I am a PhD candidate and Junior researcher at CERGE-EI, Prague. My supervisor at CERGE-EI is Professor Marek Kapicka. I have spent last two academic years at Yale Department of Economics as a visiting scholar. My supervisor at Yale is Professor Aleh Tsyvinski.
My research interests and expertise include macroeconomics of labor markets, life-cycle modelling, human capital, routine-biased technological change, automation, and environmental economics.
Embedded in a rich heritage of four generations of Biologists and Ecologists, I am the first in my family to channel this legacy into the field of Economics. My current research introduces the state-of-the-art adaptation concepts from Biology and Ecology into the models of workers' adaptation to changing labor market environment.
I am on the 2023-2024 job market.
CV: Open CV
Modelling Macroeconomics: How Macroeconomists Understand and Predict the World
CERGE-EI Foundation, Distance Learning Program
Main Instructor (Fall 2022, 2023)
Course Description: The aim of this course is to acquaint students with the general ideas behind structural macroeconomic modeling and how it can be applied to better understand real-world data, whether GDP fluctuations, evolution of lifetime income, or propensity to consume out of a monetary transfer. We will cover 2-3 basic macro models focusing on economic growth, the development of income and consumption inequality over the lifetime of individuals, and the differences in behavior of poor vs. wealthy households. For each model, we will define the decision problems of agents in a model (households/firms/government), acquire basic intuition on how a model works, and then describe how a model is calibrated to real data. The discussion of each model will conclude with a debate on how it compares with the real world and what it fails to explain.
Dynamic Programming and Applications
HSE St. Petersburg, Graduate Teaching Fellowship
Main Instructor (Spring 2020)
Course Description: The main aim of "Dynamic Programming and Applications" course is to provide students with the overview of the standard methods for the solution of problems with intertemporal trade-offs. The problems with intertemporal trade-offs, which require to weight the costs of the current decisions against the benefits of the future outcomes, have extremely wide applicability in various disciplines of the economic science. In this course we will go over the basics of the dynamic programming, a method of solving problems with intertemporal trade-offs, will see how it can be applied to a wide range of real-life situations, and then move to some of the most popular (macro)economic applications of the method.
Graduate Macro III (PhD Level)
Teaching Assistant (Summer 2020, 2021, 2022) - Instructors Veronika Selezneva, Byeongju Jeong