Giancarlo Salazar-Caicedo is an applied research scholar, econometrician, and the Principal of Econometricus LLC, an analytics firm specializing in advanced econometric modeling. His academic background spans multiple fields; he earned a Master of Science from the University of Massachusetts Boston—where he researched macroeconomic trickle-down effects—and a degree in History from the Pontificia Universidad Javeriana in Colombia. Salazar-Caicedo’s expert research integrates econometrics, open-source AI, and natural language processing. He frequently investigates macroeconomic policy, central bank communications, and complex data-matching algorithms.

Carlos Lara

Senior Quantitative Economist & Econometrician

Dr. Carlos Lara is an applied econometrician specializing in causal inference, high-dimensional data analysis, and the intersection of machine learning with traditional econometrics. He holds a PhD in Economics, where his doctoral research focused on developing microeconometric frameworks to evaluate the long-term labor market impacts of automation and targeted public policy interventions.

Currently, Dr. Lara serves as a Senior Quantitative Economist, leading a team of data scientists and researchers in designing structural models and predictive algorithms for complex economic environments. His expertise includes:

• Advanced Causal Inference: Designing quasi-experimental methods, difference-in-differences frameworks, and synthetic control models for policy evaluation.
• Predictive Analytics: Integrating open-source Python and R machine learning pipelines with traditional time-series and panel data models.
• Large-Scale Data Architecture: Processing and analyzing massive, unstructured administrative datasets to extract actionable economic insights.

Dr. Lara is a frequent speaker at international economic conferences and actively contributes to peer-reviewed journals. He is passionate about bridging the gap between rigorous academic theory and scalable, data-driven business decisions.