AAE724 Practicum for Applied Economists

This class is designed to train students in the quantitative methods typically used by professional economic analysts. Students will synthesize the material they have learned in their AAE coursework in a start-to-finish econometric analysis. The final course product is a professional analyst’s Master’s thesis, a demonstration of the student’s training and capability for professional work, to be shared with prospective employers.

Note: Multiple students may work with the same data (!), but every student must do their work [Re: Code of Conduct section].

We measure class progress in terms of Milestones. There will be four milestones during the semester.

Additionally, you will be required to (a) write code in Python or R, and (b) submit your work via Git(Hub).

• Check Chapter 19 in Wooldridge, on how to carry out an empirical project.

Course Prerequisites

• AAE 635, AAE 636, AAE 771

Programming Tools

• Languages: Python or R

• Version control: Git(Hub)

• Git is a distributed version control system designed to track changes in any types of files. Check instalattion instructions here.

• GitHub provides hosting for files development version control using Git. Sign up for an account here.

Textbook

• There is no required textbook

Deliverables

• All deliverables are due on Wednesdays @ 11:59 pm.
• To submit your work create a PRIVATE respository on GitHub and add Guanming (gshi329) and Cornelia (corneliailin) as contributors.
• We will download your submissions from GitHub after the deadline.
• Please follow the folder structure presented here.
  

Meeting times

• The class meets only on 9/05, 10/03, 10/24, 11/14, and 12/05 (these dates are highlighted in the Class Plan section).
• Please plan for about 2.5h when the class meets. We plan to allocate 20 minutes for each presentation.

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Date	Activity	Deliverable (Wed 11:59 pm)	Points (Total = 100)
Milestone 1
9/05	Course logistics
9/12	Project proposal	Draft project objective section of report: at least two paragraphs	5
9/19	Data description I
9/26	Data description II	Draft data description section of report: identify and eliminate data anomalies and issues summary statistics (tables and graphs)	15
10/03	Group presentations + Feedback	Prepare slides for presentation on: project proposal data description	5
Milestone 2
10/10	Regression model I
10/17	Regression model II	Draft regression model section of report: modelling approach is consistent with the data	20
10/24	Group presentations + Feedback	Prepare slides for presentation on: modelling approach	5
Milestone 3
10/31	Regression results I
11/07	Regression results II	Draft regression results section of report: analysis is consistent with the project objective results are based on regression model estimation	10
11/14	Group presentations + Feedback	Prepare slides for presentation on: regression results	5
11/21	Regression results III	Update draft regression results section of report: based on feedback on first analysis	10
11/28	Thanksgiving break
Milestone 4
12/05	Final presentation	Prepare slides for final presentation on: project proposal data description regression model regression results conclusions	10
12/12	Final report	Submit final report	15

NY Hospital Discharge Data (years: 2014 - 2016)

Nielsen Scanner Data (years: 1989 - 1994)

Longitudinal Study of Adolescent to Adult Health (years: 1994 - 2008)

Can You Hear Me Now? An Analysis of the Competitive Nature of the Cellular Phone Industry.

Perceived Corruption and Foreign Investment: Are Investors Vigilant?

Should They Be Mine or Should They Be Ours? An Analysis of Public and Private Property Rights in the Chesapeake Bay Oyster Industry.

Quality Controlled Release Timing in the Motion Picture Industry.

Balanced Teams versus One Player: The Effect of Scoring Distribution on Points Earned in Soccer.

Quality Controlled Release Timing in the Motion Picture Industry.

How Does Legislation Effect Crime?: An Economic Analysis of the Virginia Shall Issue Law.

Competition and Consolidation in the Audit Industry: Comparing Highly Consolidated Client Industries to a Control Group.

Should California Be Farming? A Cost-Benefit Analysis of Agricultural Subsidies in California's Central Valley.

Market Basked Analysis

Industry Applications of Conjoint Analysis

Final letter grades may be curved upward, but a minimum guarantee is made of an A for 93 or above, AB for 87 or above, B for 80 or above, BC for 75 or above, C for 70 or above, and D for 60 or above.

Cornelia: Th 11:00 - 12:00 pm, or by appointment

Guanming: M/W 12:15 - 1:00 pm, or by appointment

	Cornelia Ilin (cilin@wisc.edu)
	Guanming Shi (gshi@wisc.edu)

You are allowed to use 72 hours throughout the semester to account for late deliverable submissions.

You can discuss deliverables with your colleagues but you must do your own work! Make sure to cite everyone who helped!

We will provide a citation template that must accompany all your code submissions.

This class follows the UW-Honor Code.

McBurney Disability Resource Center syllabus statement: “The University of Wisconsin- Madison supports the right of all enrolled students to a full and equal educational opportunity. The Americans with Disabilities Act (ADA), Wisconsin State Statute (36.12), and UW-Madison policy (Faculty Document 1071) require that students with disabilities be reasonably accommodated in instruction and campus life. Reasonable accommodations for students with disabilities is a shared faculty and student responsibility. Students are expected to inform faculty [Guanming and Cornelia] of their need for instructional accommodations by the end of the third week of the semester, or as soon as possible after a disability has been incurred or recognized. Faculty [Guanning and Cornelia], will work either directly with the student [you] or in coordination with the McBurney Center to identify and provide reasonable instructional accommodations. Disability information, including instructional accommodations as part of a student's educational record, is confidential and protected under FERPA.” [Source].

Institutional statement on diversity: “Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals. The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background – people who as students, faculty, and staff serve Wisconsin and the world.” [Source].

The template of this website was adapted from TheoRekatsinas@UW and created by HazyReseach@Stanford.