We show that machine learning methods, in particular, extreme trees and neural networks
(NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts …

We investigate whether US government spending multipliers are higher during periods of
economic slack or when interest rates are near the zero lower bound. Using new quarterly …

We study how unexpected changes in uncertainty about fiscal policy affect economic activity.
First, we estimate tax and spending processes for the United States with time-varying …

The toolkit adapts a first-order perturbation approach and applies it in a piecewise fashion to
solve dynamic models with occasionally binding constraints. Our examples include a real …

Several prominent economists have argued that existing DSGE models cannot properly
account for the evolution of key macroeconomic variables during and following the recent …

This chapter provides an overview of solution and estimation techniques for dynamic
stochastic general equilibrium models. We cover the foundations of numerical …

Most countries have automatic rules in their tax‐and‐transfer systems that are partly
intended to stabilize economic fluctuations. This paper measures their effect on the …

We evaluate the hypothesis that the zero lower bound (ZLB) constraint was, in practice,
irrelevant during the recent ZLB episode experienced by the US economy (the 2009Q1 …

Using a rich dataset on government spending forecasts in Japan, we provide new evidence
on the effects of unexpected changes in government spending when the nominal interest …

We estimate non‐linear VARs to assess to what extent fiscal spending multipliers are
countercyclical in the US. We deal with the issue of non‐fundamentalness due to fiscal …