Programming for Economists
Programming for Economists
Course responsible:
Jeppe Druedahl, Associate Professor, University of Copenhagen, Department of Economics
Brigitte Hochmuth, Assistant Professor, University of Copenhagen, Department of Economics
Videos: Asker Nygaard Christensen, PhD student, University of Copenhagen, Department of Economics
This course introduces you to programming and enables you to summarize and visualize empirical data, as well as numerically solve simple economic models.
In the first part of the course, you will learn the general-purpose programming language Python. You will explore different data types and write conditional statements, loops, functions, and classes. Additionally, you will learn how to import and export data and use online databases (APIs), as well as summarize and visualize data in the context of descriptive economics.
In the second part of the course, you will learn how to use numerical optimizers and root-finders to solve and analyze economic problems from basic micro- and macroeconomics. You will also learn how to draw random numbers and run simulations.
In the third part of the course, you will get hands-on experience applying these techniques by working on a data analysis project and a model analysis project. You will learn how to structure, test, debug, and document your code, as well as collaborate effectively using a version control system (Git).
The course emphasizes hands-on programming experience from the very start. To support this, you will have access to an online interactive learning platform where you can solve programming exercises and view additional instructional videos, which will aid your progress in achieving the learning outcomes.
Finally, the course gives you are broader perspective on computational methods in economics with references to both dynamic programming and artificial intelligence (machine learning).
Datacamp: All students attending the course will receive 6 months of free access to DataCamp.
You will receive an e-mail regarding this.
In the first classes, you will follow online courses at DataCamp to learn the basics of Python.
Installation: Follow the installation guide.
The course material is availible here:
Lectures: NumEconCopenhagen/ProgEcon-lectures
Exercises: NumEconCopenhagen/ProgEcon-exercises
Deadlines for hand-in etc.: See calendar
More practical information: kurser.ku.dk
Knowledge:
Describe the differences between fundamental data types (e.g. strings, booleans, integers and floats)
Describe the differences between data containers (e.g. lists, dicts and arrays)
Explain the use of conditionals (if-elseif-else)
Explain the use of loops (for, while, continue, break)
Explain the use of functions, methods and classes
Describe the difference between views and copies of objects
Explain how to use numerical optimizers and root-finders
Explain how to use (pseudo) random numbers
Explain how to use linear interpolation
Skills:
Setup a Python environment
Write Python scripts, functions and notebooks
Structure and document code
Test and debug code
Use version control system (Git)
Import and export data and use online databases (APIs)
Summarize and visualize data
Use numerical optimizers and equation solvers
Solve economic models numerically
Simulate economic models
Calibration economic models to data
Competencies:
Write well-structured and well-documented code
Work collaboratively on code projects
Present and discuss results of a numerical analysis of empirical data and economic models