Last edited: April 22, 2026

Economics in the Age of Big Data

Course: Econ 337

Instructor: Enes Işık

Email: eisik[at]umass.edu

Venue: MoWe 17:30 - 18:45 at Machmer Hall, room E-33

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Office hours: In person, Gordon Hall, room 108, by appointment.

Click here to make an appointment (must book it at least 4 hours before the appointment starts). </aside>

Semester: Jan 29, 2026-May 8, 2026, Number of class meetings: 24

Final Grades Due ****by 11:59 p.m., May 17

Textbook: Not required. Course materials will be provided by the instructor. ****

Course Description and Goals

This course gives students ideas, analysis skills, and practical tools to judge data-based knowledge carefully and to create it themselves. Students will need these skills to take part in public debate, and understand the joke shown on the right!

by Randall Munroe, xkcd

First, we look at how knowledge is made. We study how scientists and social researchers create knowledge, and how their methods often differ. This leads to two big questions: what makes someone an expert, and how can ideology affect research that uses data?
Students will develop the ability to evaluate numbers, statistics, and visually presented information so that they can critically engage with data-driven statements in public debates. This help them examine how quality of evidence can impact public discourse.
Student will apply their newly developed analytical skills to some of the largest social problems; specifically, income inequality, growth, climate change, and gender inequality. To accomplish this, students will learn to program in R and use it to analyze data in a way that can be critically reviewed and replicated by other researchers.
By the end of the course, students should be able to evaluate factual claims critically, explain and communicate evidence clearly, and take a more active part in democratic discussions where data and experts shape group decisions.

Students are expected to complete all required readings before each class session, and a brief quiz on the assigned material will be given at the start of class in person.
After Week 7, students will take an in-class midterm exam covering the content from parts I and II of the course.
With a peer, students will present selected research papers, apply their critical evaluation skills to these papers.
Three problem sets will be assigned throughout the part III to help students apply coding skills to real-world questions that can be explored using big data distributed by the instructor.
A final project will be due at the end of the semester, in which students will use big data in R to analyze a real-world economic issue.

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All assignment details can be found on the Assignments page in Canvas.

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In addition to these assignments, students are expected to engage actively in class discussions.