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Macro-financial linkages: the role of liquidity dependence

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  • Alexey Ponomarenko
  • Anna Rozhkova
  • Sergei Seleznev

Abstract

We estimate a panel Bayesian vector autoregression model for a cross-section of seven advanced European economies and produce out-of-sample forecasts of GDP conditionally on observed developments of interest rates and credit. We show that, by using a smooth transition version of the model and allowing the parameters to vary across economies conditionally on their liquidity dependence (i.e. dependence on the availability of funding from external sources), it is possible to improve the accuracy of the forecasts. We conclude that the degree of liquidity dependence is likely to be among the important predictors of heterogeneity in macro-financial linkages across countries.

Suggested Citation

  • Alexey Ponomarenko & Anna Rozhkova & Sergei Seleznev, 2018. "Macro-financial linkages: the role of liquidity dependence," BIS Working Papers 716, Bank for International Settlements.
    • Handle: RePEc:bis:biswps:716
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    Cited by:

    1. Alexey Ponomarenko & Svetlana Popova & Sergey Sabodash, 2018. "Industry specifics of liquidity dependence in Russia and vulnerability to financial shocks," Bank of Russia Working Paper Series note18, Bank of Russia.
    2. Mikhail Stolbov & Maria Shchepeleva, 2021. "Macrofinancial linkages in Europe: Evidence from quantile local projections," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5557-5569, October.

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    More about this item

    Keywords

    liquidity dependence; macro-financial linkages; Smooth Transition Bayesian VAR;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • 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

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