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econ6905's Introduction

ECON G6905: Topics in Trade

Jonathan Dingel
Columbia University
Fall 2023

This graduate course covers topics in international trade and spatial economics. We will extensively cover the methods use to estimate, calibrate, simulate, and solve quantitative trade and spatial models. The topics covered will include estimating gravity regressions with high-dimensional fixed effects, computing counterfactual outcomes by exact hat algebra, choosing and implementing numerical solution methods, and conducting Monte Carlo simulations.

This class is designed to complement the trade and spatial subjects covered by David Weinstein in G6903 and Donald Davis in G6910. I will introduce concepts and models in a self-contained fashion, as I do not expect second-year PhD students to have already completed those classes.

Logistics

Course materials: github.com/jdingel/econ6905
Class schedule: Thursdays 10:10 AM - 12:00 PM
Email: [email protected] or [email protected]
Office: IAB 1029
Office hours: By appointment, please email

Assessment

Grades will be based on assignments (70%) and a final exam (30%).

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. 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.

Course Outline and Reading List

I may revise the course outline and reading list during the semester.

Week 1: The CES Armington model

Week 2: Gravity regressions

Week 3: Increasing returns and home-market effects

Week 4: Non-homothetic preferences

Week 5: Agglomeration economies

Week 6: Quantitative spatial models

Week 7: Quantitative urban models

Week 8: Exact hat algebra and calibration

Week 9: The canonical urban model

Week 10: Spatial sorting of skills and sectors

Week 11: Discrete choice estimation and simulations

Week 12: Spatial policies

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