Estimating nonlinear effects of fiscal policy using quantile regression methods

Konferenzbeitrag

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2015: Ökonomische Entwicklung - Theorie und Politik - Session: Fiscal policy ; No. D01-V2

Classification and Topics

• Classification: Wirtschaft ; Fiscal Policy ; Business Fluctuations; Cycles ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Winkler, Roland C. ; Linnemann, Ludger
• Event: Veröffentlichung
• (when): 2015

Further information

• Handle: http://hdl.handle.net/10419/113164
• Last update: 10.03.2025, 11:45 AM CET