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CREI - Macroeconomics

Quantitative Methods for Spatial Economics

Exploring quantitative spatial models: Methods, challenges, and policy implications in spatial economics

10h (5 days)

€675 - €1,175

Face-to-face

English

Program date: July 7 - 11, 2025

Early bird deadline: April 15, 2025

Learn more

Quantitative Methods for Spatial Economics

Applications for 2025 Summer School programs are now open!

Summer school

CREI - Macroeconomics

Quantitative Methods for Spatial Economics

Course Overview

The availability of highly disaggregated spatial data and the development of new methods have revolutionized the field of spatial economics, or economic geography, over the last few years.

This course offers an overview of state-of-the-art models of the spatial economy, which are often referred to as quantitative spatial models (QSM). It focuses on the set of economic questions this rapidly growing field seeks to answer, but also on the practical computational challenges involved in solving these models and taking them to the data.

The course is aimed at graduate students, researchers and practitioners who want to develop a working knowledge of QSM in order to answer policy-relevant questions about the geography of economic activity and its implications for the aggregate economy.

Faculty

Do you want to learn more about Quantive Spatial Models? This could be the course for you!

This course targets the following profiles:

Graduate students, researchers and practitioners who want to develop a working knowledge of QSM in order to answer policy-relevant questions.

Address policy-relevant questions about the geography of economic activity and its broader implications

Participants who take this course will receive:

A comprehensive overview of state-of-the-art quantitative spatial models (QSM) and their applications.
Skills to identify and analyze key economic questions related to the geography of economic activity.
Practical skills to tackle the computational challenges of implementing QSM and analyzing disaggregated spatial data.
Training in applying quantitative spatial models to real-world datasets and policy-relevant scenarios.
Knowledge to derive policy implications from spatial economic analyses, informing decisions in the broader economy.

Program Syllabus for Quantitative Methods for Spatial Economics course

Here is an overview of what will be covered in the program:

Course Outline

Why does space matter? Increasing returns, transport costs and the geography of economic activity
The importance of market access
Quantitative urban economics
Dynamic spatial economics

List of References

See below a list of texts and articles that may help you prepare for this course:

Articles and Books

Ahlfeldt, G., Redding, S., Sturm, D. and Wolf, N. (2015): The economics of density: Evidence from the Berlin Wall. Econometrica 83(6), 2127-2189.
Allen, T. and Arkolakis, C. (2014): Trade and the topography of the spatial economy. Quarterly Journal of Economics 129(3), 1085-1140.
Allen, T., Arkolakis, C. and Li, X. (2023): On the equilibrium properties of spatial models. American Economic Review: Insights, forthcoming.
Allen, T. and Donaldson, D. (2022): Persistence and path dependence in the spatial economy. Mimeo.
Bleakley, H. and Lin, J. (2012): Portage and path dependence. Quarterly Journal of Economics 127(2), 587-644.
Caliendo, L., Dvorkin, M. and Parro, F. (2019): Trade and labor market dynamics: General equilibrium analysis of the China trade shock. Econometrica 87(3), 741-835.
Caliendo, L., Opromolla, L., Parro, F. and Sforza, A. (2021): Goods and factor market integration: A quantitative assessment of the EU enlargement. Journal of Political Economy 129(12), 3491-3545.
Ciccone, A. and Hall, R. (1996): Productivity and the density of economic activity. American Economic Review 86(1), 54-70.
Davis, D. and Wenstein, D. (2002): Bones, bombs, and break points: The geography of economic activity. American Economic Review 92(5), 1269-1289.
Desmet, K., Nagy, D. and Rossi-Hansberg (2018): The geography of development. American Economic Review 104(4), 1211-1243.
Donaldson, D. and Hornbeck, R. (2016): Railroads and American economic growth: A “market access” approach. Quarterly Journal of Economics 131(2), 799-858.
Giannone, E. (2022): Skill-biased technical change and regional convergence. Mimeo.
Helpman, E. (1998): The size of regions. In: Topics in public economics: Theoretical and applied analysis, ed. Pines, D., Sadka, E. and Zilcha, I. 33-54. Cambridge University Press.
Kleinman, B., Liu, E. and Redding, S. (2023): Dynamic spatial general equilibrium. Econometrica 91(2), 385-424.
Krugman, P. (1991): Increasing returns and economic geography. Journal of Political Economy 99(3), 483-499.
Redding, S. (2016): Goods trade, factor mobility and welfare. Journal of International Economics 101, 148-167.
Redding, S. and Sturm, D. (2008): The costs of remoteness: Evidence from German division and reunification. American Economic Review 98(5), 1766-1797.
Tsivanidis, N. (2023): Evaluating the impact of urban transit infrastructure: Evidence from Bogotá’s TransMilenio. Mimeo.

Why join our Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs. Join us to:

1

Network with like-minded peers

2

Study in vibrant Barcelona

3

Learn from world-renowned faculty

Admissions and requirements

Applicants must ensure they meet course requirements or verify eligibility with Admissions Counselors.

Program date: July 7 - 11, 2025

Early bird deadline: April 15, 2025

Requirements

Summer School applicants normally demonstrate one or more of the following:

A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.)
Postgraduate degree or current Master’s/PhD studies related to the course topic
Relevant professional experience

Schedule

Here is your schedule for this edition of CREI Macroeconomics Summer School, Quantitative Methods for Spatial Economics course.

Time

7

mon

8

tue

9

wed

10

thu

11

fri

11:30 - 13:30

Lecture

Credit transfers (ECTS)

ECTS are not available for this course

Certificate of Attendance

Participants who attend more than 80% of the course will receive a Certificate of Attendance, free of charge.

Fees

Multiple course discounts are available, see more information about available discounts. Fees for courses in other Summer School programs may vary.

Course

The Data Economy: Tools and Applications

The Macroeconomics of Credit and Asset Bubbles

Numerical Methods for Fiscal and Monetary Policy Analysis

Climate Change, Firms, and the Green Transition

Quantitative Methods for Spatial Economics

Sovereign Debt Crises: Theory, Evidence and Policy

POLICYMETRICS: Econometrics for Macroeconomic Policy Making

Modality

Face-to-face

Total Hours

10

15

10

15

ECTS

0

Regular Fee

1,175€

1,375€

1,175€

1,375€

Reduced Fee*

675€

775€

675€

775€

* Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

FAQ

Here are some commonly asked questions by participants. Any further queries, please contact our Admissions Team.

Can I see the full Summer School calendar?

You can view the full Summer School calendar here.

Is accommodation included in the course fee?

Accommodation is not included in the course fee. Participants are responsible for finding accommodation.

Are the sessions recorded?

Sessions will NOT be recorded; however, the materials provided by the professor will be available for a month after the course has finished.

How much does each Summer School course cost?

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Yes, BSE offers a variety of discounts on its Summer School courses. See more information about available discounts or request a personalized discount quote by email.