Here’s Why the Market is Exactly Where It Should Be

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I’m not one to predict the market. Frankly, I am a firm believer in dollar-cost averaging.

For those of you who do not know what dollar-cost averaging is, it means continuously purchasing real estate despite market conditions. I will buy one or two properties every year, regardless of whether the market is up or down. Over time, this will average out, so that the state of the market has a limited impact on my overall portfolio.

Predicting the Market

However, I talk to a lot of real estate investors and real estate investors to be. What I gather from many of them is that they want to wait to buy until the market crashes again. My response to that is, “how do you know when the market is going to crash?”

You don’t. You can’t know. One of the smartest investors to ever grace this earth—Warren Buffett—has even said, “I don’t know anyone—or anyone who knows anyone—who can consistently time the market.”

While I stand by my initial point, I did decide to do a bit of research on the U.S. real estate market as a whole. I was curious to see if these people saw something. Were there any indicators showing a potential decline in the market? I know that markets differ based on each city and town. I am also aware that there are thousands of variables you can look at when determining market health. This article is meant to show a more holistic picture with some of the most common metrics used.

I also realize that there are unlimited external factors that could cause the market to tank or spike, but based on current known conditions, I want to understand in what direction the market will likely go.

What did I find? I found that the overall market is exactly where it should be — or perhaps a bit below where it should be. There are no signs of tremendous growth, and no signs of an impending crash.

Let’ts take a look.

Population vs. Properties Sold 

First, let’s take a look at comparing the U.S. population against the amount of properties sold. In this graph, the “U.S. Population” (blue) uses the left axis and the “Properties Sold” (orange) uses the right access.


All data is taken from the U.S. Census.

Analyzing the Data

All else being equal, as the U.S. population increases, the amount of people eligible to purchase homes increases — and therefore the amount of properties sold should also increase. As you’ll see in this graph, however, this is not the case. There are clearly many other factors that cause these spikes and troughs.

In the 1980s, record high interest rates made it less affordable for people to purchase homes.

In the early 1990s, the stock market crash of 1987 had destroyed many Americans’ savings, making it more difficult for them to buy homes.

Related: Worried About a Stock Market Crash? Prepare for the Bear Without Fear

From the early 1990s until the mid-2000s, the real estate industry realized impressive growth. Until 2007, when relaxed lending standards allowed people to purchase homes they could not afford, ultimately causing them to default on their loans.

After reaching historic lows, the market has continued to climb back. Despite many people thinking house values are artificially high, the amount of homes sold is about equal to the amount of homes sold in the mid-1990s when the population was about 60 million people smaller. To me, this suggests that demand has not met supply, and prices should continue to increase (albeit at a slower rate).

Population vs. New Construction

But what about all of the new construction? The increased supply would meet much of the demand, causing prices to stagnate or even decline. Let’s take a look. Population (orange) uses left axis and New Builds (yellow) uses the right.


All data is taken from the U.S. Census.

As you can see here, despite there being an ever-increasing population, the amount of new builds has declined over the past 50 years. Why? Figuring this out would take a whole new study within itself and is beyond the scope of this article.

Over the past 10 years, as the economy has recovered, you will see that the number of new builds is steadily increasing. It is increasing much faster than the U.S. population, but it still has a way to go. If this trend continues, it may cause a decline in housing prices.

As of right now, the new builds have not quite caught up to the population. However, this metric is the one I am most worried about. Especially as the average age of homeowners increases — with millennials having a higher propensity to rent.

Properties Sold vs. Interest Rates

Let’s take a look at the properties sold compared to the interest rates. Typically, interest rates and properties sold are inversely correlated. In other words, as interest rates rise, properties sold decreases. Why? Because all else remaining equal, a higher interest rate means a higher monthly payment — which means it’s harder to afford a house at the same price if interest rates had been lower.

All data is taken from the U.S. Census.

If you look at the graph above, you’ll notice that from their peak in the 1980s, mortgage rates have continuously declined. When you compare this to properties being sold, interest rates are still at a historic low — meaning people will likely continue to be able to purchase housing. This increases the demand for housing. And with increased demand comes increased (or steady) prices.

While interest rates will likely rise in the next few years, there is still a ways to go before it has a significant impact on the amount of properties sold. Once the increased interest rates cause the properties sold to decline, I believe we will see a decline in housing valuations.

Median House Price Over Time

The biggest reason why I believe people are quick to jump to the conclusion that the housing market is inflated is that prices are higher than they have ever been. As they should be.

 From 1968 through 2009, homes, on average, appreciated 5.4 percent per year. If we assume the same trajectory (see chart below), you will see that property values are almost exactly where they should be.

All data is taken from the U.S. Census.

The reason why it feels like the market is artificially inflated is that it is recovering from one of the greatest recessions in U.S. history. Over the past few years, real estate prices have just regressed to the mean.

