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Financial conditions and nonlinearities in the European Central Bank (ECB) reaction function: In-sample and out-of-sample assessment

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  • Milas, Costas
  • Naraidoo, Ruthira

Abstract

Our purpose is to investigate how the European Central Bank (ECB) sets interest rates in the context of both linear and nonlinear policy reaction functions. This work contributes to the current debate on central banks having additional objectives over and above control of inflation and output. Three findings emerge. First, the ECB takes financial conditions into account when setting interest rates. Second, amongst Taylor rule models, linear and nonlinear models are empirically indistinguishable within sample, and model specifications with real-time data provide the best description of in-sample ECB interest rate setting behaviour. Third, the 2007-2009 financial crisis witnessed a shift from inflation targeting to output stabilization, and a shift from an asymmetric policy response to financial conditions at high inflation rates to a more symmetric response regardless of the state of inflation. Finally, guidance is provided as regards models for forecasting interest rates in the Eurozone area. Without imposing an a priori choice of the parametric functional form, semiparametric models and autoregressive processes forecast the out-of-sample ECB interest rate setting behaviour better than linear and nonlinear Taylor rule models.

Suggested Citation

  • Milas, Costas & Naraidoo, Ruthira, 2012. "Financial conditions and nonlinearities in the European Central Bank (ECB) reaction function: In-sample and out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 173-189, January.
  • Handle: RePEc:eee:csdana:v:56:y:2012:i:1:p:173-189
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    Cited by:

    1. Umit Bulut, 2016. "Do Financial Conditions have a Predictive Power on Inflation in Turkey?," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 621-628.
    2. Floro, Danvee & van Roye, Björn, 2017. "Threshold effects of financial stress on monetary policy rules: A panel data analysis," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 599-620.
    3. Martin, Christopher & Milas, Costas, 2013. "Financial crises and monetary policy: Evidence from the UK," Journal of Financial Stability, Elsevier, vol. 9(4), pages 654-661.
    4. Chesang, Laban K. & Naraidoo, Ruthira, 2016. "Parameter uncertainty and inflation dynamics in a model with asymmetric central bank preferences," Economic Modelling, Elsevier, vol. 56(C), pages 1-10.
    5. John K. Ashton & Andros Gregoriou, 2014. "The Influence of Banking Centralization on Depositors: Regional Heterogeneities in the Transmission of Monetary Policy," Regional Studies, Taylor & Francis Journals, vol. 48(9), pages 1467-1482, September.
    6. repec:blg:journl:v:12:y:2017:i:2:p:35-45 is not listed on IDEAS
    7. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.

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