20469 - INSTITUTIONS, GOVERNMENT AND SOCIETY - MODULE I
Department of Social and Political Sciences
GIOVANNI FATTORE
Mission & Content Summary
MISSION
CONTENT SUMMARY
The first part of the course covers causal inference in the social sciences by presenting the main models used in contemporary research. The second part discusses validity of empirical studies and complement the first part of the course with additional methods/topics that are increasingnly popular in empirical research in the social sciences.
Part 1. Main analytical approaches for causal interference:
The conterfactual model.
Randomization and its discontents.
Regression Models.
Instrumental variables.
Regression Discontinuity Design.
Difference-in-Differences Design.
Part 2. Validity and additional topics/methods for empirical research in the social sciences:
Survey research and sampling.
Social Network Analysis
Content Analysis.
Systematic Reviews and meta-analsysis.
Validity of research designs.
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Conduct and write a systematic literature review
- Understand the logics of causal inference.
- Master different models to test causality.
- Critically review a scientific paper
- Conduct and write a systematic review
- Produce a research proposal and present it in public
APPLYING KNOWLEDGE AND UNDERSTANDING
- Work in groups to prepare a research proposal.
- Conduct a Systematic Review
- Prepare a research proposal.
- Deliver a presentation of a research proposal
Teaching methods
- Face-to-face lectures
- Group assignments
DETAILS
Through the preparation and discussion of the systematic review and the research proposal the faculty interacts with students to check their ideas. The presentation in class gives the opportunity to be exposed to a variety of research designs and methods in the social sciences in general and in economics in particular. Collaboration between peers also offers the opportunity to foster creativity, acquire presentation skills, learn from peers and understand the criteria used to assess research proposals in scientific international settings.
Assessment methods
Continuous assessment | Partial exams | General exam | |
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ATTENDING STUDENTS
Students' assessment will be based on three elements to assess the overall comprehension of the content of the course: a) testing that they fully understand the essential approaches of research methods, b) conducting a literature review to summarize scientific evidence in a transparent and systematic way, c) conceptualizing an original research proposal to be presented in class. Each of these elements tests different competences and provides students with the essential approaches to master research design in the social sciences.
Grading
Systematic review. Short paper no longer than 3000 words to be delivered on October 9th (10%).
Group project. Project proposal presented by 4 students delivered in the last four sessions of the course (20%).
Final written exam. Two hours exam with multiple choice and 2 open-ended questions (70%).
NOT ATTENDING STUDENTS
Students' assessment will be based on two elements to assess the overall comprehension of the content of the course: testing that students fully understand the essential approaches of research methods and writing an original research proposal. Each of the elements tests different competences and provides students with the essential approaches to understand research design in the social sciences.
Grading
Final written exam. Two hours exam with multiple choice and 2 open-ended questions (60%).
Individual research proposal. A word document no longer than 10000 words to be submitted submitted no later than 10 days before the date of the exam (40%).
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
The main text used in the course is
Dunning, T. 2012. Natural experiments in the social sciences. A design-based approach. Strategies for social inquiry.
Other texts that cover research design and methods that can help students to cover possible methodological gaps on specific topic are:
- Cunningham, S. 2021. Causal inference: The Mixtape.
- Angrist JD and Pische JS. 2018. Mostly Harmless Econometrics
Material for each syllabus is reported in the syllabus of the course