Summit Econometrics delivers PhD-level econometric analysis, AI-powered modeling, and data-driven economic insights to clients across every industry. We find the perfect balance between rigorous, in-depth analysis and clarity of insights — every finding communicated in a crisp, precise, and immediately actionable way.
We design and estimate structural and reduced-form econometric models — regression analysis, IV estimation, difference-in-differences, RDD, and panel data methods — to uncover causal relationships in your data with academic-grade rigor.
We integrate cutting-edge machine learning with classical econometrics — combining predictive power with interpretability to deliver insights that are both statistically rigorous and immediately actionable for decision-makers.
Rigorous economic and statistical analysis for legal proceedings, regulatory disputes, and antitrust matters. Independent, defensible quantitative expertise and clear expert reports for any forum or jurisdiction.
Comprehensive quantitative research on market structure, competitive dynamics, pricing behavior, and demand estimation across equities, commodities, real estate, and private markets.
Rigorous evaluation of policy interventions, regulatory changes, and economic programs using quasi-experimental and structural methods from the frontier of academic economics.
Bespoke quantitative research partnerships for corporations, law firms, government agencies, and financial institutions seeking sustained, high-caliber economic consulting on a project or retainer basis.
Alex Levkov — Founder & Principal Economist
Summit Econometrics was founded on a single conviction: the most consequential economic questions deserve the highest standard of quantitative analysis — the kind developed at top research universities, not packaged as consulting boilerplate.
Our principal brings a rare combination of frontier academic research and deep industry experience, having spent years at the intersection of economic theory and quantitative practice at some of the most respected institutions in finance.
Every analysis draws on peer-reviewed econometric methodology — causal identification strategies, rigorous hypothesis testing, and out-of-sample validation. We hold our work to the standard of top journals, and we translate that rigor into findings that are clear, concise, and ready to act on.
We augment classical econometrics with modern machine learning — high-dimensional regularization, natural language processing, and causal ML — to handle the scale and complexity of today's data environments without sacrificing interpretability.
Insight without action is merely academic. We deliver clear, decision-ready findings — on schedule and ahead of deadline. Every report is structured for both technical and executive audiences, ensuring your team can act immediately upon receipt.
Available for project engagements, litigation support, and advisory retainers. Response within 24 hours.