There have been several indicators in recent months that Americans are interested in smaller homes. But what if they say they would purchase smaller homes but are still looking at bigger homes? An economist for Trulia.com discusses this:
We asked people to tell us their ideal home size. They’re shunning super-sized homes, the McMansions. Only 6 percent of Americans say their ideal home size is more than 3,200 square feet. Thirty-two percent said they see the ideal home at 1,401 to 2,000 square feet. About 27 percent said 2,001 to 2,600 square feet.
This is partly due to the economic troubles of the recession and recovery. But this could be part of a permanent shift toward smaller homes. And it could reflect baby boomers wanting to downsize and increasing environmental awareness, with some people wanting a smaller environmental footprint.
On the other hand, when we look at the homes that people view on our site — even though only 6 percent of the people in our survey said the McMansion size range was ideal — 27 percent of the property views people are looking at are of that size. So even though people aren’t saying those large homes are their ideal size, they want to see what these homes look like and want to dream big.
This disconnect could be explained in several different ways:
1. Americans look at bigger houses online because it is free. These days, one can look at hundreds of homes and get a good idea what is on the market. Perhaps we would need to ask realtors about what sized homes people actually ask to see.
2. Americans actually do want to buy bigger homes but they know the economic realities and perhaps even the cultural shift and so say they would want a smaller home. As the economist suggests, Americans simply like to dream big. This certainly wouldn’t be the first time that self-reported actions and aspirations don’t match up. If the economy picked up, we could then figure out whether the shift toward smaller homes is real or was a reaction to the economic crisis.
3. Americans want to look at bigger homes because they want the features of the bigger homes in a smaller home.
Time will help us figure out which of these interpretations is most accurate as would more data.
Figures for age, sex, race/ethnicity, education, region and household income were weighted where necessary to bring them into line with their actual proportions in the population. Propensity score weighting was used to adjust for respondents’ propensity to be online. These online surveys are not based on a probability sample and therefore no estimate of theoretical sampling error can be calculated. For complete survey methodologies, including weighting variables, click here.
“Not based on a probability sample” is usually a problem for surveys, even if proper weights are assigned to results. I would like to see some more thorough survey data on some of these issues.