Time series methods for identifying structural economic disturbances often require disturbances to satisfy technical conditions that can be inconsistent with economic theory. We propose replacing these conditions with a less restrictive condition called recoverability, which only requires that the disturbances can be inferred from the observable variables. As an application, we show how shifting attention to recoverability makes it possible to construct new identifying restrictions for technological and expectational disturbances. In a vector autoregressive example using post-war U.S. data, these restrictions imply that independent disturbances to expectations about future technology are a major driver of business cycles.

We propose a model in which the emergence of a single dominant currency is driven by the need to finance international trade. The model generates multiple stable steady states, each characterized by a different dominant asset, consistent with the historical durability of real-world currency regimes. The persistence of regimes is caused by a positive interaction between the returns to saving in an asset and the use of that asset for financing trade. A calibrated version of the model shows that the welfare gains of dominance are substantial, but accrue primarily during the transition to dominance. We perform several counterfactual experiments to assess potential threats to the dollar’s continued dominance.

The literature on belief-driven business cycles treats news and noise as distinct representations of agents' beliefs. We prove they are empirically the same. Our result lets us isolate the importance of purely belief-driven fluctuations. Using three prominent estimated models, we show that existing research understates the importance of pure beliefs. We also explain how differences in both economic environment and information structure affect the estimated importance of pure beliefs.

We formalize the idea that house price changes may drive rational waves of optimism and pessimism in the economy. In our model, a house price increase caused by aggregate disturbances may be misinterpreted as a sign of higher local permanent income, leading households to demand more consumption and housing. Higher demand reinforces the initial price increase in an amplification loop that drives comovement in output, labour, residential investment, land prices, and house prices even in response to aggregate supply shocks. The qualitative implications of our otherwise frictionless model are consistent with observed business cycles and it can explain the economic impact of apparently autonomous changes in sentiment without resorting to non-fundamental shocks or nominal rigidity.