In 2006, I wrote about how my fiancee (my wife now) got a great job promotion in San Francisco. Somewhat reluctantly, I agreed to live more than 10 miles away from my birthplace for the first time in my life. I was 30 years old. I considered it a short-term move. After two years, we’d be eligible to move back and my wife would qualify for some of the top jobs in her field that Boston would have to offer. Sometimes it’s funny how life turns out.
Somewhere along the line, we began to love what is known as “the peninsula” – an area 10-15 miles south of San Francisco. When we first moved here, I remember having an application on my cell phone that would send me a text message of the week’s weather. It was convenient in Boston when you had to know whether it was going to snow or if you’d have a sudden heat wave. I deleted that application after about a month of living in the peninsula – I didn’t need to be reminded that it was going to be 75-85 and sunny every day.
Given the change of heart, we decided to look into whether it makes sense to rent or buy in the bay area. Real estate prices have dropped a lot recently. With mortgage rates low, it sure seems like the time to take advantage and buy. My wife thought it might be the right the time… how much could things continue to drop? I said, “I think I remember seeing some math on this once, let me see what I can dig up.” Fortunately, I remembered that Erica had written an article about whether it is better to buy or rent. In it she gave a couple of metrics:
- The average house should cost between 100x-150x monthly rent
- The average house should cost between 3-5x median annual income
Looking at the first metric, our $2100 rent now should buy a home between $210,000 and $315,000. However, in my area, it seems that townhouses equivalent to our apartment still run around $600,000. Granted that’s significantly less than the $783,888 asking price of this 1100 sq. ft. “fixer-upper” I found a year ago – it’s still not what I’d call a bargain by this metric.
Moving to the second metric… City-Data says my zip code has a median house $83,809 – projecting to a home price between $251,427 and $419,045. That’s a little closer to the $600,000, but it is still far from the national average. Again buying a house doesn’t make sense with this metric.
Why are these two ratios important?
If the cost of buying a house is much more than the cost to rent one, people will likely realize the value of renting. Some people have bought into the myth that “renting is throwing away money”, but I always say that I’d rent a mansion in my preferred location for one dollar a year without batting an eye. Throwing away that dollar allows me to save and invest my other dollars. I think it’s only a matter of time before everyone realizes that and discards the conventional wisdom.
The second metric could be an indication of how people potentially paid too much for a house that their income couldn’t support. In other words, if a $83,000 income in other parts of the country supports a $350,000 home, what makes my location in California different?
What about affordability?
There’s another ratio called the affordability index. From what I’ve found it measures the actual monthly cost of the mortgage to take-home income. A number over 100 typically means that people have more than enough money for a median price home. A number less than a 100 typically means that they don’t have enough. According to the California Building Industry Association San Francisco and the peninsula have an affordability index of 16.6 as of Q3 2008 (PDF). But it’s on an uptrend… and in about 20 more quarters of similar gains, it might approach “affordability.”
It’s very possible that the rent vs. buy in this area of California never get back to the national levels. It seems that people are simply willing to pay more to live in this area of the country. Nonetheless, I can’t see the value of buying in this local market – yet. I’ll continue to evaluate the numbers, perhaps using this handy calculator of Buy or Rent from the New York Times.
What about you? Did you do this kind of analysis before you decided whether it was worth buying or not? I realize in much of the country the exercise won’t lead to the big difference I found. It’s still good practice to run the numbers to make sure.