Ph.D. Candidate in Economics · Lehigh University
ECO 146, Intermediate Microeconomic Analysis
Adjunct Professor, Lehigh University — Summer 2026. A six-week online section, taught synchronously.
ECO 045, Statistical Methods — Winter 2026
FIN 125, Introduction to Finance — 2024–2025
ECO 001, Principles of Economics — 2022–2024
HHUM 125, Introduction to Health Humanities — guest lecturer, Moravian University, February 2026
Scarcity is the first thing intermediate microeconomics teaches, and it is also what my research is about. Every paper I have written asks what happens when a constraint on access moves: how far someone has to drive to reach a dispensary, whether a household can still afford the car that gets them to work, whether dental coverage exists, whether a psychiatric bed exists. The answer is almost never that people simply do without. They substitute, they travel, they postpone — and the cost lands somewhere the policy did not intend. That is the question I find worth a career, and it is the same question I put in front of students in week one.
A classroom is a scarcity problem of the same kind. My students' time has an opportunity cost: every hour in my course is an hour not spent on the other four. Their attention is scarce and unevenly distributed across the room. Six weeks is scarce — a summer session has no room to recover a week that goes badly. And my own information is scarcest of all, because I cannot see what is failing to land unless students show me. Four commitments follow from that.
Commit before you are shown. Listening is cheap; producing an answer is what costs something, so that is where the class time goes. Every ECO 146 meeting closed with a five-item exercise that students answered before any solution appeared, and the same skill returned days later on the graded problem set with new numbers — the CPI conversion they first met as a $12 sandwich came back on Problem Set 1 as a $90 textbook rental, this time also asking whether the real price had risen.
Own the derivation. A fully worked example, narrated step by step, comes first; then the structure fades. In Class 10 I worked one example from production all the way to cost — labor requirement, variable cost, total cost, marginal cost. Problem Set 3 handed students that same chain with new numbers and closed by asking them to verify their marginal cost a second way, as w/MPL. Problem Set 2 broke the market-demand problem into six numbered steps; the midterm asked for the same object in four, folded two of the steps together, and attached a new question at the end. Throughout, every calculation question carried the same instruction: show the condition, the substitution, and the intermediate steps. Unsupported final answers received little or no credit.
Space it out. Every core skill returns at least three times, in different forms, in a later cumulative context. Horizontal summation is the clearest case. Students met it in Class 8 as a wheat market with domestic and export buyers. Problem Set 2 asked them to build a two-group market demand curve and locate its kink. The midterm asked for the same construction with different demands, then added an elasticity calculation on the segment they had just derived. Problem Set 4 applied the identical logic to market supply with two types of firm. Problem Set 5 used it once more, to find the single uniform price a price-discriminating monopolist would charge. Five encounters across five weeks, each one inside a different problem.
Test my own teaching. Six weeks leaves no time to discover in week five that week two did not land, so most items are auto-graded and return a signal within a day of the deadline, the in-class exercises surface misunderstandings while there is still class left to spend on them, and each problem set is calibrated against what the previous one revealed rather than written in advance as a set. The deeper reason is that my own information is the binding constraint: students see things about my course that I cannot, which makes them the most reliable instrument I have and makes asking them faster than guessing.
Principles of Microeconomics and Macroeconomics; Intermediate Microeconomics; Statistics and Applied Econometrics; Health Economics; Introduction to Finance; data analysis with Stata, R, and Python.