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International Macroeconomics and Trade

BUSN 33946 & ECON 35101
Jonathan Dingel
Autumn 2020

This is a graduate course in international trade. It introduces the fundamental concepts and tools of international trade and economic geography to prepare students to tackle research questions in these areas.

Logistics

Email: jdingel@chicagobooth.edu
Office hours: Zoom appointments, please email
Teaching assistant: Takashi Onoda (onoda@uchicago.edu)
Course materials: github.com/jdingel/econ35101 and canvas.uchicago.edu
Class schedule: Mondays 8:30 AM - 11:30 AM via Zoom
This course will start September 21 and run through November 30. This class is remote-only.

Assessment

Grades will be based on comprehension checks (15%), assignments (60%), and a final exam (25%).

  • Comprehension checks should require little more than comprehending the assigned readings.

  • I will give three types of assignments, which require more time and creativity:

    1. Economics: I will ask you to derive a theoretical result or survey an empirical literature.

    2. Programming: I will ask you to write a function that solves for equilibrium or estimates a parameter. See comments on computation below.

    3. Referee reports: I will ask you to write a referee report on a recent working paper.

  • Students may choose between a traditional final exam or a quarter-long joint replication project. I would prefer the latter. We will discuss this during the first week of class.

  • In addition to course material, the traditional final exam may ask you to propose an original research idea, so you should be thinking about these during our class (and for the rest of your life!).

Comprehension checks and assignments will be posted to this GitHub repository. Submit your work via the Canvas site.

Computation

Scientific computation is important. I hope that you have already been exposed to the basics. Please glance at Jesus Fernandez-Villaverde's "Computational Methods for Economists" course. My workflow is outlined in my project template.

You have choices to make. See “A Comparison of Programming Languages in Economics.” I recommend the Julia language. Julia's advantages are that it is open source and typically faster than Matlab. Its downside is that it is a young language, so its syntax is evolving. To get started doing economics in Julia, see Perla, Sargent, and Stachurski's “Lectures in Quantitative Economics.” You may submit Julia or Matlab code as homework solutions. Please confer with me before submitting code written in other languages.

Standards for transparency and replicability are rising quickly. The AEA has appointed a Data Editor who will verify that code works prior to accepting papers for publication. Please write code for this class that is transparent and self-contained.

Other resources

Presentation and writing

Graduate students often underestimate the importance of good writing and presentation skills. A job market paper must teach us something new. Teaching means communicating your content to the audience. A useful idea that cannot be conveyed is not a useful idea.

Clear presentations also build others’ confidence that you are a clear thinker. As a well-known IO economist once said, “if I see typos in your slides, I know there are typos in your code.”

Course Outline and Reading List

I have opted for a minimalist reading list. Every reading listed below is required. We will discuss each paper and chapter that is listed in considerable detail. Do the readings before class each week. If you don't have time to do all the readings before class, I have marked the highest-priority item in each week with an exclamation point.

If you’re going to be a trade economist, you ought to own the following books:

Week 1: Gains from Trade and Comparative Advantage

Week 2: Deterministic Ricardian models

Week 3: Probabilistic Ricardian models

Week 4: Gravity and gains from trade

Week 5: Multiple factors of production

Week 6: Increasing returns and home-market effects

Week 7: Heterogeneous firms

Week 8: Models of agglomeration

Week 9: Economic geography

Week 10: Spatial sorting of skills and sectors

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