Have you ever found yourself scratching your head, trying to predict the housing market’s next twist? 

Mainly when the crash prophets crawl out of their corners again, like last year and at the beginning of 2023.

They are back again, and they postponed the housing crash to 2024.

But what if I told you there’s a tool to help get the bias out of these influencers’ opinions and assessments?

No, it’s not a crystal ball. 

It’s ChatGPT. 

Imagine having a buddy who can sift through tons of housing data, analyze patterns, and give you insights on potential crashes. 

Sound too good to be true? 

Stick around. 

Let’s dive into how ChatGPT could be the game-changer and help you determine which lead generation to focus on depending on the type of market it forecasts.


What Are Housing Crashes?

“Housing Crash” is another term for “housing market crash”. 

In simple terms, it is when house prices tumble down faster than a kid on a playground slide. 

Imagine a bustling real estate market where prices keep rising and everyone’s eager to buy. 

Then, that upward climb suddenly halts, and prices begin to fall. That’s the essence of a housing crash.

And the ripples of this crash? They’re felt wide and deep:

Dipping House Prices: Sellers might have to settle for less than they hoped.  

More Foreclosures: Some homeowners, sadly, can’t keep up with their mortgage payments. Their homes get taken away.

A Broader Economic Impact: Construction workers, real estate agents, and even the local cafe where agents grab their coffee – all feel the pinch.


What Causes a Housing Market to Crash?

To understand better what a housing market crash is, let’s look at its causes.

And there are many of them.

Housing markets are influenced by many factors, many of which can vary based on region, culture, and specific market conditions. 

I created a comprehensive table below with direct and indirect factors that can influence housing market crashes.

Type of InfluenceFactors
Direct Causes- Too Many Houses, Not Enough Buyers
- Loan Troubles
- Economy Takes a Hit
- Previous Price Inflation (Housing bubbles)
- Overleveraging
- Banking Practices (e.g., subprime lending)
- Interest Rate Hikes
- Tightening Credit Standards
- Mass Unemployment
Indirect Causes (Contributing Factors)- Public Perception
- Global Events
- Demographic Changes
- Technological Advancements
- Natural Disasters
- Changes in Tax Laws
- Political Instability
- Cultural Shifts
- Consumer Confidence
- Health Pandemics
- Foreign Investment Patterns
Both (Direct & Indirect)- Government Policy
- Infrastructure Developments
- Speculation
- Land Restrictions or Zoning Laws
- Environmental Laws
- Educational Opportunities
- Transport Connectivity
- Crime Rates

As you can see, there are many, many different factors involved, and even this list isn’t exhaustive. 

The reality is that the housing market is affected by an interplay of local, national, and global factors, some of which can be unforeseen. 

So, predicting a housing market’s trajectory often involves closely monitoring these factors and their interrelationships.

Let’s just keep this in mind for later…

I also applied the Pareto Principle to the above factors.


It’s a great principle to filter out the important from the less important.

It’s often known as the 80/20 rule, suggesting that roughly 80% of the outcomes are determined by 20% in many situations.

So I wanted to know the 20% of the above factors.

Applying it is challenging because of the complexity and multifaceted nature of real estate markets.

Nevertheless, based on historical data, I could identify some factors that tend to play major roles in most housing crashes.


The Top 20% of Factors Influencing 80% of Housing Crashes

Too Many Houses, Not Enough Buyers: A significant imbalance between supply and demand tends to be a primary catalyst for price declines.

Economy Takes a Hit: Economic recessions or mass unemployment events drastically impact consumers’ ability to buy homes.

Loan Troubles: Whether due to high-interest rates making mortgages expensive or risky lending practices leading to widespread defaults, loan issues have historically been central to housing crashes.

Overleveraging: Widespread borrowing beyond means, often influenced by easy credit conditions, has been a precursor to several housing downturns when borrowers default en masse. 

In this context, you may remember the 2007-2008 financial crisis.

