In this study, we document two features that have made Saudi Arabia different from other oil producers. First, it has typically maintained ample spare capacity. Second, its production has been quite volatile even though it has witnessed few domestic shocks. These features can be rationalised in a general equilibrium model in which the oil market is modelled as a dominant producer with a competitive fringe. We show that the net welfare effect of oil tariffs on consumers is null. The reason is that Saudi Arabia's monopolistic rents fall entirely on fringe producers.
This paper investigates how, in a heterogeneous agents model with financial frictions, idiosyncratic individual shocks interact with exogenous aggregate shocks to generate timevarying levels of leverage and endogenous aggregate risk. To do so, we show how such a model can be efficiently computed, despite its substantial nonlinearities, using tools from machine learning. We also illustrate how the model can be structurally estimated with a likelihood function, using tools from inference with diffusions. We document, first, the strong nonlinearities created by financial frictions. Second, we report the existence of multiple stochastic steady states with properties that differ from the deterministic steady state along important dimensions. Third, we illustrate how the generalized impulse response functions of the model are highly state-dependent. In particular, we find that the recovery after a negative aggregate shock is more sluggish when the economy is more leveraged. Fourth, we prove that wealth heterogeneity matters in this economy because of the asymmetric responses of household consumption decisions to aggregate shocks.
This paper investigates how, in a heterogeneous agents model with financial frictions, idiosyncratic individual shocks interact with exogenous aggregate shocks to generate timevarying levels of leverage and endogenous aggregate risk. To do so, we show how such a model can be efficiently computed, despite its substantial nonlinearities, using tools from machine learning. We also illustrate how the model can be structurally estimated with a likelihood function, using tools from inference with diffusions. We document, first, the strong nonlinearities created by financial frictions. Second, we report the existence of multiple stochastic steady states with properties that differ from the deterministic steady state along important dimensions. Third, we illustrate how the generalized impulse response functions of the model are highly state-dependent. In particular, we find that the recovery after a negative aggregate shock is more sluggish when the economy is more leveraged. Fourth, we prove that wealth heterogeneity matters in this economy because of the asymmetric responses of household consumption decisions to aggregate shocks.
We propose a general equilibrium framework with financial intermediaries subject to endogenous leverage constraints, and assess its ability to explain the observed fluctuations in intermediary leverage and real economic activity. In the model, intermediaries (“banks”) borrow in the form of short-term risky debt. The presence of risk-shifting moral hazard gives rise to a leverage constraint, and creates a link between the volatility in bank asset returns and leverage. Unlike TFP or capital quality shocks, volatility shocks produce empirically plausible fluctuations in bank leverage. The model replicates well the fall in leverage, assets, and GDP during the 2007–2009 financial crisis. (JEL D82, E44, G01, G21, G32)
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