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How do policies influence GDP tail risks?

Author

Listed:
  • Aida Caldera Sánchez

    (OECD)

  • Oliver Röhn

    (OECD)

Abstract
This paper explores the relationship between policy settings and extreme positive and negative growth events, what we call GDP tail risks, using quantile regression methods. Conditioning on several country characteristics such as the size, stage of development and openness to trade as well as macroeconomic policies, the following findings for a panel of mostly OECD countries emerge: First, countries with stronger banking supervision and capital market development, better quality of governance, higher foreign reserves and several labour market characteristics such as higher unemployment benefits and greater spending in active labour market policies tend to experience less severe negative growth shocks (negative tail risk). Second, greater use of macro-prudential tools is generally associated with less extreme positive growth shocks (positive tail risk) and lower average growth. Third, larger automatic stabilisers are associated with both less severe negative and positive growth shocks but also lower average growth. Comment les politiques publiques influencent les risques extrêmes du PIB? Cet article explore la relation entre les politiques publiques et les épisodes de croissance extrême positive et négative, ce que nous appelons risques extrêmes du PIB, en utilisant des méthodes de régression quantile. Une fois pris en compte plusieurs caractéristiques des pays tels que la taille, le stade de développement et de l'ouverture au commerce ainsi que les politiques macro-économiques, les résultats suivants pour un panel de la plupart des pays de l'OCDE se dégagent: Premièrement, les pays avec une supervision bancaire plus forte, un plus grand développement du marché des capitaux, une meilleure qualité de gouvernance, des réserves de change plus élevées et plusieurs caractéristiques du marché du travail tels que les prestations de chômage plus élevées et des dépenses plus importantes consacrées aux politiques du marché du travail actives ont tendance à subir des chocs de croissance négatifs moins graves (risque de queue négative). En second lieu, une plus grande utilisation des outils macro-prudentiels est généralement associée à des chocs positifs de croissance moins extrêmes et une croissance moyenne inférieure. Troisièmement, les stabilisateurs automatiques sont associés à des chocs de croissance négative et positive moins importants, mais aussi une croissance moyenne plus faible.

Suggested Citation

  • Aida Caldera Sánchez & Oliver Röhn, 2016. "How do policies influence GDP tail risks?," OECD Economics Department Working Papers 1339, OECD Publishing.
  • Handle: RePEc:oec:ecoaaa:1339-en
    DOI: 10.1787/5jln0428l1wl-en
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    References listed on IDEAS

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    Cited by:

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    2. Borsuk, Marcin & Przeworska, Joanna & Saunders, Anthony & Serwa, Dobromił, 2024. "The macroeconomic costs of the bank tax," Journal of Financial Stability, Elsevier, vol. 72(C).
    3. Belkhir, Mohamed & Naceur, Sami Ben & Candelon, Bertrand & Wijnandts, Jean-Charles, 2022. "Macroprudential policies, economic growth and banking crises," Emerging Markets Review, Elsevier, vol. 53(C).
    4. Zhou, Yang, 2024. "Benefits and costs: The impact of capital control on growth-at-risk in China," International Review of Financial Analysis, Elsevier, vol. 93(C).
    5. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    6. Tarne, Ruben & Bezemer, Dirk & Theobald, Thomas, 2022. "The effect of borrower-specific loan-to-value policies on household debt, wealth inequality and consumption volatility: An agent-based analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    7. Apergis, Nicholas & Aysan, Ahmet F. & Bakkar, Yassine, 2022. "Borrower- and lender-based macroprudential policies: What works best against bank systemic risk?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    8. Sever, Can & Yücel, Emekcan, 2022. "The effects of elections on macroprudential policy," Journal of Comparative Economics, Elsevier, vol. 50(2), pages 507-533.
    9. Caloia, Francesco G., 2024. "Borrower-based measures, house prices and household debt," Journal of International Money and Finance, Elsevier, vol. 143(C).
    10. Francesco Caloia, 2022. "Borrower-Based Measures, House Prices and Household Debt," Working Papers 738, DNB.
    11. Can Sever & Emekcan Yucel, 2020. "Macroprudential Policy and Elections: What Matters? Abstract:," Working Papers 2020/01, Bogazici University, Department of Economics.

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    More about this item

    Keywords

    financial stability; growth; quantile regression;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F3 - International Economics - - International Finance
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies

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