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Gaussian Mixture Approximations of Impulse Responses and The Non-Linear Effects of Monetary Shocks

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  • Barnichon, Régis
  • Matthes, Christian

Abstract

This paper proposes a new method to estimate the (possibly non-linear) dynamic effects of structural shocks by using Gaussian basis functions to parametrize impulse response functions. We apply our approach to the study of monetary policy and obtain two main results. First, regardless of whether we identify monetary shocks from (i) a timing restriction, (ii) sign restrictions, or (iii) a narrative approach, the effects of monetary policy are highly asymmetric: A contractionary shock has a strong adverse effect on unemployment, but an expansionary shock has little effect. Second, an expansionary shock may have some expansionary effect, but only when the labor market has some slack. In a tight labor market, an expansionary shock generates a burst of inflation and no significant change in unemployment.

Suggested Citation

  • Barnichon, Régis & Matthes, Christian, 2016. "Gaussian Mixture Approximations of Impulse Responses and The Non-Linear Effects of Monetary Shocks," CEPR Discussion Papers 11374, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11374
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    References listed on IDEAS

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    Cited by:

    1. Aruoba, S. Borağan & Bocola, Luigi & Schorfheide, Frank, 2017. "Assessing DSGE model nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 83(C), pages 34-54.
    2. Barnichon, Regis & Matthes, Christian & Ziegenbein, Alexander, 2016. "Theory Ahead of Measurement? Assessing the Nonlinear Effects of Financial Market Disruptions," Working Paper 16-15, Federal Reserve Bank of Richmond.
    3. Barnichon, Régis & Matthes, Christian & Ziegenbein, Alexander, 2016. "Assessing the Non-Linear Effects of Credit Market Shocks," CEPR Discussion Papers 11410, C.E.P.R. Discussion Papers.
    4. repec:rba:rbaacv:acv2017-04 is not listed on IDEAS
    5. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2017. "The effects of quasi-random monetary experiments," NBER Working Papers 23074, National Bureau of Economic Research, Inc.
    6. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    7. Régis Barnichon & Christian Matthes, 2016. "Understanding the size of the government spending multiplier: It's in the sign," Economics Working Papers 1555, Department of Economics and Business, Universitat Pompeu Fabra.
    8. Jorda, Oscar & Schularick, Moritz & Taylor, Alan M., 2017. "Large and State-Dependent Effects of Quasi-Random Monetary Experiments," Working Paper Series 2017-2, Federal Reserve Bank of San Francisco.
    9. Claudio Borio & Boris Hofmann, 2017. "Is Monetary Policy Less Effective When Interest Rates Are Persistently Low?," RBA Annual Conference Volume,in: Jonathan Hambur & John Simon (ed.), Monetary Policy and Financial Stability in a World of Low Interest Rates Reserve Bank of Australia.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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