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Dynamic models for monetary transmission

Author

Listed:
  • Paolo Giudici

    (Department of Economics and Management, University of Pavia)

  • Laura Parisi

    (Department of Economics and Management, University of Pavia)

Abstract

Monetary policies, either actual or perceived, cause changes in monetary interest rates. These changes impact the economy through financial institutions, which react to changes in the monetary rates with changes in their administered rates, on both deposits and lendings. The dynamics of administered bank interest rates in response to changes in money market rates is essential to examine the impact of monetary policies on the economy. Chong et al. (2006) proposed an error correction model to study such impact, using data previous to the recent financial crisis. Parisi et al. (2015) analyzed the Chong error correction model, extended it and proposed an alternative, simpler to interpret, one-equation model, and applied it to the recent time period, characterized by close-to-zero monetary rates. In this paper we extend the previous models in a dynamic sense, modelling monetary transmission effects by means of stochastic processes.The main contribution of this work consists in novel parsimonious models that provide endogenously determined and generalizable models. Secondly, this paper introduces a predictive performance assessment methodology, which allows to compare all the proposed models on a fair ground. From an applied viewpoint, the paper applies the proposed models to different interest rates on loans, showing how the monetary policy differentially impacts different types of lendings.

Suggested Citation

  • Paolo Giudici & Laura Parisi, 2015. "Dynamic models for monetary transmission," DEM Working Papers Series 106, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:demwp0106
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    File URL: http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0106.pdf
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    References listed on IDEAS

    as
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    Keywords

    Error Correction Forecasting Bank Rates; Monte Carlo predictions; Stochastic Processes.;
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