Related: Yes, I’m Afraid of a Real Estate Bubble — But I Continue to Invest Anyway. Here’s Why.


While we could go in and debate every point, many of the market health indicators suggest that the market is exactly where it should be, or it may even have room to grow.

Nothing suggests that there is an impending crash, except for the fact that house prices have risen dramatically over the past 10 years. But remember, they have risen from all-time lows.

Going forward, I suspect that we will see mild ups and downs, similar to those in the previous 75 years before 2008 (and after the Great Depression).

I do not believe we will ever see housing prices drop to 2008-to-2012 levels again.

In other words, if you continue to wait for the market to crash, you may grow very old waiting.

Despite this article defending the point that we are actually in a very normal market, I do want to reiterate my initial point: Trying to time the market is unwise. It’s akin to gambling. Take advice from the most successful investor of all time, Warren Buffett — don’t try to time the market.

What do you think?

Do you agree or disagree with my market analysis? Share your thoughts below!

About Author

Craig Curelop

Craig Curelop, aka thefiguy is an aggressive pursuer of financial independence. Starting with a net worth of negative $30K in 2016, he has aggressively saved and invested to become financially independent in 2019. From sleeping on the couch and renting out his car, he was able to invest in two house hacks in Denver and a BRRRR in Jacksonville. He plans to continue to investing in both Denver and Jacksonville for the years to come. Craig's story has caught the attention of several media outlets, including the Denver Post, BBC, and many other real estate/personal finance podcasts. He hopes to inspire the masses to grab hold of their finances and achieve financial independence. Follow his story on Instagram @thefiguy!


  1. Costin I.

    So, looking at your charts, at the peak of 2006 – supposedly there was 2,000K new builds for a total of 1,2000 properties sold?? Basically, roughly 800K new houses didn’t sell?

    And same idea, looking at 2009-2012 time frame, the new builds were in the 500K-750K houses, but total properties sold, for the same period, was under 400K annually?

    Or, in 1991 – new builds were about 1250K, but total sold about 600K? And despite the glut of 600 unsold, following years they built more and sold more?

    That looks fishy to me…

    • Costin I.

      If you were to interpolate (average) the properties sold, you have a 600K to 650K range.
      If you interpolate the new builds, you’ll see an average of probably 1400K.
      That means, on average, every year there were 700K+ new houses unsold – where is this accumulation of new builds?? I call B.S. – something is wrong with your charts.

      • Craig Curelop

        Hey Costin,

        That is a very astute analysis and I’m not sure I have a great answer for you. However, if you look at the years following the ones you mentioned, you’ll see that the properties sold increase at a higher rate than the properties built. I presume that is where the catch up is happening.

        • Costin I.

          I gave you those samples/years because they were easy to spot as the grid lines intersect the chart lines and their corresponding year in the X-axis. But the charts actually move in similar pattern, almost parallel, so the discrepancy applies all over. So there is something fishy with the numbers or the interpretation, or both.
          I actually went and downloaded the data myself – I think you are using in one chart the New Residential Construction Total Units (SFR and MF) and in the other New Residential SFR Home Sales.

        • Craig Curelop


          You are right in that I included multi-family properties in the new build. We will get this chart fixed ASAP. However, it does not change the story or any of my points at all.

          The trends are still the same.

        • Costin I.

          Semantics. Interpolation is an estimation of a value within two known values in a sequence of values. Polynomial interpolation is a method of estimating values between known data points. When graphical data contains a gap, but data is available on either side of the gap or at a few specific points within the gap, interpolation allows us to estimate the values within the gap.

          Play with the chart in Excel and add a trend line – that is an interpolation.
          It doesn’t change the problem – the new builds are more than new sold, and the glut grows at a geometrical rate. Those numbers do not make sense – we should be awash in new unsold houses according to the numbers.

        • Darin Anderson

          The numbers here are a bit off and they are also a bit misleading.

          First, the new builds includes new apartments, it is not just single family. Single family houses never got over about 1.8 million.

          New solds obvioulsy doesn’t include the apartment inventory.

          It’s also worth noting that these sales numbers presumably are for new home sales. Existing home sales are 4-5 times higher than these numbers so total sales in a year are over 6 million units and were over 8 million units at the peak in 2005.

          Also the numbers could be completions or starts. Starts get way ahead of completions and then sit when the market turns. So the houses available for sale at the peak never real equal the number of starts. These numbers are probably starts not completions.

          Given that sales will lag starts on the way up and be ahead of starts on the way down and the fact that these numbers include apartments, I think things do line up better than might be expected.

          You can see charts on total starts, single family starts, sales, etc here:

  2. Proncias MacAnEan

    Wouldn’t a chart comparing household income to house prices be relevant here. A 5.4% increase in prices is great, but if wages aren’t keeping up with that something has to give. Although if supply is low we can have historic or greater demand even with a smaller number of buyers.

