The mistake is that although an individual can ‘cash in’ the benefits of higher house prices by downgrading their house, if the housing stock is fixed that individual’s gain is a loss for the person buying their house. Higher house prices are great for the old, and bad for the young, but there is no aggregate wealth effect.
As a result, a good deal of current analysis looks at the impact house prices may have on collateral, and therefore on house owners ability to borrow. Higher house prices in effect reduce a liquidity or credit constraint. Agents who are credit constrained borrow and spend more when they become less constrained. There is no matching reduction in consumption elsewhere, so aggregate consumption rises. If it turns out that this was a house price bubble, the process goes into reverse, and we have a balance sheet recession. In this story, it is variations in the supply of credit caused by house prices that are the driving force behind consumption changes. Let’s call this a credit effect.
There is clear US evidence that house price movements were related to changes in borrowing and consumption. That would also be consistent with a wealth effect as well as a credit constraint story, but as we have noted, in aggregate the wealth effect should wash out.
Or should it? Let’s go back to thinking about winners and losers. Suppose you are an elderly individual, who is about to go into some form of residential home. You have no interest in the financial position of your children, and the feeling is mutual. You intend to finance the residential home fees and additional consumption in your final years from the proceeds of selling your house. If house prices unexpectedly fall, you have less to consume, so the impact of lower house prices on your consumption will be both large and fairly immediate. Now think about the person the house is going to be sold to. They will be younger, and clearly better off as a result of having to fork out much less for the house. If they are the archetypal (albeit non-altruistic) intertemporal consumer, they will smooth their additional wealth over the rest of their life, which is longer than the house seller. So their consumption rises by less than the house seller’s consumption falls, which means aggregate consumption declines for some time. This is a pure distributional effect, generated by life-cycle differences in consumption.
In aggregate, following a fall in house prices, the personal sector initially moves into surplus (as the elderly consume less), and then it moves into deficit (as the elderly disappear and the young continue to spend their capital gains). In the very long run we go back to balance. This reasoning assumes that the house buyer is able to adjust to any capital gains/losses over their entire life. But house buyers tend to be borrowers, and are therefore more likely to be credit constrained. So credit effects could reverse the sign of distributional effects.
This is a clear case where micro to macro modelling, of the kind surveyed in the paper by Heathcote, Storesletten and Violante, is useful in understanding what might happen. An example related to UK experience is a paper by Attanasio, Leicester and Wakefield (earlier pdf here). This tries to capture a great deal of disaggregation, and allows for credit constraints, limited (compared to the Barro ideal) bequests and much more, in a partial equilibrium setting where house price and income processes are exogenous. The analysis is only as good as its parts, of course, and I do not think it allows for the kind of irrationality discussed here. In addition, as housing markets differ significantly between countries, some of their findings could be country specific.
Perhaps the most important result of their analysis is that house prices are potentially very important in determining aggregate consumption. According to the model, most movements in UK consumption since the mid-1980s are caused by house price shocks rather than income shocks. In terms of the particular mechanism outlined above, their model suggests that the impact of house prices on the old dominate those on the young, despite credit constraints influencing the latter more. In other words the distributional effect of lower house prices on consumption is negative. Add in a collateral credit effect, and the model predicts lower house prices will significantly reduce aggregate consumption, which is the aggregate correlation we tend to observe.
But there remains an important puzzle which the paper discusses but does not resolve. In the data, in contrast to the model, consumption of the young is more responsive to house price changes than consumption of the old. The old appear not to adjust their consumption following house price changes as much as theory suggests they should, even when theory allows a partial bequest motive. So there remain important unresolved issues about how house prices influence consumption in the real world.