Speculation: When buying homes becomes more of an investment strategy rather than a place to live, and prices are driven up without foundational economic support, it can create bubbles that burst.

Again, remember that while these factors have been common triggers in many housing market downturns, one or all don’t guarantee a crash. 

Housing markets can be resilient, and various mitigating factors can offset these influences.


Why Financial Experts and Some Real Estate Influencers Assume a Housing Crash 2024

A few months back, many media outlets talked about a housing recession (an invented term). 

I covered this and how you can adapt your marketing strategy to that in this article.

One of my conclusions was that it was more hype and fallacious interpretations than factually based. 

Yes, some indicators pointed to a potential recession, but not enough.

Now, it’s a housing crash that supposedly will hit in 2024.

Let’s see in the following sections if it’s a similar phenomenon to when everyone talked about the “housing recession.”

And I will use ChatGPT to assess and forecast the future trend.

Now, what do some financial experts currently say about a housing crash in 2024?

Let’s take this video from Warren Buffet, for instance…

Warren Buffett warns in it of a potential U.S. real estate crisis due to several reasons:

Debt-Driven Surge: Over the past 15 years, there’s been a whopping $1.4 trillion surge in real estate, thanks to those enticing low-interest rates making people borrow more.

The Interest Rate Climb: Buffett thinks if those rates climb up, the monthly payments might become too steep, especially for those commercial property owners with flexible-rate loans.

Dipping Property Values: Higher interest rates could mean properties taking a value dip, sometimes even below their loan amounts.

Risk in Commercial Loans: Banks can’t go after their other assets if someone defaults with commercial real estate loans. 

This setup puts banks on thin ice.

Ripple in the Economy: Those neighborhood banks could suffer significant losses from dicey loans, hitting small and mid-sized businesses and putting brakes on economic growth.

Shift in Property Ownership: If foreclosures kick in, properties might switch owners, leading to downtown spots possibly losing their charm.

This one not only talks about a real estate crisis but a full-on crash in 2024…

Kevin has the following assumptions:

Those 2008 Vibes: Think of high loan-to-value ratios, those tricky neg-am loans, and people buying homes like they’re going out of style. These factors played a big role in the 2008 crash.

Cold Feet Syndrome: Today’s market has a chilly air of hesitation. 

People are getting cold feet because homes are pricey, making some wonder if a storm’s brewing.

A Rollercoaster of Rates: Places like Arizona and Idaho? 

They felt the jolt of rising interest rates, dipping home prices by about 20%. However, things seem to be steadying now. 

Fewer Red Flags: Unlike in 2008, distressed sales like foreclosures aren’t waving big red flags right now. This time, it might be a different ball game.

Finally, the video maker of the following video, titled “Housing Market Collapse 2024,” has similar assumptions that let him believe in a crash in 2024.

And here are his assumptions…

Mortgage Rates on the Rise: The creator thinks these rates are heading up, making monthly payments bigger and homes less wallet-friendly.

Slim Pickings in Housing: A historic low in available homes, causing fierce competition and sky-high prices.

Clinging to Low Rates: Many homeowners are already locked in super-low mortgage rates, making them less keen to sell. This adds to the low housing supply.

The Equity Worry: Homeowners might see their home’s equity shrink if prices drop to lure in new buyers at these high rates.

Déjà vu from 2008: Today, spotting issues in new home construction feels like warning signs from before the 2008 crash.

The Income Gap: With many average earners finding homes too pricey, many folks might get sidelined from buying.

Dip in Home Sales: The latest data shows fewer homes selling, hinting at a shaky market.

Experts’ Rate Warning: Some pros predict mortgage rates might even hit 8%, making dream homes even dreamier for many.

2008 Flashbacks: Current market vibes feel eerily familiar to the shaky period leading up to the 2008 crisis.

Stimulus Aftereffects: Government handouts and low rates might’ve increased home prices. 

