MACS 30250 - Perspectives on Computational Research in Economics (Spring 2020)

	Dr. Richard Evans
Email	[email protected]
Office	1155 E 60th St, Room 217 (but really in Utah)
Office Hours	M 3:00-5:00pm
GitHub	rickecon

• Meeting day/time: MW 1:30-2:50pm Central Time (Chicago), Remote access
• Office hours also available by appointment

Course description

This course focuses on applying computational methods to conducting social scientific research in economics through a student-developed research project. Students will identify a research question of their own interest that involves a direct reference to economic theory, use of data, and a significant computational component. The students will collect data, develop, apply, and interpret statistical learning models, and generate a fully reproducible research paper. We will identify how computational methods can be used throughout the research process, from data collection and tidying, to exploration, visualization and modeling, to the final communication of results. The course will include modules on theoretical and practical considerations, including topics such as epistemological questions about research design, writing and critiquing papers, and additional computational tools for analysis.

Grades

Assignment	Points	Quantity	Total points	Percent
Proposal	10	1	10	6.2%
Literature review	15	1	15	9.4%
Methods/initial results	15	1	15	9.4%
Peer evaluations of posters	2	5	10	6.2%
Poster presentation	30	1	30	18.8%
Final paper	40	1	40	25.0%
Problem sets	10	4	40	25.0%
Total Points			160	100.0%

Students will turn assignments in via their own public GitHub fork of the main class repository (e.g., https://github.com/YourGitHubHandle/persp-research-econ_Spr20). The directory structure of this repository should be the following.

• github.com/YourGithubHandle/persp-research-econ_Spr20/
  • Assignments
    • PS1
    • PS2
    • PS3
    • PS4
  • Proposal
  • LitReview
  • MethodsResults
  • Poster
  • FinalPaper

Late Problem Sets

Late problem sets will be penalized 2 points for every hour they are late. For example, if an assignment is due on Monday at 1:30pm Central Time (Chicago), the following points will be deducted based on the time stamp of the last commit.

Example PR last commit	points deducted
1:31pm to 2:30pm	-2 points
2:31pm to 3:30pm	-4 points
3:31pm to 4:30pm	-6 points
4:31pm to 5:30pm	-8 points
5:31pm and beyond	-10 points (no credit)

Disability services

If you need any special accommodations, please provide us with a copy of your Accommodation Determination Letter (provided to you by the Student Disability Services office) as soon as possible so that you may discuss with me how your accommodations may be implemented in this course.

Course schedule

Date	Day	Topic	Reading	Recording	Assignment
Apr 6	M	Overview/reproducibility in science	Slides	Video
Apr 8	W	Abstract/intro/conclusion	Slides	Video
Apr 13	M	Theory section of paper	Slides	Join Zoom
Apr 14	Tu				Proposal slides due
Apr 15	W	Proposal presentations		Join Zoom	Proposal presentations
Apr 20	M	Data/methods section of paper	Slides	Join Zoom
Apr 22	W	Computational results section of paper	Slides	Join Zoom
Apr 27	M	Kernel density estimation	Notebk	Join Zoom	PS1
Apr 29	W	Kernel density estimation		Join Zoom	Lit review section due
May 4	M	Parallel computing	Notebk	Join Zoom	PS2
May 6	W	Parallel computing	Dask Tutorial	Join Zoom
May 11	M	Workshop papers/office visits	Schedule
May 13	W	Dynamic programming with interpolation	Notebk	Join Zoom	PS3
May 18	M	Dynamic programming with interpolation		Join Zoom
May 20	W	Workshop papers/office visits	Schedule
May 25	M	No class (Memorial Day Holiday)
May 27	W	Effective presentations, poster, slides	Slides/Notes	Join Zoom	Methods/initial results section due
Jun 1	M	Overlapping generations models	Notes	Join Zoom	PS4
Jun 3	W	Overlapping generations models		Join Zoom	Poster due
Jun 4-5	Th-Fri	Zoom poster presentations		Join Zoom
Jun 10	W	Final papers due at 11:59pm			Papers due

References and Readings

• Casadevall, Arturo and Ferric C. Fang, "Reproducible Science," American Society for Microbiology: Infection and Immunity, 78:12, pp. 4972-4975 (2010).
• Christensen, Garret S. and Edward Miguel, "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, 56:3 pp. 920-980 (Sep. 2018).
• Evans, Richard W., "Public Debt, Interest Rates, and Negative Shocks," American Economic Review (forthcoming, May 2020).
• Ince, Darrel C., Leslie Hatton, and John Graham-Cumming, "The Case for Open Computer Programs," Nature, 482, pp. 485-488 (23 Feb. 2012).
• Miguel, E., C. Camerer, K. Casey, J. Cohen, K. M. Esterling, A. Gerber, R. Glennerster, D. P. Green, M. Humphreys, G. Imbens, D. Laitin, T. Madon, L. Nelson, B. A. Nosek, M. Petersen, R. Sedlmayr, J. P. Simmons, U. Simonsohn, and M. Van der Laan, "Promoting Transparency in Social Science Research," Science (3 Jan. 2014).
• Niemeyer, Kyle, "Nature Editorial: If you want reproducible science, the software needs to be open source," Ars Technica (26 Feb. 2012).