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Lending attitude as a financial accelerator in a credit network economy

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  • Daiki Asanuma

Abstract

In existing literature, commercial banks are often considered mere financial intermediaries that facilitate the flow of credit in an imperfect credit market. However, as demonstrated in the history of financial instability, the behavior of financial institutions plays an important role. This paper examines how lenders’ attitudes affect macroeconomic performance. In our analysis, the economy is composed of multiple borrowers (firms) and one lender (bank). Each borrower is directly connected to the lender through its credit contract. At the same time, each borrower is indirectly connected to all the other borrowers within the credit network. Using this model, we execute computer simulations to examine the economic consequences of lending attitudes. The results of the simulations demonstrate that the bank’s lending attitude functions as a financial accelerator; that is, it significantly affects the dynamics of the economic system through the credit network. Consequently, the same level of exogenous shock generates completely different outcomes depending on the different lending attitudes. The results also show that there exists an optimal lending attitude that leads to high economic growth and a stable growth path. Copyright Springer-Verlag 2013

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  • Daiki Asanuma, 2013. "Lending attitude as a financial accelerator in a credit network economy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 231-247, October.
  • Handle: RePEc:spr:jeicoo:v:8:y:2013:i:2:p:231-247
    DOI: 10.1007/s11403-012-0102-9
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    2. Pablo Pastory y Camarasa & Martien Lamers, 2023. "Do Actions Follow Words? How bank sentiment predicts credit growth," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 23/1073, Ghent University, Faculty of Economics and Business Administration.
    3. He, Jianmin & Sui, Xin & Li, Shouwei, 2016. "An endogenous model of the credit network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 1-14.
    4. Chiarella Carl & Di Guilmi Corrado & Zhi Tianhao, 2020. "“Animal spirits” and bank’s lending behaviour, a disequilibrium approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-21, April.
    5. Sui, Xin & Li, Liang, 2018. "Guarantee network model and risk contagion," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 323-329.
    6. Tianhao Zhi, 2016. "Animal Spirits and Financial Instability - A Disequilibrium Macroeconomic Perspective," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2016.

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    More about this item

    Keywords

    Agent-based model; Credit network economy; Bank’s lending attitudes; Financial accelerator; Optimal lending attitude; E51; G21;
    All these keywords.

    JEL classification:

    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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