ECON 418-518: Introduction to Econometrics

• Solely instructed 20+ students on econometrics and machine learning algorithms
• Taught students how to use the R language for data science, econometrics, and machine learning

• In ECON 502B: Computations Methods and Dynamic Models in Economics, I held weekly lab sessions to instruct first-year doctoral students on implementing dynamic models using numerical computing in Python. Furthermore, I held weekly office hours to assist students with course materials.
• In ECON 200: Basic Economic Issues, I was the head teaching assistant leading a small team of 10+ undergraduate, masters, and Ph.D. students in operating this 500+ student course. I also wrote Python code to automate participation recording and uploading exam scores into the online grade portal.
• In BNAN 276: Statistical Inference, I held office hours to help students with homework assignments and studying for exams as well as assisted the instructor with grading.

• Worked with a team of doctoral economics students writing code for a project regarding estimating climate damages. Translated STATA code into the R language while eliminating potential bottlenecks.
• Constructed multiple forecasting models in the R language for a project aimed at predicting inflation to understand if it is harder to forecast since the COVID-19 pandemic.

• Designed a data generating process and constructed a Monte Carlo simulation in the R language.
• The paper that this DGP was created for concerns estimating production functions when output is given exogenously.