Housing Bubble Simulator
You're the housing regulator for 20 years, starting in 2000. Set mortgage rates, lending standards, and speculation limits — quarter by quarter. Watch price expectations feed back into demand. Can you land the market without a crash?
Why housing bubbles look the same every time
The mechanics rhyme across centuries — 1720 London, 1929 Florida, 1989 Tokyo, 2006 Phoenix. Cheap credit lets buyers bid up prices. Rising prices convince more buyers to enter, expecting further gains. Rising expectations pull demand forward, driving prices higher, which reinforces expectations. This is a reflexive loop in Soros's phrase — price expectations feed price levels feed price expectations.
In this sim, the price-to-income ratio drifts with rates and lending standards, but momentum adds a feedback term: recent gains raise expected gains, which raise demand, which raise prices. The stronger the loop, the more the market detaches from fundamentals — until the smallest shock (a rate hike, a delinquency uptick, a headline) breaks belief.
You'll notice tightening early is politically unpopular and looks like a mistake right up to the moment it's obviously not. That's the regulator's dilemma. The Chinese cooling measures of 2010–2013 and the Australian macroprudential rules of 2014–2017 are rare examples of pre-emptive tightening; both are still debated.