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Estimating nonlinear effects of fiscal policy using quantile regression methods

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  • Ludger Linnemann
  • Roland Winkler

Abstract

We estimate nonlinear effects of government spending shocks on US macroeconomic activity using quantile regression methods. This amounts to allowing regression parameters to depend on how far output or the unemployment rate are from their means, conditional on past explanatory variables. Applying quantile methods to vector autoregressions and local projections as an alternative way to estimate impulse response functions, we find the output effects of fiscal policy to be notably larger for lower quantiles of the conditional output distribution. Conversely, higher government spending appears to lower the rate of unemployment considerably only at its highest deciles.

Suggested Citation

  • Ludger Linnemann & Roland Winkler, 2016. "Estimating nonlinear effects of fiscal policy using quantile regression methods," Oxford Economic Papers, Oxford University Press, vol. 68(4), pages 1120-1145.
    • Handle: RePEc:oup:oxecpp:v:68:y:2016:i:4:p:1120-1145.
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    File URL: http://hdl.handle.net/10.1093/oep/gpw020
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    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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