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The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts

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  • Michal Franta

Abstract

This paper examines the effect of non-linearities on density forecasting. It focuses on the relationship between credit markets and the rest of the economy. The possible non-linearity of this relationship is captured by a threshold vector autoregressive model estimated on the US data using Bayesian methods. Density forecasts thus account for the uncertainty in all model parameters and possible future regime changes. It is shown that considering non-linearity can improve the probabilistic assessment of the economic outlook. Moreover, three illustrative examples are discussed to shed some light on the possible practical applicability of density forecasts derived from non-linear models.

Suggested Citation

  • Michal Franta, 2013. "The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts," Working Papers 2013/09, Czech National Bank.
  • Handle: RePEc:cnb:wpaper:2013/09
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    Cited by:

    1. MeiChi Huang, 2022. "Time‐varying impacts of expectations on housing markets across hot and cold phases," International Finance, Wiley Blackwell, vol. 25(2), pages 249-265, August.
    2. repec:cnb:ocpubv:rb15/2 is not listed on IDEAS
    3. repec:cnb:ocpubv:rb16/2 is not listed on IDEAS
    4. Pfeifer, Lukáš & Hodula, Martin, 2018. "A profit-to-provisioning approach to setting the countercyclical capital buffer: the Czech example," ESRB Working Paper Series 82, European Systemic Risk Board.
    5. repec:cnb:ocpubv:rb16/1 is not listed on IDEAS
    6. repec:cnb:ocpubv:rb15/1 is not listed on IDEAS
    7. Pfeifer, Lukáš & Hodula, Martin, 2021. "A profit-to-provisioning approach to setting the countercyclical capital buffer," Economic Systems, Elsevier, vol. 45(1).
    8. repec:cnb:ocpubv:rb14/1 is not listed on IDEAS
    9. repec:cnb:ocpubv:rb14/2 is not listed on IDEAS

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    More about this item

    Keywords

    density forecasting; nonlinearity; threshold autoregressive model.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: 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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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