We use quantile regression methods to estimate the effects of government spending
shocks on output and unemployment rates. This allows to uncover nonlinear effects of fiscal policy
by letting the parameters of either vector autoregressive models or local projection regressions
vary across the distribution of macroeconomic activity. In quarterly US data, we find that fiscal
output multipliers are notably larger if GDP is predicted to be below trend. Conversely, higher
government spending appears to significantly lower unemployment only if the unemployment rate
is in the largest deciles of its conditional distribution
