- They are excellent writers,
- They get to the point – and have a clear idea of how important this sort of issue is for trying to understand cyclical phenomenon,
- They have pulled together a large data source consistently, which is a lot of work.
So as you can tell from that, I have a lot of respect for them, their work, and what they are doing. However, I have a giant misgiving about the way they’ve framed the result they have found. Fundamentally they HAVE NOT estimated the causal impact of housing wealth on retail sales/consumption. In the introduction they do not make this claim hunting down an “association” … but by the conclusion this is what they are starting to claim they have done:
The importance of housing market wealth and financial wealth in affecting consumption is an empirical matter … we do find strong evidence that variations in housing market wealth have important effects upon consumption.
These descriptions are veering on causal, which is very inappropriate in a situation where you have an obvious, and likely significant, case of omitted variable bias!
Let us think about this. Demand for housing is similar to demand for other durable goods – when confidence is high, unemployment is low, income expectations are elevated, and financial conditions are good, demand for both will rise, pushing up prices. As a result there are some “third variables” that will drive up demand for both. They cover this off at the end by stating:
Underlying our analysis is an assumption that it is useful to think of causality as running from wealth components to consumption, and not that, for example, the two are determined by some third variable, such as general confidence in the economy. We believe even more strongly that these new results demonstrate that it is useful to think of consumption as determined in accordance with the models we have presented. In consulting this evidence, recall that our measure of housing wealth excludes wealth changes due to changes in the size or quality of homes, changes that are likely to be correlated with consumption changes merely because housing services are a component of consumption. We have alluded elsewhere to others’ evidence using data on individuals that the reaction of consumption to stock market increases is stronger for stockholders than for non-stockholders (Mankiw and Zeldes, 1991), and that the reaction of consumption to housing price increases is stronger for homeowners than for renters. This lends additional credibility to our structural models when compared to a model that postulates that general confidence determines both consumption and asset prices.
To think about this point let’s think about housing. Housing is a durable consumer good. As the price of housing goes up relative to other goods and services, then given other goods and services constitute a “normal good”, spending on other goods and services should fall! Of course, it also constitutes a transfer of wealth from homeowners to renters – and as a result, we have to ask about these separate markets in order to figure out what is going on.
As a result, the point that homeowners and renters behave differently is VERY useful, and justifies the study. However, it in no way supports ignoring omitted variables and just deciding that the model is causal – in fact the way they have dismissed OVB is far too casual, given that there was no effort to deal with it (FE estimators deal with unobserved heterogeneity that is constant through time – this is not the case with our OV’s).
The evidence here appears to point at the fact that changes in house prices are a good proxy for changes in access to credit – hardly surprising given that housing is an asset and a durable consumer good. When trying to understand the tendency of movements in retail spending, and the set of risks going forward for such spending, using house prices as a proxy for a set of “real structural” variables is useful. However, this evidence is far from suggesting a causal relationship – and even further from suggesting that there is anything policy relevant here (as we need to understand the structure of the relationship in order to understand how changing policy settings will change outcomes – a change in policy settings can change the fundamental relationship between variables, think Lucas Critique!).
When the authors began to discuss this as causal, they should have stated that this provides an “upper bound” on the impact of housing wealth on consumption – and that more detailed analysis would be required. They could even have gone further and stated that “given the size of the link, it is more likely that there is a tendency for higher house prices to drive up consumption” – that would have been mildly contentious, but reasonable. As it is, their comments that they are estimating the size of a causal link are misleading.