We develop a machine-learning solution algorithm to solve for optimal portfolio choice in a detailed and quantitatively-accurate lifecycle model that includes many features of reality modelled only separately in previous work. We use the quantitative model to evaluate the consumption-equivalent...

This paper proposes a global algorithm to solve a large class of nonlinear continuous-time models in finance and economics. Using tools from machine learning, I recast problem of solving the corresponding nonlinear partial differential equations as a sequence of supervised learning problems. To...

In this paper, I show how gradient-based optimization methods can be used to estimate stochastic dynamic models in economics. By extending the state space to include all model parameters, I show that we need to solve the model only once to do structural estimation. Parameters are then estimated...

We study the role of asset revaluation in the monetary transmission mechanism. We build an analytical heterogeneous-agents model with two main ingredients: i) rare disasters; ii) heterogeneous beliefs. The model captures time-varying risk premia and precautionary savings in a setting that nests...

This paper studies the role of wealth effects in the monetary transmission mechanism in New Keynesian models. We propose a decomposition of consumption that extends the Slutsky equation to a general equilibrium setting. Wealth effects, and their amplification in general equilibrium, explain a...

We study default in a multi-firm equilibrium setting with incomplete information. Defaults are modeled to be consistent with the firm's balance sheet and aggregation over firms. Market prices and quantities of risk are derived in closed form. If the number of firms increases, the market prices...