We use supervised machine learning to approximate the expectations typically contained in the optimality conditions of an economic model in the spirit of the parameterized expectations algorithm (PEA) with stochastic simulation. When the set of state variables is generated by a stochastic...

We use supervised machine learning to approximate the expectations typically contained in the optimality conditions of an economic model in the spirit of the parameterized expectations algorithm (PEA) with stochastic simulation. When the set of state variables is generated by a stochastic...

This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....

This paper develops a global simulation-based solution method to solve large states space macro-finance models using machine learning. We use an artificial neural network (ANN) to approximate the expectations in the optimality conditions in the spirit of the parameterized expectations algorithm...

This paper develops a simulation-based solution method to solve large state space macrofinance models using machine learning. We use a neural network (NN) to approximate the expectations in the optimality conditions in the spirit of the stochastic parameterized expectations algorithm (PEA)....

Rising inflation in the wake of unprecedented debt financed stimulus packages raises concerns about a looming return of persistent inflation, as governments may be tempted to monetize debt. In this paper, we ask whether governments can use real (TIPS) bonds as part of the government debt...

In the wake of rising inflation in the aftermath of unprecedented debt financed stimulus packages, we ask: Can governments use real bonds (TIPS) as part of their debt portfolio to commit to stable inflation rates? We propose a novel framework of optimal debt management in the presence of sticky...

Although almost nonexistent 15 years ago, there are now numerous papers that analyze models with both aggregate uncertainty and a large number—typically a continuum—of heterogeneous agents. These models make it possible to study whether macroeconomic fluctuations affect different agents...

This paper formally compares the fit of various versions of the incomplete markets model with aggregate uncertainty, relying on a simple Bayesian empirical framework. The models differ in the degree of households' heterogeneity, with a focus on the role of preferences. For every specification,...

Forecasting economic activity during an invasion is a nontrivial exercise. The lack of timely statistical data and the expected nonlinear effect of military action challenge the use of established nowcasting and shortterm forecasting methodologies. In a recent study (Constantinescu (2023b)), I...