معرفی
Ivan Jeliazkov is an Associate Professor of Economics and Statistics at the Department of Economics, University of California, Irvine. His research focuses on Bayesian econometrics and simulation-based inference, emphasizing methodologies like Markov chain Monte Carlo and econometric modeling. He holds a Ph.D. in Economics from Washington University in St. Louis and a BA in Economics and Business Administration from Coe College.
His key research areas include Bayesian Econometrics, advanced simulation techniques, and causal inference applications. Notable work addresses heteroskedasticity in causal studies, quantile analysis of rental markets, and simultaneous equation models for discrete data.
Recent advising includes 2024 Ph.D. graduates Robert MacDonald, Parush Arora, and Jieyu Gao. His articles span topics like dynamic factor models, regression discontinuity designs, and model comparison techniques. He has contributed to interdisciplinary research in marketing, finance, and historical economic analysis.
His methodological innovations emphasize practical applications of Bayesian methods to address econometric challenges such as uncertainty quantification and model specification. Current work continues advancing computational tools for complex econometric problems.
