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Estimating nonlinear effects of fiscal policy using quantile regression methods

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  • Winkler, Roland C.
  • Linnemann, Ludger

Abstract

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.

Suggested Citation

  • Winkler, Roland C. & Linnemann, Ludger, 2015. "Estimating nonlinear effects of fiscal policy using quantile regression methods," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113164, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc15:113164
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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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