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The Bank Lending Channel: a FAVAR Analysis

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Abstract

We examine the role of commercial banks in monetary transmission in a factor-augmented vector autoregression (FAVAR). A FAVAR exploits a large number of macroeconomic indicators to identify monetary policy shocks, and we add commonly used lending aggregates and lending data at the bank level. While our results suggest that the bank lending channel (BLC) is stronger than previously thought, this feature is not robust. In addition, our results indicate a diffuse response to monetary innovations when individual banks are grouped according to asset sizes and loan components. This suggests that other bank characteristics could improve the identification of the BLC.

Suggested Citation

  • Chetan Dave & Scott J. Dressler & Lei Zhang, 2009. "The Bank Lending Channel: a FAVAR Analysis," Villanova School of Business Department of Economics and Statistics Working Paper Series 4, Villanova School of Business Department of Economics and Statistics.
    • Handle: RePEc:vil:papers:4
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    Cited by:

    1. Xiong, Qiyue, 2013. "The role of the bank lending channel and impacts of stricter capital requirements on the Chinese banking industry," BOFIT Discussion Papers 7/2013, Bank of Finland Institute for Emerging Economies (BOFIT).
    2. Kok, Christoffer & Gross, Marco & Żochowski, Dawid, 2016. "The impact of bank capital on economic activity - evidence from a mixed-cross-section GVAR model," Working Paper Series 1888, European Central Bank.
    3. Claudia M. Buch & Sandra Eickmeier & Esteban Prieto, 2014. "Macroeconomic Factors and Microlevel Bank Behavior," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 715-751, June.
    4. Maurin, Laurent & Andersson, Malin & Rusinova, Desislava, 2021. "Market finance as a spare tyre? Corporate investment and access to bank credit in Europe," EIB Working Papers 2021/09, European Investment Bank (EIB).
    5. Ronald A. Ratti & Joaquin L. Vespignani, 2015. "What drives the global interest rate," Globalization Institute Working Papers 241, Federal Reserve Bank of Dallas.
    6. Chen, Sophia & Ranciere, Romain, 2019. "Financial information and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1160-1174.
    7. Ratti, Ronald A. & Vespignani, Joaquin L., 2015. "Commodity prices and BRIC and G3 liquidity: A SFAVEC approach," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 18-33.
    8. Breitenlechner, Max & Scharler, Johann & Sindermann, Friedrich, 2016. "Banks’ external financing costs and the bank lending channel: Results from a SVAR analysis," Journal of Financial Stability, Elsevier, vol. 26(C), pages 228-246.
    9. Fredrik N. G. Andersson & Katarzyna Burzynska & Sonja Opper, 2016. "Lending for growth? A Granger causality analysis of China’s finance–growth nexus," Empirical Economics, Springer, vol. 51(3), pages 897-920, November.
    10. Andersson, Malin & Maurin, Laurent & Rusinova, Desislava, 2021. "Market finance as a spare tyre? Corporate investment and access to bank credit in Europe," Working Paper Series 2606, European Central Bank.
    11. Jean-Stéphane Mésonnier & Dalibor Stevanovic, 2012. "Bank Leverage Shocks And The Macroeconomy: A New Look In A Data-Rich Environment," CIRANO Papers 2012n-10a, CIRANO.
    12. Norhana Endut & James Morley & Pao-Lin Tien, 2018. "The changing transmission mechanism of US monetary policy," Empirical Economics, Springer, vol. 54(3), pages 959-987, May.
    13. Piyachart Phiromswad & Takeshi Yagihashi, 2016. "Empirical identification of factor models," Empirical Economics, Springer, vol. 51(2), pages 621-658, September.
    14. Shu‐Hua Chen, 2018. "The Credit‐Channel Transmission Mechanism And The Nonlinear Growth And Welfare Effects Of Inflation And Taxes," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 724-744, April.
    15. Jorge Mario Uribe Gil & Isabel Espinosa Castillo, 2018. "Efectos asimétricos de cambios en la tasa de interés sobre empresas del sector manufacturero colombiano," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 10(1), pages 173-187.
    16. Chetan Dave & Scott J. Dressler & Lei Zhang, 2020. "Bank Lending, Monetary Policy Transmission, and Interest on Excess Reserves: a FAVAR Analysis," Villanova School of Business Department of Economics and Statistics Working Paper Series 44, Villanova School of Business Department of Economics and Statistics.
    17. Budnik, Katarzyna & Bochmann, Paul, 2017. "Capital and liquidity buffers and the resilience of the banking system in the euro area," Working Paper Series 2120, European Central Bank.
    18. Dedu, Vasile & Stoica, Tiberiu, 2014. "The Impact of Monetaru Policy on the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 71-86, June.
    19. Ronald A. Ratti & Joaquin L. Vespignani, 2014. "Oil Prices and the Economy: A Global Perspective," CAMA Working Papers 2014-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    21. Juan S. Holguín & Jorge M. Uribe, 2020. "The credit supply channel of monetary policy: evidence from a FAVAR model with sign restrictions," Empirical Economics, Springer, vol. 59(5), pages 2443-2472, November.
    22. Xiong, Qiyue, 2013. "The role of the bank lending channel and impacts of stricter capital requirements on the Chinese banking industry," BOFIT Discussion Papers 7/2013, Bank of Finland, Institute for Economies in Transition.

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    Keywords

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    JEL classification:

    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • 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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