My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.

The Global Resource Observatory (GRO)

The Global Resource Observatory is largest single research project being undertaken at the GSI, it investigates how the scarcity of finite resources will impact global social and political fragility in the short term. The ambitious three year project, funded by the Dawe Charitable Trust, will enable short term decision making to account for ecological and financial constraints of a finite planet.

GRO will include an open source multidimensional model able to quantify the likely short term interactions of the human economy with the carrying capacity of the planet and key scarce resources. The model will enable exploration of the complex interconnections between the resource availability and human development, and provides projections over the next 5 years.

Data and scenarios will be geographically mapped to show the current and future balance and distribution of resources across and within countries. The GRO tool will, for the first time, enable the widespread integration of the implications of depleting key resource into all levels of policy and business decision-making.

My interests lie in the intersection of economics, networks, and computation. I am currently studying labour dynamics as a process where people flow throughout the economy by moving from one firm to another. I study these flows by looking at detailed data about employment histories of each individual and every firm in entire economies. Using this information, I construct networks of firms in order to map the roads that people take throughout their careers. This allows to study labour markets at an unprecedented fine-grained level of detail. I employ agent-based computing methods to understand how economic shocks and policies alter labour flows, which eventually translate into unemployment and other related problems.

Researcher in sustainable production and consumption, the service economy, energy markets, and electricity balancing mechanisms.

Matteo Richiardi is an internationally recognised scholar in  micro-simulation modelling (this includes dynamic microsimulations and agent-based modelling). His work on micro-simulations involves both methodological research on estimation and validation techniques, and applications to the analysis of distributional outcomes, the functioning of the labour market and welfare systems. He is Chief Editor of the International Journal of Microsimulation. Examples of his work are the two recent books “Elements of Agent-based Computational Economics”, published by Cambridge University Press (2016), and “The political economy of work security and flexibility: Italy in comparative perspective”, published by Policy Press (2012).

My research focuses on the interdisciplinary nexus of artificial intelligence (AI), digital economy, technological innovation, and industrial economics, with an emphasis on understanding how digital technologies reshape economic structures, policy frameworks, and societal norms. Key areas of interest include:

1. Artificial Intelligence & Digital Transformation
   Ethical and Governance Challenges of AI: Investigating algorithmic bias, data privacy, and accountability in AI systems; proposing frameworks for ethical AI development and deployment.
   AI Adoption and Economic Impact: Analyzing how AI-driven automation and innovation influence productivity, labor markets, and industrial competitiveness.
2. Digital Economy & Platform Markets
   Crowdfunding, Sharing Economy, and Digital Platforms: Examining user behavior, market dynamics, and performance drivers in emerging digital ecosystems (e.g., crowdfunding campaigns, app markets).
   Digital Innovation and Entrepreneurship: Studying the role of technological innovation in firm growth, particularly in internet-based industries.
3. Technological Innovation & Industrial Policy
   Innovation-Driven Industrial Competitiveness: Developing quantitative models (e.g., DEA, CGE) to assess the efficiency and competitiveness of emerging industries under technological disruption.
   Policy Evaluation and Simulation: Using computational modeling to analyze the economic and industrial impacts of trade policies, environmental regulations, and technological standards.
4. Resource Economics & Sustainable Development
   Water Resource Management and Policy: Evaluating the economic and environmental trade-offs of water conservation policies through general equilibrium modeling.
   Global Trade and Food Security: Assessing the impacts of international trade regulations (e.g., food safety standards) on domestic industries and global supply chains.
5. Cross-Disciplinary Methodological Innovation
   Integrating econometrics, data science, and behavioral economics to enhance the rigor and relevance of industrial and policy research.
   Leveraging big data analytics, machine learning, and agent-based modeling to uncover complex relationships in digital markets and technological ecosystems.

Quantitative Economy

My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.

Agent-based modeling, Participatory modeling, Socio-technical systems, Complexity, Sustainability, Circular Economy, Design Science, Action research.