Now, the market might need to brace for the ripple effects.

Now, let’s sum up and unite all the assumptions of the above three sources in one overview table:

Factor CategoryAssumptions
Financial Dynamics- $1.4 trillion debt-driven surge over the past 15 years due to low-interest rates.
- Risk with commercial loans; banks vulnerable if defaults occur.
- Potential for homeowners to lose equity with dropping prices.
- Rising mortgage rates leading to bigger monthly payments.
- Expert warnings of rates possibly reaching 8%.
- Impact of government stimulus on increasing home prices.
Market Behavior- A decline in available homes, leading to intense competition and price increase.
- Hesitation and reluctance in the market due to high prices.
- Decrease in home sales indicating a potential unstable market.
- Many homeowners are holding onto properties due to currently low mortgage rates.
Historical Comparisons- Current conditions reminiscent of pre-2008 vibes.
- Challenges such as high loan-to-value ratios and aggressive buying behavior that were prevalent before the 2008 crash.
- Unlike 2008, fewer distressed sales like foreclosures now.
- New home construction issues similar to early signs before the 2008 crash.
Economic Implications- Possible steep climb in interest rates causing affordability concerns, especially with adjustable-rate loans.
- Local banks might incur losses, affecting small and medium-sized businesses.
- Areas like Arizona and Idaho already witnessing price drops due to interest rate hikes.
- Income disparities causing homes to be unaffordable for average earners.


How to Assess Future Trends With ChatGPT in an Unbiased Way, Including Housing Crashes

While keeping the above assumptions as still to be fact-checked in mind, let’s continue with ChatGPT and how it can help you assess future housing trends unbiasedly.

The latter helps understand some of the crash-prophets without getting into panic mode.

You never know why, for example, Buffet talked about that. 

Could some of his investments profit from a housing crash? 

Maybe he wishes to expand his portfolio a bit with real estate…We can’t know for sure.

Well, at least ChatGPT doesn’t plan to buy cheap real estate for now, so let’s get into it.

First, we need to design the proper prompt

And I will have Chat GPT act like a futurologist.


It’s someone looking at future possibilities based on current trends, innovations, and disruptions. 

They often employ a multidisciplinary approach to understand and predict the future, drawing from various academic and professional disciplines.

So here is the prompt I will use…


[As a Futurologist employing a multidisciplinary approach, you weave together insights from fields as diverse as economy, real estate, financial analysis, data science, econometrics, demography, environmental science, political science, sociology, history, behavioral economy, and scenario planning to anticipate and analyze future trends and developments. Your expertise lies in the synthesis of varied data points and the application of multidimensional frameworks to envision possible future trajectories. Describe how you integrate insights from these varied disciplines to create holistic future scenarios and identify potential challenges and opportunities. Discuss the intricacies of merging qualitative and quantitative data, the importance of understanding historical contexts, and the challenges of predicting complex systems with many interacting variables. Share examples or case studies where your multidisciplinary approach has illuminated nuanced forecasts or solutions that a more singular approach might have missed. Explain how your expansive methodology provides stakeholders, from businesses to governments, with a comprehensive, layered understanding of the future, preparing them to navigate uncertainties and capitalize on emergent trends.] 

Which data points do you need to forecast the housing market 2024 in three scenarios with assigned odds?


And these are the data points ChatGPT needed from me. 

To avoid duplicating things, I will include the researched information at once.

1) Economic Data

GDP growth rate: 2.1% (source)

Current inflation rate: 3.7% (source)

Projected inflation rates for 2024: 2.5% (source)

National debt levels: $.32.91 trillion (source)

Consumer spending habits: Consumer spending intentions have improved since April but have not yet surpassed the 2021 baseline. Spending intentions within discretionary categories signal weakened spending confidence, with some categories like restaurants and consumer electronics on a longer-term downtrend (source).

