Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Three mutually uncorrelated economic shocks that we measure empirically explain 85% of the quarterly variation in real stock market wealth since 1952. We use a model to show that they are the observable empirical counterparts to three latent primitive shocks: a total factor productivity shock, a risk aversion shock that is unrelated to aggregate consumption and labor income, and a factors share shock that shifts the rewards of production between workers and shareholders. On a quarterly basis, risk aversion shocks explain roughly 75% of variation in the log difference of stock market wealth, but the near-permanent factors share shocks plays an increasingly important role as the time horizon extends. We find that more than 100% of the increase since 1980 in the deterministically detrended log real value of the stock market, or a rise of 65%, is attributable to the cumulative effects of the factors share shock, which persistently redistributed rewards away from workers and toward shareholders over this period. Indeed, without these shocks, today's stock market would be about 10% lower than it was in 1980. By contrast, technological progress that rewards both workers and shareholders plays a smaller role in historical stock market fluctuations at all horizons. Finally, the risk aversion shocks we identify, which are uncorrelated with consumption or its second moments, largely explain the long-horizon predictability of excess stock market returns found in data. These findings are hard to reconcile with models in which time-varying risk premia arise from habits or stochastic consumption volatility.

Zonder onderwerpscode: economie

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

To what extent did an expansion and contraction of credit drive the 2000s housing boom and bust? The existing literature lacks consensus, with findings ranging from credit having no effect to credit driving most of the house price cycle. We show that the key difference behind these disparate results is the extent to which credit insensitive agents such as landlords and unconstrained savers absorb credit-driven demand, which depends on the degree of segmentation in housing markets. We develop a model with frictional rental markets that allows us to consider cases in between the extremes of no segmentation and perfect segmentation typically assumed in the literature. We argue that the relative elasticities of the price-rent ratio and homeownership with respect to an identified credit shock is a sufficient statistic to measure the degree of segmentation. We estimate this moment using three different credit supply instruments and use it to calibrate our model. Our results reveal that rental markets are highly frictional and closer to fully segmented, which implies large effects of credit on house prices. In particular, changes to credit standards can explain between 34% and 55% of the rise in price-rent ratios over the boom.