Designing effective macroprudential policy
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Engaging with policymakers to design effective macroprudential policy
Discover how innovative agent-based models (ABMs) help in understanding the behaviour of economic systems to strengthen financial stability.
Our latest #SBMInsights brief, explores how combining borrower protections with lender requirements through agent-based models can make economies more resilient and support inclusive growth.
Using UK data and policy scenarios from the Bank of England, our research shows that integrating tools like capital buffers with loan-to-income caps reduces systemic risk without stifling the economy. This brief offers actionable recommendations for central banks, financial regulators and macroeconomic policymakers across Europe and beyond.
Who should read this brief?
Tailored for central bankers, financial regulators and economic policymakers especially those working in financial stability, prudential regulation and monetary policy. It also offers valuable insights for researchers and analysts interested in the use of computational modelling and agent-based simulations to design effective, more equitable macroeconomic policy.
This research aims to address the limited understanding of how different macroprudential tools interact and impact financial stability, credit dynamics, and the real economy. In particular, it responds to the challenges policymakers face in selecting and combining regulatory instruments effectively.— Dr Lilit Popoyan
About the researcher
Lilit Popoyan’s research focuses on policy-relevant quantitative analysis at the intersection of macroeconomic policy, financial regulation, financial stability, sustainable finance and climate change, production networks and macroeconomic dynamics. Lilit has a PhD in Economics from the Sant’Anna School of Advanced Studies in Pisa, Italy. Before joining QMUL, she was an Assistant Professor in Economic Policy at the University of Naples Parthenope. She is an Associate Editor of the Journal of Economic Interaction and Coordination and leads the ABM and Networks research stream in the Computational and Quantitative Methods (CQM) research cluster at QMUL.
Be the next author
Are you an academic at the School of Business and Management and want to share your research insights in a brief? Email Professor Elena Doldor, Research Impact & Engagement Director, at e.r.doldor@qmul.ac.uk.