Current unemployment rates 2023: 3.8% (source)

Projected unemployment rates in 2024: 4.7% (source)

2) Real Estate Data

Current housing inventory levels in July 2023: 1,100,000 (source)

Average time on the market for homes in August 2023: 46 days (source)

Housing starts issued August 2023: 1,283,000 (source)

Housing permits issued in August 2023: 1,543,000 (source)

Rental vacancy rates August 2023: 1.2% (source)

Average rental prices August 2023: $2,052 (source)

Homeownership rates: 66% (source)

3) Financial Analysis

Current interest rates: 7.31% (source)

Projected interest rates for 2024: 6.8% (source)

Mortgage approval rates August 2023: 62.4% (source)

Mortgage default rates August 2023: 3.37% (source)

Average credit score levels 2023: 714 (source)

Total household debt 2023: $17.1 trillion (source)

Debt per household end of 2022: $101,195 (source)

4) Demography

Population growth U.S. 2023: 0.5% (source)

Migration patterns U.S. 2023: North Carolina and Nevada showed inconsistent migration patterns post-pandemic, with the former switching to growth and the latter to decline. 

Texas, Tennessee, Georgia, and Maine initially grew during COVID-19 but are now declining. 

Major cities like Austin, Houston, Dallas, and others experienced significant population shifts. 

While Austin saw a unique decline in 2022, New York City continues its slow decline from pre-Covid times. 

Changes in migration patterns, influenced heavily by COVID-19, have led to significant economic implications, especially in real estate, with notably affected areas like Austin and New York City. 

Current data suggests mixed future migration trends, with only a few states consistently growing since 2019. 

The pandemic has reshaped the U.S. migration landscape, affecting both population and economic dynamics (source)

Urban vs. rural population shifts U.S. 2023: In 2022, the U.S. rural population grew slightly, reversing past declines. 

Rural counties increased by 56,000 people (0.12%), mainly from migration, which added 206,000 residents. 

This growth was offset by a natural decrease of 150,000 due to a low birth-to-death ratio. 

Major cities saw minor population drops, while medium-sized metropolitan areas grew by 0.76%. 

Remote rural counties, distant from cities, lost population. 

Regionally, growth was prominent in the Intermountain West and parts of the Midwest, with declines in areas like the Mississippi Delta and New York. 

The data comes from the 2022 Census’ county population estimates, defining rural areas as nonmetropolitan counties (source).

First-time homebuyers age groups U.S. 2023: Millennials aged 23 to 31 represent just 18% of homebuyers. Among older millennials, around 40-42 years old, 60% own homes. 

In comparison, at the same age, 73% of the Silent Generation, 68% of Baby Boomers, and 64% of Generation X had homeownership (source).

5) History & Behavioral Economy

Previous housing market booms or busts and their causative factors:

The Great Depression (1930s)

  • Boom: Roaring ’20s saw rapid growth in stock prices and real estate.
  • Bust: The stock market crash of 1929 led to bank failures, widespread unemployment, and a housing market collapse.
  • Causative Factors: Stock market speculation, lax financial regulations, bank runs.

Post-WWII Housing Boom (1940s-1960s)

  • Boom: Surge in housing demand post-WWII, fueled by returning veterans and government incentives like the GI Bill.
  • Causative Factors: Population growth, government incentives, economic prosperity, and increased suburbanization.

Savings and Loan Crisis (1980s-1990s)

  • Bust: A significant number of savings and loan associations failed.
  • Causative Factors: Deregulation, poor lending practices, rapid inflation in the late ’70s and early ’80s, followed by aggressive lending.

Early 2000s Housing Bubble & Financial Crisis (2007-2009)

  • Boom: Rapid rise in housing prices in the early 2000s.
  • Bust: Market collapse starting in 2007, leading to the global financial crisis in 2008.
  • Causative Factors: Subprime mortgage lending, financial instrument innovations like mortgage-backed securities, lax regulatory oversight, and excessive speculation.