    • Vaughn K.

      THIS. Average median income to sales price ratio. I am amazed I have not even seen it mentioned on BP anywhere thus far in my poking around on the site. It is one of those weird random numbers that seems to never change, so some see it as an almost magical golden rule for real estate pricing.

      Things I have read before:

      1. That the average range that a normal home sells for is 5-6 times the average income in the area, basically like clockwork. This is the long term stable range that pricing ALWAYS falls back into. That is to say it is the sustainable price in an area, not over or under valued. If it’s above that it’s probably overvalued, and if it’s below it’s probably undervalued, due to whatever factors are effecting things at that time. Barring any obvious, glaring reasons for being above/below (think Detroit vs San Francisco) it will always return to those values.

      2. Some economists have studied this and amazingly found it holds true back to at least the 1700s in the USA/Europe, although others claim they can verify it back much further. This is pretty incredible given the differences in how homes are bought/sold. Think paying cash or 5 year balloon mortgages being the main ways in the past, 30 year mortgages now. The theory being that’s just what people tend to be able to pay for a place to sleep, as they will always dedicate a certain percentage of their income to lodging.

      3. Even so called “global cities” which some people claim don’t adhere to this rule, in fact DO adhere to it. When they enter correction phases they go back inside the ratio the same as anywhere else. NYC for instance has a habit of staying towards the higher end (6x income) even in corrections, and pushing beyond in booms, but it still falls back into the range like anywhere else. At best you might be able to say a global city should be in the 6-7x income range, but really not much more according to data.

      That said, nationally we’re still almost perfectly in line with this “golden rule.” However many of the hot markets are WELL outside the range, so I don’t think it will last. Seattle is pushing for 10x ratio, SF and other parts of the Bay Area are trying for 20x! Other trendy cities vary, but are generally hotter than incomes warrant.

      You can get more complex with things, like the hourglass society argument of how the income is distributed matters, etc but the golden ratio still seems to be holding true for now with whatever income distribution changes have happened.

  3. Jon Wu

    You’re basically saying “the market has grown by 5.4% a year for the last 50 years…WOW! It looks like the market is exactly where it should be!” That is horrifically circular logic.

    What’s going to crash the housing market is an overall economic slowing, like the deleveraging cycle we saw during the last recession. “But population growth! People need places to live!” The drivers of home starts are economic optimism, not bodies. More optimism = greater leverage = greater purchasing power = more homes.

    So this article basically misses the whole point, which is that new home starts and real estate pricing is a symptom not of these factors, but of the health of the economy as a whole. Any prediction must start with the economic fundamentals and where we are in THAT cycle, not long-term housing dynamics.

    • Frans Swaalf

      Hi Graig, thanks for posting this thought provoking numerical breakfast for us here in Amsterdam.

      I might have to agree with Jon Wu however, that your article may contain some wishfull thinking.
      Assume for instance in the median US house prices-analysis you did that instead of 2009, you picked the year 2006 (before the crash) as the second data point.
      The median house price in 2006 was about $250,000.
      Starting again with 1968, the average yearly return (or IRR) from 1968-2006 would be around 6,25%. Assume you would have used this percentage and drawn the corresponding line in the graph. Assume now that we are in early 2007 and you would try to make the same argument: prices and market are exactly were they should be. The graph would confirm that and nobody would be any the wiser for the imminent crash. The nature of a crash is obviously a violent return to a level below historic averages..

      As I am invested in the US urban market, as a lot of us are, I also would like to see confirmation that things are moving up. But history will repeat itself. So always cover your bets, or better, use declining prices to buy cheap.

      Kind regards, Frans

  4. Eliseo Magallon

    Craig Curelop,

    Very insightful sir! I appreciate the post a lot and I will be taking your advice on buying basically every year no matter what. Deals will always be there just need to search hard and not let up. But when the market does “crash” I sure hope I have good friend with cash or I have cash to buy those properties up! Weehoo!

    – Eliseo

  5. Vaughn K.

    As I said in a post above: The sales price to income ratio is where it’s at, assuming one isn’t in a large recession, or other extreme situations. 5-6 average income in an area dictates housing prices more accurately than just about any other metric.

    By those numbers most of the country is doing perfectly fine and is right there in the historical range…

    But coastal and other trendy markets are pushing well beyond the long term average. People are starting to move out of places like San Francisco, NYC, Seattle, etc because it’s too ridiculous to live there. I will be one of them soon!

    I don’t think these hot urban markets have much upside left in them, and I think they have a lot of downside potential in the mid term (2-10 years), even if they have plenty of 30 year upside potential in them. People who don’t know about the “magic” ratio should google it. When I first stumbled upon it I found it to be very interesting reading, and the logic behind why it holds true makes a lot of sense as well. The fact that math backs it all up is what sold me though.

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