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Microeconometrics

Dynamic Structural Models for Policy Evaluation

Methods and applications of dynamic discrete choice structural models in Economics.

17.5h (5 days)

€1,399

Face-to-face

English

Program date: June 29-July 3, 2026

Early bird deadline: April 15, 2026

Learn more

Dynamic Structural Models for Policy Evaluation

Applications for BSE Summer School are now open!

Who is this Course for?

Dynamic Structural Models for Policy Evaluation

Course overview

This course deals with methods and applications of dynamic discrete choice structural models in Economics. Researchers with interests in Labor Economics, Industrial Organization, Quantitative Macro, Development Economics and many other fields in Applied Micro often use the methods that we will discuss.

The course focuses on the estimation of dynamic discrete-choice structural models that allow for modeling the behavior of forward-looking agents making discrete decisions. These models constitute a useful tool for policy evaluation and an interesting complement to reduced-form approaches. In particular, they have the advantage of allowing for ex-ante policy evaluation and of providing external validity for the inference, subject to the model assumptions. They also have the benefit of providing a close link between economic theory and empirics, and the possibility of making inferences about the predictions of a model.

The course is organized into three blocks:

Block 1: Introduction to the basic framework and a review of standard estimation techniques based on Maximum Likelihood, including the numerical solution of dynamic programming problems
Block 2: Overview of alternative estimation methods under the umbrella of Conditional Choice Probability (CCP) approaches, which avoid solving value functions during estimation
Block 3: Discussion of the additional challenges that arise in dynamic settings with strategic, game-theoretical interactions among agents. This section includes theoretical insights supported by examples from published research

Practical sessions will be devoted to the numerical solution and estimation of these models using STATA (MATA).

Faculty

Learning outcomes

Participants of the course will:

Grasp the principles and applications of dynamic discrete choice models in Economics
Master estimation techniques using Maximum Likelihood and Conditional Choice Probability methods
Connect economic theory with empirical data and make inferences about model predictions
Understand the complexities of dynamic problems involving game theoretical responses
Gain hands-on experience in the programming of solution and estimation of dynamic discrete choice structural models using the MATA facility of STATA
Gain tools to enable you to solve complex models, simulate policy outcomes and perform computational analysis at a high level

Key topics for Dynamic Structural Models for Policy Evaluation course

Here is a list of topics you will cover during the course.

Full solution Maximum Likelihood approaches

Introduction
Basic framework: conditional independence
Motivational example: Rust’s engine replacement model
Estimation using full solution techniques
Extensions: unobserved heterogeneity and equilibrium

Conditional Choice Probability (CCP) estimation

Conditional value function representation
Finite dependence
Estimation methods
Aguirregabiria and Mira’s iterative approach
Extensions: unobserved heterogeneity and equilibrium

An Introduction to Dynamic Discrete Games

List of References

The following texts will help you prepare for the course.

Recommended Texts

Adda, J. and R. W. Cooper (2003), Dynamic Economics: Quantitative Methods and Applications. The MIT Press.
Altug, S. and R. A. Miller (1998), “The Effect of Work Experience on Female Wages and Labor Supply”, Review of Economic Studies, 65, 45-85.
Aguirregabiria, V. and P. Mira (2002), “Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models”, Econometrica, 70, 1519-1543.
Aguirregabiria, V. and P. Mira (2007), “Sequential Estimation of Dynamic Discrete Games”, Econometrica, 75, 1-53.
Aguirregabiria, V. and P. Mira (2010), “Dynamic Discrete Choice Structural Models: A Survey”, Journal of Econometrics, 156: 38-67
Arcidiacono, P. and P. B. Ellickson (2011), “Practical Methods for Estimation of Dynamic Discrete Choice Models”, Annual Review of Economics, 3, 363-394.
Arcidiacono, P. and R. A. Miller (2011), “Conditional Choice Probability Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity”, Econometrica, 79, 1823-1867.
Berndt, E. K., B. H. Hall, R. E. Hall, J. A. Hausman (1974). “Estimation and Inference in Nonlinear Structural Models”, Annals of Economic and Social Measurement 3, 653-665.
Eckstein, Z. and K. Wolpin (1989), “The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey”, Journal of Human Resources, 24: 562-598
Hong, H. and M. Shum (1998), “Structural Estimation of Auction Models”, In: Patrone F., García-Jurado I., Tijs S. (eds) Game Practice: Contributions from
Applied Game Theory. Theory and Decision Library (Series C: Game Theory, Mathematical Programming and Operations Research), vol 23. Springer, Boston, MA.
Hotz, V. J. and R. A. Miller (1993), “Conditional Choice Probabilities and the Estimation of Dynamic Structural Models”, Review of Economic Studies, 60, 497-529.
Keane, M. P. and K. I. Wolpin (1997), “The Career Decisions of Young Men”, Journal of Political Economy, 105, 473-522.
Lee, D. and K. I. Wolpin (2006), “Intersectoral Labor Mobility and the Growth of the Service Sector”, Econometrica, 74, 1-46.
Llull, J. (2018), “Immigration, Wages, and Education: A Labor Market Equilibrium Structural Model”, Review of Economic Studies, 85, 1852-1896.
Llull, J. (2018), “Selective Immigration Policies and the U.S. Labor Market”, mimeo, MOVE, Universitat Autònoma de Barcelona, and BSE.
Miller, R. A. (1997), “Estimating models of dynamic optimization with microeconomic data”, in M. Pesaran and P. Schmidt (eds.), Handbook of Applied Econometrics, Vol. 2, pp. 246-299
Todd, P. and K. Wolpin (2006), “Assessing the Impact of School Subsidy Program in Mexico: Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility”, American Economic Review, 96, 1384-1417.
Rust, J. (1987), “Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher”, Econometrica, 55, 999-1033.
Rust, J. (1994), “Structural Estimation of Markov Decision Processes”, in R. E. Engle and D. L. McFadden (eds.), Handbook of Econometrics, Vol. 4, Ch. 51.

Software / Hardware

STATA (MATA) will be used during the course. Participants will receive a temporary personal license, provided by BSE, a few days before Summer School begins
Participants must bring their own portable laptop to participate fully in this course

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

Participants to BSE Summer School must check they are eligible to apply.

Program date: June 29-July 3, 2026

Early bird deadline: April 15, 2026

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 Dynamic Structural Models for Policy Evaluation

A strong understanding of Econometrics (as covered in Wooldridge, 2002) and Dynamic Programming (specifically Chapters 1-2 of Adda and Cooper, 2003) is highly recommended

Schedule

Here is your schedule for this edition of BSE Microeconometrics Dynamic Structural Models for Policy Evaluation course.

Time

29

mon

30

tue

1

wed

2

thu

3

fri

11:30 - 13:30

Lecture

17:00 - 18:30

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.

Fees

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

Course

Dynamic and Non-linear Panel Data Models

Choice Modeling Using Micro Data: Applications

Dynamic Structural Models for Policy Evaluation

Panel Data and Spatial Panels

Quantitative Methods for Public Policy Evaluation

Difference-in-Differences with Panel Data

Modality

Face-to-face

Total Hours

17.5

ECTS

1

Regular Fee

1,399€

Reduced Fee*

799€

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

FAQ

Need more information? Check out our FAQ section or 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?

Unfortunately, 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 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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