Estimating nonlinear effects of fiscal policy using quantile regression methods

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 conditional distribution of macroeconomic activity. In quarterly US data, we find that fiscal output multipliers are notably larger for lower quantiles of the conditional distribution of GDP deviations from trend. Conversely, higher government spending appears to lower the rate of unemployment significantly only at its highest deciles.