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58920-01 - Kolloquium: Causal Inference for Policy Evaluation (6 KP)

Semester Frühjahrsemester 2025
Angebotsmuster Jedes Frühjahrsem.
Dozierende Mario Bernasconi (mario.bernasconi@unibas.ch)
Conny Wunsch (conny.wunsch@unibas.ch, BeurteilerIn)
Inhalt Does welfare spending reduce poverty? Does a minimum wage destroy jobs? Does trade liberalisation increase inequality? Does development aid really help poor countries? Do longer sentences reduce crime? Do workers and consumers respond to tax incentives? Do open-plan offices harm worker productivity? Policy makers, firms and economists around the globe are confronted with such questions on a daily basis and effective measures can only be designed with good answers. Measuring and understanding the causal effect of policies and other measures economic agents use is now more important than ever in any field, from development to labour, from finance to education and beyond. This course offers students a comprehensive understanding of the state-of-the-art techniques for causal analysis and how they should be applied in practice.

Quantifying causal effects in a credible way is very challenging and the econometric methods for causal analysis provide the necessary toolkit. This course covers the main methods for causal analysis with a focus on understanding how causality can be established. The objective of this course is to enable students to understand and apply these methods. Methodologically, the course covers the following:

1. Introduction to causal analysis
2. The potential outcome model
3. Identification versus estimation
4. Method 1: Exploiting rich data to handle endogeneity issues
5. Method 2: Exploiting policy changes with a difference-in-differences approach
5. Method 3: Exploiting exogenous variation with an instrumental variable
6. Method 4: Exploiting policy discontinuities with a regression discontinuity design

For each method, the course also covers an overview of important extensions.

We start with the theoretical econometric foundations of each method and discuss the assumptions that allow the researcher to estimate a causal effect. Next, we discuss a research paper that applies the method and is easy to understand by students from different backgrounds to obtain a deeper understanding of what the assumptions mean and how an actual application looks like. In the last step, we implement the method with real data in the PC lab. Making the step from theoretical knowledge of an econometric method to actually applying it to a specific question with real data often proves very challenging. Also, presenting results in a meaningful way is important for making sure that the empirical evidence provided is a useful input, e.g. for policy makers. Therefore, students in this course also learn how to validate data, how to select the estimation sample, how to prepare the data for later analysis, how to produce and interpret relevant descriptive statistics, how to conduct the empirical analysis, how to present and interpret the results and how to provide supporting evidence for the validity of the chosen methodology.
Lernziele Learning objectives

• Understanding the challenges involved in causal analysis.
• Understanding the state-of-the-art techniques for causal analysis.
• Being able to judge the quality and credibility of empirical research.
• Being able to apply the state-of-the-art techniques for causal analysis.
• Being able to present the results of an empirical analysis in a meaningful way.

Target groups
• students who are interested in empirical policy evaluation
• students who are interested in writing an empirical master’s thesis
• students who are interested in econometric methods
• beginning doctoral students
Literatur A list with compulsory and recommended readings will be provided on ADAM. References for further readings will be provided on the slides.
Weblink Weblink

 

Teilnahmevoraussetzungen Students should be familiar with basis statistics (expectations, conditional expectations, distribution functions) as well as standard OLS and instrumental variable approaches such as 2SLS. Knowledge about panel data methods is helpful as well. Recommended courses are 10172-01 "Einführung in die Ökonometrie", 12036-01 "Econometrics" and 41957-01 "Fundamentals of Econometric Theory".
Anmeldung zur Lehrveranstaltung Registration: Please enroll in the Online Services (services.unibas.ch);

Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html
After successful registration you can enroll for the course in the Online Services (services.unibas.ch).

Applies to everyone: Enrolment = Registration for the course and the exam!
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz

 

Intervall Wochentag Zeit Raum
wöchentlich Dienstag 16.15-19.45 Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31

Einzeltermine

Datum Zeit Raum
Dienstag 18.02.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Samstag 22.02.2025 09.15-13.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 25.02.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Samstag 01.03.2025 09.15-13.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 04.03.2025 16.15-17.45 Uhr No class, --
Dienstag 11.03.2025 16.15-17.45 Uhr Fasnachstferien
Dienstag 18.03.2025 16.15-19.45 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Dienstag 25.03.2025 16.15-19.45 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Dienstag 01.04.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 08.04.2025 16.15-19.45 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Dienstag 15.04.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 22.04.2025 16.15-19.45 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Dienstag 29.04.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 06.05.2025 16.15-19.45 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Dienstag 13.05.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Dienstag 20.05.2025 16.15-17.45 Uhr Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31
Module Modul: Core Courses in Business and Economics (Masterstudium: Wirtschaftswissenschaften)
Modul: Core Courses in Data Science and Computational Economics (Masterstudium: Wirtschaftswissenschaften)
Modul: Core Courses in International Business, Trade and the Environment (Masterstudium: Wirtschaftswissenschaften)
Modul: Core Courses in Labor Economics, Human Resources and Organization (Masterstudium: Wirtschaftswissenschaften)
Modul: Core Courses in Public Policy (Masterstudium: Economics and Public Policy)
Modul: Electives in Data Science (Masterstudium: Data Science)
Modul: Fachlich-methodische Ausbildung (Promotionsfach: Staatswissenschaften)
Modul: Fachlich-methodische Weiterbildung (Doktoratsstudium - Wirtschaftswissenschaftliche Fakultät (Studienbeginn vor 01.02.2024))
Modul: Field Electives in Economics and Public Policy (Masterstudium: Economics and Public Policy)
Modul: Specific Electives in Business and Economics (Masterstudium: Wirtschaftswissenschaften)
Modul: Specific Electives in Data Science and Computational Economics (Masterstudium: Wirtschaftswissenschaften)
Modul: Specific Electives in International Business, Trade and the Environment (Masterstudium: Wirtschaftswissenschaften)
Modul: Specific Electives in Labor Economics, Human Resources and Organization (Masterstudium: Wirtschaftswissenschaften)
Prüfung Leistungsnachweis
Hinweise zur Prüfung The final grade will be based on several small bi-weekly assignments between lab sessions on the one hand, and a bigger final assignment after the last session on the other hand. The bi-weekly assignments will consist of smaller coding exercises and some open questions. For the larger final assignment, students will receive data with which they have to apply one or more of the methods covered in class. Depending on class size, assignments will be conducted in groups of 1-3 students.
An-/Abmeldung zur Prüfung Anm.: Belegen Lehrveranstaltung; Abm.: stornieren
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,1
Belegen bei Nichtbestehen beliebig wiederholbar
Zuständige Fakultät Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch
Anbietende Organisationseinheit Wirtschaftswissenschaftliche Fakultät / WWZ

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