Structural & Scientific Modeling

Service Description

This service focuses on constructing and estimating structural or scientific models — frameworks that capture the mechanisms underlying complex systems. Unlike predictive models, structural models explain why and how phenomena occur, offering a powerful foundation for simulation, scenario analysis, and policy design. My expertise in economic modeling stems from my doctoral research, where I analyzed over a million global bank loans to model how financial shocks transmit to the real economy. Since then, I’ve applied similar principles to diverse domains, from labor markets to pension policy and sustainable finance. I use mathematical and econometric techniques to formalize theoretical concepts into quantifiable systems, typically estimated using Python or R. These models can include equilibrium frameworks, agent-based simulations, or dynamic systems — depending on the problem’s nature. Structural modeling is particularly suited for institutions and research-driven organizations that need to evaluate counterfactuals: What would happen if regulations changed? How does innovation affect long-term employment? What is the systemic effect of a new investment policy? Through rigorous calibration, estimation, and validation, I ensure these models are empirically grounded and policy-relevant. The outcome is not just an abstract model, but a decision-support tool that allows clients to explore “what-if” scenarios and understand the long-term implications of their strategies.