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The hidden soul of financial innovation: An agent-based modelling of home mortgage securitization and the finance-growth nexus

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  • Lauretta, Eliana

Abstract

This paper investigates the interaction between financial innovation and securitization. To this end, it introduces the rate of financial innovation (RoFIN) as an endogenous variable in an Agent-Based Model (ABM) set up and studies its interaction with the non-fixed fraction of securitized mortgage loans. RoFIN is able to capture financial agents’ business decisions on using financial innovation tools, processes and services, such as the home mortgage securitization process. In the aftermath of the 2007–2009 financial and economic crisis it has been argued that financial innovation and securitization have increased macro/finance systemic instability via, for example, non-linear two-way spillovers between the financial system and the macroeconomy. The ABM model proposed enables the capture of these dynamics. High values of RoFIN (i.e. exceeding the threshold of 50%) make financial innovation become harmful for the economic system, leading to a switch from a virtuous to an unvirtuous business cycle. When RoFIN reaches 90%, the numerical simulations come close to the macro/finance dynamics observed before and during the financial crisis. Given its potential role in triggering financial and economic instability, RoFIN is of interest for financial regulation and supervision. How this endogenous variable may be influenced by means of operational variables under the control of policymakers remains a subject for future research.

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  • Lauretta, Eliana, 2018. "The hidden soul of financial innovation: An agent-based modelling of home mortgage securitization and the finance-growth nexus," Economic Modelling, Elsevier, vol. 68(C), pages 51-73.
    • Handle: RePEc:eee:ecmode:v:68:y:2018:i:c:p:51-73
    DOI: 10.1016/j.econmod.2017.04.019
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    8. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harre, 2020. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large scale agent-based model," Papers 2004.07571, arXiv.org.
    9. N. V. Suvorov & S. V. Treshchina & Yu. V. Beletskii, 2020. "Design of Methods for Long-Term Forecasting of Development Trends in the Russian Economy (Methodology and Model Toolkit)," Studies on Russian Economic Development, Springer, vol. 31(6), pages 636-646, November.
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    More about this item

    Keywords

    G20; G02; E32; E44; E51; O33; C63; Finance; Growth; Securitization; Financial innovation; Financial crisis; Agent-based simulation;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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