool 0.5%, Wentworthville 0.1%).

Other countries have solved this.
Singapore has 90% homeownership and a price-to-income ratio of 4.2x vs Sydney’s 13.8x. They do it with escalating stamp duties on second/third properties (20-30%), LTV caps, debt servicing limits, and government-built housing covering 75% of the population.

What would work here: tighter lending standards, tapering negative gearing and CGT discounts, broad-based land tax, and supply increases paired with credit restriction rather than supply alone.

I’ve used the following sources for this post:

• Suburb-level data: AusPropertyInsights (35 years of NSW property sales, median prices, CAGRs, cycle analysis)
• RBA: Australia’s Experience with Financial Deregulation (2007)
• RBA: Submission to the Inquiry into Home Ownership (2015)
• RBA: Household Debt: What the Data Show (2003)
• RBA: The Evolution of Household Sector Risks (2018)
• RBA: Statistical Tables, Monetary Aggregates D3
• BIS: Papers No. 46, Household Debt in Australia
• Parliamentary Education Office: Marriage Bar Abolished
• ABS: Births, Australia (2023)
• McKinsey Global Institute: The Economic Potential of Generative AI (2023)

Understanding 35 Years of Property Data: Debt vs Scarcity

This infographic breaks down the core findings from the 35-year analysis of the Australian property market.

1. The Great Price Illusion

Many believe house prices rose due to a lack of supply. The data suggests a different primary cause:

• 1995 Median House: $150,000
• 2025 Median House: $900,000
• The Reality: The house didn’t get 6x better; the “ruler” (the dollar) shrank.

2. The Math of the Boom

Over the last 35 years, three specific levers pushed prices to record highs:

3. Why Supply Isn’t the Only Story

If scarcity was the main driver, we would see different patterns:

• Rents vs. Prices: Purchase prices rose 6x, but rents only tripled. Rent reflects the value of shelter, while price reflects the availability of credit.
• Building Approvals: These have increased by 55% over 30 years, largely keeping pace with population growth.
• Gold Standard: When measured in gold, Sydney house prices have actually fallen by about 12% since 1995.

4. The “K-Shaped” Future

As AI suppresses consumer inflation, interest rates may stay lower for longer, fueling a divide:

• Asset Owners: Wealth grows alongside the expanding money supply.
• Wage Earners: Incomes stagnate while the cost of shelter continues to rise.
• The Geographic Split: Inner-ring suburbs (e.g., Northbridge at 7.7% CAGR) are pulling away from mortgage-dependent outer suburbs (e.g., Liverpool at 0.5% CAGR).

5. A Potential Solution: The Singapore Model

Singapore maintains a 90% homeownership rate compared to Australia’s 67%. They achieve this by:

• Taxing Investment: High stamp duties on second (20%) and third (30%) properties.
• Capping Credit: Strict limits on Loan-to-Value ratios and debt servicing.
• Prioritising Shelter: Treating housing as a home first and a financial vehicle second.

About this Research and the Author

The author is a Senior Data Analyst who combines data analytics expertise with a background in economics and finance. This helps them look past general market commentary and study the raw data directly to understand the macroeconomic forces driving long-term property cycles. Specifically, they use 35 years of NSW Valuer General data to identify macro trends and anomalies in the Australian housing market.

These articles were born out of a 35-year analysis of Blacktown, NSW, which was shared on Reddit. The response to the first post was huge, with hundreds of people asking for similar deep dives into their own suburbs and broader questions about how this data can be used to understand the market.

After listening to these suggestions, the author built a web tool to handle the requests. While they charge a small subscription to keep the site running, the Blacktown demo remains free for anyone curious about how 35 years of interest rates and debt have shaped that suburb.

The author’s website, AusPropertyInsights.app, allows users to zero in on specific street, building, and suburb-level data.

Further discussion on: Reddit

Used with permission.

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