Approaches to Accounting for the Financial Sector in Agent-Based Modeling
https://doi.org/10.25205/2542-0429-2022-22-4-42-59
Abstract
The article discusses approaches to introducing the financial sector into agent-based models, as well as various options for modeling the behavior of agents (firms and households) directly interacting with the financial system. Agent-based models can explain how some important macroeconomic phenomena can be generated by evolving networks of interactions between boundedly rational agents in economies, where the underlying rules of interaction can evolve endogenously over time. The importance of accounting for financial activity in macroeconomic models for reproducing business cycles and predicting financial crises is emphasized. Consideration of financial blocks in macroeconomic agent-based models includes an analysis of approaches to modeling the choice between household savings and consumption, making decisions about the amount of investment by private sector firms, as well as the rules for setting interest rates and regulatory limits by banks. Possibilities for improving approaches in terms of taking into account interest rates when modeling household savings are proposed, as well as long-term planning based on the calculation of discounted cash flows with an assessment of the impact of changes in output on market prices when forming firms’ investment plans.
Supporting agencies: The research was supported by RSF (project No. 23-28-01499).
About the Author
A. V. Ivershin
Novosibirsk State University
Russian Federation
Russian Federation
AnastasiaV. Ivershin, Student of the Faculty of Economics
WOS Research ID AAZ-5261-2021
References
1. Smets F., Wouters R. Shocks and frictions in us business cycles: A bayesian DSGE approach. American Economic Review, vol. 97, no. 3, 2007, pp. 586–606.
2. Brunnermeier M., Sannikov Y. A macroeconomic model with a financial sector. American Economic Review, 2014. Vol 104 (2), pp. 379-421
3. Caiani A., Caverzasi E., Gallegati M., Kinsella S., Stiglitz J. E. Agent basedstock flow consistent macroeconomics: towards a benchmark model. Journal of Economic Dynamics and Control, 2016, vol. 69, pp. 375–408.
4. Bezemer D. J. No one saw this coming: Understanding financial crisis through accounting models. MPRA Paper 15892, University Library of Munich, Germany, 2009.
5. Dosi G., Fagiolo G., Roventini A. Animal spirits, lumpy investment, and endogenous business cycles. LEM Working Paper Series, 2005-4, 2006.
6. Dosi G., Fagiolo G., Napoletano M., Roventini A., Treibich T. Fiscal and monetary policies in complex evolving economies. Journal of Economic Dynamics and Control, 2015, no. 52, pp. 166–189.
7. Kirman A. The economic crisis is a crisis for economic theory. CESifo Economic Studies, 2010, no. 56 (4), pp. 498–535.
8. Chan-Lau Mr. Jorge A. ABBA: An Agent-Based Model of the Banking System. IMF Working Papers 2017/136, International Monetary Fund, 2017.
9. Ponomarenko A., Seleznev S., Habibullin R.Predicting the consequences of the accumulation of international reserves using an agent model. Bank of Russia. Ser. economic research reports, 2018, no. 37.
10. Turrell A. Agent-based models: understanding the economy from the bottom up. Bank of England Quarterly Bulletin, 2016, vol. 56(4), pp. 173–188.
11. DelliGatti D., Gaffeo E., Gallegati M. Complex Agent-Based Macroeconomics: a Manifesto for a New Paradigm. Journal of Economic Interaction and Coordination, 2010, vol. 5(2), pp. 111–135.
12. DelliGatti D., Gallegati M., Cirillo P., Desiderio S., Gaffeo E. Macroeconomics from the Bottom-up, Springer-Verlag, Berlin, 2011.
13. Cincotti S., Raberto M., Teglio A. The eurace macroeconomic model and simulator, in M. Aoki, K. Binmore, S. Deakin & H. Gintis, eds, ‘Complexity and Institutions: Markets, Norms and Corporations’, New York: Palgrave Macmillan, 2012. Pp. 81–106.
