Some Independent Research on the Price of Houses
I recently ran across a website that publishes independent economic research, the American Institute for Economic Research. Just think of it, a site about economics that does not have an "axe to grind". According to the website recent analysis indicates that the price of housing is tied to the unemployment rate, the previous year's price, per capita income, and the local population. Well of course, you say, "I could have told you that without all the fancy statistics". If you believe all that then you can stop reading all the articles that are discussing a recovery in housing prices this year and next. It probably is not going to happen in any significant way.
Try out the site, it is actually fairly interesting. AIER.
Our new research shows that the housing market is not likely to recover until the unemployment rate improves.
In our study of 20 metropolitan areas for the years 1990-2009, we found that the linkage between the unemployment rate and housing market is more substantial than expected. Our analysis of the data shows that, on average, a decrease of 1 percentage point in the unemployment rate results in an increase of 3.7 percent in house prices. This suggests that the sluggishness of the housing market recovery is directly related to the slow improvement in unemployment.
No doubt the linkage works both ways. High unemployment deters home buying, and construction employment is affected by a weak housing market. Right now, unemployment is also high in many regions that are less dependent on construction employment. And it appears that the direction of causality runs stronger from jobs to housing. So look to improvements in unemployment as an early indicator of improvement in the housing market.
We uncovered a number of other factors that have an effect on future house prices and may affect prices differently in different regions. By statistical measures, our model did a remarkable job, explaining 97 percent of the variation in house prices, as measured by the Case-Shiller Indices. Our findings are statistically significant at the 95 percent confidence level.
The price of a house last year was an important predictor of this year’s price. This indicates that the housing price has trends—and positive feedback appears likely. On average, a 1 percent increase in price one year will be followed by a 0.8 percent in increase the price the next year. This effect is larger than that reported by Case and Shiller in their 1989 study. They found that a change in price observed over one year tends to predict a change in the price of the following year in the same direction by only 0.25-0.50, and their results are not statistically significant. Our new finding suggests that the market has changed, and momentum, or feedback trading, may have become more prominent in recent years.
The closer relationship of past-year and current-year prices provides additional empirical support to the notion that buying houses on trends can, on average, be successful. Rising prices lead to more rising prices. It also means that declining prices lead to more declining prices.
According to our calculations, real per capita income, a measure of general economic well-being, and population size both have a positive effect on house prices. More money in buyers’ hands’ and more buyers both add up to increased demand for houses. As real per capita income or the population increase by 1 percent, house prices will increase by 0.56 and 0.20 percent, respectively.
Among other variables we tested, the homeowner vacancy rate and the new home starts help to capture the supply side situation. We would expect a higher vacancy rate to be indicative of an excess supply of houses, and it therefore should cause house prices to fall. Our data supports this. A 1 percentage point decrease in the vacancy rate rates, on average, results in a 0.7 percent increase in house prices.
The national homeowner vacancy rate has been declining since the fourth quarter of 2010. For the last quarter of 2011, the homeowner vacancy rate was 2.3, which is below the level of the third quarter of 2006.
All the supply side changes are putting upward pressure on house prices.
We might expect that new housing starts would mean an increase in the supply of housing, and therefore put a damper on house prices. Yet the data tells us that for every 1 percent increase in new home starts, house prices rise by 2.5 percent. This result likely reflects an increase in building in response to better market conditions. Basically, new home starts are the result of higher demand and higher prices.
Similarly, a higher cost of renting tends to raise house prices by making home-buying more financially worthwhile. But recently, the popularity of renting has led to higher rents and lower home prices.