We use an identified factor-augmented vector autoregression (FAVAR) to estimate the impact of monetary policy shocks on the cross-section of stock returns. Our FAVAR combines unobserved factors extracted from a large set of financial and macroeconomic indicators with the Federal Funds rate. We...

We study the role of wealth effects, i.e. the revaluation of stocks, bonds, and human wealth, in the monetary policy transmission mechanism. The analysis of wealth effects requires to incorporate realistic asset-pricing dynamics and heterogeneous households' portfolios. Thus, we build an...

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...

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...

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...