Teaching Experience
Instructor
ECON 370: Economic Applications of Data Science
Designed and taught ECON 370, the first course in the DATA credential for undergraduate UNC economics majors. The course is intended for students to learn the R programming language to work with real world data, assuming no prior coding experience. Economic applications were used as examples to help students improve their base R skills and highlight the importance of programming in economics. Applications included auction simulation and solving basic optimization problems (e.g. utility maximization, OLS) numerically using optim. After the introduction to base R, I taught students the most common packages for working with data in R such as dplyr and tidyr in the tidyverse and data.table. I concluded the course by teaching students how to communicate their data visually using ggplot2 and how to produce write-ups of their findings using R Markdown. Any remaining time was used to teach them basic machine learning models such as clustering with K-means and EM. Syllabus
Semesters Taught: Fall 2021, Fall 2022, Fall 2023
Course Description
ECON 370 is intended to provide a broad-based introduction to numerical and data-science methods commonly used in economics. The course will first introduce students to the R programming language, assuming no prior experience. Subsequent lectures will provide students an opportunity to apply this knowledge on real-world data to achieve an economic objective. The methods used in these applications will include (but are not limited to): collecting, cleaning, merging, processing, and visualizing data, descriptive analysis, optimization, and supervised/unsupervised statistical learning. In addition, the course has an experiential component that connects students with industry leaders in economic applications of data-science through a series of on-campus events.
Student Evaluations
"Alex did a great job of teaching coding and the assignments were manageable and informative." Fall 2021 Student
"Incredibly nice human being who obviously wanted to help us in any way possible. A very good lecturer and was entertaining from the student side." Fall 2021 Student
"Super accessible and very kind! It was apparent that he cared a lot about the class material and went out of his way to be helpful to students." Fall 2022 Student
"He provided plenty of time in class to answer questions and consistently held office hours that were very helpful. Showing us real time in R what he was doing was also very helpful." Fall 2023 Student
Teaching Assistant
ECON 101: Introduction to Economics
Served as a teaching assistant for ECON 101: Intro to Economics with Dr. Robert McDonough, which is around an 800 person class at UNC. My main responsibility was leading two recitation sections where students worked on more in-depth practice problems than those seen in lecture. After students first attempted the problems with a partner, I walked through the solutions with an eye towards providing clear explanations to students to assist them in developing a deeper understanding of the material.
Semesters Taught: Spring 2024
Course Description
ECON 101 is an introductory course in microeconomics and macroeconomics. In this course students are introduced to the basic theory and models that economists use to analyze the world. The concepts introduced include comparative advantage and the gains from trade; supply, demand, and the market system; the theory of the firm; market failures; national income and its determination; inflation and unemployment; economic growth, and monetary and fiscal policy.
ECON 470: Econometrics
Served as a teaching assistant for ECON 470: Econometrics with Dr. David Guilkey. Duties included holding office hours, grading exams, and walking students through the exam solutions in the next class meeting. Topics included linear regression estimation with ordinary least squares, instrumental variable regressions, discrete dependent variable models, and models for longitudinal data.
Semesters Taught: Spring 2023
Course Description
Econometrics is the application of statistical methods and economic theory to the problem of identifying, estimating, and testing economic models. This course covers concepts and methods used in empirical economic research. Topics include the classical single-equation regression model, multiple regression models, discrete and categorical dependent variables, instrumental variables and longitudinal data. Students will learn the theory and assumptions behind each of the estimation methods so that they can determine the appropriate method for any particular analysis. In the lectures, there will be many empirical examples using a wide variety of data sets that are either cross sectional or longitudinal.