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Microeconometrics

Beyond Average Effects: Quantile Regression, Distributional Analysis and Inequality

Learn to measure how policies affect different groups using advanced methods for distributional analysis, inequality and mobility.

17.5h (5 days)

€1,470

Face-to-face

English

Next edition: July 5-9, 2027

Early bird deadline: April 15, 2027

Learn more

Microeconometrics

Beyond Average Effects: Quantile Regression, Distributional Analysis and Inequality

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Who is this Course for?

Beyond Average Effects: Quantile Regression, Distributional Analysis and Inequality

Course overview

Understanding how policies affect different groups is essential to evaluating their impact on inequality and social mobility. This course introduces practical methods for analysing how outcomes vary across the distribution, moving beyond average effects to identify who gains and who loses from policies such as minimum wage changes, tax reforms and pension reforms.

Participants will learn both quantile and distribution regression, alongside advanced methods for addressing endogeneity, sample selection and mobility analysis. Each lecture includes a practical session in R, allowing participants to apply these techniques to real data.

Designed for researchers and professionals in public institutions, central banks, and consultancies, the course provides tools to conduct more detailed policy evaluations. As distributional analysis becomes increasingly important in economic policymaking, these methods help decision-makers better understand who is affected by policy interventions and how.

Faculty

Who is this course for?

This course has been designed for:

Master’s & PhD students
Researchers and professionals
Public policy or industry practitioners

Learning outcomes

By the end of the course, students should be able to:

Understand the main concepts and methods for modeling conditional distributions and quantiles
Estimate and conduct inference on distribution and quantile regression models, including uniform inference for function-valued parameters
Understand identification and estimation in distributional models with exogenous and endogenous variables
Construct and interpret counterfactual distributions and distributional and quantile causal effects
Apply distributional methods to changes-in-changes designs, sample selection, and conditional rank-rank regressions
Implement the main methods covered in the course using R and interpret the resulting empirical estimates

Key topics for this Quantile Regression, Distributional Analysis and Inequality course

The course will explore the following topics:

Quantile Regression: Model, Estimation, and Inference

Exogenous conditional quantile models
Koenker and Bassett QR estimator
Uniform inference

Extensions of Quantile Regression: Tails, Time, and Censoring

Extremal quantile regression
Changes-in-changes
Equivariance and censored quantile regression

Quantile Regression with Endogeneity and Treatment Effects

Models with endogeneity
Treatment effects

Distribution Regression: Model, Estimation, and Extensions

Distribution regression model
Estimation
Distribution vs. quantile regression
Bivariate distribution regression

Applications of Distribution Regression

Unconditional and counterfactual distributions
Conditional rank-rank regression
Sample selection

List of References

Below is a list of references that may help you when preparing for the course. Texts are organized by topic.

Quantile Regression: Model, Estimation, and Inference

Angrist, J. D., Chernozhukov, V., & Fernández-Val, I. (2006). Quantile regression under misspecification, with an application to the U.S. wage structure. Econometrica, 74(2), 539–563.
Koenker, R. (2005). Quantile Regression (Econometric Society Monographs, No. 38). Cambridge University Press.
Koenker, R., & Bassett, G., Jr. (1978). Regression quantiles. Econometrica, 46(1), 33–50.
Koenker, R., Chernozhukov, V., He, X., & Peng, L. (Eds.). (2018). Handbook of Quantile Regression. Chapman and Hall/CRC.

Extensions of Quantile Regression: Tails, Time, and Censoring

Abrevaya, J. (2001). The effects of demographics and maternal behavior on the distribution of birth outcomes. Empirical Economics, 26(1), 247–257.
Athey, S., & Imbens, G. W. (2006). Identification and inference in nonlinear difference-in-differences models. Econometrica, 74(2), 431–497.
Chernozhukov, V. (2005). Extremal quantile regression. The Annals of Statistics, 33(2), 806–839.
Chernozhukov, V., & Fernández-Val, I. (2011). Inference for extremal conditional quantile models, with an application to market and birthweight risks. Review of Economic Studies, 78(2), 559–589.
Chernozhukov, V., Fernández-Val, I., & Kaji, T. (2017). Extremal quantile regression: An overview. arXiv preprint arXiv:1612.06850.
Gnedenko, B. (1943). Sur la distribution limite du terme maximum d’une série aléatoire. Annals of Mathematics, 44(3), 423–453.
Powell, J. L. (1984). Least absolute deviations estimation for the censored regression model. Journal of Econometrics, 25(3), 303–325.

Quantile Regression with Endogeneity and Treatment Effects

Abadie, A. (2002). Bootstrap tests for distributional treatment effects in instrumental variable models. Journal of the American Statistical Association, 97(457), 284–292.
Abadie, A. (2003). Semiparametric instrumental variable estimation of treatment response models. Journal of Econometrics, 113(2), 231–263.

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

All BSE Summer School applicants must meet the entrance requirements.

Next edition: July 5-9, 2027

Early Bird deadline: April 15, 2027

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

Requirements for Beyond Average Effects: Quantile Regression, Distributional Analysis and Inequality course

A Background in econometrics at Master’s or PhD level
Relevant professional experience

Schedule

Here is your schedule for this edition of BSE Microeconometrics Summer School, Difference in Differences with Panel Data course.

Time

5

mon

6

tue

7

wed

8

thu

9

fri

11:30-13:30

Lecture

16:15-17:45

Practical

Credit Transfers (ECTS)

To be eligible for credit transfer, students must complete a final project.

Students will deliver a short final project one week after the summer school finishes.

It will consist of completing an assignment that will include the practical and empirical issues worked on in class.

Consult the Summer School Admissions page for more information about this option.

Certificate of Attendance

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

Course

Beyond Average Effects: Quantile Regression, Distributional Analysis and Inequality

Difference-in-Differences with Panel Data

Dynamic and Non-linear Panel Data Models

Dynamic Structural Models for Policy Evaluation

Quantitative Methods for Public Policy Evaluation

Modality

Face-to-face

Total Hours

17.5

ECTS

1

Regular Fee

€1,470

Reduced Fee*

€840

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

Multiple discounts are available.

For more information on discounts for participants funding their own course, please click here.

For more information on discounts for companies and institutions enrolling their employees, please click here.

Full discount conditions are available here.

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.

Can I take more than one course?

Yes! you can combine any of the Summer School courses (schedule permitting). See the full course calendar.

Cancelation and Refund Policy

Please consult BSE Summer School policies for more information.

Are there any evening activities during the course?

Yes, a social dinner is held once a week for all participants, it is free to attend.

Contact our Admissions Team

Mix and match your summer courses!

Remember that you can combine this program with courses in any of the other BSE Summer School programs (schedule permitting). Maximise your learning this summer and take advantage of our multiple-course discount.

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