Public sentiment regarding investment in real estate: Caution and some hope for stability and renewed investment activity (source).


3 Housing Scenarios Forecasted by ChatGPT for the Housing Market 2024 (Spoiler: No Scenario is a Crash)

After intensely researching the above data points ChatGPT wanted from me, I could finally feed it with about 90% of the required data.

After I gave it all the above data, these are the three housing scenarios it forecasted for 2024…

Housing Scenario 1: Stable Growth (60% Probability)

With the economic data and real estate indicators, expecting a steady, if not robust, growth in the housing market in 2024 is plausible. 

Interest rates are predicted to decrease slightly, potentially spurring more mortgage applications. 

However, the increase in unemployment might offset this.


Housing Scenario 2: Slight Decline (30% Probability)

When we look at the migration trends, with key areas showing decline and the expected rise in unemployment, there’s a possibility of a slight downturn in the housing market. 

The cautious public sentiment around real estate investments reinforces this scenario.


Housing Scenario 3: Rapid Growth (10% Probability)

Given the housing starts and permits data and the historical context of rapid rebounds post-crises, there’s a slim chance of the market experiencing more rapid growth. 

This would depend on other external factors not provided in the data, such as potential government incentives or a significant boost in economic factors.



The U.S. housing market in 2024 is most likely to experience stable growth. 

However, external factors and ongoing demographic shifts could influence outcomes. 

Proper strategies and interventions could foster a positive trajectory, especially in declining regions.


What Real Estate Marketing Strategies to Use for Each Scenario

Now, let’s look into real estate marketing strategies for each scenario.

It’s never a bad idea to be prepared for each, at least for the most likely ones.

When looking at the housing market, you often hear the terms “buyer’s market” and “seller’s market.” 

So, what do these mean?

More houses are available in a buyer’s market than people looking to buy. 

This means, as a buyer, you’ve got the upper hand. 

You can negotiate prices, ask for perks, and take your time deciding. 

Sellers? They might have to drop their prices or make concessions.

On the flip side, a seller’s market is when more people want to buy houses than houses available (that’s where we are currently). 

Here, the seller is king. 

They can set higher prices, and they might get multiple offers. 

As a buyer, you might have to act quickly and be ready to pay a premium.

Now, based on the data from above and the scenarios ChatGPT calculated for its forecast, let’s see where the market might stand:

Real Estate Marketing for the Stable Growth Scenario

This looks like a balanced market. 


Because the demand and supply seem to be in harmony. 

Homes are on the market for an average time, neither too long nor too short. 

While there’s growth, it’s steady. 

So, neither buyers nor sellers have a clear advantage.

Your real estate lead generation efforts can thus be in both areas (thus, also balanced): seller lead generation and/ or buyer lead generation.

Real Estate Marketing for the Slight Decline Scenario (the Soft “Housing Crash” )

This scenario leans toward a buyer’s market. 

Migration trends show a decline in key areas and an anticipated unemployment rise. 

This can result in more houses available as people might look to downsize or relocate. 

Buyers might find they have more options and room to negotiate.

As a real estate pro or realtor, you will thus be more valuable if you can generate buyer leads since sellers will abound.

For this scenario, you may want to read my article “Housing Recession Blueprint,” where I consider exactly this scenario for real estate lead generation.

Real Estate Marketing for the Rapid Growth Scenario

This is a sellers’ market. 

The significant growth indicates high demand. 

Remember, sellers can set their prices when there’s high demand and not enough supply. 

Buyers might face competition and need to act quickly.

In this case, you want to focus your marketing and lead generation on sellers, as you may do currently.


Generally to Consider for Lead Generation Depending on Real Estate Market Type

The type of market can vary by location. 

A city experiencing a decline doesn’t mean the entire country is in a buyer’s market. 

So, you always want to consider your individual local factors.

This article has been reviewed by our editorial team. It has been approved for publication in accordance with our editorial policy.

Tobias Schnellbacher