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Sentiment Volatility and Bank Lending Behavior

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  • Mustafa Caglayan
  • Mustafa Caglayan
  • Bing Xu

Abstract

Using a panel of commercial, co-operative and savings banks from G7 countries, we investigate whether change in sentiment and its volatility affect banks' lending behavior. Sentiment indicators, which gauge the state of the economy from the perspective of the economic agents, are widely considered as a critical component by academics, policy makers and media in the transmission of shocks into the economic activity. We also know that leading indicators usually change before the economic activities change as a whole and provide useful information on the state of the economy. Surprisingly, earlier studies have not examined the impact of the level and volatility of economic agents sentiment on banks' lending behavior. As each type of agent acts on a specific set of (imperfect) information that emanate from the state of the economy, rational inattention, or their own asymmetric goals and strategies, it is important find out whether bank managers respond to changes and variability in sentiment. To carry out our investigation, we construct a large panel of commercial, co-operative, and savings banks collected from the Bankscope database for the G7 countries including Canada, Germany, France, the UK, Italy, Japan, and the US. This database provides detailed bank-level information yet the sample size is constrained due to the fact that we seek to examine the role of Core Tier 1 capital on banks' lending. The final dataset that we employ in our analysis is comprised of more than 9,000 banks and retains bank, country and time dimensions. The analysis covers the period between 1999-2014. The investigation implements GMM and fixed effects models to test various hypotheses. We show that the changes in economic agents' sentiment and its volatility affect bank lending negatively, while the impact sizes differ across indicators. We also find that the impact of volatility effects on banks' loan growth varies at excessive levels. We highlight the role of several bank-specific characteristics in transmission of uncertainty effects on the growth of bank loans, as uncertainty affects extenuate or mitigate through them.

Suggested Citation

  • Mustafa Caglayan & Mustafa Caglayan & Bing Xu, 2016. "Sentiment Volatility and Bank Lending Behavior," EcoMod2016 9206, EcoMod.
  • Handle: RePEc:ekd:009007:9206
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    Cited by:

    1. Christopher F. Baum & Mustafa Caglayan & Bing Xu, 2021. "The impact of uncertainty on financial institutions: A cross‐country study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3719-3739, July.
    2. Gregoriou, Greg N. & Racicot, François-Éric & Théoret, Raymond, 2021. "The response of hedge fund tail risk to macroeconomic shocks: A nonlinear VAR approach," Economic Modelling, Elsevier, vol. 94(C), pages 843-872.
    3. Wadud, Mokhtarul & Ali Ahmed, Huson Joher & Tang, Xueli, 2020. "Factors affecting delinquency of household credit in the U.S.: Does consumer sentiment play a role?," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. Byrne, Joseph P. & Lorusso, Marco & Xu, Bing, 2019. "Oil prices, fundamentals and expectations," Energy Economics, Elsevier, vol. 79(C), pages 59-75.
    5. Machokoto, Michael & Chipeta, Chimwemwe & Ibeji, Ngozi, 2021. "The institutional determinants of peer effects on corporate cash holdings," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    6. Cubillas, Elena & Ferrer, Elena & Suárez, Nuria, 2021. "Does investor sentiment affect bank stability? International evidence from lending behavior," Journal of International Money and Finance, Elsevier, vol. 113(C).
    7. Gabriele Angori & David Aristei & Manuela Gallo, 2019. "Determinants of Banks’ Net Interest Margin: Evidence from the Euro Area during the Crisis and Post-Crisis Period," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    8. Caglayan, Mustafa & Xu, Bing, 2016. "Inflation volatility effects on the allocation of bank loans," Journal of Financial Stability, Elsevier, vol. 24(C), pages 27-39.

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    More about this item

    Keywords

    G7; Finance; Monetary issues;
    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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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