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This paper presents a simple new method for estimating the size of ‘wealth effects’ on aggregate consumption. The method exploits the well-documented sluggishness of consumption growth (often interpreted as ‘habits’ in the asset pricing literature) to distinguish between short-run and long-run wealth effects. In U.S. data, we estimate that the immediate (next-quarter) marginal propensity to consume from a $1 change in housing wealth is about 2 cents, with a final long-run effect around 9 cents. Consistent with several recent studies, we find a housing wealth effect that is substantially larger than the stock wealth effect. We believe that our approach is preferable to the currently popular cointegrationbased estimation methods, because neither theory nor evidence justifies faith in the existence of a stable cointegrating vector. JEL Classification: E21, E32, C22
We estimate the degree of 'stickiness' in aggregate consumption growth (sometimes interpreted as reflecting consumption habits) for thirteen advanced economies. We find that, after controlling for measurement error, consumption growth has a high degree of autocorrelation, with a stickiness parameter of about 0.7 on average across countries. The sticky-consumption-growth model outperforms the random walk model of Hall (1978), and typically fits the data better than the popular Campbell and Mankiw (1989) model. In several countries, the sticky-consumption-growth and Campbell-Mankiw models work about equally well.