Economics is in the world around us, and so is Data Science! It’s in our every day lives. As we connect Data Science with Economics, we will be exploring real life datasets to illustrate how Economics concepts are shaped and how decisions lead to real-life impacts. This is a textbook developed for UC Berkeley’s course Data 88E: Economic Models. Data 88E is a generic course listing for Data 8 connector courses.
The idea for the class is to take students through a series of exercises to motivate and illustrate key concepts in Economics with examples in Python Jupyter notebooks. The class will cover concepts from Introductory Economics, MIcroeconomic Theory, Econometrics, Development Economics, Environmental Economics and Public Economics. The course will give data science students a pathway to apply python programming and data science concepts within the discipline of economics. The course will also give economics students a pathway to apply programming to reinforce fundamental concepts and to advance the level of study in upper division coursework and possible thesis work.
Course Instructor: Eric Van Dusen
Textbook Developers: Christopher Pyles, Rohan Jha
Content Developers: Alan Liang, Amal Bhatnagar, Andrei Caprau, Christopher Pyles, Cole Ginter, Eric Van Dusen, Peter F. Grinde-Hollevik, Matthew Yep, Rohan Jha, Sreeja Apparaju, Shashank Dalmia, Sushil Vishwanathan, Umar Maniku