Impulse response estimation via flexible local projections

TL;DR

This paper develops a flexible, non-parametric local projection method using Bayesian Additive Regression Trees to estimate impulse responses, capturing non-linear effects in economic shocks.

Contribution

It introduces a novel BART-based local projection approach that generalizes existing models to better capture non-linearities in impulse response estimation.

Findings

Fiscal multipliers are stronger during recessions for contractionary shocks.

Negative financial shocks have disproportionately larger effects than positive shocks.

The method effectively captures non-linear impulse response dynamics.

Abstract

This paper introduces a flexible local projection that generalizes the model by Jord\'a (2005) to a non-parametric setting using Bayesian Additive Regression Trees. Monte Carlo experiments show that our BART-LP model is able to capture non-linearities in the impulse responses. Our first application shows that the fiscal multiplier is stronger in recession than in expansion only in response to contractionary fiscal shocks, but not in response to expansionary fiscal shocks. We then show that financial shocks generate effects on the economy that increase more than proportionately in the size of the shock when the shock is negative, but not when the shock is positive.