PL EN


2020 | 10 | 9-22
Article title

Agent‐based modelling of macroeconomic shocks in a banking sector

Authors
Content
Title variants
Languages of publication
EN
Abstracts
EN
This paper presents an agent‐based model of banking sector, which includes three kinds of heterogenous agents – households, borrowers and banks. Households provide funds to the banking sector via deposits and are changing their bank of choice stochastically. Borrowers are main source of demand for liquidity in this system, which they utilize for a risky undertaking, that may not succeed, thus defaulting on a loan. And finally banks act as an intermediary between two previous agents and manage their simple balance sheet. Agents interact with each other, establishing a time‐varying equilibrium, that is able to receive an endogenous macroeconomic shock and return to the equilibrium, which may not be in the same place or may exhibit different characteristics depending on type of the shock. The simulation introduces shocks to the three variables, namely minimal reserve ratio, probability of default and capital adequacy ratio. The work also compares drawbacks and advantages of agent‐based models to the commonly used equation‐based models, such as dynamic stochastic general equilibrium models.
Year
Issue
10
Pages
9-22
Physical description
Contributors
author
References
  • Chan‐Lau J.A, ABBA: An Agent‐Based Model of the Banking System, IMF Working Paper, WP/17/136, 2017.
  • Dickens R.N., et. al., Bank Dividend Policy: Explanatory Factors, “Quarterly Journal of Business and Economics” 2002, vol. 41, no. 1/2.
  • Farmer J., Foley D., The economy needs agent‐based modelling. “Nature” 2009, no. 460.
  • Galí J., Some scattered thoughts on DSGE models [in:] DSGE Models in the Conduct of Policy: Use as intended, CEPR Press, London 2017.
  • Hamill L., Gilbert N., Agent‐Based Modelling in Economics, Wiley, Hoboken 2015.
  • Krugman. P, The State of Macro Is Sad (Wonkish), The New York Times, 12.08.2016, https://krugman.blogs.nytimes.com/2016/08/12/the‐state‐of‐macro‐is‐sad‐wonkish/.
  • LeBaron B., A Real Minsky Moment in an Artificial Stock Market, International Business School, Brandeis University Working Paper, 2012.
  • Markiewicz M., The concentration and competition in the banking sectors of the Baltic States in the context of a crisis, Recovery of the Baltic States after the Global Financial Crisis:
  • Necessity and Strategies, Supplement 1 to the Annual Report: Working Papers of the Research Project on the Baltic States, 2013.
  • North M., Macal C.M., Managing Business Complexity: Discovering Strategic Solutions with Agent‐Based Modeling and Simulation, Oxford University Press, Oxford 2007.
  • Poledna S., Miesse M.G., Hommes C., Economic Forecasting with an Agent‐based Model, Available at SSRN: https://ssrn.com/abstract=3484768, 2019.
  • Wickham H., ggplot2: Elegant Graphics for Data Analysis, Springer‐Verlag New York 2016.
  • Romer P., The Trouble With Macroeconomics, Delivered January 5, 2016 as the Commons Memorial Lecture of the Omicron Delta Epsilon Society.
  • Stiglitz J. E., Where Modern Macroeconomics Went Wrong, NBER Working Paper 2017, no. 23795.
  • Smets F., Wouters R., Forecasting with a Bayesian DSGE model: an application to the euro area, “JCMS: Journal of Common Market Studies” 2004, vol. 42 (4).
  • Smets F., Wouters R., Shocks and Frictions in US Business Cycles: A Bayesian DSGE approach, “American Economic Review” 2007, vol. 97, no. 3.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-ce10e75c-0a24-4893-86a0-4becd06cb079
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.