14. Assenza T., DelliGatti D., Grazzini J. Emergent dynamics of a macroeconomic agent based model with capital and credit. Journal of Economic Dynamics and Control, 2015, no. 50, pp. 5–28.
15. DelliGatti, Desiderio S. Monetary policy experiments in an agent-based model with financial frictions. Journal of Economic Interaction and Coordination, 2015, no. 10, pp. 265–286.
16. Klimek P., Poledna S., Farmer J., Thurner S. To bail-out or to bail-in? answers from an agent-based model. Journal of Economic Dynamics and Control, 2015, vol. 50, pp. 144–154.
17. Catullo E., Gallegati M., Palestrini A. Towards a credit network based early warning indicator for crises. Journal of Economic Dynamics and Control, 2015, vol. 50, pp. 78–97.
18. Deissenberg C., Van Der Hoog S., Dawid H. Eurace: A massively parallel agentbased model of the European economy. Applied Mathematics and Computation, 2008, vol. 204(2), pp. 541–552.
19. Raberto M., Teglio A., Cincotti S. Debt, deleveraging and business cycles: An agent-based perspective. Economics – The Open-Access, Open – Assessment E-Journal, 2012, no. 27, p. 50.
20. Teglio A., Raberto M., Cincotti S. The impact of banks capital adequacy regulation on the economic system: an agent-based approach. Advances in Complex Systems 15, 2012.
21. Seppecher P. Flexibility of wages and macroeconomic instability in an agentbased compuational model with endogenous money. Macroeconomic Dynamics, 2012, no. 16, pp. 284–297.
22. Seppecher P., Salle I. Deleveraging crises and deep recessions: a behavioural approach. Applied Economics, 2015, vol. 47, pp. 3771–3790.
23. Mandel A., Jaeger C., Fuerst S., Lass W., Lincke D., Meissner F., Pablo- Marti F., Wolf S. Agent-based dynamics in disaggregated growth models. Centre dEconomie de la Sorbonne Working Paper 10077, 2010.
24. Wolf S., Fuerst S., Mandel A., Lass W., Lincke D., Pablo-Martıґ F., Jaeger, C. A multi-agent model of several economic regions. Environmental Modelling & Software, 2013, vol. 44, pp. 25–43.
25. Deryugina E., Ponomarenko A., Rozhkova A. When credit score breaks are reliable? Series of reports on economic research of the Bank of Russia, 2018, no. 34.
26. Petrovic M., Bulent O., Andrea T., Marco R., Cincotti S. Should I stay or should I go? An agent-based setup for a trading and monetary union. Journal of Economic Dynamics and Control, 2020, vol. 113(C).
27. Ermolova M., Leonidov A. Agent-based model of the Russian banking system: Calibration for maturity, interest rate spread, credit risk, and capital regulation. Journal of Simulation, 2021, vol. 15, no. 1-2, pp. 82–92.
28. Popoyan L., Napoletano M., Roventini A. Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market. LEM Papers Series 2019/11, Laboratory of Economics and Management (LEM), Sant’Anna School of Advanced Studies, Pisa, Italy, 2019.
29. Grilli R., Tedeschi G., Gallegati M. Markets Connectivity and Financial Contagion. Journal of Economic Interaction and Coordination, 2015, pp. 1–18.
30. Tedeschi G., Vidal-Tomas D., Delli-Gatti D., Gallegati M. The macroeconomic effects of default and debt restructuring: An agent based exploration. International Review of Economics & Finance, 2021, vol. 76(C), pp. 1146–1163.
31. Blattner T. S., Margaritov E. Towards a robust monetary policy rule for the euro area. ECB Working Paper No. 1210, 2010.
Review
For citations:
Ivershin A.V. Approaches to Accounting for the Financial Sector in Agent-Based Modeling. World of Economics and Management. 2022;22(4):42-59. (In Russ.) https://doi.org/10.25205/2542-0429-2022-22-4-42-59
Views:
230
Email this article 
