ELLIS SCHARFENAKER

Bayesian Econometrics and Statistical Inference
Developing and applying Bayesian methods for hierarchical and multilevel models, with a focus on shrinkage estimation, causal inference, and information-theoretic foundations of statistics.

Information Theory and Entropy-Based Inference
Advancing the use of Shannon entropy and constrained maximum entropy (CME) methods in econometrics, exploring the philosophical and methodological implications for statistical reasoning and inference.

Networks, Complexity, and Economic Dynamics
Exploring the role of network topology and complexity in shaping macroeconomic outcomes, with applications to production networks, systemic risk, and the propagation of firm-level shocks in heterogeneous agent economies.

Production Networks and Granular Macroeconomics
Studying the microeconomic origins of aggregate fluctuations, inflation, and price volatility through firm-level shocks and their propagation across industry input-output networks.

Foundations of Economic Value Theory
Investigating classical and post-Keynesian theories of value, distribution, and capital, with a particular emphasis on statistical equilibrium approaches to labor value and income dynamics.

Causal Inference with Constrained Entropy Methods
Developing causal inference techniques grounded in constrained maximum entropy (CME), combining information-theoretic principles with econometric modeling to address identification challenges in observational research.

Empirical Macroeconomics and Inflation Dynamics
Empirical analysis of inflation, market concentration, and markup behavior, combining firm-level data with macroeconomic time series and price indices.