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Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment

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  • Costas Milas

    ()
    (Economics Group, Keele Management School, Keele University, UK and Rimini Centre for Economic Analysis, Rimini, Italy)

  • Ruthira Naraidoo

    ()
    (Department of Economics, University of Pretoria)

Abstract

We explore how the ECB sets interest rates in the context of policy reaction functions. Using both real-time and revised information, we consider linear and nonlinear policy functions in inflation, output and a measure of financial conditions. We find that amongst Taylor rule models, linear and nonlinear models are empirically indistinguishable within sample and that model specifications with real-time data provide the best description of in-sample ECB interest rate setting behavior. The 2007-2009 financial crisis witnesses a shift from inflation targeting to output stabilisation and a shift, from an asymmetric policy response to financial conditions at high inflation rates, to a more symmetric response irrespectively of the state of inflation. Finally, without imposing an a priori choice of parametric functional form, semiparametric models forecast out-of-sample better than linear and nonlinear Taylor rule models.

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Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200923.

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Length: 40 pages
Date of creation: Oct 2009
Date of revision:
Handle: RePEc:pre:wpaper:200923

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Keywords: monetary policy; nonlinearity; real time data; financial conditions;

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Cited by:
  1. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers, University of Pretoria, Department of Economics 201230, University of Pretoria, Department of Economics.
  2. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working papers, University of Connecticut, Department of Economics 2010-21, University of Connecticut, Department of Economics.

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