Economist, PhD student in economics and finance. I am proficient in quantitative modeling in microeconomics, macroeconomics and finance.
Among the microeconometric techniques I use are causal inference, panel data analysis, discrete choice analysis, demand modeling and merger analysis, spatial econometrics and hybrid spatial econometrics based on graph theory.
I am familiar with advanced quantitative models of financial markets and macroeconomic models. I have experience in modeling modern DSGE models including HANK. I have a thorough knowledge of state-of-the-art forecasting models, including mixture Bayesian VAR and model calibration based on interval forecasts. I am equally familiar with top newcasting models – markov switching mixed frequency VAR-s and MIDAS class models.
I have expertise in financial econometrics, high-frequency financial econometrics, financial risk management and portfolio analysis

Recently, I have been involved in studying the impact of climate change on Polish forests.
I have highly developed digital competencies. In my work I actively use programming languages: R, Python, Matlab and SQL. My knowledge of programming languages greatly facilitates my data analysis. I use advanced statistics, econometrics, text mining and machine learning, including causal machine learning, to analyze data.

I acquired my knowledge of economics and finance during my studies at Jagiellonian University. I have also participated in numerous summer schools, workshops and courses in economics and quantitative methods at leading academic centers in Europe and US.
In addition, I have almost 10 years of experience in tutoring mathematics, statistics and econometrics at the college and high school level. I underwent a higher education teaching course at Harvard University Derek Bok Center for Teaching & Learning, which provided me with exposure to the latest techniques and trends in academic teaching. I also teach courses in quantitative methods designed mainly for doctoral students.