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Level and dynamics of financial depth: consequences for volatility of GDP

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  • Jan Acedański
  • Jacek Pietrucha

Abstract

The existing literature documents positive but potentially non-linear relationship between financial depth measured as private credit to GDP ratio and volatility of GDP. In this paper, we extend the analysis by considering also the role of financial depth dynamics. We use dynamic spatial panel models to address the issue of cross-sectional dependence of errors obtained from the standard dynamic panel models. We confirm the non-linear impact of the financial depth level but also find that higher growth rates of financial depth are significantly associated with higher volatility of output. The role of the latter factor is considerably more important in terms of explained variance compared to the impact of the private credit level. These results are robust to changes in the sample range, specification of the model, and measurement of the key variables. We also document considerable differences between the estimates obtained from the standard GMM and the spatial models.

Suggested Citation

  • Jan Acedański & Jacek Pietrucha, 2019. "Level and dynamics of financial depth: consequences for volatility of GDP," Applied Economics, Taylor & Francis Journals, vol. 51(31), pages 3389-3400, July.
    • Handle: RePEc:taf:applec:v:51:y:2019:i:31:p:3389-3400
    DOI: 10.1080/00036846.2019.1578857
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    Cited by:

    1. Dąbrowski, Marek A. & Papież, Monika & Śmiech, Sławomir, 2024. "Output volatility and exchange rates: New evidence from the updated de facto exchange rate regime classifications," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 894-908.
    2. Gnangnon, Sèna Kimm, 2023. "Effect of the duration of membership in the GATT/WTO on economic growth volatility," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 448-467.
    3. Dąbrowski, Marek A., 2021. "A novel approach to the estimation of an actively managed component of foreign exchange reserves," Economic Modelling, Elsevier, vol. 96(C), pages 83-95.

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